NEK8 kinase-mediated lactate increase impairs antitumor immunity decreasing radiotherapy sensitivity in colorectal cancer

Domain: biology
Published: 2026-03-28
Editorial outcome: major_revision

Abstract
Radiotherapy effectively treats colorectal cancer (CRC), but local recurrence remains common and abscopal effects—regression of tumors distant from irradiated sites—are rarely observed even with immune checkpoint inhibitors. Here we show that the protein kinase NEK8, highly expressed in CRC, promotes radioresistance by suppressing anti-tumor immunity. In radiation-resistant tumors, NEK8 phosphorylates lactate dehydrogenase A (LDHA), driving lactate overproduction. This metabolite promotes histone modifications that silence antigen presentation machinery, while extracellular lactate directly impairs CD8+ T cell function, collectively excluding CD8+ T cell from the tumor microenvironment. Pharmacological inhibition of NEK8 using CX6258 restores CD8+ T cell infiltration and enhances both local and systemic tumor control following radiotherapy. These findings establish NEK8 as a promising therapeutic target for overcoming radioresistance and inducing abscopal responses in CRC.

Introduction
Colorectal cancer (CRC) is a highly lethal malignancy, ranking among the top three in both incidence and mortality rates globally. Approximately 22% of colorectal cancer patients are already dealing with advanced distant metastases at the time of initial diagnosis. For these metastatic cases, the primary clinical treatment modalities are mainly radiotherapy and chemotherapy. However, despite ongoing advancements in treatment, many patients still face treatment failure due to local radioresistance.The cytotoxic effect of ionizing radiation (IR) primarily relies on inflicting DNA damage in tumor cells 1. As a result, most radiosensitizing strategies focus on either inhibiting DNA repair or enhancing DNA damage2. The immune contexture is vital in radiocurability3. Radiation boosts antitumor immunity via several mechanisms. For example, cellular stress and death caused by radiation release signals like DAMPs (damage-associated molecular patterns), DNA, chemokines, and cytokines, which link innate and adaptive immunity4-6. Thus, tumor-targeted RT can be seen as an “in situ tumor vaccination.” Here, activated antigen-presenting cells (APCs) process engulfed tumor-associated antigens (TAAs) to cross-prime CD8+ T cells, which can drive systemic cancer rejection, known as the abscopal effect7-9. However, about 30% of CRC patients will develop radiotherapy resistance 10, and the incidence of RT-induced abscopal responses remains extremely low (<5%)11-13. Our limited understanding of how CRC evades the immune system after radiation therapy continues to hinder efforts to enhance radiotherapy efficacy and radiation-induced abscopal immunity.

Understanding the immune mechanisms underlying intrinsic or acquired resistance is crucial to optimize existing combination therapies. In particular, combining radiotherapy with immunotherapies, especially those that systemically activate T cells, is gaining increasing attention14,15. Previous studies have shown that radiotherapy can have both immunostimulatory effects, such as in situ vaccination and T-cell recruitment, and immunosuppressive effects, like hypoxia and the expansion of regulatory T (Treg) cells6,16-18.Tumor-derived metabolites play a key role in regulating immune cells within tumor microenvironment (TME). Lactate, the most elevated metabolite in tumors, promotes cancer progression and therapeutic resistance19. It serves as a carbon source for tumor-infiltrating Treg cells, MSDCs (mitochondria-derived damage-associated molecular patterns), and M2-like macrophages, fueling their tumor-promoting activities20-22. High lactate levels in the TME also significantly impair CD8+ T cell function. Lactate boosts PD-1 expression on Tregs but suppresses it on effector T cells23. Moreover, lactate binds directly to GLUT10 (Glucose Transporter Type 10), reducing its glucose transport activity and thus inhibiting CD8+ T cell effector functions24. During radiotherapy, pancreatic cancer cells ramp up glycolysis and secrete more lactate. This lactate activates MDSCs, fostering an immunosuppressive microenvironment that promotes pancreatic cancer progression and recurrence25. However, the impact and regulatory mechanisms of lactate on radioresistance and abscopal effect in CRC remain unclear.

