Lactate derived from macrophages drives skin dermal fibroblasts phenotypic remodeling via MCT1-primed histone H3 lysine 23 lactylation in hypertrophic scar

Domain: neuroscience
Published: 2026-02-12
Editorial outcome: major_revision

Abstract
Hypertrophic scar (HS) is a fibroproliferative disorder characterized by fibroblast hyperactivation and aberrant extracellular matrix deposition. This study identifies macrophage-derived lactate as a key mediator of fibroblast phenotypic remodeling via monocarboxylate transporter 1 (MCT1)-mediated histone H3 lysine 23 lactylation (H3K23la) in HS. Elevated lactate levels and MCT1 expression were observed in HS tissues, with macrophages in stiff mechanical microenvironments identified as the primary lactate source. Lactate influx through MCT1 upregulated H3K23la, thereby promoting transcriptional activation of profibrotic genes HEY2 and COL11A1. Mechanistically, HEY2 activated YAP1/SMAD2 signaling, while COL11A1 stabilized MCT1 to enhance lactate transport, forming a positive loop that amplified fibrosis. Fibroblast-specific Mct1 deletion or pharmacological inhibition of Mct1 in male mice reduced collagen deposition, accelerated wound healing, and attenuated scar formation. Our findings redefine the macrophage-fibroblast crosstalk in HS and establish the MCT1-H3K23la-HEY2/COL11A1 axis, particularly its self-reinforcing loop, as a novel therapeutic target.

Introduction
Cutaneous wound repair aims to restore tissue integrity and homeostasis through a precisely regulated healing cascade1. However, extensive and deeper injuries frequently lead to pathological hypertrophic scar (HS), a fibroproliferative disorder characterized by excessive deposition of extracellular matrix (ECM) components and persistent inflammation. HS represents a pathological outcome of aberrant wound healing2,3. Approximately 35% linear surgical wounds4 and up to 72% burn wounds5 would develop into HS. Accompanied by skin pruritus, pain, and functional impairment, HS significantly affects patients’ quality of life and psychological well-being. Therefore, a deeper understanding of HS pathogenesis and progression is essential for identifying potential therapeutic targets and biomarkers of HS6.

Current pathophysiological models emphasize fibroblast hyperactivation and aberrant ECM synthesis as central to HS development. While transient fibroblast activation is part of normal wound repair, persistent activation results in the transformation of fibroblasts to myofibroblasts and drives HS formation7. Thus, targeting activated fibroblasts and modulating their fibrotic behavior is the main strategy for controlling HS formation. Emerging evidence suggests that metabolic reprogramming, from oxidative phosphorylation to aerobic glycolysis during the progression of various organic fibrotic diseases, suggesting metabolic dysregulation as a potential therapeutic target of fibrosis8,9. Notably, both HS and keloid, pathological outcomes of wound healing, display markedly elevated glycolysis level10. Moreover, macrophages are major contributors to metabolic reprogramming in many diseases11,12, and promote fibroblast differentiation through TGF-β1 secretion during wound healing1. Besides, metabolic reprogramming not only generates glycolytic intermediates to support the anabolic requirements of proliferating cells but also inevitably leads to elevated production of metabolic byproducts such as lactate13. Beyond its traditional role as metabolic waste, lactate functions as a signaling molecule, an energy substrate, and an immunoregulatory molecule14,15. Lactate may originate not only from endogenous glycolysis but also originate from other cells via the lactate transport system. Some cells actively extrude lactate to prevent intracellular accumulation, maintain pH balance, and provide lactate for oxidative metabolism in highly oxidative tissues and organs16,17. Monocarboxylate transporters 1 (MCT1), a member of the solute carrier family 16 (SLC16), is primarily responsible for lactate transport18. It is the most broadly expressed among MCTs 1 to 4 and is often highly expressed in cells with high oxidative activity, such as oxidative muscle fibers19. Recent studies have highlighted the importance of MCT1 in fibrosis20,21. However, few studies demonstrate a direct link between the metabolic reprogramming of macrophages and fibroblast phenotypic remodeling in the progression of HS via lactate transport. How metabolic microenvironment created by macrophages orchestrate activation of fibroblast remain poorly understood.

Recent studies have identified lactate as a significant regulator of epigenetic modification alteration known as histone lactylation22. Histones modulate biological processes by regulating the expression and activity of downstream genes23. Histone lactylation plays a pivotal role in diverse cellular physiological mechanisms, including signal transduction, transcription regulation, metabolic homeostasis, epigenetic modifications, and immune responses24–26. Recently, the relationship between histone lactylation and fibrosis has attracted considerable attention27. However, a few strategies involving histone lactylation treatment to overcome and shift molecular landscape of HS have been achieved. Thus, a better understanding of histone lactylation in the pathology of HS still requires further investigation. Besides, how metabolic reprogramming reshapes epigenetic alterations, particularly lactylation in HS, is still unclear.

This study provides compelling evidence that MCT1-mediated lactate influx modulates gene expression through histone lactylation, specifically via elevated H3K23la in HS-associated myofibroblasts. We demonstrate significantly increased lactate accumulation and upregulated expression of lactate-generative and transport-related genes in HS, with marked overexpression of MCT1. Further analysis revealed that macrophages are the primary contributors to the high-lactate metabolic microenvironment in HS, driving lactate accumulation and H3K23la levels through MCT1. Using the cleavage under targets and tagmentation (CUT&Tag) technique, we identified H3K23la enrichment at the promoters of profibrotic genes, including Hes Related Family BHLH Transcription Factor with YRPW Motif 2 (HEY2) and Collagen Type XI Alpha 1 Chain (COL11A1). Mechanistically, transcription HEY2 transcriptionally activates YAP1 expression, thereby stimulating the YAP1/SMAD2 pathway and promoting fibrotic processes. Concurrently, COL11A1 enhances lactate transport efficiency by interacting with MCT1, creating a positive feedback loop that exacerbates intracellular lactate accumulation in fibroblasts. Pharmacological inhibition of MCT1 and silence of HEY2 and COL11A1 attenuated fibroblast activation and collagen deposition. Notably, fibroblast-specific Mct1 deletion in a murine full-thickness skin defect model enhanced wound healing, reduced scar formation, and downregulated fibrotic gene expression. These findings unveiled a role of histone lactylation, particularly H3K23la, in HS pathogenesis. Disruption of the macrophage glycolysis-MCT1-H3K23la-HEY2/COL11A1 axis and its associated feedback loop represents a promising therapeutic strategy for HS treatment.

Results
Elevated glycolysis and lactate transport capacity in hypertrophic scar
The elevated glycolytic activity correlates with the progression of various fibrosis diseases and has been documented in the pathogenesis of keloid formation28,29. Considering the metabolic reprogramming in fibrotic diseases, we revealed lactate levels in the scar tissue of HS patients. Colorimetric assay demonstrated that lactate levels were markedly elevated in HS tissue compared to normal skin (NS) tissue (Fig. 1A). To characterize the metabolic phenotype, non-targeted metabolomic analysis of HS and healthy tissues revealed a distinct metabolic profile in patients (Fig. S1A). HS tissue exhibited a significant decrease in the key TCA cycle intermediate, citric acid, and a concomitant increase in the glycolytic metabolite, phosphoenolpyruvic acid (Fig. S1A–S1C). KEGG analysis of the different metabolites revealed enrichment in the central carbon metabolism, as well as pathways critical for biosynthesis and proliferation, including amino acid biosynthesis, mTOR signaling, PI3K-Akt signaling, and linoleic acid metabolism (Fig. S1C). To further validate the metabolic profile and overcome the limitations of non-targeted metabolomics in quantifying small polar acids, we performed targeted energy metabolomics which revealed a distinct metabolic signature in HS tissues (Fig. S1D). Lactate ranked as the third most upregulated metabolite (log2FC) following Guanosine Triphosphate (GTP) and DL-Glycerate (Fig. S1E). Consistent with a shift toward aerobic glycolysis, quantitative analysis confirmed significantly elevated levels of Lactate, Pyruvic acid, and ATP in HS tissues (Fig. S1F). KEGG pathway analysis of these metabolites highlighted enrichment in Pyruvate metabolism, Carbon metabolism, and Glycolysis (Fig. S1G). Next, RT-qPCR analysis of the expression of genes related to glycolysis (LDHA, HK2, PKM2 and PFKFB3), lactate transport (MCT1 and MCT4) and OXPHOS (PDHA1, CS, IDH1 and IDH2) showed a significant increase of lactate-related genes in HS, particularly MCT1 (Fig. 1B). Specifically, the mRNA levels of PDHA1, IDH1 and IDH2 were significantly decreased compared to normal skin (Fig. 1B). Moreover, we profiled the expression of these genes in NS and HS using western blotting and the results showed that the protein level of MCT1, MCT4 and PKM2, which were markedly increased in HS, yet IDH1 and IDH2 were significantly decreased (Fig. 1C and S1H). This concurrent upregulation of the glycolytic pathway and downregulation of key OXPHOS components provides strong evidence of a metabolic switch towards aerobic glycolysis in the HS microenvironment. Despite having some minor differences, similar patterns were observed in IHC assay and immunofluorescence results (Fig. 1D, E), which indicated that the expression of MCT1 and the overall capacity for glycolysis are significantly elevated in HS tissue compared to NS. Therefore, we hypothesized that MCT1 primarily participates in the regulation of skin fibrosis in HS. Furthermore, we performed immunofluorescence co-staining of MCT1 along with antibodies against marker for myofibroblasts (α-SMA) and HS tissue displayed increased co-localization between MCT1 and α-SMA fluorescence (Fig. 1F). To quantitatively validate this observation, we calculated the Pearson’s correlation and Overlap coefficient, which revealed a significantly higher level of colocalization between MCT1 and α-SMA in HS tissues compared to NS tissues (Fig. 1F). RT-qPCR results showed that the mRNA expression level of MCT1 was significantly increased in human hypertrophic scar fibroblasts (HSFs) compared to normal human skin dermal fibroblasts (NSFs) (Fig. 1G). Together, these findings indicated that MCT1 expression is upregulated in HS, primarily in myofibroblasts. Cumulatively, our data revealed that an enhanced level of lactate accumulation and a metabolic switch happened in HS tissue and MCT1 has a potential role in transferring extracellular lactate into fibroblasts to promote phenotypic remodeling.

Lactate is a key facilitator of phenotypic remodeling of human skin fibroblasts
To clarify whether the increased lactate in HS is associated with fibroblast phenotypic remodeling into myofibroblasts, we assessed the expression of fibrotic markers in NSFs treated with different concentrations of sodium lactate (NaLac). At a lactate concentration of 10 mM, fibrotic markers such as COL1A1 and α-SMA reached maximal expression levels, while COL3A1 achieved the highest at 15 mM (Fig. S2A and S2B). Consequently, a lactate concentration of 10 mM was selected as the optimal stimulatory concentration. In addition, lactate could enhance the proliferation and migration capacity of NSFs (Fig. S2C–S2E). Notably, lactate was identified as a profibrotic factor in skin tissue.

Macrophages are a major source of lactate accumulation within the scar metabolic microenvironment
Given the significant up-regulation of lactate content in HS, it is important to explore the cellular origins of lactate within the fibrotic microenvironment. To address this, we established an in vitro system utilizing polydimethylsiloxane (PDMS) hydrogel-coated plates to recapitulate the elevated mechanical stiffness characteristic of hypertrophic scar. We fabricated substrates with Young’s moduli of 2 kPa (physiologically compliant) and 50 kPa (pathologically stiff) to simulate normal and fibrotic mechanical microenvironments, respectively30,31. Comparative lactate quantification was performed in three primary skin dermal cell populations: macrophages (THP-1 cells), vascular endothelial cells (HUVECs), and dermal fibroblasts (NSFs), which were seeded on the surface of PDMS hydrogel-coated plates. Biochemical analyses revealed that macrophages exhibited significantly elevated extracellular lactate accumulation and intracellular production compared to control conditions (Fig. 2A). No significant stiffness-dependent lactate variations were observed in endothelial cells or fibroblasts (Fig. 2A). Subsequent stimulation with TGF-β, a master regulator of fibrogenesis and collagen deposition32, revealed that macrophages demonstrated the most pronounced lactate elevation, although moderate increases were also detected in endothelial cells and fibroblasts (Fig. 2B). Metabolic profiling through extracellular acidification rate (ECAR) measurements provided functional validation, indicating that macrophages cultured on 50 kPa stiff substrates exhibited enhanced ECAR, reflecting higher levels of glycolysis, glycolytic capacity, and glycolytic reserve under the stimulation of high substrate stiffness (Fig. 2C). TGF-β stimulation produced comparable metabolic activation patterns (Fig. 2D). To definitively assess the metabolic switch, we calculated the ATP production rates. Macrophages cultured on 50 kPa stiff substrates or under TGF-β stimulation exhibited a significant shift where ATP production from glycolysis (glycoATP) markedly exceeded that from oxidative phosphorylation (mitoATP) (Fig. S3A and S3B). However, endothelial and fibroblast cultures showed marginal ECAR increases and no significant shift in the glycoATP/mitoATP ratio under stiff conditions (Figs. 2E, F, S3C and S3D).

To validate in vivo that macrophages are a primary source of lactate during scar formation, we isolated primary macrophages, vascular endothelial cells and dermal fibroblasts from fresh NS and HS tissues using magnetic activated cell sorting (MACS) and protein-level validation was performed on these cells using western blotting (Fig. S4A–S4C). In line with previous results, primary macrophages from HS tissues showed a profoundly elevated extracellular lactate accumulation and intracellular production, but lactate levels in fibroblasts and endothelial cells remained constant (Fig. 2G). In addition, enhanced ECAR level and glycoATP/mitoATP ratio was observed in primary macrophages from HS tissues compared to control (Fig. 2H and S4D). This macrophage-specific metabolic shift was corroborated by the selective upregulation of glycolytic enzymes HK2 and LDHA within CD68+ macrophages in HS tissue (Figs. 2I, J), with no corresponding change in CD31+ endothelial cells (Fig. S4E and S4F). To further rule out the contribution of other immune cell populations to the lactate-rich microenvironment, we also performed immunofluorescence co-staining of key glycolytic enzymes (HK2 or LDHA) with markers for mast cells (Tryptase) and T cells (CD3) in human NS and HS tissues. Quantitative analysis revealed no statistically significant differences in the number of glycolytic-enzyme-positive mast cells or T cells (Fig. S4G–S4J). Crucially, we utilized clodronate liposomes to deplete macrophages in the full-thickness skin defect model on the dorsal region of C57BL/6 mice. Immunofluorescence analysis confirmed a significant depletion of F4/80-positive macrophages in the scar tissue of clodronate liposomes-treated mice compared to saline-treated controls (Fig. S4K). Importantly, this macrophage depletion resulted in a marked decrease in lactate levels within the scar tissue (Fig. S4L). Collectively, these in vivo findings strongly support our conclusion that macrophages are a key contributor to the lactate-rich microenvironment in HS. This investigation identifies macrophages as the predominant lactate source in mechanically stressed fibrotic microenvironments, with both substrate stiffness and TGF-β signaling independently potentiating the shift towards glycolysis in macrophages in HS.

Macrophages-derived lactate accumulation facilitates skin dermal fibroblasts phenotypic remodeling via MCT1
Our previous findings demonstrated the upregulated expression of MCT1 in myofibroblasts and lactate accumulation from macrophages in HS microenvironment. Therefore, it was important to explore the involvement of MCT1 and macrophages-derived lactate in fibroblasts phenotypic remodeling. As shown in Fig. 3A, conditioned medium (CM) of different substrate stiffness induced THP-1 cells (Mφ-CM@2 kPa, Mφ-CM@50kPa) and HUVECs (EC-CM@2kPa, EC-CM@50kPa) were added into NSFs to induce fibrosis. Elevated fibrotic markers expression observed in NSFs stimulated by Mφ-CM@50kPa was decreased in NSFs treated with AZD3965 (Fig. 3B, C), a potent and selective MCT1 inhibitor that could disrupt cancer cell metabolism by blocking lactate transport33. Furthermore, AZD3965 reversed the increased fibroblasts phenotypic remodeling induced by treatment with CM originating from macrophages cultured on 50 kPa stiff substrates, including the cell migration and proliferative capacity and the mRNA expression of profibrotic biomarkers (Fibronectin, SPARC, POSTN, TNC, CD248 and SMAD2) (Fig. 3D–F and S5A–B). These results demonstrated that Mφ-CM@50kPa-induced phenotypic remodeling in NSFs is caused by lactate transport from macrophages to fibroblasts via MCT1. To further validate this finding, we decreased the lactate production using the LDHA inhibitor oxamate. Consistent with our hypotheses, a reduction in lactate production levels in macrophages cultured on 50 kPa stiff substrates via oxamate significantly attenuated fibroblasts phenotypic remodeling (Fig. 3G, K and S5C, D). Furthermore, AZD3965 also could mitigate fibrosis in NSFs treated with CM of macrophages stimulated by TGF-β (Fig. 3L, M). In contrast, conditioned medium from ECs stimulated by high substrate stiffness or TGF-β exhibited negligible effects on the expression of fibrotic markers (Fig. S5E and S5F). Collectively, these findings support the hypothesis that macrophages had a notably increased glycolysis capacity in HS microenvironment, and MCT1 plays a key role in transferring macrophages-derived lactate into fibroblasts to promote phenotypic remodeling.

Histone lactylation is increased and the H3K23la level is specifically elevated in myofibroblasts in HS
To investigate the mechanism by which increased lactate levels promote scar formation, we assessed the levels of protein lactylation in five pairs HS tissues and NS tissues. Higher levels of global/pan-lysine lactylation (PanKla) were observed in HS tissues (Fig. 4A). Notably, a distinct band around histone locations was observed, prompting us to focus on alterations in histone lactylation. We examined several previously confirmed sites of histone lactylation and found that only the H3K23la level was markedly elevated in HS tissue (Fig. 4B). However, the expression of other common H3 and H4 lactylation sites, including H3K9la, H3K14la, H3K18la, H3K27la, H4K5la and H4K12la, did not change. Furthermore, we also found that there was a clear dose-dependent increase in H3K23la level under the different concentration of NaLac (Fig. S6A). To examine histone lactylation changes in different skin dermal cell types, we performed immunofluorescence co-staining of H3K23la along with antibodies against markers for vascular endothelial cells (CD31), macrophages (CD68), and myofibroblasts (α-SMA). Most cells displayed H3K23la fluorescence (Fig. 4C–H), and no obvious differences in H3K23la intensity were observed in vascular endothelial cells or macrophages between NS and HS tissue (Fig. 4C–F). In contrast, the H3K23la signal intensity was significantly elevated in myofibroblasts as compared with myofibroblasts in HS tissue or NS tissue (Fig. 4G, H). We isolated myofibroblasts from HS followed by western blotting analysis with antibodies against PanKla and H3K23la, which revealed that HSFs had a significant upregulation of the expression of Pan Kla and H3K23la compared with NSFs (Fig. 4I). These results indicated that H3K23la was the primary differentially affected histone lactylation modification in the myofibroblasts of HS tissue.

MCT1 and P300 are potential regulators and writers of histone lactylation in HSFs
Previous findings have highlighted that MCT1 facilitated the transport of macrophage-derived lactate into fibroblasts, promoting their differentiation into myofibroblasts in HS microenvironment. To explore the regulatory influence of MCT1 on histone lactylation, we used MCT1 knockdown (si-MCT1) treatment in HSFs. Fig. S7A and S7B demonstrated that si-MCT1-1 exhibited the highest knockdown efficiency. Therefore, we selected si-MCT1-1 for subsequent experiments. Fibrotic markers (COL1A1, COL3A1 and α-SMA) and histone lactylation H3K23la examined by western blotting and immunofluorescent staining revealed MCT1 silencing attenuated fibrosis and H3K23la level in HSFs (Fig. S7C and S7D). Furthermore, MCT1 silencing in HSFs resulted in a substantial reduction in cell proliferation by using Ki-67 immunofluorescent staining (Fig. S7E). Wound scratch and Transwell assays revealed that MCT1 silencing also significantly impaired HSF migration (Fig. S7F). These results suggest that MCT1 as potential regulator of histone lactylation, promoted phenotypic remodeling of fibroblast in HS.

P300, a histone acetyltransferase, is a transcriptional coactivator involved in chromatin remodeling and gene regulation34. Recent studies suggest that P300 may also modulate histone lactylation35. However, its involvement in HS progression remains understudied. We used P300 knockdown (si-P300) treatment in HSFs and selected si-P300-1 due to its higher knockdown efficiency (Fig. S8A and S8B). Under si-P300 treatment, the expression of fibrotic markers and histone lactylation H3K23la similarly decreased (Fig. S8C and S8D). Additionally, proliferation and migration capacity were weakened when P300 was silenced (Fig. S8E and S8F). These findings suggested that P300, the potential writer of histone lactylation, promotes the progression of fibroblasts in HS.

H3K23la activates HEY2 and COL11A1 transcription in HS
Epigenetic modulation of histone post-translational modifications governs transcriptional activation and repression of target genes36. To investigate the functional relevance of H3K23la in HS pathobiology, we conducted genome-wide CUT&Tag assays employing H3K23la-specific antibodies. Comparative analysis revealed pronounced enrichment of H3K23la peaks in HS tissues relative to NS control (Fig. 5A). The HS cohort exhibited 16,860 differential H3K23la peaks, with 18.69% mapping to promoter regions. Specifically, 7424 upregulated peaks in HS tissues accounted for 25.26% located in promoter sequences (Fig. 5B). HS tissues demonstrated 2313 upregulated and 49 down-regulated lactylation peaks within promoter regions compared with NS tissues (Fig. 5C). The GO and KEGG pathways enrichment analysis of HS-specific promoter-associated peaks identified significant associations with carbohydrate derivative biosynthetic process, positive regulation of fibroblast migration, collagen-containing extracellular matrix, and hypertrophic scar-related pathways such as TGF-β signaling pathway that are involved in glycolysis and scar formation (Fig. 5D). We also conducted an RNA-seq assay to screen the potential target genes regulated by H3K23la in mRNA levels. When compared with the NS tissue, there were upregulated 1515 genes and downregulated 1341 genes in HS tissue (Fig. S9A). Enrichment profiling of upregulated differentially expressed genes (DEGs) highlighted similar pathways to CUT&Tag data (Fig. 5E). These findings indicated that histone lactylation H3K23la lactylation promotes transcriptional programs underlying extracellular matrix deposition and fibroblast activity, and TGF-β signaling pathway activation, which were closely related to the pathological mechanisms of HS.

By intersecting the genesets among CUT&Tag and RNA-seq data, we identified 21 differential expressed genes that exhibited significantly increased mRNA levels and enhanced enrichment of the H3K23la signal at the promoter region in HS group (log FoldChange > 2, P value < 0.05) (Fig. 5F). Given that both the CUT&Tag and RNA-seq enriched in the TGF-β signaling pathway and collagen-containing extracellular matrix, we focused on the genes highly likely involved in scar formation: HEY2 and COL11A1. Notably, HEY2 is a transcription factor closely associated with the Notch signaling pathway, primarily through repressing downstream target genes to regulate cardiovascular system development, organogenesis, and cell differentiation37,38. COL11A1 is an extracellular matrix protein that plays a role in various cancers by promoting mechanisms such as oncogenic proliferation, angiogenesis, and drug resistance, and it is closely associated with the activation of cancer-associated fibroblasts39,40. In addition, COL11A1 might be associated with keloids formation41. Consequently, we decided to investigate these two genes.

Specifically, the peaks identified candidate genomic loci at HEY2 and COL11A1 genes showed that the levels of H3K23la at promoters of these genes were elevated (Fig. 5G). A ChIP-qPCR analysis to further confirm that the histone lactylation H3K23la was enriched at the HEY2 and COL11A1 promoters in HS group compared with NS group (Fig. 5H). Consistently, RT-qPCR and western blotting analysis showed that the mRNA and protein levels expression levels of HEY2 and COL11A1 were significantly elevated in HS tissue (Fig. 5I, J). IHC analysis revealed a significant increase in HEY2 and COL11A1 expression in HS tissue (Fig. 5K). Furthermore, immunofluorescence assays between H3K23la and HEY2 or H3K23la and COL11A1 demonstrated markedly upregulated colocalization in HS tissue samples compared to NS tissue (Fig. S9B and S9C). These findings collectively implicate H3K23la-mediated epigenetic upregulation of HEY2 and COL11A1 in HS progression.

The high levels of HEY2 and COL11A1 are associated with phenotypic remodeling of fibroblasts
To investigate the effects of HEY2 and COL11A1 in HS progression, we detected their expression in fibroblasts. The transcription levels of HEY2 and COL11A1 were significantly higher in HSFs compared to NSFs (Figure S10A). Immunofluorescence double staining against HEY2 and COL11A1 for α-SMA showed that upregulation of HEY2 and COL11A1 was specifically colocalized in HS dermal myofibroblasts (Fig. 6A, B), which aligns with the elevated H3K23la levels previously detected in HS dermal myofibroblasts (Fig. 4I, S9B and S9C). These results support the notion that HEY2 and COL11A1 exhibited elevated expression predominantly in myofibroblasts of HS.

To assess the function of HEY2 and COL11A1 in HS, we used siRNA transfection to knockdown HEY2 or COL11A1 expression in HSFs. We selected the siRNAs (si-HEY2-1 and si-COL11A1-3) which exhibited the highest knockdown efficiency for subsequent experiments (Figs. S10B–S10E). Knockdown of either HEY2 or COL11A1 resulted in a significant reduction in the expression of fibrotic markers (COL1A1, COL3A1 and α-SMA) for HSFs compared to the control group (Fig. 6C, D). Immunofluorescence results demonstrate consistent expression patterns (Fig. 6E, F). Additionally, cell migration and proliferation capabilities of HSFs were diminished by knockdown of HEY2 or COL11A1 (Fig. 6G, H, S10F and S10G). These findings indicated that HEY2 and COL11A1 play critical roles in the phenotypic transition of fibroblasts in HS, and their inhibition can reverse this phenomenon.

HEY2 promotes fibroblast phenotypic remodeling via upregulated YAP1 expression
To investigate the mechanism underlying high HEY2 expression in HS, we searched the GTEx, FIMO, JASPAR, and GTRD databases for the genes that might be regulated by transcription factor HEY2 in HS. This led to the identification of six candidates: SDK1, KLHDC4, HERC1, YAP1, TMEM204 and CDK5R1 (Fig. 7A). Yes-associated protein 1 (YAP1), a key effector of the Hippo signaling pathway, promotes fibroblasts proliferation, migration, and ECM overproduction in hypertrophic scar42. Furthermore, we found that YAP1 expression in HS tissues was significantly increased compared to that in NS tissues (Fig. 7B) and analysis of GTEx data revealed a positive association between the mRNA levels of HEY2 and YAP1 (Fig. 7C). The JASPAR database was used to predict potential HEY2-binding sites in the YAP1 promoter. Three predicted binding sites were present in this genomic segment (Fig. 7D). Subsequently, a ChIP-qPCR assay was conducted to confirm the binding of HEY2 to the YAP1 promoter region in HS (Fig. 7E). YAP1 could interact with SMAD pathway, amplifying profibrotic signals, suggesting its potential as a therapeutic target to mitigate HS43,44. Knockdown of HEY2 resulted in a significant reduction in the expression of YAP1, SMAD2 and P-SMAD2 (Fig. 7F). Immunofluorescence co-staining of SMAD2 or P-SMAD2 along with α-SMA in HSFs showed that the fluorescence intensity of fibrotic marker and SMAD2 pathway were diminished by silencing of HEY2 (Fig. 7G, H). These results indicated that HEY2 increased YAP1 transcription by interacting with the YAP1 promoter, contributing to scar formation via YAP1/SMAD2 pathway in HS.

COL11A1 aggravates lactate accumulation in fibroblasts by combination of MCT1
To clarify how COL11A1 promotes fibrosis and contributes to fibroblasts phenotypic remodeling in HS, we utilized BioGRID database to find the proteins interactions about COL11A1. Figure 8A demonstrated that 22 proteins interact with COL11A1, including SLC16A1, also known as MCT145. To confirm this interaction, co-immunoprecipitation (Co-IP) experiments revealed a significant interaction between COL11A1 and MCT1 (Fig. 8B, C). Their colocalization was also assessed in NSFs and HSFs via immunofluorescence analysis, which revealed an upregulated colocalization of COL11A1 and MCT1 within the region of the cytoplasm adjacent to the membrane of HSFs compared to NSFs (Fig. 8D). We co-stained myofibroblasts (α-SMA) with antibodies against COL11A1 and MCT1 in NS and HS tissue. Myofibroblasts with strong COL11A1 and MCT1 colocalization signals in HS tissue (Fig. 8E). While our Co-IP and immunofluorescence data confirmed a physical interaction between COL11A1 and MCT1, the functional consequence of this binding remained unclear. To determine precisely how COL11A1 binding might modulate MCT1’s activity, we performed molecular modeling. Through computational simulations utilizing AutoDock Vina software, we identified key amino acid residues mediating the COL11A1-MCT1 interaction. Specifically, residues 52, 81, and 121 in the COL11A1 N-terminal domain formed hydrogen bonds with residues 160, 303, and 315 of MCT1 (Fig. 8F). We then mutated the predicted binding sites between COL11A1 and MCT1 (Fig. 8G). Co-IP assays suggested that the interaction between COL11A1 and MCT1 was effectively impeded by mutations in the TRIM34-binding site (FLAG-COL11A1-MUT) or UPF1- binding site (His-MCT1-MUT), whether introduced individually or in conjunction (Fig. 8G). Molecular dynamics simulations revealed enhanced structural stability in the COL11A1-MCT1 complex compared to MCT1 monomer, as evidenced by lower root mean square deviation (RMSD) values (Fig. S11A). Root mean square fluctuation (RMSF) analysis demonstrated reduced structural variability in complex-associated MCT1, suggesting COL11A1-mediated stabilization of MCT1 conformation (Fig. S11B).

Next, we hypothesize that COL11A1 may modulate lactate transport through its interaction with MCT1. Based on the structures of the COL11A1-MCT1 complex and MCT1 protein depicted in Fig. 8F, we performed molecular docking by introducing lactate as a small molecule compound. The results demonstrated that lactate existed conserved hydrogen bonding with MCT1 residues ARG-313 (2.8/2.3 Å) and SER-154 (1.9 Å), irrespective of COL11A1 presence (Fig. 8H). Dynamic simulations of ternary complexes showed superior structural stability in COL11A1-MCT1-lactate systems compared to MCT1-lactate pairs, with reduced ligand RMSD values (Fig. S11C). Binding free energy calculations revealed strengthened lactate affinity in the ternary complex, mediated by enhanced interactions with PHE-367, PRO-155, LEU-281, and LEU-305 (Fig. 8I; and Supplementary Table 1). To test these results, we assessed the effects of COL11A1 protein on intracellular lactate levels in HSFs under condition supplemented with 10 mM exogenous lactate. The results revealed a positive correlation between COL11A1 protein concentration and intracellular lactate levels, suggesting that COL11A1 may enhance lactate accumulation within cells (Fig. S11D). Given that histone lactylation is dependent on the presence of lactate and considering our finding that H3K23la modification promotes the expression of COL11A1, it seems plausible that there could be a positive feedback loop between lactate accumulation and H3K23la that propagates the phenotypic switch that we observed in the fibroblasts of HS tissue. The simulations provide a structural and energetic basis for how COL11A1 enhances MCT1’s lactate transport affinity, thereby closing the loop.