In this study, using single-cell RNA sequencing (scRNA-seq), we comprehensively characterized the immune microenvironment changes and mechanisms in radioresistant CRC, with a focus on reinvigorating CD8+ T cells to enhance therapeutic efficacy. By conducting RNA-seq on resistant cell lines and analyzing public databases, we identified Never-in-Mitosis-related kinase 8 (NEK8) as a radiotherapy-resistant gene associated with CD8+ T cell anti-tumor immunity. Research indicates that NEK8 is closely linked to tumor development. In breast cancer, NEK8 is upregulated and promotes cell proliferation, migration, invasion, and stemness via the β-catenin pathway26,27. It also drives gastric cancer cell proliferation28. Moreover, NEK8 plays a key role in tumor metabolic reprogramming. For instance, NEK8 interacts with aspartate synthetase (ASNS) to regulate its ubiquitination, influencing tumor growth in gastric cancer 29. In CRC, NEK8 enhances c-MYC protein stability by phosphorylating serine 405, thereby promoting CRC progression30. Here, we demonstrate that overexpression of NEK8 in CRC promotes lactate production by activating LDHA. This dual mechanism not only enhances lactate secretion but also increases histone lactylation levels in the promoter regions of MHC-I genes, thereby suppressing their expression. As a result, CD8+ T cell infiltration and antitumor activity are inhibited, leading to radioresistance and suppression of the abscopal effect. Targeting NEK8 can enhance the efficacy of radiotherapy in tumors and induce the abscopal effect, thereby inhibiting the growth of distant metastatic tumors.

Results
CD8+ T cells as the primary mediators of radiotherapy resistance in colorectal cancer
To investigate the potential mechanisms involved in radiotherapy resistance in CRC, we used a syngeneic mouse tumor model to generate an in vivo resistance model (Fig. 1A). As shown in Figure S1A-B, after performing cycles of radiotherapy along with serial passage, resistant MC38 (IR-MC38) tumors were nonresponsive to radiotherapy, as shown by the similar tumor growth to the untreated group (Supplemental Fig. 1A-B). Radiation clonogenic assays and CCK8 assays further verified IR-MC38 is a radiotherapy-resistant cell line (Supplemental Fig. 1C-D). To elucidate the tumor immune microenvironment (TIME) differences between the IR-sensitive cell line MC38 and IR-resistant cell line IR-MC38 , we characterized CD45+ immune cells isolated from MC38 and IR-MC38 tumors by high-throughput single cell RNA sequencing (scRNA-seq). We identified four major cell lineages including myeloid cells, granulocytes, T cells or natural killer (NK) cells and B cells, based on gene expression signatures (Fig. 1B). We then characterized the changes of these cell subtypes in IR-MC38 tumors compared with MC38 tumors. The percentage of T cells or natural killer (NK) cells significantly decreased, while myeloid cells and granulocytes increased (Fig. 1C). ScRNA-seq resolved myeloid cells into nine transcriptionally defined subsets (Supplemental Fig. 1E): C01 (Ccr2+ Trem1+ M/MdM), C02 (Gpnmb+ Mph), C03 (Ms4a7+ Mrc1hi Mph), C04 (Cd3e+ Myeloid Cells), C05 (Mki67+ Myeloid Cells), C06 (APCs), C07 (Ifitm6+ Mono), C08 (Tnfrsf4+ Ikzf2+ Myeloid Cells), C09 (S100a9+ M/MdM), and a residual C10 (Others). Cluster percentages diverged sharply between conditions (Supplemental Fig. 1F): C02 (Gpnmb⁺ Mph), C03 (Ms4a7⁺ Mrc1hi Mph), and C04 (Cd3e⁺ Myeloid Cells) showed the greatest shifts in IR-MC38 versus MC38 tumors, reflecting radiation-driven remodeling of the myeloid niche.Focusing on the T cells or natural killer (NK) cells compartment, we identified the percentage of CD8+ T cells dramatically decreased in IR-MC38 tumors compared with MC38 tumors, while regulatory T cells (Tregs) increased (Fig. 1D-F). Thus, the tumor microenvironments of MC38 tumors and IR-MC38 tumors exhibited significant differences, particularly in the infiltration of immune cells such as CD8+ T cells, Tregs, myeloid cells, and granulocytes. Among these, the infiltration of CD8+ T cells showed the most pronounced difference.