Mct1-specific ablation in fibroblasts speeds up wound healing and ameliorates collagen deposition in a wound model of c57 male mice
We next achieved specific deletion of Mct1 in mouse fibroblasts by crossing Mct1f/f mice with Col1a2CreERT mice (Fig. 9A). 4-week-old mice were given 20 mg/kg tamoxifen (intraperitoneal injection) for 5 consecutive days. Mice were divided into four groups: Mct1fl/flCol1a2-cre-, Mct1fl/flCol1a2-cre-+NaLac, Mct1fl/flCol1a2-cre+, Mct1fl/flCol1a2-cre++NaLac groups. During the sixth week, we created a full-thickness skin defect model on the dorsal region of mice. On the day of model construction, 100 µL NaLac (10 mM) was administered perilesionally. Subsequent administrations of 100 µL were performed sub-eschar every two days. Systematic photographic documentation was performed at days 0, 3, 7, 10, and 14 post-wounding (Fig. 9A). As is shown in Fig. 9B, these photographs clearly showed that the wound closure rate was higher in the wound of Mct1fl/flCol1a2-cre+ mice than Mct1fl/flCol1a2-cre- mice. As expected, treatment with NaLac exhibited a delayed wound closure rate (Figs. 9B, C). Next, tissue samples were collected at 21 days post-injury for histological analysis, and we rarely observed the hypertrophic scar features in the Mct1 knockout wounds as well (Fig. 9D). However, under the condition of lactate treatment, these hypertrophic phenotypes significantly were evident (Figs. 9D, E). Histological analysis with H&E staining revealed that wounds in the Mct1 knockout group exhibited a more organized skin architecture, characterized by a well-formed epidermis with rete ridges and signs of hair follicle regeneration, and a dermis with reduced inflammatory cell infiltration compared to the control group. In contrast, the control and NaLac-treated groups showed features of hypertrophic scarring, including a thickened, flattened epidermis and a disorganized dermal structure (Fig. 9D). Masson staining showed obviously reduced blue collagen deposition and collagen fibers were arranged in a smoother, more orderly pattern in the Mct1fl/flCol1a2-cre+ compared to Mct1fl/flCol1a2-cre- mice (Fig. 9D). Quantitative analysis confirmed these observations, showing a significantly reduced collagen area and dispersion index—indicating more orderly collagen alignment—in the Mct1 knockout group (Fig. 9E and S12A). The Sirius red staining results were also consistent with this result (Fig. 9D). The collagen I to III ratios of groups were reduced in Mct1 knockdown mice compared to the control mice (Fig. 9D, G). Meanwhile, NaLac treatment resulted in enhanced collagen synthesis, disorganized collagen alignment, and elevated collagen I to III ratios, as notably observed in the histological analysis (Fig. 9D-G). These data indicated a shift from a fibrotic to a more regenerative healing phenotype in Mct1 knockdown mice. Additionally, immunofluorescence staining analysis conducted at 21 days post-injury demonstrated that a decrease of α-SMA and H3K23la expression in Mct1fl/flCol1a2-cre+ mice (Fig. 9H). Besides, western blotting showed obviously decreased levels of fibrotic markers (Col1a1, Col3a1 and α-SMA) and lactylation modification downstream products (Col11a1 and Hey2) in scar tissue of Mct1fl/flCol1a2-cre+ compared to Mct1fl/flCol1a2-cre- mice (Fig. 9I). These findings suggested that fibroblasts-specific Mct1 knockout could inhibit scar formation and fibroblast phenotype transformation in full-thickness skin defect model. Furthermore, we isolated mouse fibroblast cells from Mct1fl/flCol1a2-cre+ and Mct1fl/flCol1a2-cre- mice. The expression levels of fibrotic markers and H3K23la increased in NaLac-treated fibroblasts and decreased in Mct1 knockout fibroblasts (Fig. 9J). To further confirm the role of Mct1 in HS progression, RT-qPCR data showed that the mRNA expression of profibrotic biomarkers (Fibronectin, SPARC, POSTN, TNC, CD248 and SMAD2) were also significantly increased in NaLac-treated fibroblasts compared to Mct1 knockout fibroblasts (Figure S12B). Collectively, these results suggested that the pro-fibrotic signaling driven by lactate and MCT1 creates a pathological microenvironment that simultaneously impairs the rate of wound closure and drives the excessive fibrotic gene expression characteristic of hypertrophic scar, mediated by increased H3K23la levels in fibroblasts.

Pharmacological inhibition of MCT1 or elimination of macrophages as a strategy for scar treatment
To further identify the role of MCT1 in the development of scar, six-week-old adult C57BL/6 mice were randomly allocated into four experimental groups: Control, Control + NaLac, AZD3965, and AZD3965 + NaLac. Full-thickness skin defects were surgically induced in the dorsal region of the six-week mice. Notably, the administration of AZD3965 markedly speeded up wound healing compared to the lactate-treated groups (Figs. 10A, B). H&E, Masson and Sirius red staining demonstrated that decreased collagen synthesis, smoothed collagen alignment, and diminished collagen I to III ratios in lactate-treated mice at 21 days post-injury following AZD3965 treatment (Fig. 10C–F and S12C). Moreover, as evidenced by immunofluorescent staining, α-SMA signal levels significantly decreased in AZD3956-treated mice but reversed by lactate treatment (Fig. 10G). Fig. S4K and S4L showed that the depletion of macrophages using clodronate liposomes in the late stage of wound healing significantly reduced the secretion of lactic acid during scar formation. To validate the role of in vivo macrophage depletion, reducing the source of lactate, in scar formation, we then performed H&E and Masson’s trichrome staining on the collected scar tissue at post-injury day 21. The results indicated that clodronate liposomes significantly reduced scar formation in the dorsal wounds of mice and promoted hair follicle regeneration, suggesting that macrophages play an important pathological role in the late stage of wound healing (Figure S12D–F). Collectively, MCT1 inhibition via AZD3965 or clearance of the source of lactate may be an effective therapeutic strategy for hypertrophic scar.

Methods
Humansubjects
Postoperative discarded hypertrophic scar tissues were procured from patients diagnosed with hypertrophic scars at the Department of Burns and Cutaneous Surgery of Xijing Hospital, Air Force Medical University, along with normal skin samples from age-matched non-hypertrophic scar patients. Collected tissue samples were immediately trimmed and either immersed in fixative solution (4% paraformaldehyde, Servicebio, G1101) or rapidly cryopreserved in liquid nitrogen, followed by storage at -80°C for subsequent processing. Except for questionnaire-based assessments, all participants were screened based on medical history, laboratory tests, and physical examinations. A total hypertrophic scar tissue samples and fifteen age-matched normal control skin samples were collected. Sex was not considered as a specific variable in the study design or analysis. Informed consent was obtained from all participants, and no financial compensation was provided for their participation. The study was approved by the Medical Ethics Committee of Xijing Hospital, Air Force Medical University (KY20252080-C-1). Subject baseline characteristics of individuals with hypertrophic scars and controls are presented in the Supplementary Table 2.

Animalmodels
All male mice in this study were from the C57BL/6 background. Mct1f/f mice were kindly provided by Prof. Yan Chen (Shanghai Institute of Nutrition and Health, China) and Col1a2-creERT mice were purchased from Shulaibao (Wuhan) Biotechnology (Wuhan, China). Col1a2-creERT mice were maintained as hemizygous by breeding with C57BL/6. To generate Mct1fl/flCol1a2-cre+ mice, Mct1f/f mice were crossed with Col1a2-creERT mice, which would yield two groups of mice (Mct1fl/flCol1a2-cre+ and Mct1fl/flCol1a2-cre-). Mice genotypes were confirmed via PCR amplification of DNA extracted from tail biopsies. Other 6-8 weeks old C57BL/6 mice were purchased from Air Force Medical University Animal Center (Xi’an, China). All mice were maintained at 18±3°C under a 12-h light/dark cycle, with a relative humidity of 50±5%, in a filtered, pathogen-free environment. Ad libitum access to food and water was provided throughout the study. All animal surgeries were performed with inhalation anesthesia with isoflurane at a concentration of 1–2% in oxygen at 3 L min−1.

Mice with Mct1 specific knockout in fibroblasts were induced by tamoxifen (Sigma-Aldrich, T5648). Briefly, tamoxifen was dissolved in corn oil (Sigma-Aldrich, C8267) to a final concentration of 20 mg/ml. To ablate Mct1 in fibroblasts, 4-week-old mice were given 20 mg/kg tamoxifen by intraperitoneal injection for 5 consecutive days. In the sixth week, after the mice were anesthetized with 2% isoflurane, their back hair was removed at approximately 2 cm below the ear. On the following day, a translucent, single-sided adhesive silicone ring (outer diameter: 14 mm, inner diameter: 10 mm and thickness: 0.6 mm) was securely affixed to the midline of the hairless dorsal area. Subsequently, a sterile scalpel was used to create a full-thickness circular wound along the inner circumference of the silicone ring. For lactate treatment groups, NaLac (Sigma-Aldrich, L7022) was dissolved in sterile water and prepared at a concentration of 10 mM. On the day of model induction, 100 µL was administered perilesionally. Subsequent administrations of 100 µL were performed sub-eschar every two days. To examine the anti-fibrosis function of pharmacological inhibition of MCT1, C57BL/6 mice aged 6 to 8 weeks were randomly assigned to four groups (Control, Control + NaLac, AZD3965, and AZD3965 + NaLac). AZD3965 was administered with a solution prepared in 0.5% hydroxypropylmethylcellulose (Sigma-Aldrich, H7509) and 0.1% Tween 80 (Servicebio, GC204001) at a dose of 100 mg/kg, administered twice daily (BID) via oral gavage for 21 days. To identify the source of lactate in the scar microenvironment in vivo, C57BL/6 mice aged 6 to 8 weeks were randomly assigned to three groups (Control, Clodronate liposome and Nalac). Clodronate liposomes (Yeasen, 40337ES) were administered of 40 µL sub-eschar every three days starting from day 7 post-injury with a solution prepared at a dose of 50 ug/ml61. Systematic photographic documentation was conducted at days 0, 3, 7, 10, and 14 post-wounding. On day 21, tissue collection was conducted for subsequent protein extraction and histopathological analysis to facilitate comprehensive biochemical assessment. All mouse experiments were performed in accordance with the guidelines of the Institutional Animal Care and Use Committees of the Air Force Medical University (20250030).

Isolation and culture of dermal fibroblasts from human normal skin and hypertrophic scar
Normal skin tissue and hypertrophic scar tissue were collected clinically and immediately transferred to sterile workbench. The tissues were rinsed three times with prechilled PBS. The tissues were trimmed into elongated strips and then washed three times with 1% Penicillin-Streptomycin (Gibco, 15140122) solution dissolved in PBS. Normal skin tissue was incubated overnight (14–18 h) at 4°C on a shaker in 2.5% sterile Dispase II solution (Sigma-Aldrich, D4693) dissolved in DMEM basic medium (Gibco, 11885500). The next day, the epidermis and the dermis were gently separated using forceps. However, scar tissue could directly separate into dermis and epidermis using scissors instead of incubating in 2.5% Dispase II solution. Both types of dermal tissues were minced into chylous tissue blocks and then evenly seeded into 25 cm² culture flasks using a pipette, with each block measuring approximately 0.3×0.3 cm. The tissue blocks were incubated at 37°C with 5% CO₂ for 6–8 h, after which 2 ml of complete medium (DMEM basic medium + 10% FBS (Vazyme Biotech, F103)) was added. The medium was replaced every two days. When confluent fibroblasts with a spindle-shaped morphology were observed surrounding the tissue blocks, the cells were passaged. Third-to Sixth-generation fibroblasts were used for subsequent experiments.

Isolation and culture of dermal fibroblasts from Mct1fl/flCol1a2-cre+ and Mct1fl/flCol1a2-cre- mice skin
Neonatal mice (1–2 days postnatal) were anesthetized and immersed in 75% ethanol for 5 minutes. The skin was rapidly dissected and placed in PBS containing 1% Penicillin-Streptomycin, rinsed three times. The skin tissue was incubated overnight at 4°C on a shaker (10–16 hours) in 2.5% sterile Dispase II solution (65 mg Dispase II+ 26 ml DMEM basic medium). The following day, the epidermis and dermis were separated using forceps, and the dermal tissue was minced into a chylous mixture. An equal volume of DMEM basic medium containing 1% Collagenase Type I (Sigma-Aldrich, SCR103) was prepared and mixed with the dermal tissue, followed by incubation at 37°C on a shaker for enzymatic digestion. After 1 hour, the reaction was neutralized with an equal volume of complete medium (containing 10% FBS). The mixture was sequentially filtered through 100-μm and 70-μm filters. After centrifugation at 200g for 5 minutes, the primary mouse dermal fibroblasts were seeded into culture flasks and maintained at 37°C with 5% CO₂. Third- to Sixth-generation fibroblasts were used for subsequent experiments. For Mct1 knockout, 0.5 μM 4-hydroxytamoxifen (MedChemExpress, HY-16950) was added to the medium and cultured for 3 days before treating with sodium lactate (Sigma-Aldrich, L7022). After treating with sodium lactate (10 mM) or vehicle (PBS) for another 24h, fibroblasts were collected for subsequent experiments.

Isolation of primary macrophages, vascular endothelial cells and dermal fibroblasts using magnetic activated cell sorting (MACS)
Primary macrophages, vascular endothelial cells and dermal fibroblasts were isolated from mouse scar tissues using magnetic separation (MACS) Technology (Miltenyi Biotec) according to the manufacturer’s instructions. Briefly, wash human skin tissue sample in PBS. After scraping off the subcutaneous fat using a scalpel, tissues were dissociated using Whole Skin Dissociation Kit (Miltenyi Biotec, 130-101-540). CD68-positive macrophages were labeled with PE Mouse Anti-Human CD68 (BD Biosciences, 556078). CD31-positive vascular endothelial cells were labeled with PE Mouse Anti-Human CD31 (BD Biosciences, 566125). Vimentin-positive dermal fibroblasts were labeled with PE Mouse Anti-Human Vimentin (BD Biosciences, 562337). After combined with Anti-R-Phycoerythrin (PE) Magnetic Particles (BD Biosciences, 557899), cells separated using a MACS Column (Miltenyi Biotec, 130-021-101), and centrifuged at 400g at 4°C for 5 minutes. The supernatant was discarded, and the isolated primary cells were retained for subsequent use.

PDMS Hydrogel-coated plates
PDMS Hydrogel of varying stiffness were fabricated using protocols62. These silicone dielectric gels were prepared using Dow Corning Sylgard 527 (Part A and B, Ellsworth Adhesives, 527 SILDIELECTGEL). The components of Part A and Part B were mixed in specific volumetric ratios to achieve the desired mechanical properties. For the 2 kPa gel, the A:B ratio was 1.2:1, while for the 50 kPa gel, the A:B ratio was 0.3:1. Cell culture plates were coated with the hydrogel and incubated for a duration of 16–18 hours at 60°C. For 6-well plates, 2 mL of gel was applied to each well, and for 24-well plates, 0.4 mL of gel was applied to each well. After 24 hours, the gels were functionalized with fibronectin (1 μg/mL in PBS, Sigma-Aldrich, F2006) for 4 hours at 37°C, followed by subsequent rinsing with sterile PBS.

Cell culture and treatment
The human cell lines THP-1 and HUVEC cells were sourced from Procell Life Science & Technology. THP-1 cells were cultured in RPMI 1640 medium (Gibco, 11875500) and HUVECs were cultured in DMEM basic, low glucose medium (Gibco, 11885500), which were supplemented with 10% FBS (Vazyme Biotech, F103) and 1% penicillin/streptomycin (Gibco, 15140122). NSFs, HSFs and mouse skin dermal fibroblasts were cultured in DMEM basic, low glucose medium (Gibco, 11885500) supplemented with 10% FBS (Vazyme Biotech, F103) and 1% penicillin/streptomycin (Gibco, 15140122). For high matrix stiffness culture conditions, cells were seeded onto PDMS hydrogel-coated plates. After adhering for 24h, supernatants were collected, or subsequent experimental procedures were initiated. To validate whether macrophage-derived lactate enters fibroblasts via the MCT1 lactate transport channel, supernatants from THP-1 cells and HUVECs cultured under 2 kPa and 50 kPa conditions for 24h were mixed at a 1:1 ratio with DMEM complete medium (DMEM basic medium with 10% FBS) to stimulate NSFs. AZD3965 (100 nM) was added to the respective treatment groups. The lactate production inhibitor Oxamate (10 mM) was used to pre-treat THP-1 cells and HUVECs prior to supernatant collection after 24h. THP-1 cells and HUVECs were pretreated for 24h with TGF-β (10 ng/ml, Proteintech, HZ-1011). This concentration was selected as a well-established and widely used concentration in the literature for effectively inducing a fibrotic response in in vitro models of hypertrophic scarring and fibrosis63,64. All drugs were pH-neutralized before treatment.

Histone extraction
Histones were isolated from tissues or cells via a standardized acid-extraction protocol65. Briefly, tissue or cellular samples were harvested and resuspended in lysis buffer (10 mM Tris-HCl, 1 mM KCl, 1.5 mM MgCl₂, and 1 mM DTT, pH 8.0) supplemented with protease inhibitors for nuclear extraction. The isolated nuclei were subsequently resuspended in acidic extraction buffer (0.2 M H₂SO₄) through an overnight incubation at 4°C, and histones were extracted followed by centrifugation at 16,000 × g for 10 minutes at 4°C. The supernatant fractions were collected, and histone pellets were precipitated using trichloroacetic acid (TCA, Sigma-Aldrich, T8657) to a final concentration of 35% on ice. Following extensive washing and drying, the histone pellets were resuspended in deionized water and the samples concentration was quantified by Pierce Rapid Gold BCA Protein Assay Kit (Thermo Scientific, A53225). Histone were loaded onto a 15% SDS-PAGE gel and subjected to western blot analysis.

Western blotting
Skin tissues or cells were lysed with RIPA lysis buffer (NCM Biotech, WB3100) containing PMSF (Beyotime, ST506). The protein concentration of lysates was measured by Pierce Rapid Gold BCA Protein Assay Kit (Thermo Scientific, A53225) and was adjusted to the same final concentration. The denatured proteins were separated by SDS-PAGE and transferred onto a PVDF membrane (Millipore, IPVH00010). After blocking with 5% bovine serum albumin (BSA, Beyotime, ST506) for 1 h at room temperature, the membranes were then incubated with primary antibodies overnight at 4°C, followed by three washes with TBST, and subsequent incubation with horseradish peroxidase (HRP)-conjugated secondary antibodies for 1 h at room temperature. The immunoreactive proteins were then detected using Super Femto ECL Master Mix (Vazyme Biotech, E433) and visualized with ChemiDoc Imaging System (BIO-RAD, USA). Equal loading of proteins was verified by immunoblotting for β-Actin and Histone 3. All the antibodies used in immunoblot analysis are listed in the Supplementary Table 3.

Protein co-immunoprecipitation
For the protein co-immunoprecipitation (Co-IP) assay, cells were collected and lysed in IP lysis buffer (Pierce Classic Magnetic IP/Co-IP Kit, Thermo Scientific, 88804) containing PMSF (Beyotime, ST506). After centrifugation at 14,000 × g for 10 min, the supernatant was collected and incubated overnight with 5 μg of target antibodies or IgG at 4°C. Protein A/G magnetic beads (Pierce Classic Magnetic IP/Co-IP Kit, Thermo Scientific, 88804) were added to a 4°C shaker for 4 h. The immunoprecipitated protein complexes were washed with Co-IP wash buffer and resuspended in protein-loading buffer. Finally, the immunoprecipitated proteins were separated using SDS-PAGE and analyzed via immunoblotting. Plasmid construction, protein expression, and protein purification were performed by Sangon Biotech (Shanghai, China). All the antibodies used in Co-IP analysis are listed in the Supplementary Table 3.

RNA isolation and qRT-PCR assays
All primers were designed, synthesized, and PAGE-purified by Sangon Biotech (Shanghai, China). Total RNA was extracted using Trizol (Invitrogen, 15596018) and a total of 500 ng of RNA was reverse transcribed to cDNA using PrimeScript RT Master Mix (Takara, RR036A). The cDNA was subjected to qRT-PCR analysis with the TB Green Premix Ex Taq II (Takara, RR820A) using a CFX96 real-time PCR instrument (BIO-RAD, USA). The reaction mixture was predenatured at 95°C for 10 min, denatured at 95°C for 15 s, annealed at 60°C for 1 min and entered a melting-curve phase with 40 cycles of amplification. The levels of target mRNAs were normalized to those of β-Actin. The primer sequences are listed in Supplementary Table 4.

siRNA transfection
All siRNA were designed, synthesized, and PAGE-purified by Tsingke Biotech (Beijing, China). SiRNA was dissolved to a working concentration of 50 nM. Equal numbers of HSFs were plated on 6 or 24-well plates and then subjected to siRNA transfection by following the manufacturer’s instructions with Lipofectamine 3000 Transfection Reagent (Invitrogen, L3000015). Cells were harvested for subsequent experiments at 48h after transfection. The sequences of siRNA are listed in Supplementary Table 5.

Wound scratch assay
NSFs or HSFs were cultured in 6-well cell culture plates and grown to 90–100% confluence, scratching wounds were generated using a 200 µL sterile pipette tip. The shedding of the cell debris was washed off with PBS. After changing the serum-free medium, the culture was maintained for 24h. siRNA transfection was performed prior to cells being cultivated to 90–100% confluence, while other treatments involved sustained stimulation of the cells throughout the period before and after the wound scratch test. Photographs were captured at 0 and 24h after wound generation using an FSX100 microscope (Olympus, Japan). Subsequently, the wound areas were quantified using Image J software (National Institutes of Health, Bethesda, MD, USA).

Transwell assay
The migration abilities of NSFs and HSFs cells were evaluated using a chamber of 8-µm transwell inserts (Corning Life Science, USA). 2×104 Cells were plated in the upper transwell chamber of a 24-well plate in 200 µL medium without fetal bovine serum, while the lower chamber was filled with 700 µL medium containing 10% fetal bovine serum as the attractant. siRNA transfection was performed prior to Transwell assay, while other treatments supplemented in lower chamber medium. After the 24h incubation, the migrated cells were fixed with 4% paraformaldehyde (Servicebio, G1101) and stained with Crystal Violet Staining Solution (Beyotime, C0121). The stained cells were photographed using an FSX100 microscope (Olympus, Japan).

Non-targeted metabolomic
Non-targeted metabolomic were performed by Tgene Biotech (Shanghai, China) Co., Ltd. 100 mg solid sample was added to a 2 mL centrifuge tube and a 6 mm diameter grinding bead was added. 800 μL of extraction solution (methanol: water = 4:1 (v:v) containing four internal standards (0.02 mg/mL L-2-chlorophenylalanine, etc.) were used for metabolite extraction. Samples were ground by the Wonbio-96c (Shanghai wanbo biotechnology co., LTD) frozen tissue grinder for 6 min (-10°C, 50Hz), followed by low-temperature ultrasonic extraction for 30 min (5°C, 40kHz). The samples were left at -20°C for 30 min, centrifuged for 15 min (4°C, 13000g), and the supernatant was transferred to the injection vial for LC-MS/MS analysis. The LC analysis was performed on a Vanquish UHPLC System (Thermo Fisher Scientific, USA). Chromatography was carried out with an ACQUITY UPLC® HSS T3 (2.1×100 mm, 1.8 µm) (Waters, Milford, MA, USA). The column maintained at 40°C. The flow rate and injection volume were set at 0.3 mL/min and 2 μL, respectively. For LC-ESI(+)-MS analysis, the mobile phases consisted of (B2) 0.1% formic acid in acetonitrile (v/v) and (A2) 0.1% formic acid in water (v/v). Separation was conducted under the following gradient: 0~1 min, 8% B2; 1~8 min, 8%~98% B2; 8~10 min, 98% B2; 10~10.1 min, 98%~8% B2; 10.1~12 min, 8% B2. For LC-ESI(-)-MS analysis, the analytes was carried out with (B3) acetonitrile and (A3) ammonium formate (5 mM). Separation was conducted under the following gradient: 0~1 min, 8% B3; 1~8 min, 8%~98% B3; 8~10 min, 98% B3; 10~10.1 min, 98%~8% B3; 10.1~12 min, 8% B3. Mass spectrometric detection of metabolites was performed on Q Exactive (Thermo Fisher Scientific, USA) with ESI ion source. Simultaneous MS1 and MS/MS (Full MS-ddMS2 mode, data-dependent MS/MS) acquisition was used. The parameters were as follows: sheath gas pressure, 40 arb; aux gas flow, 10 arb; spray voltage, 3.50 kV and -2.50 kV for ESI(+) and ESI(-), respectively; capillary temperature, 325°C; MS1 range, m/z 100-1000; MS1 resolving power, 70000 FWHM; number of data dependents scans per cycle, 10; MS/MS resolving power, 17500 FWHM; normalized collision energy, 30 eV; dynamic exclusion time, automatic.

Non-targeted metabolomic data preprocessing and analysis
The raw data were firstly converted to mzXML format by MSConvert in ProteoWizard software package (v3.0.8789) and processed using R XCMS (v3.12.0) for feature detection, retention time correction and alignment. Key parameters settings were set as follows: ppm=15, peakwidth=c(5,30), mzdiff=0.01, method=centWave. The batch effect was then eliminated by correcting the data based on QC samples. Metabolites with RSD > 30% in QC samples were filtered and then used for subsequent data analysis. The metabolites were identified by accuracy mass and MS/MS data which were matched with HMDB, massbank, KEGG, LipidMaps, mzcloud and the metabolite database build by Tgene Biotech (Shanghai) Co., Ltd. (Shanghai, China). The molecular weight of metabolites was determined according to the m/z (mass-to-charge ratio) of parent ions in MS data. Molecular formula was predicted by ppm (parts per million) and adduction, and then matched with the database. At the same time, the MS/MS data from quantitative table of MS/MS data, were matched with the fragment ions and other information of each metabolite in the database, so as to realize the MS/MS identification of metabolite. Two different multivariate statistical analysis models, unsupervised and supervised, were applied to discriminate the groups (PCA; PLS-DA; OPLS-DA) by R ropls (v1.22.0) package. The statistical significance of P value was obtained by statistical test between groups. Finally, combined with P value, VIP (OPLS-DA variable projection importance) and FC (multiple of difference between groups) to screen biomarker metabolites. By default, when P value < 0.05 and VIP value > 1, we think that metabolite were considered to have significant differential expression.

Targeted energy metabolomic data preprocessing and analysis
Non-targeted metabolomic were performed by Metware Metabolism Biotech (Wuhan, China) Co., Ltd. HPLC-grade acetonitrile (ACN) and methanol (MeOH) were purchased from Merck (Darmstadt, Germany). MilliQ water (Millipore, Bradford, USA) was used in all experiments. All of the standards were purchased from Sigma-Aldrich (St. Louis, MO, USA) and Zhenzhun etc. Formic acid was bought from Sigma-Aldrich (St. Louis, MO, USA). The stock solutions of standards were prepared at the concentration of 1 mg/mL in MeOH and other solutions. All stock solutions were stored at -20°C. The stock solutions were diluted with MeOH to working solutions before analysis. After the sample was thawed and smashed, an amount of 0.05 g of the sample was mixed with 500 µL of 70% methanol/water. The sample was vortexed for 3 min under the condition of 2500 r/min and centrifuged at 12000 r/min for 10 min at 4°C. Take 300 µL of supernatant into a new centrifuge tube and place the supernatant in -20°C refrigerator for 30 min, Thenthe supernatant was centrifuged again at 12000 r/min for 10 min at 4°C. After centrifugation, transfer 200 µL of supernatant through Protein Precipitation Plate for further LC-MS analysis. All those metabolites were detected by MetWare (http://www.metware.cn/) based on the AB Sciex QTRAP6500 LC-MS/MS platform. Significantly regulated metabolites between groups were determined by VIP and absolute Log2FC (fold change). VIP values were extracted from OPLS-DA result, which also contain score plots and permutation plots, and was generated using R package MetaboAnalystR. The data was mean centering before OPLS-DA. In order to avoid overfitting, a permutation test (200 permutations) was performed. Identified metabolites were annotated using KEGG compound database (http://www.kegg.jp/kegg/compound/), annotated metabolites were then mapped to KEGG Pathway database (http://www.kegg.jp/kegg/pathway.html). Pathways with significantly regulated metabolites mapped to were then fed into MSEA(metabolite sets enrichment analysis), their significance was determined by hypergeometric test’s P Values.

CUT&Tag
CUT&Tag were performed by Wuhan IGENEBOOK Biotechnology Co., Ltd (Wuhan, China). Briefly, CUT&Tag assays were performed by using Hyperactive Universal CUT&Tag Assay Kit for Illumina Pro (Vazyme Biotech, TD904). Briefly, NS and HS samples were dissociated into nucleus suspension, nucleus were harvested and incubated with concanavalin A coated magnetic beads for 15 min at RT. Then, bead-bound nucleus were resuspended and incubated with H3K23la antibody (PTM-1413RM, PTM BIO) and IgG (2729, Cell Signaling Technology) overnight at 4°C. Afterwards, goat anti-rabbit secondary antibody (35401, Cell Signaling Technology) was added to this mixture for 30 min at RT. The magnet stand was used to remove unbound antibodies. pA/G-Tn5 adapter complex was added at this step at RT for 1 h, then remove unbound pA-Tn5 protein. Next, cells were resuspended in tagmentation buffer at 37°C for 1 h. After that, immunoprecipitated DNA was saved. To amplify libraries, 21 µL DNA was mixed with 2 µL of a universal i5 and a uniquely barcoded i7 primer, using a different barcode for each sample. A volume of 25 µL NEBNext High-Fidelity 2X PCR Master Mix (New England Biolabs, M0541) was added and mixed. The sample was placed in a Thermocycler with a heated lid using the following cycling conditions: 72°C for 5 min (gap filling); 98°C for 30 s; 14 cycles of 98°C for 10 s and 63°C for 30 s; final extension at 72°C for 1 min and hold at 8°C. Library was sequenced on Illumina novaseq 6000 with PE150 method.

CUT&Tag data analysis and visualization
Trimmomatic (version 0.36) was used to filter out low-quality reads. Clean reads were mapped to the GRCh38.p14 genome by Bwa (version 0.7.15). Samtools (version 1.3.1) was used to remove potential PCR duplicates. MACS2 software (version 2.1.1.20160309) was used to call peaks by default parameters (bandwidth, 300 bp; model fold, 5, 50; p value, 0.00001). If the midpoint of a peak is located closest to the TSS of one gene, the peak will be assigned to that gene. HOMER (version 3) was used to predict motif occurrence within peaks with default settings for a maximum motif length of 12 base pairs. Cluster Profiler in R package was employed to perform GO and KEGG enrichment analysis. The GO and KEGG enrichment analysis were calculated using hypergeometric distribution with a qvalue cutoff of 0.05. The data were visualized using the IGV (version 2.19.3).