To investigate the anti-tumor CD8+ T cell response in IR-MC38 tumors and MC38 tumors, we clustered Tumor-infiltrating CD8+ T cells into four clusters based on well-established marker genes: effector-like (Prf1, Gzmd, Gzmf), memory-like (Xcl1, Ccr7), naive-like (Lef1, Tcf7), and proliferating-like (Mki67, Top2a) (C01–C04) (Fig. 1G, Supplemental Fig. 1G). We found that the majority of CD8+ T cells isolated from MC38 tumors clustered in the C01 effector-like cluster and C02 memory-like cluster, while CD8+ T cells from IR-MC38 tumors showed increased density in the C03 naive-like cluster and C04 proliferating-like cluster (Fig. 1H). Notably, we observed that CD8+ T cells from IR-MC38 tumors displayed decreased expression of cytotoxic molecules and effector molecules compared with MC38 tumors (Supplemental Fig. 1H). Consistent with scRNA-seq, flow cytometry revealed a sharp drop in CD8⁺ T cells and a concomitant surge in Tregs in IR-MC38 tumors (Fig. 1I, Supplemental Fig. 1I). The same analysis showed depletion of effector-like C01 (GZMB⁺ Perforin+) and memory-like C02 (CCR7+) subsets, offset by expansion of naïve-like C03 (TCF7+) and proliferating-like C04 (MKi67+) subsets (Fig. 1J, Supplemental Fig. 1J).

We further investigated the differentially expressed genes in C01 CD8+ T cells from MC38 and IR-MC38 tumors (Supplemental Fig. 1K, Supplementary Data 1) and conducted Gene Ontology (GO) enrichment analysis on the upregulated genes in IR-MC38 C01 CD8+ T cells. Our analysis revealed that these genes were significantly enriched in the negative regulation of cytokine production pathway (Supplemental Fig. 1L). These suggested that cytokine secretion by CD8+ T cells in IR-MC38 tumors was substantially inhibited, thereby diminishing their anti-tumor activity.

NEK8 is a radiotherapy resistance gene negatively correlated with CD8+ T cell anti-tumor immunity
To identify potential oncogenic targets that influenced CD8+ T cell infiltration and function during radiotherapy, we first performed RNA sequencing (RNA-seq) between the MC38 cells and IR-MC38 cells without IR. DEG (differentially expressed genes) analysis revealed a series of genes with dramatic differences in expression (Fig. 2A, Supplemental Data 2). Among these DEGs, Nek8, Casp1, Atp1a3, Mgp, and Nes were the top five upregulated genes upon radiotherapy resistance IR-MC38 (Fig. 2A-B). We classified TCGA-COADREAD patients into two groups based on Tcell antitumor immunity using a scoring system31. DEGs between high (top 10%, n=64) and low (bottom 10%, n=64) CD8+ T-score CRC tumors in TCGA (Fig. 2C), and those differentially expressed in IR-resistant vs. IR-sensitive samples in GSE133057 and GSE119409, were identified. NEK8 and CELSR3 were the common genes in all three groups (Fig. 2D). CELSR3 was down-regulated in IR-resistant samples. NEK8 was the sole gene convergently identified by both screens and up-regulated in IR-resistant samples, so we focused our study on NEK8. In the TCGA-COADREAD cohort, NEK8 expression correlated with the radiosensitivity index (RSI) 32—a genomic proxy inversely linked to tumor radiosensitivity—being markedly higher in RSI-high than in RSI-low CRC (Fig. 2E). Furthermore, NEK8 expression exhibited an inverse correlation with the transcriptional levels of genes linked to CD8+ T-cell infiltration and antitumor immune responses (Supplemental Fig. 2A). Analysis using the TIMER algorithm revealed that colorectal cancer tumors with elevated NEK8 expression displayed reduced infiltration of CD8+ T cells (Fig. 2F). These results suggested that NEK8 might play a critical role in attenuating CD8+ T cell-mediated antitumor immunity.

We next examined NEK8’s role in radioresistance. Western blotting confirmed markedly higher NEK8 expression in IR-MC38 than in parental MC38 cells, with the most pronounced elevation observed 24 h after 4 Gy irradiation (Supplemental Fig. 2B). NEK8 has been previously described as a ciliary kinase，we discovered that NEK8 can colocalize with cilia (axoneme marker: acetylated tubulin, a basal body marker: Gamma-tubulin), but a significant amount of NEK8 remains uncolocalized in the cytoplasm, suggesting that NEK8 may function through other pathways in addition to its role via the cilia signaling (Supplemental Fig. 2C).Nek8 was stably knocked down in MC38, IR-MC38, CT26, the melanoma B16 cell lines and the breast cancer 4T1 cell lines by two short hairpin RNAs (shRNA), and overexpressed in MC38 cell lines (Supplemental Fig. 2D). Radiation clonogenic assays and CCK8 assays showed that NEK8 overexpression induced radioresistance in MC38 cells, whereas NEK8 depletion increased radiosensitivity in both MC38 and IR-MC38 cells (Fig. 2G-H，Supplemental Fig. 2E-F). In MC38 model, primary tumor growth was significantly suppressed in Nek8 knockdown tumors compared to the control group (Fig. 2I). Moreover, local irradiation treatment could further inhibit the tumor growth of Nek8 knockdown tumors compared with the control group (Fig. 2I), and this similar phenotype was also observed in the CT26 model (Fig. 2J), while overexpression of Nek8 had opposite effects (Supplemental Fig. 2G). We also implanted Nek8-deficient (shNek8) or Nek8-sufficient (shNC) IR-MC38 cells on the flanks of mice and then monitored tumor growth after local radiation treatment and observed a similar phenotype. In addition, in the IR-MC38 model, local irradiation therapy led to a more pronounced inhibition of tumor growth in Nek8 knockdown tumors compared with the control group (Fig. 2K). Moreover, to verify whether NEK8 has a similar effect in other cancer types, we used melanoma B16 cells and obtained consistent results (Supplemental Fig. 2H). Taken together, these data indicated that deleting NEK8 in cancer cells enhanced the efficacy of radiotherapy.

NEK8 inhibition leads to abscopal effects of radiotherapy in CRC
Radiotherapy can induce antitumor immune responses and has the potential to mediate abscopal effects33. We investigated whether NEK8 deficiency enhances the abscopal effects of radiotherapy.

We implanted WT MC38 tumors into left flank of C57BL/6J mice and Nek8-deficient or Nek8-sufficient MC38 tumors into right flank. Right tumors were irradiated at 15 Gy. Abscopal tumor growth was significantly delayed in mice bearing primary Nek8-deficient MC38 tumors post-RT (Fig. 3A Supplemental Fig. 3A). Similar results were obtained in murine CT26 and IR-MC38 colorectal tumors (Fig. 3B, Supplemental Fig. 3B-D).

Colon orthotopic tumors and orthotopic liver metastasis tumors are more resistant to immunotherapy than subcutaneous colorectal cancer models due to their distinct tumor microenvironments34,35. To address these challenges, we implanted MC38-luciferase cells orthotopically into the cecum or liver by injecting into the spleen and simultaneously transplanted Nek8-deficient or Nek8-sufficient MC38 cells into the subcutaneous tissue. The subcutaneous tumors were then treated with radiotherapy (15 Gy; Fig. 3C, Fig. 3H). We observed that radiotherapy significantly increased the complete response (CR) rates in both irradiated (subcutaneous) and abscopal (cecal or liver metastasis) tumors in the Nek8-deficient group compared to the control group (Fig. 3D-G, Fig. 3I-K). Similarly, we implanted IR-MC38-luciferase cells orthotopically into the cecum and simultaneously transplanted Nek8-deficient or Nek8-sufficient IR-MC38 cells into the subcutaneous tissue. The subcutaneous tumors were then treated with radiotherapy (15 Gy; Supplemental Fig. 3E). We also observed that radiotherapy significantly increased the complete response (CR) rates in both irradiated (subcutaneous) and abscopal (cecal) tumors in the Nek8-deficient group compared to the control group (Supplemental Fig. 3F-I). These results suggested that tumor cell-intrinsic NEK8 deficiency in irradiated primary tumors restricted the growth of unirradiated secondary tumors by enhancing antitumor adaptive immune responses.