Total RNA extraction, RNA-seq library construction and sequencing
RNA-seq were performed by Wuhan IGENEBOOK Biotechnology Co., Ltd. Briefly, the total RNA was extracted using Trizol method. All the RNA samples were assessed for their integrity using Qsep400 instrument. To construct RNA libraries with the VAHTS mRNA-seq V8 Library Prep Kit for Illumina, 1 µg of total RNA was used. The procedure included PolyA-selected RNA extraction, RNA fragmentation, random hexamer primed reverse transcription, and 150 nt paired-end sequencing by Illumina Novaseq 6000.

Bioinformatics analysis of RNA-seq
The adapter and low-quality reads were filtered out through Cutadapt (version 1.11). Clean reads were mapped to the GRCh38.p14 reference genomes by Hisat2 (version 2.1.0), allowing up to two mismatches. These genes were subjected to alignment against public protein databases; NR (RefSeq non-redundant proteins). Feature count (v1.6.0) was used for transcript abundance estimation and normalization of expression values as FPKM (Fragments per kilobase of transcript per million fragments mapped). Differentially expressed genes were identified with edgeR with a filter threshold of FDR < 0.05 and |log2FoldChange| > 1. Cluster Profiler in R package was employed to perform GO and KEGG enrichment analysis. The GO and KEGG enrichment analysis were calculated using hypergeometric distribution with a p-value cutoff of 0.05.

ChIP-qPCR
Chromatin immunoprecipitation assays were performed by Wuhan IGENEBOOK Biotechnology Co., Ltd. Briefly, 2-4g samples were washed twice in cold PBS buffer and cross-linked with 1% formaldehyde for 10 minutes at room temperature and then quenched by addition of glycine (125 mmol/L final concentration). Afterwards, samples were lysed, and chromatins were obtained on ice. Chromatins were sonicated to get soluble sheared chromatin (average DNA length of 200–500 bp). 20 ul chromatin was saved at –20°C for input DNA, and 100 ul chromatin was used for immunoprecipitation by primary antibodies and Anti-IgG (2729, Cell Signaling Technology) respectively. 10 µg of antibody was used in immunoprecipitation reactions at 4°C overnight. The next day, 30 µL of protein G beads (10004D, Invitrogen) were added and the samples were further incubated for 3 h. The beads were next washed once with 20 mM Tris/HCL (pH 8.1), 50 mM NaCl, 2 mM EDTA, 1% Triton X-100, 0.1% SDS; twice with 10 mM Tris/HCL (pH 8.1), 250 mM LiCl, 1 mM EDTA, 1% NP-40, 1% deoxycholic acid; and twice with 1× TE buffer (10 mM Tris/HCL at pH 7.5 and 1 mM EDTA). Bound material was then eluted from the beads in 300 µL of elution buffer (100 mM NaHCO3 and 1% SDS), treated first with RNase A (final concentration 8 µg/mL) during 6 h at 65°C and then with proteinase K (final concentration 345 µg/mL) overnight at 45°C. Immunoprecipitated DNA was amplified by PCR using their specific primers. The enrichment values were normalized to the input sample and calculated using the 2^(-ΔΔCt) method. All primers are listed in the Supplementary Table 6.

Measurements of lactate
The levels of lactate in frozen tissues, culture medium and cells were determined using commercially available L-Lactate Assay kit (65331, Abcam) following the manufacturer’s instructions.

Seahorse assay
The extracellular acidification rate (ECAR) of the THP-1 cells, HUVECs and NSFs were assessed according to the manufacturer’s protocol using a Seahorse XFe96 Analyzer (Agilent Technologies, US). On the day of the assay, cells were seeded into a Seahorse 96-well microplate (103794-100, Agilent Technologies) at a density of 2×104 cells (THP-1 cells and HUVECs) or 1×104 cells (NSFs) per well, followed by high substrate stiffness or THF-β treatment for 10 days before measurement. The next day, the growth medium in the wells was replaced with Seahorse XF DMEM medium (103680-100, Agilent Technologies), which was freshly supplemented with glutamine (4 mM) and warmed to 37 °C. For ECAR measurement, glucose, oligomycin and 2-deoxyglucose were added to final concentrations of 10 mM, 2 µM and 100 mM, respectively. The ECAR were measured three times at baseline and three times after each drug was added, with the average taken from multiple measurements calculated. The ECAR was normalized to the cell number at the end of the experiments. Data were analyzed using Seahorse XF96 Wave software (version 2.2), and the results were represented as mpH/min.

Immunohistochemistry
The skin and scar tissues from patients and mice models were fixed with 4% paraformaldehyde (Servicebio, G1101) overnight and embedded in paraffin, and 5-µm-thick sections were prepared. Tissue sections were deparaffinized, followed by rehydrated in xylene and graded concentrations of ethanol. Quenching of endogenous peroxidase activity was achieved using 3% hydrogen peroxide, while antigen retrieval was performed with an EDTA buffer. The tissue was uniformly covered with 3% BSA in the tissue chemical circle and closed at room temperature for 30 min. Then, sections were incubated overnight at 4°C in a humid chamber with the indicated primary antibodies. The DAB chromogenic reagent for histochemical kit (Servicebio, G1212) was employed to visualize the staining after 1 h incubation with secondary antibodies at room temperature. The antibodies used in this study are listed in the Supplementary Table 3.

Immunofluorescence staining
The skin and scar tissues from patients and mice models were fixed with 4% paraformaldehyde (Servicebio, G1101) overnight and embedded in paraffin, and 5-µm-thick sections were prepared. Put the tissue section in 3 changes of xylene, 10 min each, then dehydrate in 3 changes of pure ethanol for 5 min each, wash in distilled water. After the antigen retrieval was performed, it is naturally cooled. Put the slide for 5 min PBS (PH 7.4) and shake it on a decoloring shaker for 3 times, each time for 5 minutes. Thereafter, 10% BSA was used to block the tissue at room temperature for 60 min. Thereafter, the tissues were incubated overnight with primary antibodies at 4 °C. After washing thrice with PBS, the tissues were incubated in the dark with secondary antibodies for 1 h and DAPI for 10 min at room temperature. Images were captured using a laser confocal scanning microscope (Zeiss, Germany). The antibodies used in this study are listed in the Supplementary Table 3.

For cells Immunofluorescence staining, NSFs or HSFs were fixed with 4% paraformaldehyde (Servicebio, G1101) for 20 min and permeabilized with 0.5% Triton X-100 (Servicebio, G1204) for 20 min at room temperature. Thereafter, 3% BSA was used to block the cells at room temperature for 60 min. Cells were subsequently incubated overnight with primary antibodies at 4°C. After washing three times with PBST, the cells were incubated with secondary antibodies for 1 h and with 4,6-diamidino-2-phenylindole (DAPI, Beyotime) in the dark for 10 min at room temperature. Images were captured using an FSX100 microscope (Olympus, Japan). Quantitative analysis of colocalization was performed using the ImageJ software (v1.53, USA) equipped with the JACoP Plugin. The antibodies used in this study are listed in the Supplementary Table 3.

H&E, Masson, and Sirius red staining
Wound and scar tissue at the dorsal skin of mice were studied using tissue cross-sections. At 14 days post full-thickness skin wound modeling, the wound and surrounding normal skin were dissected out and embedded within an OCT compound (Sakura, 4583). The portion containing the wound was cut consecutively into 5 µm sections. To assess the wound healing, scar formation, collagen content, and fibrosis level, sections were stained with H&E staining (C0105, Beyotime, China), Masson (G1006, Servicebio, China), and Sirius red (PH1099, Phygene, China) for fibrosis analysis according to the manufacturer’s instructions. Images were captured using a bright-field microscope (CX33, Olympus, Japan). Quantitative analysis was performed using the ImageJ software (v1.53, USA).

Molecular docking
Structural predictions of the MCT1 protein (PDB ID: 7cko) and COL11A1 protein (UniProt ID: P12107) were initially conducted using AlphaFold3. Subsequent protein structure optimization involved protonation state determination at physiological conditions (pH 7.0) through the H++ web server (version 3.0), followed by Amber14SB partial charge assignment using UCSF Chimera software. Molecular docking simulations were performed with AutoDock Vina (version, 1.2.5) employing the empirical iterative scoring function ITScorePP, where negative binding scores indicate favorable molecular interactions with magnitude reflecting binding affinity strength. The docking protocol was configured to generate 100 output conformations, with the top 10 scored conformations selected for analysis. The highest-ranked conformation based on docking score underwent three-dimensional structural visualization using PyMOL (version, 2.5.7). For lactate introduction studies, Gasteiger partial charges were assigned via the prepare_ligand4 script in MGLtools (version, 1.4.2). Subsequent docking experiments with AutoDock Vina (version, 1.2.5) utilized the lactate-binding site as the docking centroid within a cubic box (15 Å edge length), generating 20 conformations that were ranked by binding scores. The conformation exhibiting maximal absolute score magnitude was selected for subsequent analytical procedures.

Molecular dynamics simulations
The molecular dynamics simulations were conducted using the Gromacs (version, 2023.2) software package. The AMBER99SB-ILDN force field was employed for the protein system, while small molecules were processed through AmberTools21 to acquire AM1-BCC charges and parameterized using the GAFF force field. The TIP3P water model was implemented within a cubic periodic boundary system encompassing both protein and ligand components. Non-bonded interactions were treated with a 1.0 nm cutoff for both electrostatic and van der Waals forces, complemented by the Particle Mesh Ewald (PME) method for long-range electrostatic corrections. Simulations utilized a 2 fs integration time step under isothermal-isobaric conditions (303.15 K maintained via V-rescale thermostating and 1 bar pressure regulated through Parrinello-Rahman barostat). The system underwent sequential energy minimization, followed by 200 ps NVT ensemble equilibration and 100 ps NPT ensemble equilibration. Production dynamics were extended to 100 ns for trajectory sampling. Structural stability was analyzed through root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) calculations using native Gromacs utilities. Binding free energy estimations were performed via the gmx_MMPBSA toolkit (version 1.6.4) employing molecular mechanics/Poisson-Boltzmann surface area methodology.

Statistical analysis
Statistical analyses were performed using GraphPad Prism software (version 10.0). Image analysis was performed using Fiji (ImageJ). All samples and mice were randomly allocated to experimental groups on a per-experiment basis. Because measurements are quantitative, data from the experiments are shown as the mean ± standard deviation (SD) unless otherwise described. After using the Shapiro–Wilk test and the Brown–Forsythe tests to confirm that the data were normally distributed and equal in variance, appropriate statistical tests were selected. The two groups were compared using Student’s unpaired t-test. Multiple groups were analyzed using one-way analysis of variance or two-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison test. Where data did not conform to a normal distribution in both groups, analysis was performed using the Mann-Whitney U test. Statistical parameters can be found in figures and figure legends.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this manuscript, the authors investigated the critical role of macrophage-derived lactate in the progression of hypertrophic scarring (HS), offering valuable insights into its pathogenesis. Initially, by comparing normal and HS human samples, the authors identified a significant metabolic shift from oxidative phosphorylation in normal tissue to glycolysis in HS, marked by notable lactate accumulation; subsequently, they demonstrated that macrophages, rather than fibroblasts or vascular endothelial cells, are the primary lactate producers in response to increased mechanical stiffness of the substrate extracellular matrix (ECM) in vitro. Mechanistically, the authors propose novel lactate—monocarboxylate transporter (MCT1) —histone H3 lysine 23 lactylation (H3K23la)—Hairy-related family bHLH transcription factor with YRPW motif 2 (HEY2)/collagen type XI (COL11)—Yes1 associated transcriptional regulator (YAP1)/Smad family member 2 (SMAD2) pathway to drive fibrotic processes in HS, supported by evidence that pharmacological inhibition of this cascade effectively reduces fibroblast activation and collagen deposition. Furthermore, utilizing a splinted excision wound model in mice with the C57BL/6 background, the authors found that sodium lactate delayed wound reepithelialization while disrupting Mct1 signaling pathways accelerated wound closure. The manuscript is well-crafted with minimal typographical errors and provides sufficiently detailed methods to ensure experimental reproducibility. However, several specific concerns have been identified during the review process that, in my opinion, should be addressed prior to publication.\n\nConcerns with the manuscript:\n1. It is unclear why gene expression data were presented by a heatmap (e.g., Figs. 1B, 3F, and 3K). While heatmaps with color gradients effectively summarize large datasets and may facilitate clustering to uncover gene-sample relationships, their application seems less advantageous here, given the limited comparison of only a few genes across two groups; furthermore, they fail to convey detailed information on data distribution (e.g., standard deviation) or statistical significance.\n2. Some immunofluorescent staining figures (e.g., Figs. 1E, 1F, 6A, 6B, 6E, and 8D, as well as Supplementary Figs. 1B, 2A, 2C, 3D, 4D, 5D, 5E, 6D, 6E, and 9A) are presented in low quality, which hinders a thorough assessment of the data.\n3. Transwell assays (e.g., Supplementary Figs. 1D, 2B, 2D, 3E, 4E, and 6E) should be quantified to enhance reliability, as it is widely recognized that single representative photographs may introduce artificial effects, particularly in transwell assays where uneven cell distribution is evident, as seen in the second panel of Supplementary Fig. 2B.\n4. Supplementary Fig. 1E is cited in the main text before Supplementary Fig. 1B-D.\n5. The authors compellingly demonstrated that a pathologically (high) stiff ECM enhances lactate production by macrophages, a key finding in this study. Since a high-stiff ECM is a defining characteristic of HS, reflecting the altered biomechanical and biochemical environment that drives excessive scar formation, it raises the question of whether HS formation, to some extent, precedes and triggers lactate production, potentially exacerbating the condition. The critical cause-and-effect relationship between HS initiation/establishment and lactate secretion should be demonstrated convincingly before moving to the other studies in this manuscript. Moreover, if HS onset precedes lactate release, it is critical to investigate whether and how the proposed strategy can effectively reverse this pathological process, which is essential for clinical applications in the real world.\n6. Lines 236-237, ‘We selected si-MCT1-1 or subsequent experiments which exhibited the highest knockdown efficiency.’\nFirstly, the study includes only two groups with the knockdown procedure, indicating a need for careful language revision. (A similar concern is also raised regarding the statements related to si-HEY2-1 and si-COL11A1-2.)\nSecondly, the relevant data (Supplementary Fig. 3A, second panel) do not support the statement, as no statistical differences are observed between si-MCT1-1 and si-MCT1-2 according to the provided source data.\n7. Type XI collagen is a heterotrimer, comprising three distinct polypeptide chains—alpha1(XI), alpha2(XI), and alpha3(XI)— encoded by the genes Col11A1, Col11A2, and Col2A1, respectively. It is noteworthy that only Col11A1 appears to be affected, which merits a more thorough discussion to explore the underlying mechanisms and implications.\n8. The quality of Fig. 7D and 8A is insufficient for proper assessment. It needs improvement to enable a thorough evaluation.\n9. In Fig. 8E, the enlarged section: The notes of amino acid interactions are blurry. A similar illustration to Fig. 8F should be considered.\n10. The splinted excisional wound model in mice used in the current study is a widely recognized tool for studying wound healing, as it effectively simulates crucial processes like re-epithelialization and granulation tissue formation that occur in humans. However, it falls short of being a standard model for HS. A compelling 2022 systematic review of HS animal models (PMID: 35743999) concluded that no murine model, including those utilizing splinted wounds, can truly replicate the intricacies of human hypertrophic scars. This limitation arises from fundamental differences in skin anatomy and healing mechanisms between species. It is essential to acknowledge these differences and consider using more suitable models for the current research.\n11. Delayed wound closure is not a defining characteristic of HS. Instead, its occurrence is usually influenced by factors such as infection, inadequate blood supply, or underlying conditions like diabetes. While delayed healing can be seen as a general indicator of wound healing and may lead to chronic wounds (e.g., ulcers), it does not specifically lead to HS. However, it can create conditions that predispose wounds to HS, especially in situations involving prolonged inflammation or mechanical tension. In contrast, the formation of HS is more directly related to the quality of healing, particularly excessive deposition of ECM, rather than the speed of wound closure. For instance, HS can develop in wounds that heal quickly if they are accompanied by exaggerated inflammatory and fibrotic responses. Therefore, it is important to carefully reconsider the interpretation of animal study data in light of these insights.\n12. Lines 400-402, ‘According to the specific structure of the skin shown by HE staining, collagen arrangement was smoother and more orderly … ’\nFirstly, the description of ‘the specific structure’ requires more detail to enhance clarity and understanding.\nSecondly, incorporating established methods to quantitatively assess the smoothness and orderliness of collagen fibers would strengthen the supporting evidence for the statement.\n13. The ratio of collagen I to collagen III undergoes a dynamic shift during the wound healing process, reflecting the stages of tissue repair and remodeling. Thus, the noted reduction in the collagen I/III ratio in Figs. 9 and 10 may be just a secondary effect of delayed healing, which should not be overrated.\n14. Line 475: The reference to Zhang et al. should be provided.", "reviewer_2": "In the manuscript titled “Lactate derived from macrophages drives skin dermal fibroblasts phenotypic remodeling via MCT1‑primed histone H3 lysine 23 lactylation in hypertrophic scar,” the authors investigate how matrix stiffness–activated macrophages produce excess lactate, which is shuttled into dermal fibroblasts via MCT1. This influx promotes site‑specific histone H3K23 lactylation (H3K23la), leading to upregulation of profibrotic genes HEY2 and COL11A1. Through CUT&Tag, RNA‑seq, molecular simulations, and both genetic (fibroblast‑specific Mct1 knockout) and pharmacological (AZD3965) interventions in murine wound models, they demonstrate that disrupting the MCT1–H3K23la–HEY2/COL11A1 feedback loop attenuates hypertrophic scar formation. The presented findings are new and supported by the experimental data. The reviewer has several comments listed below.\n1) The immunofluorescence images in Figure 1F show MCT1 colocalization with α‑SMA–positive myofibroblasts, but no quantitative colocalization analysis (e.g., Pearson’s coefficient) is provided. Please include such metrics to substantiate the claim.\n2) The rationale for using 10 ng/mL TGF‑β is not explained. Cite relevant literature or provide preliminary data to justify this concentration.\n3) The manuscript proposes that lactate enters fibroblasts via MCT1 to induce H3K23la and activate HEY2 and COL11A1 transcription, but lacks details on the dynamic regulation of this process. For example, the dose–response relationship between lactate concentration and H3K23la levels has not been fully characterized..\n4) The authors state that 2 kPa and 50 kPa hydrogels were used to model physiological and pathological matrix stiffness, but no supporting references or experimental stiffness measurements are provided. Please cite precedent studies or supply experiment data.", "reviewer_3": "In their manuscript, entitled “Lactate derived from macrophages drives skin dermal fibroblasts’ phenotypic remodeling via MCT1-primed histone H3 lysine 23 lactylation in hypertrophic scar,” Yuan et al. investigate increased lactate production in the hypertrophic skin and its influence on fibroblast function in fibrosis and wound healing. The authors further determined that MCR-1 functions to transport lactate into fibroblasts, where it is utilized for histone lactylation. This, in turn, activates the transcription of profibrotic genes HEY2 and COL11A1, which activate YAP1 expression and aggravate lactate accumulation, respectively. Finally, the authors test the relevance of MCT1 expression in skin fibroblasts using a wound healing model, employing genetic depletion and compound blocking.\nThis reviewer is deeply concerned about the novelty of the findings, the technical quality of the presented data, and the technical quality of the manuscript. The role of MCT1 in fibrosis and keloid fibroblasts has been known for some time (Jinhua Feng et al., 2024; David R. Ziehr et al., 2024 preprint; Kyounghee Min, 2023; Jing-Jing Gu 2025, and many others), as well as the role of lactylation in fibrosis (Huanwei Liang et al., 2025 review). Therefore, the novelty of the study results is limited, if any.\nThe presented manuscript is generally poorly written, contains numerous grammatical errors, and references data that are not present in the figures. Additionally, it includes too many figures that do not contribute to the study's quality.\nMajor concerns:\n1. The majority of the paper utilizes an in vitro system to investigate a complex and multifaceted disease that affects complex tissue, while only selected experiments employ tissue samples. It is unclear why these shifts in experimental systems are made, as they are by no means beneficial to the study.\n2. In the first figure, authors proceed directly to measuring lactate levels in the hypertrophic skin, providing little justification for why they chose to present precisely this metabolite and not assess the overall metabolomic profile of hypertrophic versus normal skin. The authors should provide an extended metabolomic profile of hypertrophic versus normal skin, allowing for a comparison of the presence of different metabolites in the skin.\n3. If the authors want to discuss shifts between energy-supplying pathways, they should demonstrate that the actual transition from one to another occurs. What is the relative expression of genes involved in oxidative phosphorylation? Is glycolysis indeed the dominating pathway used for energy generation in the hypertrophic skin?\n4. The quality of IF is very poor, and it´s difficult to see individual cells. Higher quality imaging should be provided.\n5. There is a discrepancy in the relative protein expression measured by Western blot, IHC, and IF in Figure 1. The authors should explain why.\n6. The authors talk about data that is not present in the figure: “ and we did not observe noticeable differences of MCT1 intensity in vascular endothelial cells between NS and HS (Figure 1F)” – no markers of vascular endothelial cells has been used in the whole figure, and in particular not the referred Figure 1F.\n7. In Figure 2, the authors use an in vitro system to investigate the cellular origin of lactate, which is detected in hypertrophic skin tissue. This approach is reductionistic, as it does not aim to identify which of the various cell types in the hypertrophic skin is the primary producer of lactate. Instead, they select specific cells to probe for lactate production. The authors should either use patient material (as in Figure 1) or the developed mouse model to answer this question.\n8. The molecular interaction modeling exercise doesn’t contribute to the main message of the study.", "reviewer_4": "In the study titled “Lactate derived from macrophages drives skin dermal fibroblasts phenotypic remodeling via MCT1-primed histone H3 lysine 23 lactylation in hypertrophic scar,” Hu et al. delineated the role of macrophage-derived lactate in hypertrophic scar (HS) formation. They identified that macrophage-derived lactate serves as a critical mediator of fibroblast phenotypic remodeling through monocarboxylate transporter 1 (MCT1)-mediated histone H3 lysine 23 lactylation (H3K23la) in HS. The authors observed that fibroblast-specific deletion of Mct1 or pharmacological inhibition of Mct1 in mice reduced collagen deposition, accelerated wound healing, and attenuated scar formation.\nThe study is highly interesting, well designed, and clearly presented. Nevertheless, several minor issues need to be addressed:\n1. Multiple immunofluorescence images in the manuscript are of relatively low resolution (e.g., Figure 1E and Figure S6). Higher-resolution images should be provided.\n2. In Figure 9C and Figure 10C, the blue coloration of the Masson’s trichrome staining is uneven, suggesting possible overstaining. Higher-resolution Masson’s staining images are required.\n3. The authors demonstrated in vitro that macrophages are the primary source of lactate accumulation in the scar metabolic microenvironment. Given the substantial differences between in vitro and in vivo conditions, in vivo validation of macrophage-mediated lactate accumulation in the hypertrophic scar microenvironment would further strengthen the credibility of this conclusion.\n4. The authors identified an interaction between COL11A1 and MCT1. However, it remains unclear whether additional proteins are involved in this interaction. Further experimental validation or detailed discussion in the Discussion section is warranted.\n5. The authors observed elevated lactate levels and increased MCT1 expression in HS tissues. What is the relationship between lactate levels, MCT1 expression, and HS disease progression?\n6. In Figure S6C, nonspecific bands are present for COL11A1, and the two bands in the si-NC group are difficult to distinguish. A clearer Western blot image should be provided."}, "author_response": "Response to Reviewers\nDear Editors and Reviewers,\nThank you for your letter and for the reviewers’ comments concerning our manuscript entitled\n“Lactate derived from macrophages drives skin dermal fibroblasts phenotypic remodeling via\nMCT1-primed histone H3 lysine 23 lactylation in hypertrophic scar” (Manuscript Number:\nNCOMMS-25-39200). Those comments are all valuable and very helpful for revising and\nimproving our manuscript, as well as the important guiding significance to our researches. We\nhave studied comments carefully and have made corrections which we hope meet with\napproval. Revised portions are marked in yellow in the revised manuscript. The main\ncorrections in the paper and the responses to the reviewer’s comments are as flowing:\nResponses to the reviewer’s comments:\nReviewer #1:\nIn this manuscript, the authors investigated the critical role of macrophage-derived lactate in\nthe progression of hypertrophic scarring (HS), offering valuable insights into its pathogenesis.\nInitially, by comparing normal and HS human samples, the authors identified a significant\nmetabolic shift from oxidative phosphorylation in normal tissue to glycolysis in HS, marked\nby notable lactate accumulation; subsequently, they demonstrated that macrophages, rather\nthan fibroblasts or vascular endothelial cells, are the primary lactate producers in response to\nincreased mechanical stiffness of the substrate extracellular matrix (ECM) in vitro.\nMechanistically, the authors propose novel lactate—monocarboxylate transporter (MCT1)—\nhistone H3 lysine 23 lactylation (H3K23la)—Hairy-related family bHLH transcription factor\nwith YRPW motif 2 (HEY2)/collagen type XI (COL11)—Yes1 associated transcriptional\nregulator (YAP1)/Smad family member 2 (SMAD2) pathway to drive fibrotic processes in\nHS, supported by evidence that pharmacological inhibition of this cascade effectively reduces\nfibroblast activation and collagen deposition. Furthermore, utilizing a splinted excision\nwound model in mice with the C57BL/6 background, the authors found that sodium lactate\ndelayed wound reepithelialization while disrupting Mct1 signaling pathways accelerated\nwound closure. The manuscript is well-crafted with minimal typographical errors and\nprovides sufficiently detailed methods to ensure experimental reproducibility. However,\nseveral specific concerns have been identified during the review process that, in my opinion,\nshould be addressed prior to publication.\nConcerns with the manuscript:\nComment #1: It is unclear why gene expression data were presented by a heatmap (e.g., Figs.\n1B, 3F, and 3K). While heatmaps with color gradients effectively summarize large datasets\nand may facilitate clustering to uncover gene-sample relationships, their application seems\nless advantageous here, given the limited comparison of only a few genes across two groups;\nfurthermore, they fail to convey detailed information on data distribution (e.g., standard\ndeviation) or statistical significance.\nReply:\nThanks for your suggestions. We have carefully considered your valuable comment regarding\nthe use of heatmaps. We fully agree with your point that heatmaps are not the most effective\nway to present data when comparing a limited number of genes between only two groups.\nFollowing your recommendation, we have revised the figures and have replaced the heatmaps\nin Figure 1B, 3F, and 3K with bar graphs in the revised manuscript. The new figures clearly\ndisplay the mean and standard deviation of the gene expression data and, most importantly,\ninclude statistical significance to provide a more comprehensive and accurate representation\nof our findings. Thank you again for your guidance.\nRevised figures:\nFigure 1B\nFigure 3F\nFigure 3K\nComment #2: Some immunofluorescent staining figures (e.g., Figs. 1E, 1F, 6A, 6B, 6E, and\n8D, as well as Supplementary Figs. 1B, 2A, 2C, 3D, 4D, 5D, 5E, 6D, 6E, and 9A) are\npresented in low quality, which hinders a thorough assessment of the data.\nReply:\nThank you for your valuable feedback and the time you have dedicated to reviewing our\nmanuscript. We sincerely apologize for the low quality of the immunofluorescent images in\nthe original submission. We agree that high-quality images are crucial for the interpretation of\nthe data presented. In response to your comment, we have carefully revised all the figures you\nmentioned. Specifically, we have replaced the original images in Figures 1E, 1F, 6A, 6B, 6E,\nand 8D, as well as in Supplementary Figures 2B, 4A, 4C, 6D, 7D, 8B, 8C, 9F, 9G, and 11D,\nwith new, high-resolution versions. These new images provide much greater clarity and detail,\nwhich we believe will allow for a comprehensive and accurate assessment of our findings. As\nseen in the revised manuscript, these figures now clearly show the co-localization and\nexpression levels of the stained markers. For example, in the updated Figure 1F, the specific\nupregulation of MCT1 in α-SMA+ myofibroblasts in hypertrophic scar tissue is now much\nmore distinct. Similarly, the revised Figures 6A and 6B now provide a clearer visualization of\nthe colocalization of HEY2 and COL11A1 with α-SMA in hypertrophic scar dermal\nmyofibroblasts. We have ensured that all images in the revised manuscript meet the high-\nquality standards required for publication. We are confident that these changes have\nsignificantly strengthened our manuscript and have addressed your concerns. Once again, we\nthank you for your insightful feedback. We hope that the revised manuscript is now suitable\nfor publication.\nRevised figures:\nFigure 1F\nFigure 6A\nFigure 6B\nComment #3: Transwell assays (e.g., Supplementary Figs. 1D, 2B, 2D, 3E, 4E, and 6E)\nshould be quantified to enhance reliability, as it is widely recognized that single representative\nphotographs may introduce artificial effects, particularly in transwell assays where uneven\ncell distribution is evident, as seen in the second panel of Supplementary Fig. 2B.\nReply:\nThanks for your suggestions. We appreciate your insightful comments regarding the\nTranswell assays. We agree that quantification is crucial for enhancing the reliability of these\nresults and that relying solely on single representative photographs can indeed introduce\npotential artifacts, especially given the possibility of uneven cell distribution. For each\nexperiment, we captured multiple images from different areas of each Transwell membrane.\nThe number of migrated cells was then counted and the data are now presented as graphs,\nshowing the mean and standard deviation from replicate experiments. We have now\nperformed quantification for all Transwell assays presented in the manuscript (Figure 6G, 6H\nand Supplementary Figure 2E, 4B, 4D, 6F, 7F). Furthermore, we have specifically addressed\nyour concern about the uneven cell distribution observed in the second panel of\nSupplementary Figure 4B. We have replaced the previous representative image with a new\none that accurately reflects the results of the quantified data. Thank you again for your\nguidance.\nRevised figure:\nFigure 6G\nFigure 6H\nFigure S2E\nFigure S4B\nFigure S4D\nFigure S6F\nFigure S7F\nComment #4: Supplementary Fig. 1E is cited in the main text before Supplementary Fig. 1B-\nD.\nReply:\nThanks for your suggestions. We apologize for this error in the previous version of the\nmanuscript. As suggested, we have revised the manuscript to ensure that all supplementary\nfigures are cited in the correct order. The citation for Supplementary Figure 2B-D now\nprecedes Supplementary Figure 2E in the main text. Thank you again for your guidance.\nRevised figures:\nFigure S2\nComment #5: The authors compellingly demonstrated that a pathologically (high) stiff ECM\nenhances lactate production by macrophages, a key finding in this study. Since a high-stiff\nECM is a defining characteristic of HS, reflecting the altered biomechanical and biochemical\nenvironment that drives excessive scar formation, it raises the question of whether HS\nformation, to some extent, precedes and triggers lactate production, potentially exacerbating\nthe condition. The critical cause-and-effect relationship between HS initiation/establishment\nand lactate secretion should be demonstrated convincingly before moving to the other studies\nin this manuscript. Moreover, if HS onset precedes lactate release, it is critical to investigate\nwhether and how the proposed strategy can effectively reverse this pathological process,\nwhich is essential for clinical applications in the real world.\nReply:\nWe sincerely thank the reviewer for this insightful and thought-provoking comment. This\nquestion touches upon the critical 'chicken-and-egg' dilemma regarding the temporal sequence\nof events in HS pathogenesis and is fundamental to understanding the therapeutic potential of\nour proposed strategy. We appreciate the opportunity to clarify our perspective on this crucial\ncause-and-effect relationship.\nWe concur with the reviewer that a stiff ECM is a hallmark of an established hypertrophic\nscar. However, we respectfully propose that the process is not a simple linear event where a\nfully formed, stiff HS matrix is a prerequisite for lactate production. Instead, we believe it is a\nself-amplifying positive feedback loop that begins much earlier in the HS formation cascade,\nwith inflammation being the initial trigger (Younesi FS et al., 2024).\nOur proposed sequence of events is as follows: (1) Initiation by inflammation: The process\nbegins with the initial skin injury, which immediately triggers a robust inflammatory phase of\nwound healing. This phase is characterized by the infiltration of various immune cells, most\nnotably macrophages, into the wound site. These macrophages are activated by damage-\nassociated molecular patterns (DAMPs) and pro-inflammatory cytokines present in the early\nwound environment (Oscar A Peña et al., 2024). (2) Early metabolic reprogramming of\nmacrophages: It is well-established that pro-inflammatory (M1-like) macrophages, which\ndominate the early phase of wound healing, undergo significant metabolic reprogramming\n(Yi-Kai Hong et al., 2023). They shift from oxidative phosphorylation towards aerobic\nglycolysis (the Warburg effect) (Zitong Wang et al., 2024; Sabine A Eming et al., 2023). A key\nconsequence of this metabolic switch is the substantial production and secretion of lactate.\nThis initial wave of lactate production occurs before the development of a pathologically stiff,\nfibrotic matrix. (3) Lactate-driven fibroblast activation: As our study demonstrates, this\nearly, inflammation-driven lactate acts as a crucial signaling molecule for dermal fibroblasts.\nThe influx of lactate into fibroblasts via MCT1, as shown in our paper, primes histone\nlactylation (specifically H3K23la) and promotes their phenotypic transition into hyperactive,\npro-fibrotic myofibroblasts. These activated myofibroblasts are the primary source of\nexcessive collagen and other ECM component deposition. (4) Establishment of a vicious\npositive feedback loop: The excessive deposition of ECM by these myofibroblasts begins to\nincrease the stiffness of the matrix. As we compellingly demonstrated in our in\nvitro experiments using PDMS hydrogels of varying stiffness (Figure 2), and as the reviewer\nkindly noted, this stiff mechanical microenvironment is a potent stimulus for macrophage\nlactate production. This creates a vicious, self-perpetuating cycle: Inflammation →\nMacrophage glycolysis → Lactate secretion → Fibroblast activation → ECM stiffening →\nEnhanced macrophage glycolysis → More lactate → Worsening fibrosis. This feedback loop\nexplains how a normal healing process can be derailed into the pathological state of\nhypertrophic scar and why the condition persists.\nRegarding the second comment, our therapeutic strategy, targeting the glycolysis-MCT1-\nH3K23la axis, is designed precisely to break this pathological feedback loop. By inhibiting\nMCT1 (AZD3965), we block the ability of fibroblasts to take up and respond to the\nmacrophage-derived lactate. This intervention decouples the inflammatory and fibrotic\nprocesses. Even if the scarring process has been initiated and some level of matrix stiffening\nis present, inhibiting MCT1 would still dampen the pro-fibrotic response of fibroblasts,\nreduce their activation and collagen production, and prevent the further amplification of the\ncycle. Our in vivo studies (Figures 9, 10 and S11), where we applied either genetic deletion\nof Mct1 in fibroblasts or pharmacological inhibition with AZD3965 in a full-thickness wound\nmodel, support this concept. In these experiments, the intervention was initiated after the\nwound was created, meaning the inflammatory and healing processes were already underway.\nThe resulting accelerated wound healing and attenuated scar formation strongly suggest that\ndisrupting this lactate-driven axis is effective at mitigating the fibrotic outcome, not just in a\npreventative setting but also during the active phase of scar formation. Therefore, this strategy\nholds the potential to effectively reverse or at least halt the progression of the pathological\nprocess, which is essential for real-world clinical applications.\nTo ensure this critical cause-and-effect relationship is more clearly articulated for our readers,\nwe have revised the Discussion sections of our manuscript to explicitly detail this proposed\ntemporal sequence and highlight the central role of the positive feedback loop in the\nestablishment and progression of hypertrophic scar. Thank you again for your guidance.\nRevised manuscript:\n“Our findings in HS pathogenesis point to a self-amplifying \"mechano-metabolic vicious\ncycle,\" rather than a simple linear causality between matrix stiffening and lactate production.\nWe posit that initial wound healing processes, including inflammation and ECM deposition,\nstiffen the tissue microenvironment. This mechanical cue, as demonstrated in vitro and in\nvivo, triggers a metabolic shift in macrophages towards increased glycolysis and lactate\nsecretion. Subsequently, fibroblast uptake of macrophage-derived lactate via MCT1 instigates\nH3K23la-dependent pathological activation and excessive ECM production. This not only\nintensifies fibrosis but also further stiffens the matrix, locking in a positive feedback loop that\ndrives HS formation. Crucially, our work identifies this amplification loop as a novel\ntherapeutic target. Pharmacological inhibition of MCT1 validated this concept, effectively\naccelerating wound closure and mitigating scar formation. This demonstrates that\ntherapeutically interrupting this lactate-driven, mechano-metabolic crosstalk can steer the\nrepair process away from pathological fibrosis, even after the initial injury. Though the\npotential of this strategy to reverse established, chronic scar remains a key area for future\nstudies, as our current investigation centered on the proliferative phase of scarring.”\nReferences:\n(1) Younesi, F. S., Miller, A. E., Barker, T. H., Rossi, F. M. V., & Hinz, B. (2024). Fibroblast\nand myofibroblast activation in normal tissue repair and fibrosis. Nature reviews. Molecular\ncell biology, 25(8), 617–638.\n(2) Peña, O. A., & Martin, P. (2024). Cellular and molecular mechanisms of skin wound\nhealing. Nature reviews. Molecular cell biology, 25(8), 599–616.\n(3) Hong, Y. K., Chang, Y. H., Lin, Y. C., Chen, B., Guevara, B. E. K., & Hsu, C. K. (2023).\nInflammation in Wound Healing and Pathological Scarring. Advances in wound care, 12(5),\n288–300.\n(4) Wang, Z., Zhao, F., Xu, C., Zhang, Q., Ren, H., Huang, X., He, C., Ma, J., & Wang, Z.\n(2024). Metabolic reprogramming in skin wound healing. Burns & trauma, 12, tkad047.\n(5) Eming, S. A., Murray, P. J., & Pearce, E. J. (2021). Metabolic orchestration of the wound\nhealing response. Cell metabolism, 33(9), 1726–1743.\nComment #6: Lines 236-237, ‘We selected si-MCT1-1 for subsequent experiments which\nexhibited the highest knockdown efficiency.’\nFirstly, the study includes only two groups with the knockdown procedure, indicating a need\nfor careful language revision. (A similar concern is also raised regarding the statements\nrelated to si-HEY2-1 and si-COL11A1-2.)\nSecondly, the relevant data (Supplementary Fig. 3A, second panel) do not support the\nstatement, as no statistical differences are observed between si-MCT1-1 and si-MCT1-2\naccording to the provided source data.\nReply:\nThanks for your suggestions. We have carefully considered your suggestions and have revised\nthe manuscript accordingly to address the concerns you raised. Regarding your comments on\nlines 236-237, we acknowledge that our original phrasing and data presentation were not\nsufficiently robust. Firstly, we agree that with only two siRNA groups, the term \"highest\" was\nnot the most appropriate. We have now expanded our study to include three different siRNA\nsequences for MCT1, as well as for P300, HEY2 and COL11A1, to allow for a more rigorous\nselection of the most effective siRNA. Furthermore, we have conducted additional RT-qPCR\nexperiments to provide a more comprehensive and statistically sound validation of the\nknockdown efficiency for each siRNA. The new data, now presented in the revised Figure\nS6A, S6B, S7A, S7B and S9B-S9E, clearly demonstrates that si-MCT1-1 (and similarly si-\nP300-1, si-HEY2-1 and si-COL11A1-3) exhibits the most significant knockdown efficiency\namong the tested sequences. We are confident that these additions and the corresponding\nrevisions to the text have addressed your concerns and strengthened this aspect of our study\nand we have revised the Result sections of our manuscript. We are grateful for your\nconstructive criticism, which has significantly improved the quality and clarity of our\nmanuscript. Thank you again for your guidance.\nRevised figures:\nFigure S6A-S6B\nFigure S7A-S7B\nFigure S9B-S9C\nFigure S9D-S9E\nComment #7: Type XI collagen is a heterotrimer, comprising three distinct polypeptide\nchains—alpha1(XI), alpha2(XI), and alpha3(XI)—encoded by the genes Col11A1, Col11A2,\nand Col2A1, respectively. It is noteworthy that only Col11A1 appears to be affected, which\nmerits a more thorough discussion to explore the underlying mechanisms and implications.\nReply:\nThanks for your suggestions. We appreciate your expertise and the thoughtful consideration\nyou have given to our work. We concur that the specific upregulation of COL11A1 without a\ncorresponding increase in COL11A2 and COL2A1 is a significant finding that requires further\nelaboration. Our initial unbiased screening using CUT&Tag and RNA-seq analyses pointed\nspecifically to an epigenetic and transcriptional upregulation of COL11A1 in HS. Based on\nyour feedback, we have further explored the literature to provide a more comprehensive\ndiscussion of the potential reasons for this specific observation.\nThere are several potential explanations for the specific upregulation of COL11A1 in the\ncontext of hypertrophic scar: (1) Distinct transcriptional regulation: The genes encoding\nthe three alpha chains of type XI collagen are located on different chromosomes and are\nsubject to independent transcriptional control (Karl E Kadler et al., 2008). This allows for\ntheir expression to be differentially regulated in response to specific cellular signals and\nmicroenvironmental cues. Our study identifies a lactate-rich microenvironment as a key\ndriver of the profibrotic phenotype in HS. We demonstrate that H3K23la, a direct\nconsequence of elevated lactate, is enriched at the promoter of COL11A1, leading to its\ntranscriptional activation. It is highly probable that the promoters of COL11A2 and COL2A1\ndo not possess the same sensitivity to this specific epigenetic modification, leading to the\nselective upregulation of COL11A1. (2) Non-canonical roles of COL11A1 beyond the\nheterotrimer: While classically viewed as a component of the type XI collagen heterotrimer,\nthere is growing evidence that COL11A1 can have significant biological functions\nindependent of its role in the trimer, particularly in pathological conditions like cancer\n(Sameera Nallanthighal et al., 2021; Yihui Wu et al., 2021). Several studies have highlighted\nthat COL11A1 can be secreted as a monomer or homotrimer and can interact with the\nextracellular matrix and cell surface receptors to promote fibroblast activation, migration, and\nmatrix deposition (Jiayu Zhang et al., 2023). Our findings support such a non-canonical role,\nwhere we show a novel interaction between COL11A1 and the lactate transporter MCT1. This\ninteraction stabilizes MCT1 and enhances lactate influx, thereby creating a positive feedback\nloop that perpetuates the fibrotic state. This function is likely independent of the assembly of\nthe full type XI collagen heterotrimer. (3) COL11A1 as a Key Pro-fibrotic Mediator: The\nupregulation of COL11A1 has been specifically identified as a hallmark of various fibrotic\nconditions. For instance, it is a known biomarker for cancer-associated fibroblasts (CAFs) and\nis implicated in promoting a fibrotic tumor microenvironment that enhances tumor\nprogression (Jiayu Zhang et al., 2023; Xuzhen Yan et al., 2025). Furthermore, its expression\nhas been found to be elevated in keloids, a fibroproliferative disorder closely related to\nhypertrophic scar (Pingping Lin et al., 2022). This consistent association of COL11A1 with\nfibrosis across different pathologies suggests that it may be a more central and primary driver\nof the fibrotic process compared to the other two chains of type XI collagen. (4) Alternative\nChain Composition in Pathological ECM: The composition of collagen heterotrimers can\nbe altered in different tissues and under pathological conditions. It is possible that in the\ndisorganized and rapidly remodeling ECM of a hypertrophic scar, the stoichiometric balance\nof collagen chain synthesis is disrupted. The pronounced upregulation of the α1(XI) chain\nmay lead to its incorporation into other collagen fibril types or the formation of atypical\ncollagen structures that contribute to the pathological stiffness and density of the scar tissue.\nIn summary, we propose that the specific upregulation of COL11A1 in hypertrophic scars is\nnot an anomaly but rather a key mechanistic event driven by the unique metabolic and\nepigenetic landscape of the scar microenvironment. The lactate-induced epigenetic activation\nof COL11A1, coupled with its potent, non-canonical pro-fibrotic functions, positions it as a\ncritical driver in the pathogenesis of hypertrophic scar.