NEK8 impedes CD8+ T cell migration and suppressive function after radiotherapy
To determine whether tumor cell-intrinsic NEK8 deficiency is required for the reconstitution of immune cell populations in tumors after radiation, we used flow cytometry to analyze the proportions of various immune cell types within the TME. In MC38 and CT26 tumors, Nek8 knockdown alone increased DCs, M-MDSCs, and CD8+ T cells while decreasing macrophages and CD4+ T cells. B cells rose only in MC38, neutrophils fell only in CT26. Under RT, Nek8 knockdown increased DCs and CD8+ T cells, increased granulocytes only in MC38, increased NK cells and decreased CD4+ T cells only in CT26 (Fig. 4A, Supplemental Fig. 4A-C). Inspiring, radiation combined with Nek8 knockdown boosted intratumoral CD8⁺ T-cell infiltration in both Nek8-deficient MC38 and CT26 tumors, an effect recapitulated in IR-MC38 tumors. (Fig. 4A, Supplemental Fig. 4C). Immunohistochemistry (IHC) results were consistent with the flow cytometry data (Supplemental Fig. 4D). To further investigate this, we harvested Nek8-sufficient or Nek8-deficient MC38 tumor fragments containing pre-existing CD8+ T cells from CD45.1 wild-type (WT) mice and transplanted them into CD45.2 mice, which were then treated with irradiation. Four days after IR, there was a significant increase in tumor-infiltrating CD45.2+ CD8+ T cells in Nek8-deficient tumors compared to controls. Conversely, a similar result was obtained (Fig. 4B). We further explored whether newly infiltrating T cells are necessary for the observed effects by administering the sphingosine-1-phosphate receptor agonist fingolimod (FTY720), which blocks T cells from exiting the thymus and secondary lymphoid organs and prevents their migration to sites of inflammation36. In the absence of new lymphocyte infiltration, the radiosensitizing effect and antitumor effect of Nek8 knockdown were abolished (Fig. 4C). Additionally, the proportions of Perforin+ and GZMB+ cells among tumor-infiltrating CD8+ T cells were significantly higher in irradiated Nek8-deficient MC38, CT26 and IR-MC38 tumors compared to controls (Fig. 4D, Supplemental Fig. 4E). These additional effector markers (including IFN-γ, IL-2 and TNF-α) are increased in irradiated Nek8-deficient MC38 tumors, while the exhaustion markers (PD-1, TIM-3 and CTLA4) are decreased in irradiated Nek8-deficient MC38 tumors compared to controls (Supplemental Fig. 4F). This indicated that IR-induced activation of the CD8+ T cell antitumor immune response was enhanced in Nek8-deficient tumors. Furthermore, the depletion of CD8+ T cells abolished the growth delay of Nek8-deficient tumors after radiation treatment (Fig. 4E, Supplemental Fig. 4G). To investigate the impact of tumor-derived NEK8 on T cells during T cell receptor (TCR)-mediated tumor antigen recognition, we co-cultured MC38-OVA-shNC and MC38-OVA-shNek8 cells (with or without 4 Gy irradiation) with OT-1 CD8+ T cells for 24 hours. Notably, OT-1 T cells co-cultured with Nek8-deficient tumor cells exhibited robust production of Perforin and GZMB (Fig. 4F-G), along with enhanced cytotoxic T lymphocyte (CTL) activity against target tumor cells. This effect was further amplified under radiotherapy conditions (Fig. 4G).

To investigate the abscopal tumor microenvironment, we used flow cytometry to analyze immune cell proportions. Compared to controls, macrophages significantly decreased and CD8+ T cells significantly increased in the abscopal tumor of irradiated Nek8-deficient MC38 and IR-MC38 tumors. (Fig. 4H, Supplemental Fig. 4H). Additionally, the proportions of Perforin+ and GZMB+ cells among tumor-infiltrating CDI8+ T cells were higher in the abscopal tumor of irradiated Nek8-deficient MC38 and IR-MC38 tumors (Fig. 4I). Notably, blocking CD8+ T cells with a neutralizing antibody effectively restored abscopal effects mediated by Nek8 deficiency, while blocking macrophages with anti-CSF1 did not enhance abscopal effects in Nek8-sufficient tumors (Supplemental Fig. 4I). The above results indicated that CD8+ T cells were the critical cell population mediating the abscopal effects in the context of NEK8 deficiency.

NEK8 interacts with LDHA to induce its Ser196 phosphorylation and promotes lactate production
MS, conducted post-Co-IP, was performed on MC38 and CT26 cells to identify NEK8-interacting proteins. Ingenuity Pathway Analysis of NEK8-interacting proteins revealed that lactate biosynthetic process and lactate metabolic process were among the top enriched metabolic pathways (Fig. 5A, Supplemental Data 3). We identified lactate metabolism-related proteins (LDHA, LDHC, PARK7) among NEK8-binding proteins. LDHA, which reduces pyruvate to lactate, was our primary focus. Using the HDOCK website, we predicted NEK8-LDHA binding in both humans and mice, confirming direct interaction (Supplemental Fig. 5A). This interaction was further confirmed using Co-IP, which showed that LDHA was a potent NEK8-interacting protein (Fig. 5B). We collected MC38 cells with stable Nek8 overexpression or knockdown and their supernatants, then measured lactate levels. Nek8 knockdown significantly decreased lactate in cells and supernatant, while Nek8 overexpression increased it, with the most pronounced elevation observed 24 h after 4 Gy irradiation (Fig. 5C，Supplemental Fig. 5B). Additionally, Nek8 knockdown inhibited LDH enzymatic activity, whereas Nek8 overexpression enhanced it in MC38, with the most pronounced elevation observed 24 h after 4 Gy irradiation (Fig. 5D, Supplemental Fig. 5C). The above results indicated that NEK8 can significantly enhance the enzymatic activity of LDHA, thereby promoting lactate production.

Given that NEK8 is a protein kinase involved in substrate phosphorylation, we hypothesized that it might act as a LDHA kinase. The phosphorylation LDHA by the NEK8 kinase was characterized using [γ-32P]-ATP, with a kinase-inactive NEK8 (NEK8 Lys33Met) as a negative control (Supplemental Fig. 5D), and the level of phosphorylation continuously increased over time (Supplemental Fig. 5E). The Michaelis constant (Km) for the LDHA–NEK8 interaction was determined by autoradiography to be 0.35 μM, with a Vmax of 9.2 × 10^5 signal per 5 min， indicating that protein LDHA is a highly efficient substrate for NEK8 (Supplemental Fig. 5F-G).An in vitro kinase assay and MS analysis showed that NEK8 phosphorylates LDHA at S196, T213, and S310 (Supplemental Fig. 5H). To investigate this further, we analyzed the conservation of three LDHA phosphorylation sites (T213, S310, and S196) across multiple species. Only the S196 site was highly conserved (Supplemental Fig. 5I), suggesting it may be the primary site through which NEK8 regulates LDHA activity. Additionally, A previous study reported that ULK1 can interact with LDHA and phosphorylate Ser196 under nutrient scarcity, enhancing LDHA activity and lactate production37. This supports our conclusion that LDHA-S196 is a critical site for regulating LDHA activity and lactate production. We developed a polyclonal antibody specific to LDHA phosphorylated at Serine-196 and validated it in LDHA-KO cell (followed by expression of either LDHAWT, LDHAS196A, or LDHAS196D) (Supplemental Fig. 5J). Then, we used the antibody to detect the Nek8 stable strain, and the results showed that Nek8 knockdown significantly reduced LDHA Serine-196 phosphorylation, while Nek8 overexpression significantly increased it. This effect was even more pronounced under radiotherapy conditions (Fig. 5E). Therefore, these results suggested that NEK8 as an upstream regulator mediated LDHA S196 phosphorylation.

To verify whether LDHA is a crucial downstream target molecule of NEK8, we constructed cell lines with Ldha knockdown in Nek8-overexpressing cells and cell lines with Ldha overexpression in Nek8-knockdown cells, confirmed by Western blot (Supplemental Fig. 5K). We then subcutaneously implanted these cell lines into mice to evaluate their responses to radiotherapy. Results showed that Ldha knockdown significantly reversed the radiotherapy resistance mediated by Nek8 overexpression (Supplemental Fig. 5L), while Ldha overexpression significantly rescued the radiosensitization caused by Nek8 knockdown (Supplemental Fig. 5M). Furthermore, we knocked out endogenous Ldha in the Nek8 overexpressing MC38 cells, and overexpressed LdhaWT, LdhaS196A, or LdhaS196D, respectively, followed by validation of successful construction through Western blot analysis (Supplemental Fig. 5N). We then subcutaneously implanted these cell lines into mice to evaluate their responses to radiotherapy. Results showed that LDHA KO or LDHAS196A significantly reversed the radiotherapy resistance mediated by NEK8 overexpression (Supplemental Fig. 5O). These findings further confirmed that LDHA was a critical downstream target of NEK8.

Lactate inhibits radiosensitization and abscopal effects mediated by NEK8 knockdown.
To elucidate the impact of lactate metabolism on the efficacy of radiotherapy and the abscopal effects in CRC, we treated MC38-Vector and MC38-Nek8 subcutaneous tumor models with 2-deoxy-D-glucose (2-DG, a glycolysis inhibitor) and oxamate (a lactate dehydrogenase inhibitor). The results showed that 2-DG and oxamate significantly reversed NEK8-mediated radioresistance and their combination with radiotherapy markedly suppressed tumor growth (Fig. 5F). Moreover, we examined lactate levels in subcutaneous tumor tissues and found that Nek8 overexpression boosts lactate production, especially under radiotherapy. However, this effect was significantly dampened by 2-DG and oxamate (Supplemental Fig. 5P). Then, we treated bilateral subcutaneous tumor models of MC38-shNC and MLC38-shNek8 with lactate and found that it significantly rescued the anti-tumor and abscopal effects induced by Nek8 knockdown combined with radiotherapy (Fig. 5G-H). We measured lactate in tumor tissues and serum. Lactate increased serum and bilateral tumor lactate levels in MC38-shNek8 mice (Fig. 5I, Supplemental Fig. 5Q). These findings indicated that lactate might play a crucial role in NEK8-mediated suppression of radiotherapy sensitivity and the abscopal effects in CRC.