\nWe have now incorporated this detailed explanation into the Discussion section of our revised\nmanuscript to provide a clearer and more complete interpretation of our findings. Thank you\nagain for your guidance.\nRevised manuscript:\n“The selective upregulation of COL11A1 in HS, independent of its heterotrimeric partners\nCOL11A2 and COL2A1, is driven by metabolic-epigenetic crosstalk. The genes for each\nalpha chain are subject to independent transcriptional control. Specifically, the lactate-rich HS\nmicroenvironment promotes H3K23la enrichment at the COL11A1 promoter, selectively\nactivating its transcription. Furthermore, the COL11A1 protein exhibits a non-canonical\nfunction by directly interacting with the lactate transporter MCT1. Molecular modeling shows\nthis interaction stabilizes MCT1 and enhances its lactate affinity, potentiating lactate\ntransport. This establishes a pathogenic, self-reinforcing positive feedback loop (lactate-\nH3K23la-COL11A1-MCT1), which sustains the scar microenvironment.”\nReferences:\n(1) Kadler, K. E., Hill, A., & Canty-Laird, E. G. (2008). Collagen fibrillogenesis: fibronectin,\nintegrins, and minor collagens as organizers and nucleators. Current opinion in cell\nbiology, 20(5), 495–501.\n(2) Nallanthighal, S., Heiserman, J. P., & Cheon, D. J. (2021). Collagen Type XI Alpha 1\n(COL11A1): A Novel Biomarker and a Key Player in Cancer. Cancers, 13(5), 935.\n(3) Wu, Y. H., Huang, Y. F., Chang, T. H., Chen, C. C., Wu, P. Y., Huang, S. C., & Chou, C. Y.\n(2021). COL11A1 activates cancer-associated fibroblasts by modulating TGF-β3 through the\nNF-κB/IGFBP2 axis in ovarian cancer cells. Oncogene, 40(26), 4503–4519.\n(4) Zhang, J., Lu, S., Lu, T., Han, D., Zhang, K., Gan, L., Wu, X., Li, Y., Zhao, X., Li, Z.,\nShen, Y., Hu, S., Yang, F., Wen, W., & Qin, W. (2023). Single-cell analysis reveals the\nCOL11A1+ fibroblasts are cancer-specific fibroblasts that promote tumor\nprogression. Frontiers in pharmacology, 14, 1121586.\n(5) Yan, X., Han, Q., Wu, W., Li, H., Zhang, W., Wang, Y., Chen, W., Yang, A., & You, H.\n(2025). ITGA8 deficiency in hepatic stellate cells attenuates CCl -Induced liver fibrosis via\n4\nsuppression of COL11A1. Biochemical and biophysical research communications, 756,\n151522.\n(6) Lin, P., Zhang, G., Peng, R., Zhao, M., & Li, H. (2022). Increased expression of\nbone/cartilage-associated genes and core transcription factors in keloids by RNA\nsequencing. Experimental dermatology, 31(10), 1586–1596.\nComment #8: The quality of Fig. 7D and 8A is insufficient for proper assessment. It needs\nimprovement to enable a thorough evaluation.\nReply:\nThanks for your suggestions. We agree that their resolution was not optimal for a thorough\nevaluation, and we sincerely apologize for this oversight. We have now revised both figures to\nimprove their clarity and detail in the revised manuscript. For Figure 7D, we would like to\nclarify that this figure was generated by the JASPAR database, a professional bioinformatics\ntool used for predicting transcription factor binding sites (Ieva Rauluseviciute et al., 2024). It\nillustrates the predicted binding regions of the HEY2 transcription factor on the YAP1\npromoter. This prediction was fundamental to our study, as it guided the design of the three\nprimers used to validate these binding sites in our ChIP-qPCR experiments (results shown in\nFigure 7E). In the revised version, we have significantly increased the figure's resolution and\nenlarged the font for the key predicted sequences to ensure they are clear and legible for\nproper assessment. Figure 8A is a protein-protein interaction network diagram sourced from\nthe BioGRID database (Rose Oughtred et al., 2021), which summarizes proteins reported to\ninteract with COL11A1. This analysis was crucial as it led us to identify the potential\ninteraction between COL11A1 and SLC16A1 (MCT1), a key hypothesis in our work. To\naddress your concern, we have replaced the previous figure with a high-resolution version.\nFurthermore, to better highlight our findings, we have emphasized the interaction between\nCOL11A1 and SLC16A1 with a thick red line, making it easier to identify. We believe these\nrevisions have addressed your concerns, and the improved figures now provide the necessary\nclarity for a comprehensive evaluation. Thank you again for your guidance.\nRevised figures:\nFigure 7D\nFigure 8A\nReferences:\n(1) Rauluseviciute, I., Riudavets-Puig, R., Blanc-Mathieu, R., Castro-Mondragon, J. A.,\nFerenc, K., Kumar, V., Lemma, R. B., Lucas, J., Chèneby, J., Baranasic, D., Khan, A., Fornes,\nO., Gundersen, S., Johansen, M., Hovig, E., Lenhard, B., Sandelin, A., Wasserman, W. W.,\nParcy, F., & Mathelier, A. (2024). JASPAR 2024: 20th anniversary of the open-access\ndatabase of transcription factor binding profiles. Nucleic acids research, 52(D1), D174–D182.\n(2) Oughtred, R., Rust, J., Chang, C., Breitkreutz, B. J., Stark, C., Willems, A., Boucher, L.,\nLeung, G., Kolas, N., Zhang, F., Dolma, S., Coulombe-Huntington, J., Chatr-Aryamontri, A.,\nDolinski, K., & Tyers, M. (2021). The BioGRID database: A comprehensive biomedical\nresource of curated protein, genetic, and chemical interactions. Protein science : a publication\nof the Protein Society, 30(1), 187–200.\nComment #9: In Fig. 8E, the enlarged section: The notes of amino acid interactions are\nblurry. A similar illustration to Fig. 8F should be considered.\nReply:\nThanks for your suggestions. We have addressed this concern by completely remodeling the\nfigure. The new Figure 8E and 8F have a significantly higher resolution, and we have created\na new inset that clearly visualizes the key amino acid residues involved in the interaction. We\nare grateful for your constructive criticism, which has significantly improved the quality and\nclarity of our revised manuscript. Thank you again for your guidance.\nRevised figures:\nFigure 8E\nFigure 8F\nComment #10: The splinted excisional wound model in mice used in the current study is a\nwidely recognized tool for studying wound healing, as it effectively simulates crucial\nprocesses like re-epithelialization and granulation tissue formation that occur in humans.\nHowever, it falls short of being a standard model for HS. A compelling 2022 systematic\nreview of HS animal models (PMID: 35743999) concluded that no murine model, including\nthose utilizing splinted wounds, can truly replicate the intricacies of human hypertrophic\nscars. This limitation arises from fundamental differences in skin anatomy and healing\nmechanisms between species. It is essential to acknowledge these differences and consider\nusing more suitable models for the current research.\nReply: Thanks for your suggestions. We agree completely with the reviewer's assessment of\nthe splinted excisional wound model in mice and the inherent limitations of using murine\nmodels for HS research. We have carefully read the systematic review by Rössler et al.\n(Stefan Rössler et al., 2022) that the reviewer kindly pointed out, and other meaningful\nreviews (Jialun Li et al., 2020; Mony, M. P. et al., 2023). We find its conclusions to be highly\ncompelling and agree with its central thesis: currently, no single animal model perfectly\nreplicates all the complex features of human HS, and therefore, a universal \"gold standard\"\nmodel does not exist. The choice of model must be carefully weighed against the specific\nresearch question being addressed.\nOur study was designed to investigate the in vivo mechanistic role of a specific gene, Mct1,\nwithin the fibroblast population during the process of excessive scar formation. To rigorously\ntest our hypothesis, a genetically knockout model that allows for cell-type-specific, inducible\ngene deletion was essential. As detailed in our manuscript, we utilized a Mct1fl/flCol1a2-\ncre+ mouse model to achieve fibroblast-specific knockout of Mct1. Moreover, the mouse\nremains the most feasible, established, and accessible mammalian system for creating\nsuch sophisticated conditional knockout models. While larger animal models, such as the\nrabbit ear or porcine models, offer superior anatomical and physiological similarity to human\nskin (Stefan Rössler et al., 2022), the generation of conditional gene-edited lines in these\nspecies is associated with prohibitive costs, extended timelines, and significant technical\nchallenges. To maintain consistency and rigorously test our genetic hypothesis, the mouse\nmodel was the most appropriate choice. Furthermore, while the human skin xenograft\nmodel on nude mice is a valuable tool (Stefan Rössler et al., 2022), it is unsuitable for our\nspecific research question, as it does not permit the conditional knockout of a gene within the\ngrafted human fibroblasts in vivo. Therefore, we selected the splinted full-thickness excisional\nwound model as the best available compromise. This model, by mechanically splinting the\nwound, prevents the contraction-based healing characteristic of rodents and instead promotes\nhealing through granulation and re-epithelialization, which develops certain key features of\nhuman-like excessive scarring (e.g., increased collagen deposition, hypercellularity, and some\ndermal thickening). As our results show, this model was sufficiently sensitive to demonstrate\nboth the effects of the Mct1 knockout and the exacerbating phenotype caused by lactate\nadministration, thus allowing us to validate our in vitro mechanistic findings.\nIn light of the reviewer's valid point, we have added this detailed explanation to\nthe Limitations of the current study section in our revised manuscript to explicitly\nacknowledge these limitations and provide a clear justification for our model selection. Thank\nyou again for your guidance.\nRevised manuscript:\n\"Third, while our murine full-thickness excisional wound model partially recapitulates late-\nphase hypertrophic scar formation, interspecies differences in healing mechanisms persist:\nmurine dermis containing the panniculus carnosus facilitates contractile healing through\nregenerative processes. However, the primary in vivo objective of our study was to elucidate\nthe specific genetic function of fibroblast-expressed Mct1 in a fibrotic healing context. This\nrequired a genetically knockout model allowing for conditional gene deletion, for which the\nmouse is the most established and feasible system. We chose the splinted wound model as the\nbest available tool to investigate this specific molecular mechanism, while recognizing that\nfuture validation in larger animal models that more closely mimic human skin would be a\nvaluable next step.\"\nReferences:\n(1) Rössler, S., Nischwitz, S. P., Luze, H., Holzer-Geissler, J. C. J., Zrim, R., & Kamolz, L. P.\n(2022). In Vivo Models for Hypertrophic Scars-A Systematic Review. Medicina (Kaunas,\nLithuania), 58(6), 736.\n(2) Li, J., Wang, J., Wang, Z., Xia, Y., Zhou, M., Zhong, A., & Sun, J. (2020). Experimental\nmodels for cutaneous hypertrophic scar research. Wound repair and regeneration : official\npublication of the Wound Healing Society [and] the European Tissue Repair Society, 28(1),\n126–144.\n(3) Mony, M. P., Harmon, K. A., Hess, R., Dorafshar, A. H., & Shafikhani, S. H. (2023). An\nUpdated Review of Hypertrophic Scarring. Cells, 12(5), 678.\nComment #11: Delayed wound closure is not a defining characteristic of HS. Instead, its\noccurrence is usually influenced by factors such as infection, inadequate blood supply, or\nunderlying conditions like diabetes. While delayed healing can be seen as a general indicator\nof wound healing and may lead to chronic wounds (e.g., ulcers), it does not specifically lead\nto HS. However, it can create conditions that predispose wounds to HS, especially in\nsituations involving prolonged inflammation or mechanical tension. In contrast, the formation\nof HS is more directly related to the quality of healing, particularly excessive deposition of\nECM, rather than the speed of wound closure. For instance, HS can develop in wounds that\nheal quickly if they are accompanied by exaggerated inflammatory and fibrotic responses.\nTherefore, it is important to carefully reconsider the interpretation of animal study data in\nlight of these insights.\nReply:\nThanks for your suggestions. We completely agree with your expert assessment that HS is\nfundamentally a disorder of healing quality, characterized by excessive ECM deposition,\nrather than healing speed. The reviewer’s point that delayed wound closure does not directly\ncause HS, but can create a predisposing pro-fibrotic environment, is well-taken and has\nallowed us to refine the interpretation of our findings. Furthermore, this comment allows us to\nbetter highlight a central novel aspect of our study. As the reviewer astutely noted, a\nprolonged inflammatory phase is a key factor that predisposes wounds to HS. The\nsignificance of our research lies in expanding the understanding of the macrophage's\nrole in this process. Traditionally, macrophages are viewed as drivers of fibrosis primarily\nthrough the secretion of classical cytokines and growth factors (Geoffrey C Gurtner et al.,\n2008; Marc G Jeschke et al., 2023). Our work proposes a complementary and critical axis:\nmacrophages also act as key metabolic regulators of the wound microenvironment through\nthe secretion of lactate. This perspective shifts the view of lactate from a mere metabolic\nbyproduct to a pivotal signaling molecule that directly orchestrates fibroblast phenotype and\nsubsequent fibrosis. Therefore, we interpret the delayed wound closure observed in our\nmodel not as a direct cause of HS, but as a clinical manifestation of this persistent,\nlactate-rich, pro-inflammatory, and pro-fibrotic microenvironment orchestrated by\nmacrophages. When we inhibit this axis (via genetic ablation of Mct1 or pharmacological\ninhibition with AZD3965), we are targeting this fundamental metabolic crosstalk. This leads\nto two parallel improvements: (1) Improved healing speed: A more rapid wound closure,\nwhich we interpret as a sign of a more efficiently resolved, less pathologically active\nmicroenvironment. (2) Improved healing quality: A reduction in fibrotic gene expression\n(Col1a1, Col3a1), decreased collagen deposition, and attenuated scar formation, by directly\ncutting off the lactate signal to fibroblasts.\nWe acknowledge that our original manuscript may have conflated these two outcomes. Based\non the reviewer's valuable guidance, we have carefully revised the manuscript, particularly in\nthe Results and Discussion sections, to present this more precise interpretation. We now\nclarify that accelerated wound closure and reduced scarring are both consequences of\ntargeting the fundamental lactate-driven fibrotic mechanism, rather than suggesting that one\ncauses the other. We thank the reviewer again for helping us to significantly improve the\nclarity and impact of our manuscript.\nRevised manuscript:\n“Collectively, these results suggested that the pro-fibrotic signaling driven by lactate and\nMCT1 creates a pathological microenvironment that simultaneously impairs the rate of\nwound closure and drives the excessive fibrotic gene expression characteristic of hypertrophic\nscarring, mediated by increased H3K23la levels in fibroblasts.”\n“Critically, targeting this pathway via fibroblast-specific Mct1 deletion or pharmacological\ninhibition (AZD3965) mitigated the core pathology. This intervention resulted in two\nconcomitant benefits: an acceleration of wound closure, likely reflecting a more rapid\nresolution of the pro-fibrotic inflammatory phase and a reduction in the excessive collagen\ndeposition that defines the quality of the scar.”\nReferences:\n(1) Gurtner, G. C., Werner, S., Barrandon, Y., & Longaker, M. T. (2008). Wound repair and\nregeneration. Nature, 453(7193), 314-321.\n(2) Jeschke, M. G., Wood, F. M., Middelkoop, E., Bayat, A., Teot, L., Ogawa, R., et al.\n(2023). Scars. Nature reviews Disease primers, 9(1), 64.\nComment #12: Lines 400-402, ‘According to the specific structure of the skin shown by HE\nstaining, collagen arrangement was smoother and more orderly … ’\nFirstly, the description of ‘the specific structure’ requires more detail to enhance clarity and\nunderstanding.\nSecondly, incorporating established methods to quantitatively assess the smoothness and\norderliness of collagen fibers would strengthen the supporting evidence for the statement.\nReply:\nThanks for your suggestions. We are sorry for the inappropriate description of the histological\nfindings and the absence of quantitative evidence for collagen arrangement. We have carefully\nrevised the manuscript according to your suggestions. (1) Regarding the description of H&E\nstaining: We acknowledge that the phrase ‘the specific structure’ was ambiguous. To address\nthis, we have revised the text to provide a more detailed and professional description of the\nhistopathological features observed in the H&E-stained sections. We now describe specific\nchanges in the epidermis and dermis, including epidermal thickness, the presence or absence\nof rete ridges, inflammatory cell infiltration, hair follicle, and the overall dermal architecture\nin different experimental groups. We believe these changes have greatly enhanced the clarity\nof our findings. (2) Regarding the quantitative assessment of collagen fibers: We concur that\nour qualitative description of collagen arrangement as ‘smoother and more orderly’ should be\nsupported by objective, quantitative data. To achieve this, we have performed a quantitative\nanalysis of collagen fiber alignment on our Masson’s trichrome-stained histological images\nusing the widely accepted image analysis software ImageJ with the Directionality plugin\n(Alberto Sensini et al., 2018). This method allowed us to calculate the dispersion index of\ncollagen fibers, where a lower value indicates a more orderly and aligned arrangement. The\nnew quantitative data demonstrates a significantly lower dispersion of collagen fibers in\nthe Mct1 knockout group compared to the control group, which corroborates our initial\nqualitative observation. These results, along with the corresponding statistical analysis, have\nbeen added to the manuscript as a new figure panel (Figure S11A and S11C) and are\ndescribed in the Results section. We are confident that these revisions have substantially\nimproved the rigor and quality of our manuscript, and we are grateful for the opportunity to\nstrengthen our work based on your expert guidance. Thank you again for your guidance.\nRevised manuscript:\n“Histological analysis with H&E staining revealed that wounds in the Mct1 knockout group\nexhibited a more organized skin architecture, characterized by a well-formed epidermis with\nrete ridges and signs of hair follicle regeneration, and a dermis with reduced inflammatory\ncell infiltration compared to the control group. In contrast, the control and NaLac-treated\ngroups showed features of hypertrophic scarring, including a thickened, flattened epidermis\nand a disorganized dermal structure (Figure 9D). Masson staining showed obviously reduced\nblue collagen deposition and collagen fibers were arranged in a smoother, more orderly\npattern in the Mct1fl/flCol1a2-cre+ compared to Mct1fl/flCol1a2-cre- mice (Figure 9D).\nQuantitative analysis confirmed these observations, showing a significantly reduced collagen\narea and dispersion index—indicating more orderly collagen alignment—in the Mct1\nknockout group (Figure 9E and S10A).”\nRevised figures:\nFigure S8A\nFigure S8C\nReferences:\n(1) Sensini, A., Gualandi, C., Zucchelli, A., Boyle, L. A., Kao, A. P., Reilly, G. C., Tozzi, G.,\nCristofolini, L., & Focarete, M. L. (2018). Tendon Fascicle-Inspired Nanofibrous Scaffold of\nPolylactic acid/Collagen with Enhanced 3D-Structure and Biomechanical Properties.\nScientific reports, 8(1), 17167.\nComment #13: The ratio of collagen I to collagen III undergoes a dynamic shift during the\nwound healing process, reflecting the stages of tissue repair and remodeling. Thus, the noted\nreduction in the collagen I/III ratio in Figs. 9 and 10 may be just a secondary effect of delayed\nhealing, which should not be overrated.\nReply:\nThanks for your suggestions. We agree entirely that the collagen I/III ratio is a dynamic\nmarker that changes significantly throughout the phases of wound healing. Your point that a\nchange in this ratio could reflect the healing stage rather than a direct therapeutic effect is\nwell-taken, and we appreciate the opportunity to clarify our interpretation.\nOur analysis was conducted at day 21 post-wounding, a time point that is well within the\nremodeling phase of healing, where collagen III, prevalent in the early proliferative phase, is\ntypically replaced by the stronger, more mature collagen I (Oscar A Peña et al., 2024; Pauline\nD H M Verhaegen et al., 2009). While a shift towards collagen I is part of normal remodeling,\nan excessively high collagen I/III ratio, coupled with disorganized collagen fiber arrangement,\nis a well-established hallmark of pathological fibrosis and hypertrophic scar (Ying Zhang et\nal., 2023; Qing Zhang et al., 2022).\nTherefore, our finding that Mct1 ablation (Figure 9) or pharmacological inhibition with\nAZD3965 (Figure 10) leads to a reduced collagen I/III ratio at day 21 should be interpreted\nnot as a sign of delayed healing, but as a shift away from a pro-fibrotic, pathological\ntrajectory towards a more regenerative healing process that better resembles the\ncomposition of normal dermis. This interpretation is strongly supported by our\ncomplementary findings presented in Figures 9 and 10: (1) Accelerated wound closure:\nBoth genetic ablation and pharmacological inhibition of MCT1 led to significantly faster wound\nclosure (Figure 9C and 10B), which contradicts the idea of delayed healing. The lactate-\ntreated groups, which exhibited a higher collagen I/III ratio, showed delayed wound closure.\n(2) Reduced overall collagen deposition: Masson and Sirius red staining, and the subsequent\nquantification (Figure 9F and 10E), clearly show a significant reduction in total collagen\ncontent in the MCT1-inhibited groups. (3) Improved collagen organization: As observed in\nthe Masson staining images and quantitative analysis of dispersion index, the collagen fibers\nin the treated groups were more organized, resembling normal skin architecture, whereas the\nwhereas the\ncontrol/lactate-treated groups showed thick, disorganized collagen bundles characteristic of\nscar tissue (Figure 9D, 10C, S11A and S11C). (4) Reduced myofibroblast presence: We also\nobserved a decrease in α-SMA expression (Figure 9H, 9I and 10G) in the Mct1 knockout and\ninhibition groups, indicating a reduction in the key cell type responsible for excessive matrix\ndeposition and scar contraction. In summary, the reduced collagen I/III ratio, when viewed in\nthe context of accelerated healing, reduced total collagen, improved collagen organization,\nand decreased myofibroblast markers, provides compelling evidence for an anti-fibrotic\neffect. Our intervention does not delay healing but rather modulates it to produce a higher-\nquality, less-scarred tissue.\nTo clarify this important point for the reader, we have revised the manuscript to discuss these\nresults with greater nuance, explicitly contextualizing the collagen I/III ratio as a marker of\nhealing quality, not just healing stage. Thank you again for your constructive feedback.\nRevised manuscript:\n“The collagen I to III ratios of groups were reduced in Mct1 knockdown mice compared to\nthe control mice (Figure 9D and 9G). Meanwhile, NaLac treatment resulted in enhanced\ncollagen synthesis, disorganized collagen alignment, and elevated collagen I to III ratios, as\nnotably observed in the histological analysis (Figure 9D-G). These data indicated a shift from\na fibrotic to a more regenerative healing phenotype in Mct1 knockdown mice.”\nReferences:\n(1) Peña, O. A., & Martin, P. (2024). Cellular and molecular mechanisms of skin wound\nhealing. Nature reviews. Molecular cell biology, 25(8), 599–616.\n(2) Verhaegen, P. D., van Zuijlen, P. P., Pennings, N. M., van Marle, J., Niessen, F. B., van der\nHorst, C. M., & Middelkoop, E. (2009). Differences in collagen architecture between keloid,\nhypertrophic scar, normotrophic scar, and normal skin: An objective histopathological\nanalysis. Wound repair and regeneration : official publication of the Wound Healing Society\n[and] the European Tissue Repair Society, 17(5), 649–656.\n(3) Zhang, Y., Wang, S., Yang, Y., Zhao, S., You, J., Wang, J., Cai, J., Wang, H., Wang, J.,\nZhang, W., Yu, J., Han, C., Zhang, Y., & Gu, Z. (2023). Scarless wound healing programmed\nby core-shell microneedles. Nature communications, 14(1), 3431.\n(4) Zhang, Q., Shi, L., He, H., Liu, X., Huang, Y., Xu, D., Yao, M., Zhang, N., Guo, Y., Lu, Y.,\nLi, H., Zhou, J., Tan, J., Xing, M., & Luo, G. (2022). Down-Regulating Scar Formation by\nMicroneedles Directly via a Mechanical Communication Pathway. ACS nano, 16(7), 10163–\n10178.\nComment #14: Line 475: The reference to Zhang et al. should be provided.\nReply: Thanks for your suggestions. We would like to express our gratitude to the reviewer\nfor pointing out this omission. We have now added the requested citation for Zhang et al. in\nthe manuscript.\nReviewer #2:\nIn the manuscript titled “Lactate derived from macrophages drives skin dermal fibroblasts\nphenotypic remodeling via MCT1‑primed histone H3 lysine(cid:3031)23 lactylation in hypertrophic\nscar,” the authors investigate how matrix stiffness–activated macrophages produce excess\nlactate, which is shuttled into dermal fibroblasts via MCT1. This influx promotes site‑specific\nhistone H3K23 lactylation (H3K23la), leading to upregulation of profibrotic genes HEY2 and\nCOL11A1. Through CUT&Tag, RNA‑seq, molecular simulations, and both genetic\n(fibroblast‑specific Mct1 knockout) and pharmacological (AZD3965) interventions in murine\nwound models, they demonstrate that disrupting the MCT1–H3K23la–HEY2/COL11A1\nfeedback loop attenuates hypertrophic scar formation. The presented findings are new and\nsupported by the experimental data. The reviewer has several comments listed below.\nComment #1: The immunofluorescence images in Figure(cid:3031)1F show MCT1 colocalization with\nα‑SMA–positive myofibroblasts, but no quantitative colocalization analysis (e.g., Pearson’ s\ncoefficient) is provided. Please include such metrics to substantiate the claim.\nReply:\nThanks for your suggestions. We agree that a quantitative analysis of the colocalization\nbetween MCT1 and α-SMA is essential to substantiate our claim and significantly strengthen\nour findings. Following the reviewer's recommendation, we have performed a quantitative\ncolocalization analysis on the immunofluorescence images from Figure 1F using Pearson's\ncorrelation coefficient analysis in software ImageJ. The results confirm a significantly higher\ndegree of colocalization between MCT1 and α-SMA in HS tissues compared to NS tissues.\nWe have now included these quantitative results as a new panel of Figure 1H. We have also\nupdated the manuscript text in the Results section and the legend for Figure 1 to refer to this\nnew analysis. We believe these additions have greatly improved the manuscript by providing\nrobust, quantitative evidence for our observations. We are grateful for the opportunity to\nenhance the quality of our work. Thank you again for your guidance.\nRevised figures:\nFigure 1H\nRevised manuscript:\n“To quantitatively validate this observation, we calculated the Pearson's correlation and\nOverlap coefficient, which revealed a significantly higher level of colocalization between\nMCT1 and α-SMA in HS tissues compared to NS tissues (Figure 1F).”\nComment #2: The rationale for using 10(cid:3031)ng/mL TGF‑β is not explained. Cite relevant\nliterature or provide preliminary data to justify this concentration.\nReply:\nThank you for your valuable feedback and for highlighting the need to clarify our choice of\nTGF-β concentration. We agree that the rationale for using 10 ng/mL of TGF-β1 was not\nsufficiently explained in the original manuscript, and we appreciate the opportunity to address\nthis. This concentration has been shown to be optimal for stimulating fibroblast proliferation,\ndifferentiation into myofibroblasts, and excessive ECM deposition, which are key events in\nthe pathogenesis of hypertrophic scars. For instance, several studies investigating the\nmechanisms of hypertrophic scar have successfully used 10 ng/mL of TGF-β to activate\nhuman hypertrophic scar fibroblasts (HSFs) and normal skin fibroblasts (NSFs) (Keun Jae\nAhn et al., 2022; Amy S Colwell et al., 2005). Furthermore, this concentration is commonly\nemployed in broader fibrosis research to create reliable in vitro models of fibrosis suitable for\nmechanistic studies and screening of anti-fibrotic agents (Ruijuan Guan et al., 2022; Li Xiao\net al., 2012; Qihe Xu et al., 2007). Based on this strong precedent in the field, we selected this\nconcentration to ensure a potent and reproducible fibrotic stimulation in our experimental\nsystem, particularly for activating macrophages (THP-1 cells) to study their subsequent\neffects on fibroblasts, as described in our manuscript.\nTo address your concern, we have revised the Methods section of our manuscript to include\nthis justification and have cited relevant literature. We believe this addition strengthens the\nmethodological foundation of our study. Thank you again for your constructive suggestion.\nRevised manuscript:\n“This concentration was selected as a well-established and widely used concentration in the\nliterature for effectively inducing a fibrotic response in in vitro models of hypertrophic\nscarring and fibrosis62,63.”\nReferences:\n(1) Ahn, K. J., & Kim, J. S. (2022). TGF-β1 upregulates Sar1a expression and induces\nprocollagen-I secretion in hypertrophic scarring fibroblasts. Open medicine (Warsaw,\nPoland), 17(1), 1473–1482.\n(2) Colwell, A. S., Phan, T. T., Kong, W., Longaker, M. T., & Lorenz, P. H. (2005).\nHypertrophic scar fibroblasts have increased connective tissue growth factor expression after\ntransforming growth factor-beta stimulation. Plastic and reconstructive surgery, 116(5),\n1387–1392.\n(3) Guan, R., Yuan, L., Li, J., Wang, J., Li, Z., Cai, Z., Guo, H., Fang, Y., Lin, R., Liu, W.,\nWang, L., Zheng, Q., Xu, J., Zhou, Y., Qian, J., Ding, M., Luo, J., Li, Y., Yang, K., Sun, D., …\nLu, W. (2022). Bone morphogenetic protein 4 inhibits pulmonary fibrosis by modulating\ncellular senescence and mitophagy in lung fibroblasts. The European respiratory\njournal, 60(6), 2102307.\n(4) Xiao, L., Du, Y., Shen, Y., He, Y., Zhao, H., & Li, Z. (2012). TGF-beta 1 induced\nfibroblast proliferation is mediated by the FGF-2/ERK pathway. Frontiers in bioscience\n(Landmark edition), 17(7), 2667–2674.\n(5) Xu, Q., Norman, J. T., Shrivastav, S., Lucio-Cazana, J., & Kopp, J. B. (2007). In vitro\nmodels of TGF-beta-induced fibrosis suitable for high-throughput screening of antifibrotic\nagents. American journal of physiology. Renal physiology, 293(2), F631–F640.\nComment #3: The manuscript proposes that lactate enters fibroblasts via MCT1 to induce\nH3K23la and activate HEY2 and COL11A1 transcription, but lacks details on the dynamic\nregulation of this process. For example, the dose–response relationship between lactate\nconcentration and H3K23la levels has not been fully characterized.\nReply:\nThanks for your suggestions. We agree that characterizing the dynamic relationship between\nlactate concentration and H3K23la is crucial for strengthening the core argument of our study.\nTo address your concern, we have performed additional experiments. Specifically, we treated\nnormal skin fibroblasts (NSFs) with a gradient of sodium lactate concentrations (0, 5, 10,\n15, 20 and 25 mM) and assessed the levels of H3K23la by Western blot. Our new data reveal a\nclear dose-dependent increase in H3K23la level, with the induction of H3K23la becoming\nsignificant at 5 mM and peaking at approximately 10-15 mM. These findings directly\ndemonstrate that extracellular lactate levels dynamically regulate histone lactylation in\nfibroblasts. We have incorporated these new findings into the manuscript. The text in the\nResults section has been revised, and we have added a new supplementary figure (Figure\nS5A) to present this dose-response data. We believe these additions substantially strengthen\nour manuscript by providing the quantitative evidence you rightly pointed out was missing.\nThank you again for your constructive suggestion.\nRevised figures:\nFigure S4A\nRevised manuscript:\n“Furthermore, we also found that there was a clear dose-dependent increase in H3K23la level\nunder the different concentration of NaLac (Figure S5A).”\nComment #4: The authors state that 2(cid:3031)kPa and 50(cid:3031)kPa hydrogels were used to model\nphysiological and pathological matrix stiffness, but no supporting references or experimental\nstiffness measurements are provided. Please cite precedent studies or supply experiment data.\nReply:\nThanks for your suggestions. We agree that providing justification for the selected hydrogel\nstiffness values is crucial for the manuscript. We apologize for this oversight and have revised\nthe manuscript to include appropriate citations that support our choice of 2 kPa and 50 kPa to\nmodel physiological and pathological matrix stiffness, respectively. The selection of these\nvalues is based on well-established precedents in the literature that characterize the\nmechanical properties of normal and fibrotic skin (Jiahao He et al., 2023). Normal, healthy\ndermal tissue typically exhibits a Young's modulus in the low kPa range. Our use of 2\nkPa hydrogels to mimic a \"physiologically compliant\" substrate is consistent with findings\nfrom multiple studies investigating dermal fibroblast mechanobiology. In contrast, fibrotic\ntissues, such as hypertrophic scars and keloids, are characterized by excessive extracellular\nmatrix deposition, leading to a significant increase in tissue stiffness. The use of hydrogels\nwith a Young's modulus of 50 kPa to simulate a \"pathologically stiff\" or fibrotic\nmicroenvironment is a well-established in vitro model. For instance, He et al. in their study on\nmechanical stiffness and skin fibrosis, utilized the exact same values of 2 kPa and 50 kPa to\nrepresent normal and fibrotic skin, respectively (Jiahao He et al., 2023). Furthermore, Lin et\nal. investigated the role of matrix stiffness in benign prostatic hyperplasia and fibrosis,\nsimilarly using soft substrates in the low kPa range (~1-2 kPa) and rigid substrates in the tens\nof kPa range (~50 kPa) to model normal versus pathological conditions, reinforcing the\nprinciple of our experimental design (Dongxu Lin et al., 2024). We have now incorporated\nthese and other relevant citations into the manuscript to provide clear support for our\nexperimental model. We believe these additions address your concern and strengthen the\nmethodological foundation of our study. Thank you again for your valuable feedback.\nReferences:\n(1) He, J., Fang, B., Shan, S., & Li, Q. (2023). Mechanical stiffness promotes skin fibrosis\nthrough Piezo1-mediated arginine and proline metabolism. Cell death discovery, 9(1), 354.\n(2) Lin, D., Luo, C., Wei, P., Zhang, A., Zhang, M., Wu, X., Deng, B., Li, Z., Cui, K., & Chen,\nZ. (2024). YAP1 Recognizes Inflammatory and Mechanical Cues to Exacerbate Benign\nProstatic Hyperplasia via Promoting Cell Survival and Fibrosis. Advanced science (Weinheim,\nBaden-Wurttemberg, Germany), 11(5), e2304274.\nReviewer #3\nIn their manuscript, entitled “Lactate derived from macrophages drives skin dermal fibroblasts\nphenotypic remodeling via MCT1‑primed histone H3 lysine(cid:3031)23 lactylation in hypertrophic\nscar,” Yuan et al. investigate increased lactate production in the hypertrophic skin and its\ninfluence on fibroblast function in fibrosis and wound healing. The authors further determined\nthat MCT1 functions to transport lactate into fibroblasts, where it is utilized for histone\nlactylation. This, in turn, activates the transcription of profibrotic genes HEY2 and COL11A1,\nwhich activate YAP1 expression and aggravate lactate accumulation, respectively. Finally,\nthe authors test the relevance of MCT1 expression in skin fibroblasts using a wound healing\nmodel, employing genetic depletion and compound blocking.\nThis reviewer is deeply concerned about the novelty of the findings, the technical quality of\nthe presented data, and the technical quality of the manuscript. The role of MCT1 in fibrosis\nand keloid fibroblasts has been known for some time (Jinhua Feng et al., 2024; David R.\nZiehr et al., 2024 preprint; Kyounghee Min, 2023; Jing-Jing Gu 2025, and many others), as\nwell as the role of lactylation in fibrosis (Huanwei Liang et al., 2025 review). Therefore,\nthe novelty of the study results is limited, if any.\nThe presented manuscript is generally poorly written, contains numerous grammatical errors,\nand references data that are not present in the figures. Additionally, it includes too many\nfigures that do not contribute to the study's quality.\nReply:\nThank you for your time and for providing a detailed critique of our manuscript. We\nappreciate the opportunity to respond to the concerns raised and to improve our work. While\nwe understand the reviewer's reservations, we believe there may be a misunderstanding of the\nspecific context and the novel mechanistic details our study provides. We have addressed each\nof the concerns below.\nRegarding the novelty of the findings\nWe thank the reviewer for highlighting the existing literature. We agree that metabolic\nreprogramming, including the roles of MCT1 and histone lactylation, are recognized as\nimportant factors in various fibrotic diseases. However, we respectfully assert that our study\nprovides a significant and novel contribution to the field by elucidating a previously\nuncharacterized, specific, and complete mechanistic pathway in the distinct context\nof hypertrophic scar. Our novelty is multi-faceted and lies in the integration and specificity of\nour findings: (1) A novel and specific axis in hypertrophic scar: While the cited papers discuss\nMCT1 in broader fibrosis or keloids, our study is the first to establish the complete axis in\nHS: Stiff microenvironment → Macrophage glycolysis → Lactate secretion → Fibroblast\nMCT1 uptake → Histone H3K23 lactylation → HEY2/COL11A1 upregulation →\nYAP1/SMAD2 activation & Positive feedback. To our knowledge, this integrated pathway\nhas never been described before. The papers cited by the reviewer discuss parts of this puzzle\nin different contexts (e.g., MCT1 in keloid metabolism or general lactylation in fibrosis), but\nnone have connected these specific molecular players in this precise sequence to drive HS\npathogenesis. (2) Identification of a specific histone mark (H3K23la): The reviewer mentions\na review on \"lactylation in fibrosis.\" Our work moves beyond this by providing new, primary\ndata identifying H3K23la as the specific and key epigenetic modification that is significantly\nupregulated in HS myofibroblasts. We demonstrate through CUT&Tag analysis that H3K23la\nenrichment is directly responsible for the transcriptional activation of the specific profibrotic\ngenes HEY2 and COL11A1. This level of specificity—linking a single histone mark to\nspecific gene promoters in HS—is a core novel finding of our study. (3) Elucidation of the\nupstream cellular source and trigger: A major novel contribution of our work is the\nidentification of macrophages, activated by a stiff mechanical microenvironment, as the\nprimary source of lactate that fuels fibroblast remodeling in HS. Previous studies have often\nfocused on fibroblast-intrinsic metabolic changes (Xinxian Meng et al., 2022). Our findings\nreveal a critical intercellular crosstalk (macrophage-to-fibroblast) that initiates the fibrotic\ncascade, redefining the upstream triggers in HS pathology. (4) Discovery of a self-\nperpetuating positive feedback loop: Our study uncovers a novel positive feedback\nmechanism where a downstream target, COL11A1, physically interacts with and stabilizes\nMCT1, thereby enhancing further lactate transport and amplifying the fibrotic signal. This\nself-reinforcing loop (Lactate → H3K23la → COL11A1 → MCT1 stabilization → more\nLactate influx) provides a new paradigm for understanding the persistence and progression of\nhypertrophic scars.\nTo better emphasize these points, we have revised the Introduction and Discussion sections\nand cited relatively new literature about MCT1 and histone lactylation. We now more\nexplicitly contextualize our work within the existing literature and then clearly articulate the\nspecific, novel contributions that our detailed mechanistic investigation provides to the field\nof skin fibrosis and hypertrophic scar.\nRegarding the technical quality of the manuscript and figures\nWe sincerely apologize that the manuscript's language did not meet the reviewer's standards.\nThe manuscript was professionally edited by Language Editing Services prior to submission\nto ensure linguistic accuracy. However, we acknowledge that scientific clarity goes beyond\ngrammar. We have meticulously re-read the entire manuscript to improve sentence structure,\nenhance clarity, and ensure the logical flow of our arguments is easy to follow. We have\nfocused on simplifying complex sentences to make our findings more accessible.\nFurthermore, we have performed a rigorous check of the entire manuscript, cross-referring\nevery statement in the results section with its corresponding figure panel and legend. We have\ncorrected any discrepancies to ensure that all claims are directly and clearly supported by the\ndata presented. Finally, we appreciate the reviewer's feedback on the manuscript's structure.\nWe believe that each figure is essential for building our comprehensive story, from the initial\nobservation of metabolic dysregulation (Figure 1), to identifying the cellular source (Figure\n2), to systematically dissecting the entire molecular pathway (Figures 3-8), and finally, to\nvalidating our findings using in vivo genetic and pharmacological models (Figures 9-10). The\nlogical progression from in vitro mechanism to in vivo relevance necessitates this level of\ndetail. However, taking the reviewer's comment into consideration, we have re-evaluated all\nsupplementary figures and have consolidated some panels to improve the manuscript's focus\nwithout compromising the data's integrity.\nIn summary, we are confident that our study presents a significant and novel contribution by\ndelineating a complete and specific metabolic-epigenetic axis that drives hypertrophic scar\nformation. We have taken the reviewer's constructive feedback seriously and have thoroughly\nrevised the manuscript to improve its clarity, accuracy, and impact. We thank you again for\nyour valuable time and consideration.\nReferences:\n(1) Meng, X., Yu, Z., Xu, W., Chai, J., Fang, S., Min, P., Chen, Y., Zhang, Y., & Zhang, Z.\n(2022). Control of fibrosis and hypertrophic scar formation via glycolysis regulation with\nIR780. Burns & trauma, 10, tkac015.\nComment #1: The majority of the paper utilizes an in vitro system to investigate a complex\nand multifaceted disease that affects complex tissue, while only selected experiments employ\ntissue samples. It is unclear why these shifts in experimental systems are made, as they are by\nno means beneficial to the study.\nReply:\nWe sincerely thank the reviewer for this insightful comment and appreciate the opportunity to\nclarify our experimental rationale. We agree that hypertrophic scar is a complex,\nmultifactorial process involving intricate crosstalk between various cell types within a\ndynamic extracellular matrix. It was precisely this complexity that guided our decision to\nemploy a multi-tiered experimental approach, progressing logically from controlled in\nvitro systems to clinically relevant human tissues and finally to functional in vivo models.\nWe believe this strategic progression is a key strength of our study, allowing us to build a\nrobust, evidence-based narrative from fundamental mechanism to potential therapeutic application.\nWe would like to elaborate on the specific purpose and necessity of each experimental\nsystem: (1) The necessity of the in vitro system for mechanistic dissection: Our primary\ngoal was to dissect the specific molecular and cellular drivers of fibroblast activation in HS.\nThe complex microenvironment of scar tissue, with its multitude of cell types and signaling\nmolecules, makes it exceedingly difficult to isolate and study the contribution of a single\nfactor, such as mechanical stiffness, on a specific cell type. Our in vitro system, utilizing\nPDMS hydrogels of varying stiffness (2 kPa vs. 50 kPa), was essential to answer a critical\ninitial question: What is the primary cellular source of the elevated lactate we observe in\nHS tissue? By culturing the three main dermal cell populations (macrophages, fibroblasts,\nand endothelial cells) separately on these defined substrates, we were able to unequivocally\ndemonstrate that macrophages, when subjected to a pathologically stiff environment, are the\npredominant source of lactate (Figure 2). Furthermore, the in vitro system was indispensable\nfor testing direct causal relationships. For instance, using conditioned medium (CM) from\nmacrophages cultured on stiff substrates, we could directly test its effect on fibroblasts. The\nsubsequent use of the MCT1 inhibitor (AZD3965) and the glycolysis inhibitor (Oxamate)\nallowed us to prove that macrophage-derived lactate, transported via MCT1, was the key\nmediator of fibroblast activation and phenotypic remodeling (Figure 3). Similarly, our siRNA-\nmediated knockdown experiments (e.g., silencing of MCT1, HEY2, and COL11A1) were\ncritical for mapping the downstream epigenetic (H3K23la) and transcriptional pathways,\nwhich can only be performed in a controlled cell culture environment. (2) The role of human\ntissue samples for clinical validation: While our in vitro work provided strong mechanistic\nevidence, its relevance hinges on whether these pathways are active in human disease.\nTherefore, we used human hypertrophic scar and normal skin tissues to validate our findings\nand bridge the translational gap. Our analyses of patient-derived tissues confirmed that the\nkey components of our proposed axis are indeed dysregulated in HS. We demonstrated\nelevated levels of lactate, increased expression of MCT1, and a specific and significant\nupregulation of histone H3K23 lactylation in HS tissue compared to normal skin (Figure 1,\nFigure 4). We further showed that the downstream targets, HEY2 and COL11A1, were also\nsignificantly elevated in patient scar tissue (Figure 5). This step was vital to confirm that the\nmechanism we dissected in vitro is a genuine feature of the human pathology. Crucially, we\nalso utilized these patient samples to directly test our key in vitro conclusion regarding\nthe cellular origin of lactate (Question 7). First, through multicolor immunofluorescence\nstaining of human HS and NS sections, we confirmed that glycolytic pathway activity was\nsignificantly increased specifically within the macrophage population (Figure 2I and 2J). In\ncontrast, endothelial cells showed no statistically significant changes, mirroring our in\nvitro observations (Figure S3D and S3E). Second, to further substantiate this, we isolated\nprimary macrophages, endothelial cells, and fibroblasts directly from both normal skin and\nhypertrophic scar tissues. Direct measurement of extracellular and intracellular lactate levels\nin these primary cells revealed that macrophages isolated from HS exhibited the most\nsubstantial and significant increase in lactate content, and elevated ECAR level (Figure 2G\nand 2H). Furthermore, we have performed a new in vivo experiment using our full-thickness\nskin defect mouse model. In this experiment, we selectively depleted macrophages during the\nwound healing process to directly assess their contribution to lactate production. Specifically,\nwe administered clodronate liposomes subcutaneously starting on day 7 post-injury to deplete\nmacrophages, with a control group receiving saline injections. On day 21, wound tissues were\nharvested for analysis. Immunofluorescence staining for the macrophage marker F4/80\nconfirmed a significant reduction in macrophage numbers in the scar tissues of clodronate-\ntreated mice compared to controls (Figure S2F). Crucially, lactate concentration was\nmarkedly decreased in the scar tissue of macrophage-depleted mice (Figure S2G). These\nexperiments, performed on clinically relevant human tissues and animal model, provide\ncompelling evidence that corroborates our in vitro findings. They strongly support our\nconclusion that macrophages are the principal source of the lactate-rich microenvironment\nthat drives fibrotic remodeling in hypertrophic scars. (3) The importance of the in\nvivo model for functional and therapeutic proof-of-concept: Finally, to move beyond\ncorrelation and establish causality in a complex biological system, we utilized a murine full-\nthickness wound model. This in vivo model allowed us to test the functional necessity of our\npathway in the context of tissue repair and scarring. By employing a fibroblast-specific\nknockout of Mct1 (Mct1fl/flColla2-cre+ mice), we demonstrated that ablating lactate transport\nspecifically in fibroblasts leads to accelerated wound healing and attenuated scar formation\n(Figure 9). This genetic evidence provides powerful, direct proof of our hypothesis. The in\nvivo model was also essential for testing the therapeutic viability of targeting this pathway.\nThe pharmacological inhibition of MCT1 with AZD3965 in our wound model recapitulated\nthe positive effects of the genetic knockout, significantly reducing scar features (Figure 10).\nThis provides a critical preclinical proof-of-concept that MCT1 is a druggable target for HS\ntherapy.\nIn summary, our experimental design was intentionally structured to investigate this complex\ndisease in a logical and stepwise manner. The in vitro system was necessary to dissect the\nfundamental cellular and molecular mechanisms with high precision. The human tissue\nsamples were essential to validate the clinical relevance of these mechanisms. Lastly, the in\nvivo animal model was crucial to confirm the functional importance of the pathway and to\nprovide a preclinical proof-of-concept for a novel therapeutic strategy. Therefore, we\nrespectfully argue that these shifts in experimental systems are not only beneficial but are in\nfact essential to the study's design. This multi-pronged approach allows us to build a\ncomprehensive, multi-level narrative from molecular mechanism to clinical observation and,\nultimately, to therapeutic implication. We hope this explanation has adequately addressed the\nreviewer's concerns. We would be pleased to incorporate a more detailed explanation of our\nexperimental strategy into the revised manuscript if deemed appropriate. Thank you again for\nyour valuable guidance.\nRevised manuscript:\n“Our study establishes a novel axis linking metabolic reprogramming and epigenetic\nregulation in hypertrophic scar pathogenesis. First and foremost, we redefine the upstream\ntrigger of fibroblast activation by identifying mechanically stressed macrophages as the key\nlactate producers. The stiff microenvironment induces macrophages to adopt a\nhyperglycolytic phenotype, producing lactate that is shuttled into fibroblasts via MCT1.\nSecond, this lactate influx primes H3K23la, activating profibrotic genes HEY2 and COL11A1.\nHEY2 amplifies fibrotic signaling via YAP1/SMAD2, while COL11A1 stabilizes MCT1 to\nenhance lactate transport, creating a self-reinforcing loop that perpetuates fibrosis.\nFurthermore, the process initiates in the stiff HS microenvironment, which induces\nmacrophages to produce excessive lactate. Critically, targeting this pathway via fibroblast-\nspecific Mct1 deletion or pharmacological inhibition (AZD3965) mitigated the core\npathology. This intervention resulted in two concomitant benefits: an acceleration of wound\nclosure, likely reflecting a more rapid resolution of the pro-fibrotic inflammatory phase and a\nreduction in the excessive collagen deposition that defines the quality of the scar. This work\nprovides the first evidence that macrophage-derived lactate fuels HS progression through\nMCT1-dependent histone lactylation, redefining lactate as a metabolic-epigenetic mediator\nrather than a passive byproduct. These findings position MCT1 as a therapeutic target and\nestablish histone lactylation as a novel epigenetic driver of HS progression.”\nComment #2: In the first figure, authors proceed directly to measuring lactate levels in the\nhypertrophic skin, providing little justification for why they chose to present precisely this\nmetabolite and not assess the overall metabolomic profile of hypertrophic versus normal skin.\nThe authors should provide an extended metabolomic profile of hypertrophic versus normal\nskin, allowing for a comparison of the presence of different metabolites in the skin.\nReply:\nWe thank you for this insightful comment and for the opportunity to clarify our scientific\nrationale. We agree completely that providing a broader metabolomic context is crucial for\njustifying our focus on lactate and significantly strengthens the introduction to our findings.\nIn response to your suggestion, we have performed and now included data from a non-\ntargeted metabolomic analysis of hypertrophic scar (HS) and normal skin (NS) tissues. This\ninitial exploratory analysis revealed a significant and distinct metabolic reprogramming in HS\ntissues. Specifically, we found that key intermediates of the TCA cycle, such as citric acid,\nwere significantly decreased in HS. Conversely, metabolites of the glycolytic pathway, such\nas phosphoenolpyruvic acid, were significantly increased (Figure S1A-S1C). This compelling\nevidence strongly indicates a metabolic shift in hypertrophic scar away from oxidative\nphosphorylation and towards aerobic glycolysis. As lactate is the primary end-product of\naerobic glycolysis, these metabolomic data provided a robust, data-driven rationale for our\nsubsequent, more targeted investigation into lactate accumulation and its functional role in HS\npathogenesis, as presented in Figure 1.\nTo incorporate this important context into the manuscript, we have made the following\nchanges. We have created a new Supplementary Figure (Figure S1) to present the key findings\nfrom our non-targeted metabolomic analysis (including a volcano plot of differential\nmetabolites and levels of citrate and phosphoenolpyruvate). We have substantially revised the\nfirst section of the Results to begin with these metabolomic findings, establishing the\nmetabolic shift to glycolysis as the logical basis for our subsequent focus on lactate. We have\nupdated the Discussion to integrate these findings, further highlighting the importance of\nmetabolic reprogramming in HS and strengthening our comparison with the metabolism of\nkeloids. We have also made our raw metabolomics data publicly available in the GSA-Human\ndatabase as referenced in the manuscript, ensuring full transparency. We believe these\nadditions directly address your concern and have made the manuscript's narrative clearer and\nmore scientifically rigorous. We are grateful for your valuable feedback, which has\nundoubtedly improved the quality of our paper. Thank you again for your valuable guidance.\nRevised figures:\nFigure S1\nRevised manuscript:\n“To characterize the metabolic phenotype, non-targeted metabolomic analysis of HS and\nhealthy tissues revealed a distinct metabolic profile in patients (Figure S1A; Supplemental\ndata 1). HS tissue exhibited a significant decrease in the key TCA cycle intermediate, citric\nacid, and a concomitant increase in the glycolytic metabolite, phosphoenolpyruvic acid\n(Figure S1A-S1C).”\n“This concurrent upregulation of the glycolytic pathway and downregulation of key OXPHOS\ncomponents provides strong evidence of a metabolic switch towards aerobic glycolysis in the\nHS microenvironment.”\n“We have now further confirmed that this lactate accumulation arised from a clear metabolic\nshift, where the upregulation of glycolysis is coupled with the downregulation of oxidative\nphosphorylation.”\n“The raw non-targeted metabolomic data are available online through OMIX database\n(https://ngdc.cncb.ac.cn/omix/) with the study accession ID: OMIX011916.”\nComment #3: If the authors want to discuss shifts between energy-supplying pathways, they\nshould demonstrate that the actual transition from one to another occurs. What is the relative\nexpression of genes involved in oxidative phosphorylation? Is glycolysis indeed the\ndominating pathway used for energy generation in the hypertrophic skin?\nReply:\nThank you for your insightful and constructive comments. We agree that demonstrating a\nclear shift between energy-supplying pathways is crucial for our manuscript. Your feedback\nhas prompted us to perform additional experiments that we believe have substantially\nstrengthened our conclusions. To directly address your questions, we have performed new RT-\nqPCR experiments to assess the relative mRNA expression of key genes involved in oxidative\nphosphorylation (OXPHOS) and the TCA cycle in hypertrophic scar tissues compared to\nnormal skin tissues. We specifically analyzed PDHA1 (a key component of the pyruvate\ndehydrogenase complex, which links glycolysis to the TCA cycle), CS, IDH1, IDH2,\nand OGDH (critical enzymes within the TCA cycle). Our new results show a significant\ndownregulation in the expression of PDHA1, IDH1, and IDH2 in HS tissues. However, we\nobserved a decreasing trend for CS and OGDH, although these did not reach statistical\nsignificance in our cohort. Futhermore, we have performed a non-targeted metabolomic\nanalysis of HS and NS tissues. The results indicated that key intermediates of the TCA cycle,\nsuch as citric acid, were significantly decreased in HS. Conversely, metabolites of the\nglycolytic pathway, such as phosphoenolpyruvic acid, were significantly increased (Figure\nS1A-S1C).\nThis demonstrated downregulation of the OXPHOS pathway, when viewed in conjunction\nwith our original findings, provides compelling evidence for a metabolic transition. Our\noriginal data already showed: (1) Significantly elevated lactate levels in HS tissues (Figure\n1A). (2) Upregulated expression of key glycolysis-related genes and transporters\n(PKM2, LDHA, MCT1, MCT4) (Figure 1B-E). (3) A heightened extracellular acidification\nrate (ECAR) in macrophages, which are the primary source of lactate in the stiff HS\nmicroenvironment (Figure 2). The combination of these findings—the upregulation of\nglycolysis and the concurrent downregulation of OXPHOS—strongly supports the conclusion\nthat a metabolic shift towards aerobic glycolysis occurs in hypertrophic scars. This shift\nestablishes glycolysis as a dominant metabolic pathway fueling the profibrotic conditions,\nparticularly by providing the lactate substrate for the epigenetic modifications that are central\nto our study.\nWe have revised the Results and Discussion sections of the manuscript to incorporate these\nnew findings and to more explicitly articulate this metabolic transition. We believe these\nadditions and revisions fully address your concerns and have made our manuscript much\nmore robust. Thank you again for your valuable guidance.\nRevised manuscript:\n“To characterize the metabolic phenotype, non-targeted metabolomic analysis of HS and\nhealthy tissues revealed a distinct metabolic profile in patients (Figure S1A; Supplemental\ndata 1). HS tissue exhibited a significant decrease in the key TCA cycle intermediate, citric\nacid, and a concomitant increase in the glycolytic metabolite, phosphoenolpyruvic acid\n(Figure S1A-S1C).”\n“Next, RT-qPCR analysis of the expression of genes related to glycolysis (LDHA, HK2,\nPKM2 and PFKFB3), lactate transport (MCT1 and MCT4) and OXPHOS (PDHA1, CS,\nIDH1, IDH2 and OGDH) showed a significant increase of lactate-related genes in HS,\nparticularly MCT1 (Figure 1B). Specifically, the mRNA levels of PDHA1, IDH1 and IDH2\nwere significantly decreased compared to normal skin (Figure 1B). This concurrent\nupregulation of the glycolytic pathway and downregulation of key OXPHOS components\nprovides strong evidence of a metabolic switch towards aerobic glycolysis in the HS\nmicroenvironment.”\n“We have now further confirmed that this lactate accumulation arised from a clear metabolic\nshift, where the upregulation of glycolysis is coupled with the downregulation of oxidative\nphosphorylation.”\nRevised figures:\nFigure 1D\nFigure S1\nComment #4: The quality of IF is very poor, and it´s difficult to see individual cells. Higher\nquality imaging should be provided.\nReply:\nThank you for your insightful and constructive comments. We agree that the quality of the\noriginal immunofluorescence images was insufficient and we apologize that this made it\ndifficult to visualize individual cells clearly. To address this important issue, we have taken\nthe following steps to improve the manuscript: (1) Increased image resolution: We have\nincreased the resolution of all immunofluorescence images presented in the manuscript. This\nshould provide much greater detail and clarity. (2) Image replacement: We have carefully\nreviewed all our IF images and have replaced several of the lower-quality ones with new,\nclearer images from our experiments (for example, in Figure 1E and 1F). In these new\nimages, the morphology and outlines of individual cells are now clearly discernible. We have\nupdated all relevant figures in the revised manuscript. We believe these changes have\nsignificantly improved the quality of our data presentation. We are grateful for the opportunity\nto improve our manuscript and hope the revised images are now satisfactory. Thank you again\nfor your constructive suggestion.\nRevised figures:\nFigure 1E\nFigure 1F\nComment #5: There is a discrepancy in the relative protein expression measured by Western\nblot, IHC, and IF in Figure 1. The authors should explain why.\nReply:\nWe sincerely thank the reviewer for their careful reading of our manuscript and for this\ninsightful comment. We acknowledge the reviewer's observation regarding the apparent\nvariations in the magnitude of relative protein expression for key glycolytic markers,\nparticularly MCT1, as measured by WB, IHC, and IF in Figure 1. We agree that this point\nwarrants clarification. The variations observed do not undermine our conclusion but rather\nstem from two main factors: the inherent biological variability among patient samples and the\nfundamental technical differences between these analytical methods.\nThe primary reason for this variation is the biological heterogeneity among human subjects.\nAs detailed in our Methods section, the HS and NS samples were collected from a cohort of\ndifferent patients. For ethical and practical reasons, the exact same tissue specimen from a\nsingle patient was not used across all three experimental procedures (WB, IHC, and IF).\nWhile we analyzed multiple biological replicates for each experiment (e.g., n=5 for WB, as\nstated in the Figure 1 legend) to ensure the statistical validity of the observed trend, patient-\nto-patient variability in protein expression levels is expected. Furthermore, it is crucial to\nrecognize the distinct nature of these three techniques, each providing a different type of\ninformation: (1) Western blotting provides a semi-quantitative analysis of the average protein\nexpression across a bulk population of cells from a homogenized tissue lysate. In contrast,\nIHC and IF are primarily qualitative or semi-quantitative methods that provide indispensable\nspatial information, revealing the cellular localization and distribution of the target protein\nwithin the intact tissue architecture. For instance, our IF co-staining in Figure 1F was crucial\nto demonstrate that MCT1 is specifically upregulated in α-SMA-positive myofibroblasts in\nHS tissue, a critical finding that a bulk lysate WB could not resolve. (2) The sample\npreparation for each method is vastly different. WB analysis involves harsh protein\ndenaturation and solubilization from lysates. IHC and IF, however, rely on formalin-fixed,\nparaffin-embedded tissue sections that require antigen retrieval procedures to unmask\nepitopes. These distinct processes can influence the antibody's binding affinity and,\nconsequently, the resulting signal intensity. (3) The signal detection and amplification systems\nare unique to each method. WB uses an enzyme-conjugated secondary antibody that generates\na chemiluminescent signal, quantified via densitometry. IHC employs an enzymatic reaction\n(DAB staining) visualized by bright-field microscopy, while IF uses fluorescently labeled\nantibodies visualized by fluorescence or confocal microscopy. These methods have different\nsensitivities, dynamic ranges, and signal-to-noise ratios, making a direct comparison of\nexpression magnitudes across these platforms inappropriate.\nIn summary, while the exact magnitude of expression may differ, the key conclusion remains\nhighly consistent and robust across all three independent assays: the expression of MCT1\nand the overall capacity for glycolysis are significantly elevated in hypertrophic scar\ntissue compared to normal skin. The consistency of this directional trend across multiple\nmethodologies strongly supports the validity of our findings.\nTo address the reviewer's excellent point and improve the manuscript's clarity, we will add a\nsentence to the Results section (in the paragraph corresponding to Figure 1) to briefly state\nthat while all methods confirm the upregulation of these proteins in HS, a direct comparison\nof the magnitude of change is not appropriate due to inter-patient variability and the distinct\ntechnical nature of each assay. Once again, we thank the reviewer for their constructive\nfeedback, which has helped us to enhance the precision of our manuscript.\nRevised manuscript:\n“Despite having some minor differences, similar patterns were observed in IHC assay and\nimmunofluorescence results (Figure 1D and 1E), which indicated that the expression of\nMCT1 and the overall capacity for glycolysis are significantly elevated in HS tissue compared\nto NS.”\nComment #6: The authors talk about data that is not present in the figure: “ and we did not\nobserve noticeable differences of MCT1 intensity in vascular endothelial cells between NS\nand HS (Figure 1F)” – no markers of vascular endothelial cells has been used in the whole\nfigure, and in particular not the referred Figure 1F.\nReply:\nWe sincerely thank you for your careful and detailed review of our manuscript and for\npointing out this important inconsistency. We agree completely with the reviewer. Our\noriginal statement regarding the lack of change in MCT1 intensity in vascular endothelial\ncells was an overstatement and not directly supported by the data presented. The reviewer is\ncorrect that Figure 1F showed co-staining for MCT1 and α-SMA, which is a marker for\nmyofibroblasts and smooth muscle cells, but not a specific marker for vascular endothelial\ncells. Our initial comment was based on a general morphological observation of the blood\nvessel structures, but it was not appropriate to make a definitive claim without using a\nspecific endothelial marker (such as CD31). To address this issue and ensure the scientific\naccuracy of our manuscript, we have removed the unsubstantiated sentence from the revised\ntext. The deleted sentence is: \"and we did not observe obvious differences of MCT1 intensity\nin vascular endothelial cells between NS and HS (Figure 1F)\". We appreciate the reviewer’s\nvaluable feedback, which has helped us improve the precision and quality of our paper.\nComment #7: In Figure 2, the authors use an in vitro system to investigate the cellular origin\nof lactate, which is detected in hypertrophic skin tissue. This approach is reductionistic, as it\ndoes not aim to identify which of the various cell types in the hypertrophic skin is the primary\nproducer of lactate. Instead, they select specific cells to probe for lactate production. The\nauthors should either use patient material (as in Figure 1) or the developed mouse model to\nanswer this question.\nReply:\nWe thank you for this insightful and constructive comment. We agree that identifying the\nprimary source of lactate directly within the complex cellular milieu of HS tissue is critical to\nsubstantiating our claims. The reviewer’s concern regarding the reductionist nature of our\ninitial in vitro system is well-taken, and we recognize that relying solely on cell lines may not\nfully recapitulate the in vivo cellular dynamics. To address this pivotal point directly, we have\nperformed three new sets of experiments using human patient-derived materials, as you\nsuggested.\nFirst, to provide direct quantitative evidence, we successfully isolated primary macrophages,\nendothelial cells, and fibroblasts using magnetic activated cell sorting (MACS) from both\nfresh HS and NS tissues. We then directly measured the extracellular and intracellular lactate\nlevels in these distinct primary cell populations. We found that primary macrophages isolated\nfrom HS tissues exhibited the most substantial and significant increase in lactate content\ncompared to their counterparts from NS when compared to other cell types isolated from HS\n(Figure 2G). In addition, enhanced ECAR level was observed in primary macrophages from\nHS tissues compared to control (Figure 2H). Second, we conducted multispectral\nimmunofluorescence staining on human HS and NS tissues to investigate the in situ activity\nof the glycolytic pathway in different cell types. Our new results reveal a significant\nupregulation of key glycolytic enzymes (HK2 and LDHA) specifically within the macrophage\npopulation in HS tissues (Figure 2I and 2J). In contrast, endothelial cells did not show\nstatistically significant changes in glycolytic activity between HS and NS (Figure S3D and\nS3E). This provides strong evidence from patient material that macrophages, in particular,\nadopt a hyper-glycolytic phenotype within the scar microenvironment.\nFurthermore, we have performed a new in vivo experiment using our full-thickness skin\ndefect mouse model. In this experiment, we selectively depleted macrophages during the\nwound healing process to directly assess their contribution to lactate production and\nsubsequent scar formation. Specifically, we administered clodronate liposomes sub-eschar\nevery three days starting on day 7 post-injury to deplete macrophages, with a control group\nreceiving saline injections. On day 21, wound tissues were harvested for analysis.\nImmunofluorescence staining for the macrophage marker F4/80 confirmed a significant\nreduction in macrophage numbers in the scar tissues of clodronate-treated mice compared to\ncontrols (Figure S2F). Crucially, lactate concentration was markedly decreased in the scar\ntissue of macrophage-depleted mice (Figure S2G). These experiments, performed on clinically relevant human tissues and animal model, provide\ncompelling evidence that corroborates our in vitro findings. They strongly support our\nconclusion that macrophages are the principal source of the lactate-rich microenvironment\nthat drives fibrotic remodeling in hypertrophic scars.\nTogether, these new findings, derived directly from patient tissue and mouse model, strongly\ncorroborate the hypothesis generated from our in vitro system (the original Figure 2) and\nprovide a more robust and clinically relevant answer to the question of the cellular origin of\nlactate. We have now incorporated these new data into a new figure in the manuscript and\nrevised the Results section accordingly. We believe these additions significantly strengthen\nthe manuscript by providing direct, patient-derived evidence that pinpoints macrophages as\nthe major source of lactate in the HS microenvironment. We are grateful to the reviewer for\nprompting this important validation. Thank you again for your guidance.\nRevised figures:\nFigure 2G\nFigure 2H\nFigure 2I\nFigure 2J\nFigure S3\nFigure S11D-S11F\nRevised manuscript:\n“To validate in vivo that macrophages are a primary source of lactate during scar formation,\nwe isolated primary macrophages, vascular endothelial cells and dermal fibroblasts from fresh\nNS and HS tissues using magnetic activated cell sorting (MACS) and protein-level validation\nwas performed on these cells using western blotting (Figure S3A-S3C). In line with previous\nresults, primary macrophages from HS tissues showed a profoundly elevated extracellular\nlactate accumulation and intracellular production, but lactate levels in fibroblasts and\nendothelial cells remained constant (Figure 2G). In addition, enhanced ECAR level was\nobserved in primary macrophages from HS tissues compared to control (Figure 2H). This\nmacrophage-specific metabolic shift was corroborated by the selective upregulation of\nglycolytic enzymes HK2 and LDHA within CD68+ macrophages in HS tissue (Figure 2I and\n2J), with no corresponding change in CD31+ endothelial cells (Figure S3D and S3E).\nCrucially, we utilized clodronate liposomes to specifically deplete macrophages in the full-\nthickness skin defect model on the dorsal region of C57BL/6 mice. Immunofluorescence\nanalysis confirmed a significant depletion of F4/80-positive macrophages in the scar tissue of\nclodronate liposomes-treated mice compared to saline-treated controls (Figure S3F).\nImportantly, this macrophage depletion resulted in a marked decrease in lactate levels within\nthe scar tissue (Figure S3G). Collectively, these in vivo findings strongly support our\nconclusion that macrophages are a key contributor to the lactate-rich microenvironment in\nHS.”\n“To identify the source of lactate in the scar microenvironment in vivo, C57BL/6 mice aged 6\nto 8 weeks were randomly assigned to two groups (Control, Clodronate liposome).\nClodronate liposomes (Yeasen, 40337ES) were administered of 40 µL sub-eschar every three\ndays starting from day 7 post-injury with a solution prepared at a dose of 50ug/ml.”\n“To validate the role of in vivo macrophage depletion, reducing the source of lactate, in scar\nformation, we then performed H&E and Masson's trichrome staining on the collected scar\ntissue at post-injury day 21. The results indicated that clodronate liposomes significantly\nreduced scar formation in the dorsal wounds of mice and promoted hair follicle regeneration,\nsuggesting that macrophages play an important pathological role in the late stage of wound\nhealing (Figure S11D-F). Collectively, MCT1 inhibition via AZD3965 or clearance of the\nsource of lactate may be an effective therapeutic strategy for hypertrophic scar.”\nComment #8: The molecular interaction modeling exercise doesn’t contribute to the main\nmessage of the study.\nReply:\nWe sincerely thank you for their insightful feedback and for raising this important point. We\nappreciate the opportunity to clarify the essential role of the molecular interaction modeling in\nsubstantiating our study's central message. We concede that the manuscript may not have\nmade this link sufficiently explicit, and we have revised the text to better integrate these\nfindings.\nOur study's main message is not only the identification of a linear pathway (macrophage\nlactate → MCT1 → H3K23la → HEY2/COL11A1 expression) but, more critically, the\ndiscovery of a self-reinforcing positive feedback loop that perpetuates the fibrotic state in\nhypertrophic scars (HS). The molecular modeling is the linchpin that provides the direct\nmechanistic evidence for this feedback loop. Here is a step-by-step explanation of its\nindispensability to our core argument: (1) Establishing the physical interaction: Our\nexperimental data, including Co-immunoprecipitation (Figure 8B) and immunofluorescence\ncolocalization assays (Figures 8C, 8D), provided strong evidence that a physical interaction\noccurs between COL11A1 (a downstream product of the pathway) and the lactate transporter\nMCT1 (a key upstream component). This observation was the first indication of a potential\nfeedback mechanism. (2) The crucial question: what is the functional consequence of this\ninteraction? While our biochemical and cellular data confirmed that COL11A1 and MCT1\nbind, these experiments could not explain the functional consequence of this interaction. Does\nthis binding event alter MCT1's activity? If so, how? Answering this question is paramount to\nproving that the pathway is not merely linear but circular and self-amplifying. Without\nunderstanding the functional outcome, the feedback loop remains a speculative concept. (3)\nThe role of molecular modeling: bridging the gap from interaction to function. This is the\nprecise knowledge gap that our molecular interaction modeling was designed to fill. Its\ncontributions are twofold: First, the docking simulations provided a structurally plausible\nmodel for how these two proteins interact, identifying specific amino acid residues that likely\nmediate the binding (Figure 8E). This elevates our finding from a simple observation to a\nconcrete, testable molecular mechanism. Second, and most critically, our molecular dynamics\nsimulations and binding free energy calculations revealed a crucial functional consequence:\nthe binding of COL11A1 not only stabilizes the conformation of MCT1 (Figure S10A, S10B)\nbut also significantly enhances its affinity for lactate (Figure 8G and S10D). This\ncomputational result directly supports our experimental data showing that COL11A1\nexpression correlates with increased intracellular lactate levels (Figure S10D).