To investigate the impact of lactate on CD8+ T cell infiltration and function during radiotherapy, we used IHC to examine CD8+ T cell infiltration in bilateral tumor tissues from a subcutaneous model treated with lactate. Nek8 knockdown with radiotherapy increased CD8+ T cell infiltration in both irradiated and non-irradiated tumors, but exogenous lactate reversed this effect (Supplemental Fig. 5R-S). We co-cultured OT1 CD8+ T cells with MC38-OVA-shNek8 or control cells after radiotherapy. One group received lactate, the other PBS. After 24 hours, flow cytometry showed Nek8 knockdown with RT increased Perforin and GZMB secretion, but lactate inhibited this effect (Fig. 5J). In a parallel experiment, OT1 CD8+ T cells were co-cultured with MC38-OVA-Nek8 or control cells after radiotherapy. One group received oxamate, the other PBS. Flow cytometry after 24 hours showed Nek8 overexpression with RT inhibited Perforin and GZMB secretion, but oxamate reversed this effect (Fig. 5K). The above results demonstrated that lactate significantly inhibited the infiltration and anti-tumor activity of CD8+ T cells.

NEK8-mediated H3K18 lactylation inhibits MHC-I gene transcription in CRC.
Our previous findings showed that NEK8 not only increased lactate levels in tumor cell culture supernatants but also significantly raised intracellular lactate levels in tumor cells (Supplemental Fig. 5B). Lactate accumulation within cells can drive histone lysine lactylation, and cancer-associated alterations in lactylation can promote tumor progression and immune evasion38. We hypothesized that NEK8-mediated lactate accumulation promotes protein lactylation, influencing gene expression and immune evasion in CRC. Using pan-lactylation antibodies, we found that Nek8 knockdown reduced protein lactylation in MC38 and IR-MC38, especially in histone regions (around 15 kDa), while Nek8 overexpression increased it in MC38 (Fig. 6A, Supplemental Fig. 6A). This effect was more pronounced in cells treated with 4Gy radiation. Lactylation levels at various histone H3 and H4 sites were also significantly reduced by Nek8 knockdown in MC38 and IR-MC38 (Fig. 6B, Supplemental Fig. 6B). Among them, H3K18la is a key histone lactylation modification involved in tumorigenesis, immune cell regulation, and metabolism-epigenetics crosstalk. Previous studies showed that H3K18la enhances immune evasion in non-small cell lung cancer by activating the POM121/MYC/PD-L1 pathway39. Thus, we focused on investigating NEK8's effects via H3K18la.

The H3K18la-regulated downstream targets were identified in MC38-shNek8 through Cut&Tag, which revealed H3K18la enrichment in gene promoter regions (Fig. 6C-D, Supplemental Data 4). We also performed bulk RNA-seq on subcutaneous MC38-shNC and MC38-shNek8 tumor tissues of mice after radiotherapy, identifying 230 upregulated genes and 384 downregulated genes (Fig. 6E, Supplemental Data 5). KEGG enrichment of the differentially expressed genes revealed significant over-representation of the cytokine–cytokine receptor interaction and antigen processing and presentation pathways (Supplemental Fig. 6C).

Subsequently, we performed a joint analysis of the Cut&Tag sequencing and bulk RNA-seq results. We intersected the genes with decreased H3K18la levels in their promoter regions following Nek8 knockdown with the genes that were upregulated in the shNek8 + IR vs. shNC + IR comparison, identifying a total of 246 genes (Fig. 6F). These 246 genes were analyzed using the Metascape website, revealing significant enrichment in the R-MMU-983169: Class I MHC mediated antigen processing & presentation pathway (Fig. 6G).

We further used qRT-PCR to analyze the expression of 21 genes enriched in the R-MMU-983169: Class I MHC mediated antigen processing & presentation pathway in subcutaneous tumor tissues from MC38-shNC+IR and MC38-shNek8+IR groups. The results showed that 17 of the 21 genes were significantly upregulated in MC38-shNek8+IR tumor tissues, except Arhgap1, Mdd, Uba52, and Actr1b (Fig. 6H). We analyzed the Cut&Tag sequencing data and found that Nek8 knockdown significantly reduced H3K18la levels in the promoter regions of representative genes including Calr, Tapbp and Psmb4 (Fig. 6I), which was further confirmed by Cut&Tag qPCR experiments (Fig. 6J).