\nTherefore, the molecular modeling is not an ancillary exercise; it is the critical evidence that\nmechanistically closes the proposed feedback loop: lactate → H3K23la → COL11A1 →\nCOL11A1 binds MCT1 → MCT1 affinity for lactate increases → more lactate enters the cell,\nthus perpetuating the cycle. Without this modeling, we could only state that COL11A1 and\nMCT1 interact. With the modeling, we can propose a complete, mechanistically detailed\nnarrative: that the upregulation of COL11A1 in HS is not just a marker of fibrosis but an\nactive driver that enhances the metabolic reprogramming that initiated its expression. This\ntransforms our understanding of HS pathogenesis from a linear process to a self-sustaining\ndisease state, which we believe is the most significant message of our study. We hope this\nexplanation clarifies the indispensable role of the modeling data. We have revised the relevant\nsections of the manuscript (particularly in the Results and Discussion) to state more clearly\nhow the modeling provides the functional explanation for the positive feedback loop. Thank\nyou again for your valuable comment, which has helped us to improve the clarity and impact\nof our paper.\nRevised manuscript:\n“While our Co-IP and immunofluorescence data confirmed a physical interaction between\nCOL11A1 and MCT1, the functional consequence of this binding remained unclear. To\ndetermine precisely how COL11A1 binding might modulate MCT1's activity, we performed\nmolecular modeling.”\n“The simulations provide a structural and energetic basis for how COL11A1 enhances\nMCT1's lactate transport affinity, thereby closing the loop.”\n“Furthermore, the COL11A1 protein exhibits a non-canonical function by directly interacting\nwith the lactate transporter MCT1. Molecular modeling shows this interaction stabilizes\nMCT1 and enhances its lactate affinity, potentiating lactate transport. This establishes a\npathogenic, self-reinforcing positive feedback loop (lactate-H3K23la-COL11A1-MCT1),\nwhich sustains the scar microenvironment.”\nReviewer 4:\nIn the study titled “Lactate derived from macrophages drives skin dermal fibroblasts\nphenotypic remodeling via MCT1-primed histone H3 lysine 23 lactylation in hypertrophic\nscar,” Hu et al. delineated the role of macrophage-derived lactate in hypertrophic scar (HS)\nformation. They identified that macrophage-derived lactate serves as a critical mediator of\nfibroblast phenotypic remodeling through monocarboxylate transporter 1 (MCT1)-mediated\nhistone H3 lysine 23 lactylation (H3K23la) in HS. The authors observed that fibroblast-\nspecific deletion of Mct1 or pharmacological inhibition of Mct1 in mice reduced collagen\ndeposition, accelerated wound healing, and attenuated scar formation.\nThe study is highly interesting, well designed, and clearly presented. Nevertheless, several\nminor issues need to be addressed:\nComment #1: Multiple immunofluorescence images in the manuscript are of relatively low\nresolution (e.g., Figure 1E and Figure S6). Higher-resolution images should be provided.\nReply:\nThank you for your valuable feedback and for your careful review of our manuscript. We\nsincerely appreciate your constructive comments. We agree that the clarity and resolution of\nimages are critical for presenting our findings accurately, and we thank you for bringing this\nissue to our attention.\nIn response to your concern, we have taken immediate action to improve the quality of the\nfigures in our manuscript. We have replaced all the immunofluorescence images that were of\nlow resolution, including the specific examples you mentioned, Figure 1E and Figure S9, with\nnew, high-resolution versions. The issue in the original submission was likely due to an\nunintentional loss of quality during the file conversion and PDF generation process. To\naddress this thoroughly, we have returned to our original, raw image files captured by the\nmicroscope. We have carefully re-exported these images at a high resolution and have re-\nassembled the figures to ensure that all details are sharp and clearly visible. Furthermore, we\nhave taken this opportunity to conduct a comprehensive review of all figures throughout the\nmanuscript and its supplementary materials to ensure that they all meet the highest standards\nfor publication. We are confident that the revised images in the updated manuscript now\nclearly and accurately illustrate our data. We hope these improvements satisfactorily address\nyour concerns. Thank you once again for your time and guidance.\nRevised figures:\nFigure 1E\nFigure S9F\nFigure S9G\nComment #2: In Figure 9C and Figure 10C, the blue coloration of the Masson’s trichrome\nstaining is uneven, suggesting possible overstaining. Higher-resolution Masson’s staining\nimages are required.\nReply:\nWe sincerely thank the reviewer for their careful evaluation and valuable feedback on our\nmanuscript. We agree that high-quality images are crucial for conveying our findings\naccurately.\nIn response to the reviewer's comments, we have taken the following actions: (1)\nReplacement of images with higher-resolution versions: As requested, we have replaced the\noriginal Masson's trichrome staining images in Figure 9D and Figure 10C with new, higher-\nresolution versions. We believe these updated images provide significantly greater detail and\nclarity, allowing for a more thorough assessment of the tissue histology. These changes have\nbeen implemented in the revised manuscript. (2) Clarification on the \"uneven\" blue coloration\nand \"overstaining\": We appreciate the reviewer pointing out the \"uneven\" and intense blue\ncoloration in certain panels. We would like to respectfully clarify that this observation is,\nin fact, a key histopathological finding of our study and is not an artifact of overstaining. In our\nstudy, Masson’s trichrome staining is used to visualize collagen deposition, a hallmark of\nfibrosis and hypertrophic scar. The key characteristics of hypertrophic scar are the excessive\nsynthesis and disorganized, dense deposition of collagen fibers. In the control and lactate-\ntreated groups (e.g., the Mct1fl/flColla2-cre- + NaLac group in Fig. 9D and the Control +\nNaLac group in Fig. 10C), the tissue exhibits significant fibrosis. This pathological state is\ncharacterized by thick, irregularly arranged, and densely packed collagen bundles. Masson’s\nstain, which stains collagen blue, therefore produces an intense, deep, and non-uniform\n(uneven) blue appearance that accurately reflects this disorganized and excessive collagen\nmatrix. Conversely, in the groups where scar formation was ameliorated through our\ninterventions (i.e., the Mct1 knockout group in Fig. 9D and the AZD3965-treated\ngroup in Fig. 10C), the wound healing process is improved. This results in collagen fibers that\nare finer, more organized, and less dense, arranging themselves in a smoother, parallel fashion\nthat more closely resembles normal dermis. Consequently, the blue staining in these panels\nappears lighter and more uniform, which is indicative of reduced fibrosis. Therefore, the\nvariation in staining intensity and the \"unevenness\" observed across the different\nexperimental groups are a direct visual representation of the biological differences in collagen\narchitecture and density, which supports our central conclusion that inhibiting the MCT1-\nlactate axis ameliorates hypertrophic scar formation.\nWe are confident that the new high-resolution images, combined with this explanation, will\nmake this crucial distinction even clearer to the reader. We thank the reviewer again for\nproviding us with the opportunity to clarify this important point and improve the quality of\nour figures.\nFigure 9D\nFigure 10C\nComment #3: The authors demonstrated in vitro that macrophages are the primary source of\nlactate accumulation in the scar metabolic microenvironment. Given the substantial\ndifferences between in vitro and in vivo conditions, in vivo validation of macrophage-\nmediated lactate accumulation in the hypertrophic scar microenvironment would further\nstrengthen the credibility of this conclusion.\nReply:\nThank you for your constructive and insightful feedback on our manuscript. We agree that\nvalidating our in vitro findings in vivo is crucial for strengthening the conclusions of our\nstudy. Your point regarding the substantial differences between in vitro and in vivo conditions\nis well-taken, and we appreciate the opportunity to enhance the credibility of our work.\nTo address this important concern, we have performed three additional sets of experiments\nusing human hypertrophic scar (HS) and normal skin (NS) tissues to validate our conclusion\nthat macrophages are the primary source of lactate in the HS microenvironment. First, to\nprovide more direct and quantitative evidence, we successfully isolated primary\nmacrophages, endothelial cells, and fibroblasts from freshly obtained human NS and HS\ntissues using magnetic activated cell sorting (MACS). We then directly measured the\nintracellular lactate content of these distinct cell populations. Consistent with our in\nvitro data (original Figure 2), we found that primary macrophages isolated from HS tissues\nexhibited the most significant increase in lactate levels compared to those from NS (Figure\n2G). This increase was markedly more pronounced than that observed in fibroblasts or\nendothelial cells from the same HS tissues (Figure 2G). In addition, enhanced ECAR level\nwas observed in primary macrophages from HS tissues compared to control (Figure 2H).\nSecond, we conducted multicolor immunofluorescence staining on human HS and NS\nspecimens. We co-stained for macrophage markers (CD68), endothelial cell markers\n(CD31), and key glycolytic enzymes (e.g., HK2 and LDHA). The results clearly\ndemonstrated a significant upregulation of these glycolytic enzymes specifically within the\nCD68+ macrophage population in HS tissues (Figure 2I and 2J). In contrast, no statistically\nsignificant changes were observed in the CD31+ endothelial cells (Figure S3D and S3E). This\nprovides strong in vivo evidence that macrophages in the scar microenvironment possess a\nheightened glycolytic state compared to other cell types. Furthermore, we have performed a\nnew in vivo experiment using our full-thickness skin defect mouse model. In this\nexperiment, we selectively depleted macrophages during the wound healing process to\ndirectly assess their contribution to lactate production. Specifically, we administered\nclodronate liposomes subcutaneously every three days starting on day 7 post-injury to deplete\nmacrophages, with a control group receiving saline injections. On day 21, wound tissues were\nharvested for analysis. Immunofluorescence staining for the macrophage marker F4/80\nconfirmed a significant reduction in macrophage numbers in the scar tissues of clodronate-\ntreated mice compared to controls (Figure S3F). Crucially, lactate concentration was\nmarkedly decreased in the scar tissue of macrophage-depleted mice (Figure S3G). Moreover,\nclodronate liposomes significantly reduced scar formation in the dorsal wounds of mice and\npromoted hair follicle regeneration (Figure S11D-F).\nTogether, these new findings, derived directly from human clinical samples and mouse model,\nrobustly corroborate our original conclusion based on the in vitro model. They provide\ncompelling evidence that macrophages are indeed a major source of lactate accumulation\nwithin the hypertrophic scar metabolic microenvironment. We have incorporated these new\nresults into the revised manuscript. We have added a new Figure 2G-2J and S3 to present the\ndata from these experiments and have updated the Results section. We have also added\ndetailed protocols for these new experiments to the Methods section. We are grateful for your\nvaluable suggestion, which has allowed us to substantially strengthen our manuscript. We\nhope that these additions and revisions have fully addressed your concerns. Thank you once\nagain for your time and guidance.\nRevised figures:\nFigure 2G\nFigure 2H\nFigure 2I\nFigure 2J\nFigure S3\nFigure S11D-S11F\nRevised manuscript:\n“To validate in vivo that macrophages are a primary source of lactate during scar formation,\nwe isolated primary macrophages, vascular endothelial cells and dermal fibroblasts from fresh\nNS and HS tissues using magnetic activated cell sorting (MACS) and protein-level validation\nwas performed on these cells using western blotting (Figure S3A-S3C). In line with previous\nresults, primary macrophages from HS tissues showed a profoundly elevated extracellular\nlactate accumulation and intracellular production, but lactate levels in fibroblasts and\nendothelial cells remained constant (Figure 2G). In addition, enhanced ECAR level was\nobserved in primary macrophages from HS tissues compared to control (Figure 2H). This\nmacrophage-specific metabolic shift was corroborated by the selective upregulation of\nglycolytic enzymes HK2 and LDHA within CD68+ macrophages in HS tissue (Figure 2I and\n2J), with no corresponding change in CD31+ endothelial cells (Figure S3D and S3E).\nCrucially, we utilized clodronate liposomes to specifically deplete macrophages in the full-\nthickness skin defect model on the dorsal region of C57BL/6 mice. Immunofluorescence\nanalysis confirmed a significant depletion of F4/80-positive macrophages in the scar tissue of\nclodronate liposomes-treated mice compared to saline-treated controls (Figure S3F).\nImportantly, this macrophage depletion resulted in a marked decrease in lactate levels within\nthe scar tissue (Figure S3G). Collectively, these in vivo findings strongly support our\nconclusion that macrophages are a key contributor to the lactate-rich microenvironment in\nHS.”\n“To identify the source of lactate in the scar microenvironment in vivo, C57BL/6 mice aged 6\nto 8 weeks were randomly assigned to two groups (Control, Clodronate liposome).\nClodronate liposomes (Yeasen, 40337ES) were administered of 40 µL sub-eschar every three\ndays starting from day 7 post-injury with a solution prepared at a dose of 50ug/ml.”\n“To validate the role of in vivo macrophage depletion, reducing the source of lactate, in scar\nformation, we then performed H&E and Masson's trichrome staining on the collected scar\ntissue at post-injury day 21. The results indicated that clodronate liposomes significantly\nreduced scar formation in the dorsal wounds of mice and promoted hair follicle regeneration,\nsuggesting that macrophages play an important pathological role in the late stage of wound\nhealing (Figure S11D-F). Collectively, MCT1 inhibition via AZD3965 or clearance of the\nsource of lactate may be an effective therapeutic strategy for hypertrophic scar.”\nComment #4: The authors identified an interaction between COL11A1 and MCT1. However,\nit remains unclear whether additional proteins are involved in this interaction. Further\nexperimental validation or detailed discussion in the Discussion section is warranted.\nReply:\nThank you for your insightful and constructive comment. We agree that this is a crucial point\nthat warrants further consideration. Our Co-IP and colocalization results strongly indicate a\nrobust interaction between COL11A1 and MCT1 within the cellular context. Furthermore, our\ncomputational modeling supports the plausibility of a direct binding interface.\nHowever, we concur that in a complex biological system, this interaction is likely not\noccurring in isolation and may be stabilized or mediated by other associated proteins. Your\nquery prompted us to delve deeper into the literature and consider potential candidates. A\nparticularly strong candidate for such a role is CD147 (also known as Basigin or\nEMMPRIN). It is well-established that CD147 acts as an essential ancillary/chaperone\nprotein for the proper trafficking, cell surface expression, and functional activity of\nmonocarboxylate transporters, including MCT1 (Nan Wang et al., 2021; Andrew P Halestrap,\n2013). Without association with CD147, MCT1 is often retained intracellularly and rapidly\ndegraded. Given that our study focuses on the function of MCT1 at the plasma membrane for\nlactate transport, the involvement of CD147 is almost certain and highly relevant. Moreover,\nCD147 itself is deeply implicated in ECM remodeling and fibrosis. As an \"Extracellular\nMatrix Metalloproteinase Inducer\" (EMMPRIN), it stimulates the production of MMPs,\nwhich are critical for tissue remodeling in processes like wound healing and scarring. Its\nexpression is often upregulated in fibrotic conditions and it plays a significant role in cell-\nmatrix interactions (Jiao Wu et al., 2022; Mingchuan Liu et al., 2023). Therefore, we propose\na compelling hypothesis that the interaction we observed may exist as a ternary complex of\nCOL11A1-CD147-MCT1. In this model: (1) CD147 acts as the direct chaperone, binding to\nMCT1 to ensure its stability and presence at the cell surface. (2) COL11A1, as a key\ncomponent of the fibrotic ECM, could then interact with the CD147-MCT1 complex. This\ninteraction might serve to anchor the lactate transport machinery within specific membrane\ndomains, or it could sterically stabilize the complex, thereby enhancing MCT1-mediated\nlactate transport and perpetuating the positive feedback loop we described. While definitively\nvalidating this ternary complex through further experiments like sequential Co-IP is beyond\nthe scope of our current study, we believe this is a highly plausible mechanism and a\nfascinating avenue for future research.\nTo address your excellent point, we have now added a detailed paragraph in the Discussion\nsection to elaborate on the potential role of CD147 as a key intermediary in the COL11A1-\nMCT1 interaction, citing relevant literature. We believe this addition significantly enriches the\nmanuscript and provides a more complete mechanistic picture for our readers. Thank you\nagain for helping us improve the quality of our manuscript.\nRevised manuscript:\n“Furthermore, while our co-immunoprecipitation and computational data support an\ninteraction between COL11A1 and MCT1, it is critical to consider the potential involvement\nof other proteins that may mediate or stabilize this complex in the cellular milieu. A prime\ncandidate is the chaperone protein CD147, which is indispensable for the membrane\nlocalization and functional stability of MCT1. We thus hypothesize that COL11A1 forms a\nternary complex with CD147 and MCT1. This complex would anchor the lactate transporter,\nenhancing its activity and thereby amplifying pro-fibrotic signaling. Future sequential\nimmunoprecipitation experiments are required to elucidate the precise composition and\nstoichiometry of this putative complex.”\nReferences:\n(1) Wang, N., Jiang, X., Zhang, S., Zhu, A., Yuan, Y., Xu, H., Lei, J., & Yan, C. (2021).\nStructural basis of human monocarboxylate transporter 1 inhibition by anti-cancer drug\ncandidates. Cell, 184(2), 370–383.e13.\n(2) Halestrap A. P. (2013). The SLC16 gene family - structure, role and regulation in health\nand disease. Molecular aspects of medicine, 34(2-3), 337–349.\n(3) Wu, J., Chen, L., Qin, C., Huo, F., Liang, X., Yang, X., Zhang, K., Lin, P., Liu, J., Feng,\nZ., Zhou, J., Pei, Z., Wang, Y., Sun, X. X., Wang, K., Geng, J., Zheng, Z., Fu, X., Liu, M.,\nWang, Q., Chen, Z. N. (2022). CD147 contributes to SARS-CoV-2-induced pulmonary\nfibrosis. Signal transduction and targeted therapy, 7(1), 382.\n(4) Liu, M., Peng, T., Hu, L., Wang, M., Guo, D., Qi, B., Ren, G., Wang, D., Li, Y., Song, L.,\nHu, J., & Li, Y. (2023). N-glycosylation-mediated CD147 accumulation induces cardiac\nfibrosis in the diabetic heart through ALK5 activation. International journal of biological\nsciences, 19(1), 137–155.\nComment #5: The authors observed elevated lactate levels and increased MCT1 expression\nin HS tissues. What is the relationship between lactate levels, MCT1 expression, and HS\ndisease progression?\nReply:\nThank you for your insightful question, which highlights the central mechanism we aimed to\nelucidate in our study. The relationship between elevated lactate, increased MCT1 expression,\nand the progression of HS is indeed the cornerstone of our findings. This relationship is not\nmerely a correlation but rather a causative, self-reinforcing feedback loop that drives the\nfibrotic process. We have detailed this mechanism throughout our manuscript, and we\nappreciate the opportunity to summarize and clarify it here.\nBased on our findings, the relationship can be understood through the following sequential\nand cyclical steps: (1) Origin of lactate: We identified that in the stiff, pathological\nmicroenvironment of HS, macrophages undergo a metabolic shift to a hyperglycolytic\nphenotype. These activated macrophages become the primary source of the elevated lactate\nlevels observed in HS tissues (as shown in our findings related to Figure 2 and S3). (2)\nLactate uptake by fibroblasts via MCT1: Concurrently, we observed a significant upregulation\nof MCT1 expression specifically on dermal fibroblasts, particularly myofibroblasts, within\nthe HS tissue (Figure 1). This increased MCT1 expression functions as a crucial gateway,\nfacilitating the transport of the abundant macrophage-derived lactate from the extracellular\nspace into the fibroblasts. (3) Lactate as an epigenetic signal: Once inside the fibroblast,\nlactate is not merely a metabolic byproduct but acts as a substrate for a key epigenetic\nmodification—histone lactylation. We demonstrated that this lactate influx leads to a specific\nincrease in H3K23la in the myofibroblasts of HS (Figure 4). (4) Activation of a profibrotic\nprogram: The elevated H3K23la then acts as an epigenetic activator, promoting the\ntranscription of key profibrotic genes, namely HEY2 and COL11A1 (Figure 5). These genes\nare critical drivers of the fibroblast-to-myofibroblast transition and extracellular matrix\ndeposition, which are hallmarks of HS progression. (5) A vicious positive feedback loop\ndriving progression: This is the most critical part of the relationship, explaining the \"disease\nprogression.\" The process becomes a self-perpetuating cycle: The upregulation\nof HEY2 further amplifies fibrotic signaling through the YAP1/SMAD2 pathway (Figure 7).\nCrucially, the other upregulated protein, COL11A1, directly interacts with and stabilizes the\nMCT1 transporter on the fibroblast membrane (Figure 8). This stabilization enhances MCT1's\nefficiency, leading to even greater lactate uptake by the fibroblast. This creates a vicious\npositive feedback loop: (Extracellular lactate) → (MCT1-mediated influx) → (Increased\nH3K23la) → (Upregulated COL11A1) → (Stabilized, more efficient MCT1) → (Even more\nlactate influx). This self-reinforcing loop explains how the fibrotic state in HS is not only\ninitiated but also maintained and amplified over time, thus driving disease progression. Our in\nvivo experiments, where genetic ablation or pharmacological inhibition of MCT1 led to\nattenuated scar formation and accelerated wound healing (Figures 9 and 10), provide strong\nevidence for the essential role of this axis in HS pathogenesis. The concept of lactate fueling\npathological states is increasingly recognized in other diseases such as cancer and liver\nfibrosis (Hyunsoo Rho et al., 2023; George A Brooks et al., 2018).\nWe hope this detailed explanation fully addresses your question. We agree that this central\nrelationship could be highlighted more explicitly in the manuscript. As per your suggestion,\nwe will revise the Discussion section to include a more focused and clearer paragraph\nsummarizing this metabolic-epigenetic feedback loop. Thank you again for your valuable\nfeedback.\nRevised manuscript:\n“Our study establishes a novel axis linking metabolic reprogramming and epigenetic\nregulation in hypertrophic scar pathogenesis. First and foremost, we redefine the upstream\ntrigger of fibroblast activation by identifying mechanically stressed macrophages as the key\nlactate producers. The stiff microenvironment induces macrophages to adopt a\nhyperglycolytic phenotype, producing lactate that is shuttled into fibroblasts via MCT1,\nwhich has a significant upregulation in hypertrophic scar tissue. Second, this lactate influx\nprimes H3K23la, activating profibrotic genes HEY2 and COL11A1. HEY2 amplifies fibrotic\nsignaling via YAP1/SMAD2, while COL11A1 stabilizes MCT1 to enhance lactate transport,\ncreating a self-reinforcing loop that perpetuates fibrosis. Furthermore, the process initiates in\nthe stiff HS microenvironment, which induces macrophages to produce excessive lactate.\nCritically, targeting this pathway via fibroblast-specific Mct1 deletion or pharmacological\ninhibition (AZD3965) mitigated the core pathology. This intervention resulted in two\nconcomitant benefits: an acceleration of wound closure, likely reflecting a more rapid\nresolution of the pro-fibrotic inflammatory phase and a reduction in the excessive collagen\ndeposition that defines the quality of the scar. This work provides the first evidence that\nmacrophage-derived lactate fuels HS progression through MCT1-dependent histone\nlactylation, redefining lactate as a metabolic-epigenetic mediator rather than a passive\nbyproduct. These findings position MCT1 as a therapeutic target and establish histone\nlactylation as a novel epigenetic driver of HS progression.”\nReferences:\n(1) Rho, H., Terry, A. R., Chronis, C., & Hay, N. (2023). Hexokinase 2-mediated gene\nexpression via histone lactylation is required for hepatic stellate cell activation and liver\nfibrosis. Cell metabolism, 35(8), 1406–1423.e8.\n(2) Brooks G. A. (2018). The Science and Translation of Lactate Shuttle Theory. Cell\nmetabolism, 27(4), 757–785.\nComment #6: In Figure S6C, nonspecific bands are present for COL11A1, and the two bands\nin the si-NC group are difficult to distinguish. A clearer Western blot image should be\nprovided.\nReply:\nThank you for your valuable feedback and the opportunity to revise our manuscript. We\nappreciate the thoroughness of your review, which has helped us improve the quality of our\npaper. We agree that the original Western blot image for COL11A1 in Figure S6C lacked the\nnecessary clarity, with the presence of non-specific bands and difficulty in distinguishing the\nbands in the control group. To address this concern, we have repeated the Western blot\nexperiment for COL11A1 knockdown. The new experiment was performed with optimized\nconditions to reduce background and non-specific binding, resulting in a much clearer image\nwith distinct, specific bands. This new result more effectively demonstrates the successful\nknockdown of COL11A1 following siRNA transfection. The improved, clearer Western blot\nimage has now replaced the previous one in the revised Figure S9E of the supplementary\nmaterials. We believe this revision fully addresses the reviewer's concern and provides clear\nevidence for our findings. Thank you again for your valuable feedback.\nFigure S9E\nResponse to Reviewers\nDear Editors and Reviewers,\nThank you for your letter and for the reviewers’ comments concerning our manuscript entitled\n“Lactate derived from macrophages drives skin dermal fibroblasts phenotypic remodeling via\nMCT1-primed histone H3 lysine 23 lactylation in hypertrophic scar” (Manuscript Number:\nNCOMMS-25-39200). Those comments are all valuable and very helpful for revising and\nimproving our manuscript, as well as the important guiding significance to our researches. We\nhave studied comments carefully and have made corrections which we hope meet with\napproval. Revised portions are marked in yellow in the revised manuscript. The main\ncorrections in the paper and the responses to the reviewer’s comments are as following:\nResponses to the reviewer’s comments:\nReviewer #3 (Remarks to the Author):\nIt’s appreciated that the authors have performed additional experiments in response to the\nprevious review. These efforts have improved the manuscript and clarified several aspects of\nthe study. Nonetheless, several important points remain outstanding, and further clarification\nand supporting evidence are needed to validate the study’s conclusions fully:\n# Regarding the novelty of the findings\nThe authors have provided a detailed explanation of their view on the novelty of the study and\nhave clarified how their findings integrate previously known concepts into a more specific\nmechanistic framework. While these additions and contextual revisions are appreciated, this\nreviewer remains unconvinced that the presented work constitutes a substantial conceptual\nadvance. The roles of MCT1-mediated lactate transport, macrophage-derived lactate\nsignaling, and histone lactylation in fibroblast activation have been previously established\nacross several fibrotic contexts, including keloid and dermal fibrosis. The current study\nextends these findings to hypertrophic scar and delineates their interconnection in this specific\nmodel, but this represents more of a contextual refinement than a discovery of a\nfundamentally new mechanism. While the addition of new molecular players (e.g., H3K23la,\nHEY2, and COL11A1) provides valuable mechanistic depth, the overarching concept of\nlactate-mediated metabolic–epigenetic crosstalk driving fibrosis remains consistent with prior\nreports. Thus, the study represents a meaningful refinement and contextualization of\nestablished mechanisms rather than the identification of a fundamentally new pathway.\nReply:\nWe sincerely thank the reviewer for this thoughtful and critical assessment. We fully\nunderstand your reservation regarding the conceptual novelty, given that lactate, MCT1,\nand histone lactylation have indeed been implicated in various fibrotic contexts, particularly in\nkeloids and organ fibrosis. However, we respectfully submit that our study goes beyond a\n\"contextual refinement.\" Based on the unique metabolic landscape of HS revealed in our\ndata—which fundamentally differs from the established \"Warburg effect\" model in keloids—\nwe believe our findings represent a distinct mechanometabolic mechanism. We wish to\nhighlight three specific aspects where our work provides a substantial conceptual advance:\n1. Redefining the Metabolic Landscape: HS is biologically distinct from Keloids\nThe reviewer correctly notes that lactate signaling is known in keloids. However,\nthe source and the cellular logic of this lactate are fundamentally different in our HS model,\nrepresenting a new paradigm for skin fibrosis. As we discuss in the revised text, previous\nliterature establishes that keloid fibroblasts (KFs) themselves undergo metabolic\nreprogramming (aerobic glycolysis), exhibiting cancer-like bioenergetics with intrinsic lactate\noverproduction (Wang et al., 2021). In keloids, the fibroblast is the producer and the\nconsumer (autocrine signaling). In sharp contrast, our targeted metabolomics and Seahorse\nassays (Figure 2) demonstrate that HS fibroblasts do not exhibit glycolytic\nelevation (consistent with Su et al., 2022). Instead, we identified that mechanically stressed\nmacrophages are the primary lactate source. This establishes a \"parasitic\" or \"coupled\"\nmetabolic circuit where fibroblasts rely on macrophage-derived lactate via MCT1. This\ndistinction is crucial because it implies that targeting fibroblast glycolysis (a strategy\nproposed for keloids) would fail in HS. Instead, blocking the transport (MCT1) or\nthe source (macrophage stiffness-response) is required. This redefines the metabolic etiology\nof HS as distinct from keloids.\n2. Identification of a Novel \"Non-Canonical\" Protein Interaction (COL11A1-MCT1\nLoop)\nWhile the general concept of \"lactate leading to gene expression\" is known, we discovered a\nfundamentally new molecular mechanism regarding how this signal is sustained. We found\nthat the lactylation-induced gene COL11A1 does not merely function as an extracellular\nmatrix structural protein. Our data (Figure 8 and molecular docking) reveals a non-canonical\nintracellular function: COL11A1 physically interacts with and stabilizes the MCT1\ntransporter on the plasma membrane. This creates a specific positive feedback\nloop (Macrophage Lactate→ Fibroblast MCT1→ H3K23la→ COL11A1→ Stabilized\nMCT1→ More Lactate influx). This self-reinforcing protein-protein interaction has not been\nreported in other fibrotic or cancer contexts and provides a structural explanation for the\nchronicity of the scar.\n3. Specificity of the Epigenetic Code (H3K23la vs. H3K18la)\nPrevious studies in keloids identified H3K18la as the driver of fibrosis (Li et al., 2023). In\ncontrast, our results identified H3K23la as the specific mark in HS myofibroblasts, while\nH3K18la levels remained unchanged (Figure 4B). This suggests that histone lactylation is not\na generic \"on-switch\" for fibrosis but follows a specific \"code\" depending on the disease\npathology (Keloid vs. HS). We mapped this specific H3K23la mark to the promoter of HEY2,\na transcription factor not previously linked to this metabolic axis, which subsequently\nactivates the YAP1/SMAD2 pathway. This delineates a precise, novel signaling axis (Lactate-\nH3K23la-HEY2-YAP1) rather than a generic application of lactylation.\nIn summary, while the components (lactate, MCT1) are known, the circuit topology we\ndescribe is novel and specific to HS: (1) Input: Macrophage mechano-transduction (not\nfibroblast glycolysis). (2) Mechanism: A specific epigenetic mark (H3K23la) and a novel\nprotein-stabilization loop (COL11A1-MCT1). (3) Outcome: A distinct therapeutic\nvulnerability (MCT1 inhibition in oxidative fibroblasts). We believe these findings provide\nthe \"mechanistic depth\" and \"differentiation from keloid pathophysiology\" necessary to\nconstitute a conceptual advance. We have taken your constructive feedback seriously and\nhave thoroughly revised the manuscript to improve its clarity, accuracy, and impact. We thank\nyou again for your valuable time and consideration.\nReference:\n(1) Wang, Q., Wang, P., Qin, Z., Yang, X., Pan, B., Nie, F., & Bi, H. (2021). Altered glucose\nmetabolism and cell function in keloid fibroblasts under hypoxia. Redox biology, 38, 101815.\n(2) Su, Z., Jiao, H., Fan, J., Liu, L., Tian, J., Gan, C., Yang, Z., Zhang, T., & Chen, Y. (2022).\nWarburg effect in keloids: A unique feature different from other types of scars. Burns :\njournal of the International Society for Burn Injuries, 48(1), 176–183.\nOriginal Comment 1:\nUsing in vitro model systems to dissect mechanistic details is acceptable when grounded in\ninitial observations derived from the native tissue context. However, in this study, the focus\non fibroblasts, macrophages, and endothelial cells appears selective rather than empirically\nestablished. A more systematic analysis that includes other key skin-resident cell types—such\nas adipocytes, mast cells, and additional immune populations—would have been essential to\naccurately identify the principal contributors to the observed interactions. Moreover, the use\nof cell lines for in vitro experiments represents a significant limitation, as these models often\ndiverge from primary cells and therefore cannot faithfully reproduce the complexity of tissue-\nlevel signaling and cell–cell communication. This methodological choice reduces the\nphysiological relevance of the mechanistic findings and may limit the generalizability of the\nconclusions to in vivo or clinical settings.\nReply:\nWe sincerely appreciate your insightful comments regarding the cellular complexity of the\nskin microenvironment and the methodological considerations of our in vitro models. We\nagree that a systematic analysis of other resident cell types is crucial to accurately identify the\nprincipal metabolic contributors. To address your concerns, we have performed additional\nexperiments and included a detailed discussion based on both our new data and existing\nliterature.\n1. Regarding the selectivity of cell types and the inclusion of other key skin-resident\ncells:\nWe acknowledge that the skin environment is multicellular and that other cell types, such as\nmast cells, T cells, and adipocytes, play roles in wound healing. To determine if these cells\ncontribute significantly to the lactate-rich microenvironment in HS, we conducted the\nfollowing additional analyses: (1) Mast cells and T cells: We performed double\nimmunofluorescence staining on human HS and NS tissues using markers for Mast cells\n(Tryptase) and T cells (CD3) alongside key glycolytic enzymes (HK2 and LDHA). As shown\nin the newly added Figure S4G-S4I, we observed no statistically significant difference in the\nexpression of HK2 or LDHA within Tryptase+ Mast cells or CD3+ T cells when comparing\nHS to NS tissues. While these immune cells are present in the scar tissue, our data suggests\nthey do not undergo the profound \"glycolytic switch\" (upregulation of lactate-generating\nenzymes) observed in macrophages (Figure 2G-J). This reinforces our finding that\nmacrophages are the predominant source of elevated lactate in the HS microenvironment. (2)\nAdipocytes: Regarding adipocytes, we carefully considered their potential role based on\ntissue architecture and literature: Histologically, HS is characterized by excessive collagen\ndeposition primarily in the reticular dermis, which significantly thickens and creates a spatial\nbarrier separating the active fibrotic core from the subcutaneous adipose tissue (Marc G\nJeschke et al., 2023). This physical distance suggests that paracrine metabolic signals (like\nlactate) from subcutaneous adipocytes are less likely to be the primary drivers of fibroblast\nphenotypes in the upper/mid-dermis compared to infiltrating macrophages which are in direct\nphysical contact with fibroblasts. Current literature suggests the primary contribution of\nadipocytes to scarring is not through lactate secretion, but rather through the Adipocyte-\nMyofibroblast Transition (AMT), where intradermal adipocytes lose their lipid content and\ntransdifferentiate into myofibroblasts (Brett A Shook et al., 2019). Therefore, in the context of\nour study—which focuses on the source of lactate driving epigenetic changes—adipocytes are\nless likely to be the \"producers\" and more likely to be a lineage responding to the fibrotic\nsignals.\n2. Regarding the use of cell lines vs. primary cells:\nWe appreciate your critique regarding the physiological relevance of cell lines. We wish to\nclarify that while cell lines were used for initial screening due to their stability in mechanical\nstiffness models, the core findings of our study were rigorously validated using primary cells\nand human tissues: (1) Primary lactate source validation: As shown in Figure 2G-J, we\nisolated primary macrophages, endothelial cells, and fibroblasts directly from fresh\npatient tissues (NS and HS) using magnetic-activated cell sorting (MACS). We measured\nintracellular/extracellular lactate levels and performed Seahorse metabolic flux analysis\n(ECAR and ATP production rate) on these primary cells, confirming that primary HS\nmacrophages exhibit the highest glycolytic capacity and lactate secretion, consistent with our\ncell line data. (2) Fibrosis mechanism validation: For the downstream mechanistic\nexperiments (histone lactylation, gene regulation), we primarily utilized primary Human\nSkin Fibroblasts (HSFs and NSFs) isolated from patient samples (Figures 1, 3, 4, 6, 7, 8)\nrather than cell lines. All key observations were further corroborated in human HS tissue\nsamples via Western Blot and IHC (Figures 1, 4, 5) and in our in vivo mouse models.\nWe believe these additional data and clarifications demonstrate that macrophages are indeed\nthe principal contributors to the lactate-rich microenvironment and that our findings are\ngrounded in physiologically relevant primary cell and tissue contexts and we have revised the\nResult sections of our manuscript. We are grateful for your constructive criticism, which has\nsignificantly improved the quality and clarity of our manuscript. Thank you again for helping\nus strengthen the rigor of our study.\nRevised figures:\nFigure S4G\nFigure S4H\nFigure S4I\nFigure S4J\nRevised manuscript:\n“To further rule out the contribution of other immune cell populations to the lactate-rich\nmicroenvironment, we also performed immunofluorescence co-staining of key glycolytic\nenzymes (HK2 or LDHA) with markers for mast cells (Tryptase) and T cells (CD3) in human\nNS and HS tissues. Quantitative analysis revealed no statistically significant differences in the\nnumber of glycolytic-enzyme-positive mast cells or T cells (Figure S4G-S4J).”\n“Although the skin comprises a heterogeneous population of cells, our systematic analysis\nidentifies macrophages as the principal source of lactate.”\n“While adipocytes are key components of the skin stroma, their contribution to the lactate\npool in HS was considered less prominent due to spatial constraints; the significantly\nthickened reticular dermis in HS creates a physical barrier that separates the fibrotic core from\nthe subcutaneous adipose layer, limiting the potential for adipocyte-derived paracrine\nmetabolic signaling to reach dermal fibroblasts. Additionally, our supplementary data\nconfirmed that vascular endothelial cells and other resident immune cells, such as mast cells\nand T cells, do not exhibit the robust glycolytic upregulation observed in macrophages.”\nReferences:\n(1) Jeschke, M. G., Wood, F. M., Middelkoop, E., Bayat, A., Teot, L., Ogawa, R., & Gauglitz,\nG. G. (2023). Scars. Nature reviews. Disease primers, 9(1), 64.\n(2) Shook, B. A., Wasko, R. R., Rivera-Gonzalez, G. C., Salazar-Gatzimas, E., López-\nGiráldez, F., Dash, B. C., Muñoz-Rojas, A. R., Aultman, K. D., Zwick, R. K., Lei, V., Arbiser,\nJ. L., Miller-Jensen, K., Clark, D. A., Hsia, H. C., & Horsley, V. (2018). Myofibroblast\nproliferation and heterogeneity are supported by macrophages during skin repair. Science\n(New York, N.Y.), 362(6417), eaar2971.\nOriginal Comment 2:\nWhile this reviewer acknowledges the authors’ effort in performing a non-targeted\nmetabolomic analysis, the rationale for selecting lactate as the central metabolite of interest\nstill remains insufficiently justified. Specifically, it is unclear whether lactate was directly\ndetected and quantified in the presented metabolomic dataset, and if so, whether it represents\nthe most significantly upregulated metabolite in hypertrophic scar (HS) compared with\nnormal skin. If lactate is not the top metabolite showing increased abundance, the authors\nshould clarify why it was prioritized over other metabolites with potentially stronger\ndifferential expression. Furthermore, identifying the metabolite(s) with the highest\nupregulation and discussing their potential relevance would provide critical context, ensuring\nthat the mechanistic focus on lactate is data-driven rather than selectively interpretive.\nReply:\nWe sincerely appreciate the reviewer’s insightful comment. We agree that relying solely on\nthe previous non-targeted metabolomics data was insufficient to fully justify selecting lactate\nas the primary candidate, especially without a rigorous comparison to other highly\nupregulated metabolites.\nTo address this concern and provide a solid data-driven rationale, we have performed a\nnew Targeted Energy Metabolomics analysis on HS and NS tissues. Furthermore, we have\nthoroughly analyzed the \"top\" metabolites identified in both non-targeted and targeted\ndatasets to exclude confounding factors (such as exogenous drug metabolites) and to pinpoint\nthe bioactive molecules most relevant to the fibrotic pathology.\nOur specific responses and revisions are detailed below:\n1. Verification of Lactate Elevation via Targeted Metabolomics\nIn our original non-targeted analysis, lactate was detected but was not the single most\nstatistically significant peak due to the inherent ionization competition and dynamic range\nlimitations of non-targeted LC-MS/MS for small polar molecules. To overcome this, we\nconducted Targeted Energy Metabolomics (using standard curves for absolute\nquantification). The results confirmed that lactate is indeed one of the most significantly\nupregulated metabolites in HS. As shown in the new Figure S1D (Volcano plot) and Figure\nS1E, lactate ranks as the 3rd highest metabolite in terms of log2FC among all energy-related\nmetabolites. Figure S1F demonstrates a robust quantitative increase in Lactate, ATP, and\nPyruvate. Figure S1G (KEGG enrichment) confirms that \"Pyruvate metabolism,\" \"Carbon\nmetabolism,\" and \"Glycolysis\" are the enriched pathways, supporting lactate's central role.\n2. Rationale for Prioritizing Lactate over the \"Top\" Upregulated Metabolites\nFollowing the reviewer’s suggestion, we scrutinized the metabolites with higher upregulation\nthan lactate to ensure our focus was not selectively interpretive. (1) Analysis of the top\nmetabolite in non-targeted data: The metabolite with the highest fold change in our non-\ntargeted dataset was N-Desmethylaminopyrine. Upon rigorous literature review, we identified\nthis as a major metabolite of Aminophenazone/Metamizole, an analgesic and anti-\ninflammatory drug (L Cardon et al., 1958). Since HS patients frequently undergo surgical\nexcision or receive pain management, the presence of this compound is an exogenous\npharmacological artifact rather than an endogenous driver of fibrosis. Therefore, we excluded\nit from mechanistic investigation. (2) Analysis of top metabolites in targeted data (GTP and\nDL-Glycerate): In our targeted panel, two metabolites showed a slightly higher log2FC than\nlactate: Guanosine Triphosphate (GTP) and DL-Glycerate. GTP is essential for protein\nsynthesis and gluconeogenesis. While elevated GTP supports the high proliferative state of\nfibroblasts, it is a general indicator of high anabolic activity rather than a specific signaling\nmolecule that triggers the epigenetic shift we observed. Glycerate is an intermediate in serine\nmetabolism and glycolysis. Its accumulation supports the metabolic shift (Warburg effect) but\nlacks the documented capacity to directly modify histones (Lactylation) or act as an\nintercellular signaling transmitter (via MCT1) to the same extent as lactate (Sheng Hui et al.,\n2017). (3) Why Lactate (Rank 3) is the Key: Lactate is not merely a fuel source or\nbyproduct; it is a bioactive signaling molecule. Our study focuses on histone lactylation\n(H3K23la). Lactate is the obligate substrate for this modification (Di Zhang et al., 2019).\nFurthermore, the concurrent upregulation of MCT1 (lactate transporter) suggests an active\ntransport mechanism specifically for lactate, which is not shared by GTP or Glycerate.\nTherefore, biologically and mechanistically, lactate is the most relevant driver of\nthe phenotypic remodeling observed.\n3. Clarification on Discrepancies between Non-Targeted and Targeted Results\nThe reviewer may note differences between the two datasets. Non-targeted metabolomics\nprovides a broad \"snapshot\" but suffers from ion suppression and lower sensitivity for small\npolar acids like lactate. Targeted metabolomics uses optimized extraction methods and\ninternal standards, providing superior sensitivity and accuracy for energy metabolites (Anton\nRibbenstedt et al., 2018). This explains why lactate's significance is more pronounced and\nreliable in our new targeted dataset.\nWe have revised the manuscript to reflect these findings: We have inserted the Targeted\nMetabolomics data (New Figure S1D-G) and explicitly mentioned the exclusion of N-\nDesmethylaminopyrine as a drug artifact. Moreover, we added a section justifying the\nselection of lactate over GTP/Glycerate, emphasizing lactate’s unique role in epigenetic\nregulation (lactylation) and cell-to-cell transport (MCT1). We believe these additional\nexperiments and analyses provide the robust justification the reviewer requested. We are\ngrateful for your constructive criticism, which has significantly improved the quality and\nclarity of our manuscript. Thank you again for helping us strengthen the rigor of our study.\nRevised figures:\nFigure S1D-G\nRevised manuscript:\n“KEGG analysis of the different metabolites revealed enrichment in the central carbon\nmetabolism (Figure S1C). To further validate the metabolic profile and overcome the\nlimitations of non-targeted metabolomics in quantifying small polar acids, we performed\ntargeted energy metabolomics which revealed a distinct metabolic signature in HS tissues\n(Figure S1D). Lactate ranked as the third most upregulated metabolite (log2FC) following\nGuanosine Triphosphate (GTP) and DL-Glycerate (Figure S1E). Consistent with a shift\ntoward aerobic glycolysis, quantitative analysis confirmed significantly elevated levels of\nLactate, Pyruvic acid, and ATP in HS tissues (Figure S1F). KEGG pathway analysis of these\nmetabolites highlighted enrichment in Pyruvate metabolism, Carbon metabolism, and\nGlycolysis (Figure S1G).”\n“Our combined metabolomic approach clarifies the metabolic landscape of HS. While non-\ntargeted analysis provided a broad overview, targeted energy metabolomics allowed for the\nprecise quantification of glycolytic intermediates. A critical evaluation of the most\nupregulated metabolites was necessary to identify the pathogenic driver. We excluded N-\nDesmethylaminopyrine as a pharmacological artifact. Among endogenous metabolites, while\nGTP and DL-Glycerate were highly upregulated—reflecting the increased biosynthetic\ndemand of proliferating fibroblasts—we prioritized lactate for mechanistic investigation.”\nReferences:\n(1) CARDON, L., COMESS, O. H., NOBLE, T. A., & POMARANC, M. M. (1958). Value of\naminopyrine. Annals of internal medicine, 48(3), 616–634.\n(2) Hui, S., Ghergurovich, J. M., Morscher, R. J., Jang, C., Teng, X., Lu, W., Esparza, L. A.,\nReya, T., Le Zhan, Yanxiang Guo, J., White, E., & Rabinowitz, J. D. (2017). Glucose feeds\nthe TCA cycle via circulating lactate. Nature, 551(7678), 115–118.\n(3) Zhang, D., Tang, Z., Huang, H., Zhou, G., Cui, C., Weng, Y., Liu, W., Kim, S., Lee, S.,\nPerez-Neut, M., Ding, J., Czyz, D., Hu, R., Ye, Z., He, M., Zheng, Y. G., Shuman, H. A., Dai,\nL., Ren, B., Roeder, R. G., … Zhao, Y. (2019). Metabolic regulation of gene expression by\nhistone lactylation. Nature, 574(7779), 575–580.\n(4) Ribbenstedt, A., Ziarrusta, H., & Benskin, J. P. (2018). Development, characterization and\ncomparisons of targeted and non-targeted metabolomics methods. PloS one, 13(11),\ne0207082.\nOriginal Comment 3:\nThe addition of transcript-level measurements for selected TCA cycle enzymes is appreciated;\nhowever, this approach alone does not constitute definitive evidence of a metabolic shift from\noxidative phosphorylation (OXPHOS) to glycolysis in hypertrophic scar (HS) tissue. Given\nthat the authors have already provided Western blot data for glycolysis-related proteins,\nequivalent protein-level validation for the selected OXPHOS-associated genes would be\nnecessary for methodological consistency and to strengthen this comparison.\nFurthermore, the added metabolomic analysis requires deeper exploration. The authors should\nprovide a more comprehensive overview of the metabolites involved in OXPHOS and\nglycolysis, demonstrating whether OXPHOS intermediates are indeed reduced in HS and\nwhether glycolytic intermediates are correspondingly elevated. Highlighting only a single\nmetabolite (citric acid) from the TCA cycle does not sufficiently support the claim of an\nenergy pathway shift, particularly since other relevant pathways, e.g., fatty acid oxidation,\nhave not been considered.\nFinally, expanding the Seahorse data presented in Figure 2 to include an OCR/ECAR ratio\nwould provide a functional readout of the relative balance between oxidative and glycolytic\nmetabolism, thereby offering further support for the proposed shift toward glycolysis.\nReply:\nWe would like to express our sincere gratitude for your insightful and constructive comments.\nWe agree that protein-level validation and a more comprehensive functional analysis of the\nmetabolic shift are essential to strengthen the conclusions of our study. In response to your\nsuggestions, we have performed additional Western blot assays, conducted a deeper analysis\nof our metabolomic data (including targeted metabolomics), and re-analyzed our Seahorse\ndata to calculate ATP production rates. Our point-by-point responses are detailed below:\n1. Protein-level validation of OXPHOS-associated genes.\nWe fully agree with the reviewer that Western blot validation is necessary to confirm the\ndownregulation of OXPHOS at the protein level. In the revised manuscript, we have\nexamined the protein expression of key OXPHOS-associated enzymes, specifically PDHA1,\nCS, IDH1, and IDH2 in NS and HS tissues. As shown in Figure S1H of the revised\nmanuscript, the results demonstrate a distinct downregulation of these OXPHOS-related\nproteins in HS tissues compared to NS. Specifically, quantification revealed statistically\nsignificant decreases in IDH1 and IDH2 levels. This protein-level data corroborates our RT-\nqPCR findings and provides robust evidence that the TCA cycle and oxidative\nphosphorylation capacity are suppressed in HS tissue, supporting the conclusion of a\nmetabolic switch from OXPHOS to glycolysis. We have updated the Results section to\nincorporate these findings.\n2. Deeper exploration of metabolomic analysis and the specific metabolic profile.\nWe fully appreciate this suggestion. We have expanded our analysis to provide a\ncomprehensive overview of the metabolic landscape in HS. As shown in Figure S1C, KEGG\nenrichment analysis of our non-targeted metabolomics revealed that, in addition to central\ncarbon metabolism, pathways such as Amino acid biosynthesis, mTOR signaling, PI3K-Akt\nsignaling, and Linoleic acid metabolism were significantly enriched. This suggests that the\nmetabolic reprogramming in HS is a complex network supporting rapid cell proliferation and\nmatrix synthesis, driven by both glycolytic flux and anabolic signaling.\nTo overcome the limitations of non-targeted metabolomics in quantifying small polar acids,\nwe utilized targeted energy metabolomics. As presented in Figure S1F, we observed\nsignificantly elevated levels of Lactate, Pyruvate, and ATP in HS tissues. The simultaneous\naccumulation of pyruvate and lactate, coupled with the downregulation of TCA enzymes\n(IDH1/2), strongly supports a \"Warburg-like\" shift where pyruvate is shunted toward lactate\nproduction rather than entering the TCA cycle efficiently. We also noted an elevation\nin Malate in the HS group (Figure S1E). While a reduction in TCA activity typically lowers\nTCA intermediates (like the observed decrease in Citric acid), the elevation of Malic acid is\nconsistent with metabolic reprogramming seen in fibroproliferative disorders and cancer.\nLiterature indicates that Malate accumulation often results from: (1) The malate-aspartate\nshuttle: To sustain high glycolytic rates, cells must regenerate cytosolic NAD+. Malate is a\nkey component of the shuttle system that transports reducing equivalents into the\nmitochondria, indirectly supporting high cytosolic glycolysis (Jason W Locasale et al., 2011).\n(2) Anaplerosis (Glutaminolysis): Proliferating cells often utilize glutamine anaplerosis to\nreplenish the TCA cycle. Glutamine-derived carbon can generate Malate, which is then\nconverted to Pyruvate by Malic Enzyme to generate NADPH, which is crucial for lipid and\nnucleotide synthesis required for HS formation (Ralph J DeBerardinis et al., 2008). Therefore,\nthe increase in Malate does not contradict the suppression of OXPHOS but rather reflects the\nhigh biosynthetic and redox demands of the hypertrophic scar microenvironment.\nWe have revised the Results section to include this deeper interpretation of the metabolomic\nprofile.\n3. Functional readout of the metabolic shift (OCR/ECAR vs. ATP Production Rate).\nThank you for this excellent suggestion. To provide a more functional and intuitive readout of\nthe balance between oxidative and glycolytic metabolism, we analyzed the ATP Production\nRate derived from our Seahorse data. This metric specifically distinguishes between ATP\nproduced via Glycolysis (glycoATP) and ATP produced via Oxidative Phosphorylation\n(mitoATP), offering a clearer picture than the raw OCR/ECAR ratio. As shown in the\nnew Figure S3A and S3B, macrophages cultured on stiff substrates (50 kPa) or treated with\nTGF-β exhibited a significant shift in their bioenergetic profile. The contribution\nof glycolytic ATP production was markedly increased compared to oxidative ATP production\nin these stimulated macrophages. This confirms that mechanical and inflammatory stimuli\ndrive macrophages toward a glycolytic phenotype. Crucially, as shown in Figure S3C and\nS3D, neither endothelial cells nor fibroblasts exhibited a comparable increase in the glycolytic\nATP ratio under high stiffness conditions. Most importantly, corroborating our cell line data,\nprimary macrophages from HS tissue demonstrated a significantly higher rate of ATP\nproduction from glycolysis compared to OXPHOS (Figure S4D). This validates our\nhypothesis that macrophages are the primary source of the elevated lactate in the HS\nmicroenvironment, while fibroblasts are the downstream effectors that utilize this lactate.\nWe have integrated these ATP production rate analyses into the Results section and updated the\nrelevant figure legends.\nWe believe these additional experiments and analyses fully address your concerns and\nsignificantly strengthen the manuscript. Thank you again for your time and guidance.\nRevised figures:\nFigure S1H\nFigure S1C\nFigure S1G\nFigure S3\nFigure S4D\nRevised manuscript:\n“KEGG analysis of the different metabolites revealed enrichment in the central carbon\nmetabolism, as well as pathways critical for biosynthesis and proliferation, including amino\nacid biosynthesis, mTOR signaling, PI3K-Akt signaling, and linoleic acid metabolism (Figure\nS1C).”\n“Moreover, we profiled the expression of these genes in NS and HS using western blotting\nand the result showed that the protein level of MCT1, MCT4 and PKM2, which were\nmarkedly increased in HS, yet IDH1 and IDH2 were significantly decreased (Figure 1C and\nS1H).”\n“To definitively assess the metabolic switch, we calculated the ATP production rates.\nMacrophages cultured on 50kPa stiff substrates or under TGF-β stimulation exhibited a\nsignificant shift where ATP production from glycolysis (glycoATP) markedly exceeded that\nfrom oxidative phosphorylation (mitoATP) (Figure S3A and S3B). However, endothelial and\nfibroblast cultures showed marginal ECAR increases and no significant shift in the\nglycoATP/mitoATP ratio under stiff conditions (Figure 2E, 2F, S3C and S3D).”\n“In addition, enhanced ECAR level and glycoATP/mitoATP ratio was observed in primary\nmacrophages from HS tissues compared to control (Figure 2H).”\nReferences:\n(1) Locasale, J. W., Grassian, A. R., Melman, T., Lyssiotis, C. A., Mattaini, K. R., Bass, A. J.,\nHeffron, G., Metallo, C. M., Muranen, T., Sharfi, H., Sasaki, A. T., Anastasiou, D., Mullarky,\nE., Vokes, N. I., Sasaki, M., Beroukhim, R., Stephanopoulos, G., Ligon, A. H., Meyerson,\nM., Richardson, A. L., … Vander Heiden, M. G. (2011). Phosphoglycerate dehydrogenase diverts\nglycolytic flux and contributes to oncogenesis. Nature genetics, 43(9), 869–874.\n(2) DeBerardinis, R. J., Lum, J. J., Hatzivassiliou, G., & Thompson, C. B. (2008). The\nbiology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell\nmetabolism, 7(1), 11–20.\nOriginal Comment 7:\nWhile this reviewer acknowledges the substantial effort undertaken to isolate primary cells\nfrom patient skin samples and assess their contribution to lactate production, the rationale for\nexcluding other skin-resident cell types remains unclear. Additional cell populations—such as\nadipocytes, mast cells, and other immune subsets—could plausibly contribute to the altered\nmetabolic landscape of hypertrophic scar. The authors should either extend their analysis to\ninclude these dominant skin cell types or provide a clear and experimentally grounded\njustification for their exclusion. Addressing this point would ensure that the presented\nconclusions regarding the cellular origin of lactate are comprehensive and not selectively\nderived.\nReply:\nWe sincerely thank the reviewer for this critical and constructive feedback. We fully agree\nthat the skin microenvironment is complex and that attributing the metabolic alteration solely\nto macrophages requires a rigorous exclusion of other potential cellular contributors. To\naddress your concern regarding the \"selectivity\" of our analysis and to ensure a\ncomprehensive understanding of the lactate source, we have performed additional\nexperimental validations and provided a detailed, grounded justification regarding specific\ncell populations:\nPrompted by your suggestion, we expanded our histological analysis to include Mast cells and\nT cells, which are significant immune components of the skin. We performed dual\nimmunofluorescence staining on human NS and HS tissues to detect the co-localization of\ncell-specific markers—Tryptase (for Mast cells) and CD3 (for T cells)—with the key lactate-\ngenerating enzymes HK2 and LDHA. As presented in the newly added Figure S4G-S4J, our\nquantitative analysis revealed that: Unlike the significant upregulation observed in CD68+\nmacrophages, there was no statistically significant difference in the expression levels of HK2\nor LDHA within Tryptase+ Mast cells or CD3+ T cells when comparing HS tissues to NS\ntissues. This experimental evidence suggests that while these cells are present in the scar\ntissue, they do not undergo the profound \"glycolytic switch\" characteristic of the\nmacrophages in this specific pathological context. Thus, their contribution to the elevated\nlactate pool appears negligible compared to macrophages.\nRegarding adipocytes, we carefully evaluated their potential role based on the specific tissue\narchitecture of hypertrophic scar and established literature. We excluded them as a primary\nsource of lactate for fibroblasts in this study based on two key factors: (1) Spatial\nseparation: Histologically, hypertrophic scar is defined by the excessive deposition of\nextracellular matrix in the reticular dermis, which becomes significantly thickened (Marc G\nJeschke et al., 2023). This creates a substantial physical barrier and distance between the\nactive fibrotic core (where fibroblasts are located) and the subcutaneous adipose tissue. Given\nthis spatial segregation, it is unlikely that labile metabolites like lactate secreted by\nsubcutaneous adipocytes would act as the primary paracrine driver for fibroblasts located in\nthe upper and mid-dermis, especially compared to macrophages which are known to\nphysically infiltrate the fibroblast-dense regions. (2) Mechanistic distinction: Current\nliterature indicates that the primary contribution of dermal adipocytes to wound healing and\nscarring is not metabolic secretion, but rather lineage plasticity. Studies have shown that\nadipocytes promote scarring primarily through the adipocyte-myofibroblast transition, where\nthey transdifferentiate into myofibroblasts (Brett A Shook et al., 2019). Therefore, in the\ncontext of our study—which focuses on the source of the lactate signal rather than the source\nof the myofibroblast lineage itself—adipocytes are less likely to be the \"producers\" of the\nlactate gradient.\nBy combining our original data on macrophages/endothelial cells/fibroblasts with these new\nfindings on Mast cells/T cells and the spatial logic regarding adipocytes, we believe we have\nnow provided a comprehensive identification of the cellular origin of lactate. Our data\nstrongly supports the conclusion that macrophages are the dominant driver of the lactate-rich\nmetabolic microenvironment in hypertrophic scar. We have updated the Results section and\nthe Discussion section of the revised manuscript to reflect these new data and justifications.\nWe believe these additional experiments significantly strengthen the mechanistic depth of our\nstudy. Thank you again for your time and guidance.\nRevised figures:\nFigure S4G\nFigure S4H\nFigure S4I\nFigure S4J\nRevised manuscript:\n“To further rule out the contribution of other immune cell populations to the lactate-rich\nmicroenvironment, we also performed immunofluorescence co-staining of key glycolytic\nenzymes (HK2 or LDHA) with markers for mast cells (Tryptase) and T cells (CD3) in human\nNS and HS tissues. Quantitative analysis revealed no statistically significant differences in the\nnumber of glycolytic-enzyme-positive mast cells or T cells (Figure S4G-S4J).”\n“Although the skin comprises a heterogeneous population of cells, our systematic analysis\nidentifies macrophages as the principal source of lactate.”\n“While adipocytes are key components of the skin stroma, their contribution to the lactate\npool in HS was considered less prominent due to spatial constraints; the significantly\nthickened reticular dermis in HS creates a physical barrier that separates the fibrotic core from\nthe subcutaneous adipose layer, limiting the potential for adipocyte-derived paracrine\nmetabolic signaling to reach dermal fibroblasts. Additionally, our supplementary data\nconfirmed that vascular endothelial cells and other resident immune cells, such as mast cells\nand T cells, do not exhibit the robust glycolytic upregulation observed in macrophages.”\nReferences:\n(1) Jeschke, M. G., Wood, F. M., Middelkoop, E., Bayat, A., Teot, L., Ogawa, R., & Gauglitz,\nG. G. (2023). Scars. Nature reviews. Disease primers, 9(1), 64.\n(2) Shook, B. A., Wasko, R. R., Rivera-Gonzalez, G. C., Salazar-Gatzimas, E., López-\nGiráldez, F., Dash, B. C., Muñoz-Rojas, A. R., Aultman, K. D., Zwick, R. K., Lei, V., Arbiser,\nJ. L., Miller-Jensen, K., Clark, D. A., Hsia, H. C., & Horsley, V. (2018). Myofibroblast\nproliferation and heterogeneity are supported by macrophages during skin repair. Science\n(New York, N.Y.), 362(6417), eaar2971.\nOriginal Comment 8:\nWithout experimental verification, the molecular modeling remains speculative. The authors\nshould indicate whether the model’s predictions can be experimentally tested. Validation\nthrough targeted mutagenesis or binding assays would significantly enhance the credibility of\nthese computational results.\nReply:\nWe sincerely thank the reviewer for this insightful and critical comment. We agree that while\nmolecular docking provides a structural hypothesis, experimental validation is essential to\nconfirm the specific interaction interface between COL11A1 and MCT1. To address this\nconcern and move beyond speculation, we have performed additional experiments\nincluding reverse Co-Immunoprecipitation and site-directed mutagenesis assays to\nphysically validate the predictions made by our model.\nIn our original manuscript, we demonstrated the interaction primarily by immunoprecipitating\nCOL11A1. To further confirm the specificity and robustness of this complex, we performed a\nreverse Co-IP using an anti-MCT1 antibody. The results unequivocally showed that MCT1\npulls down COL11A1 in HSFs, confirming a stable physical interaction between these two\nproteins in the cellular context.\nBased on the molecular docking results presented in Figure 8E of our original manuscript, we\nidentified specific amino acid residues at the binding interface. To test whether these sites are\nindeed responsible for the interaction, we constructed expression vectors with specific point\nmutations at these predicted sites. We generated Flag-tagged COL11A1 mutants (FLAG-\nCOL11A1-MUT) and His-tagged MCT1 mutants (His-MCT1-MUT). We then performed Co-\nIP assays in cells co-transfected with these vectors. The results demonstrated that the\ninteraction was strong between COL11A1-WTand MCT1-WT. Crucially, the interaction\nwas significantly impeded when mutations were introduced into the predicted binding\ninterface of either COL11A1 or MCT1. The disruption was most pronounced when both\nbinding sites were mutated.\nThese experimental findings provide direct biological evidence supporting our computational\nmodel. They confirm that COL11A1 interacts with MCT1 through the specific domains\nidentified in our docking simulation, thereby validating the proposed mechanism by which\nCOL11A1 may stabilize MCT1 and facilitate lactate transport. We have integrated these new\ndata into Figure 8 of the revised manuscript and updated the Results section to reflect this\nexperimental verification. We believe these additional experiments significantly strengthen\nthe mechanistic depth of our study. Thank you again for your time and guidance.\nRevised figures:\nFigure 8C\nFigure 8G\nRevised manuscript:\n“To confirm this interaction, co-immunoprecipitation (Co-IP) experiments revealed a\nsignificant interaction between COL11A1 and MCT1 (Figure 8B and 8C).”\n“We then mutated the predicted binding sites between COL11A1 and MCT1 (Figure 8G). Co-\nIP assays suggested that the interaction between COL11A1 and MCT1 was effectively\nimpeded by mutations in the TRIM34-binding site (FLAG-COL11A1-MUT) or UPF1-\nbinding site (His-MCT1-MUT), whether introduced individually or in conjunction (Figure\n8G).”\nResponse to Reviewers\nDear Editors and Reviewers,\nThank you for your letter and for the reviewers’ comments concerning our manuscript entitled\n“Lactate derived from macrophages drives skin dermal fibroblasts phenotypic remodeling via\nMCT1-primed histone H3 lysine 23 lactylation in hypertrophic scar” (Manuscript Number:\nNCOMMS-25-39200). This comment is valuable and very helpful for revising and\nimproving our manuscript, as well as the important guiding significance to our researches. The\nresponses\nto the reviewer’s comments are as following:\nResponses to the reviewer’s comment:\nReviewer #3 (Remarks to the Author):\nThe manuscript has been substantially improved. Although this reviewer still has some\nreservations regarding the rationale and justification for selecting lactate as the key\nmetabolite, the overall quality of the work warrants publication in Nature Communications.\nReply:\nWe are deeply grateful for your positive assessment of our work and your recommendation\nfor its publication in Nature Communications. We strictly value your reservation regarding the\nrationale for selecting lactate as the key metabolite, as this is indeed the foundational premise\nof our study. We would like to take this opportunity to further clarify our screening logic and\njustification, which combines metabolomic screening with mechanistic specificity:\nAs presented in our \"Targeted energy metabolomic\" analysis (Figure S1E and Lines 153-158\nof the manuscript), lactate was identified as the third most upregulated metabolite (based on\nlog2FC) in hypertrophic scar (HS) tissues. The top candidate, N-Desmethylaminopyrine, was\nexcluded as it is a pharmacological artifact (Line 566). The other top candidates, GTP\n(Guanosine Triphosphate) and DL-Glycerate, were indeed highly upregulated. However, as\ndiscussed in our manuscript (Lines 567-568), these metabolites largely reflect the heightened\n\"biosynthetic demand\" and general proliferative state of fibroblasts, which are common\nfeatures in many proliferative disorders. We prioritized lactate over GTP and DL-Glycerate\nbecause our core objective was to identify a metabolite that functions not just as a fuel, but as\na signaling molecule capable of driving the specific \"phenotypic remodeling\" in HS.\nEpigenetic Link: Unlike GTP or Glycerate, lactate serves as the specific substrate for histone\nlactylation (specifically H3K23la, as shown in Figure 4). This aligns with the \"Warburg\neffect\" observed in HS (Lines 589-593), offering a direct mechanistic link between metabolic\nreprogramming and epigenetic gene regulation (the MCT1-H3K23la-HEY2/COL11A1 axis).\nOur transcriptomic and protein analysis (Figure 1B-C) revealed a significant upregulation of\nMCT1 (a specific lactate transporter) in HS myofibroblasts, further pinpointing lactate\ntransport as a critical regulatory node in this pathology. Our functional assays confirmed that\nexogenous lactate (10 mM) was sufficient to induce the expression of key fibrotic markers\n(COL1A1, α-SMA) in a dose-dependent manner (Figure S2A-B), verifying its role as a\n\"pathogenic driver\" rather than a passive bystander.\nIn summary, while other metabolites were upregulated, lactate was selected because it\nuniquely bridges the gap between the metabolic microenvironment (macrophage-derived\nglycolysis) and the epigenetic reprogramming of fibroblasts (histone lactylation), which\nconstitutes the novel mechanism we aimed to elucidate. We hope this explanation effectively\naddresses your reservation and reinforces the rationale behind our experimental design."}, {"round": 2, "reviewer_comments": {"reviewer_3": "The manuscript has been substantially improved. Although this reviewer still has some reservations regarding the rationale and justification for selecting lactate as the key metabolite, the overall quality of the work warrants publication in Nature Communications."}, "author_response": "Response to Reviewers\nDear Editors and Reviewers,\nThank you for your letter and for the reviewers’ comments concerning our manuscript entitled\n“Lactate derived from macrophages drives skin dermal fibroblasts phenotypic remodeling via\nMCT1-primed histone H3 lysine 23 lactylation in hypertrophic scar” (Manuscript Number:\nNCOMMS-25-39200). This comment is valuable and very helpful for revising and\nimproving our manuscript, as well as the important guiding significance to our researches. The\nresponses\nto the reviewer’s comments are as following:\nResponses to the reviewer’s comment:\nReviewer #3 (Remarks to the Author):\nThe manuscript has been substantially improved. Although this reviewer still has some\nreservations regarding the rationale and justification for selecting lactate as the key\nmetabolite, the overall quality of the work warrants publication in Nature Communications.\nReply:\nWe are deeply grateful for your positive assessment of our work and your recommendation\nfor its publication in Nature Communications. We strictly value your reservation regarding the\nrationale for selecting lactate as the key metabolite, as this is indeed the foundational premise\nof our study. We would like to take this opportunity to further clarify our screening logic and\njustification, which combines metabolomic screening with mechanistic specificity:\nAs presented in our \"Targeted energy metabolomic\" analysis (Figure S1E and Lines 153-158\nof the manuscript), lactate was identified as the third most upregulated metabolite (based on\nlog2FC) in hypertrophic scar (HS) tissues. The top candidate, N-Desmethylaminopyrine, was\nexcluded as it is a pharmacological artifact (Line 566). The other top candidates, GTP\n(Guanosine Triphosphate) and DL-Glycerate, were indeed highly upregulated. However, as\ndiscussed in our manuscript (Lines 567-568), these metabolites largely reflect the heightened\n\"biosynthetic demand\" and general proliferative state of fibroblasts, which are common\nfeatures in many proliferative disorders. We prioritized lactate over GTP and DL-Glycerate\nbecause our core objective was to identify a metabolite that functions not just as a fuel, but as\na signaling molecule capable of driving the specific \"phenotypic remodeling\" in HS.\nEpigenetic Link: Unlike GTP or Glycerate, lactate serves as the specific substrate for histone\nlactylation (specifically H3K23la, as shown in Figure 4). This aligns with the \"Warburg\neffect\" observed in HS (Lines 589-593), offering a direct mechanistic link between metabolic\nreprogramming and epigenetic gene regulation (the MCT1-H3K23la-HEY2/COL11A1 axis).\nOur transcriptomic and protein analysis (Figure 1B-C) revealed a significant upregulation of\nMCT1 (a specific lactate transporter) in HS myofibroblasts, further pinpointing lactate\ntransport as a critical regulatory node in this pathology. Our functional assays confirmed that\nexogenous lactate (10 mM) was sufficient to induce the expression of key fibrotic markers\n(COL1A1, α-SMA) in a dose-dependent manner (Figure S2A-B), verifying its role as a\n\"pathogenic driver\" rather than a passive bystander.\nIn summary, while other metabolites were upregulated, lactate was selected because it\nuniquely bridges the gap between the metabolic microenvironment (macrophage-derived\nglycolysis) and the epigenetic reprogramming of fibroblasts (histone lactylation), which\nconstitutes the novel mechanism we aimed to elucidate. We hope this explanation effectively\naddresses your reservation and reinforces the rationale behind our experimental design."}]

Decision letter