Additionally, we measured MHC-I expression on tumor cells after Nek8 knockdown via flow cytometry. Nek8 knockdown increased MHC-I expression, further enhanced by radiotherapy (Fig. 6K).

We obtained the same results in breast cancer 4T1 cells (Supplemental Fig. 6D). Pharmacologic inhibition of histone acetyltransferase p300 with C646 fully reversed the Nek8-driven elevation of H3K18la and restored MHC-I expression in Nek8-high MC38 cells, establishing a causal link between Nek8-induced histone lactylation and antigen-presentation capacity (Supplemental Fig. 6E). Moreover,we treated MC38-Vector and MC38-Nek8 subcutaneous tumor models with C646 and the results showed that C646 significantly reversed NEK8-mediated radioresistance and their combination with radiotherapy markedly suppressed tumor growth (Supplemental Fig. 6F). In Ldha stable cell lines, Ldha overexpression reversed Nek8 knockdown-induced H3K18la downregulation, while Ldha knockdown reversed Nek8-induced H3K18la upregulation and all other histone H3 and H4 sites can also rescued(Fig. 6L, Supplemental Fig. 6G-H). In the Ldha KO-Nek8 overexpressing MC38 cells (followed by expression of either LdhaWT, LdhaS196A, or LdhaS196D), Ldha KO or LdhaS196A significantly reversed the upregulation of H3K18la mediated by Nek8 overexpression, while LdhaS196D only partially reversed it (Supplemental Fig. 6I). Similarly, under radiotherapy, Ldha reintroduction restored MHC-I upregulation caused by Nek8 knockdown, while Ldha knockdown restored MHC-I downregulation induced by Nek8 overexpression (Fig. 6M). These results suggested that NEK8 knockout combined with radiotherapy reduced H3K18la levels in the promoter region of MHC-I genes, thereby promoting MHC-I expression and enhancing antigen presentation.

Pharmacological inhibition of NEK8 enhances responses to radiotherapy and abscopal effects.
Given the significant radiosensitization and abscopal effects mediated by NEK8 knockdown, targeting NEK8 could be a promising strategy for cancer treatment. To preclinically prove this concept, we aimed to identify NEK8 inhibitors. By virtual screening of chemical libraries consisting of 50,000 small-molecule drugs, the chemical compounds capable of binding to the ATP binding site (key amino acids include VAL10/VAL18/LYS33) of NEK8 were scored. The top 5 hits were selected (Supplemental Fig. 7A) and their ability to inhibit tumor growth in vitro was tested. Notably, CX6258, a potent and kinase-selective pan-Pim kinase inhibitor40, also acts as an inhibitor of haploid germ cell-specific nuclear protein kinase (Haspin)41 and effectively kills tumors at the nM level (Supplemental Fig. 7B). CX6258 formed two hydrogen bonds with the NEK8 protein (Fig. 7A). We used surface plasmon resonance (SPR) to monitor the real-time interaction between CX6258 and NEK8. The results showed that the dissociation constant (KD) was 3.38 µM, the association rate constant (ka) was 4443.454/Ms, and the dissociation rate constant (kd) was 0.015/s (Fig. 7BC). We then purified human NEK8 protein in vitro and conducted a kinase activity assay, revealing that NEK8 can consume ATP at a concentration of 200 nM (Fig. 7C). Further kinase inhibition assays showed that CX6258 inhibited NEK8 kinase activity with an IC50 of 3.011 µM (Fig. 7D-E). These findings demonstrated that CX6258 was a small-molecule inhibitor of NEK8.

To investigate whether CX6258 improves the response to IR at a similar level as NEK8 genetic deletion, we treated CT26 subcutaneous tumors and AOM/DSS-induced CRC models with CX6258. We found that CX6258 alone inhibited tumor growth, while its combination with radiotherapy significantly amplified this effect without affecting mouse body weight. (Fig. 7F, Supplemental Fig. 7D). Given CX6258's multiple targets, we tested if its radiosensitizing effect on CRC is mediated by NEK8. Using a subcutaneous MC38-shNek8 tumor model treated with CX6258 and radiotherapy, we found that Nek8 knockdown abolished CX6258's ability to inhibit tumor growth and enhance radiotherapy efficacy (Supplemental Fig. 7E-F). We also explored whether CX6258 could enhance the efficacy of IR and anti-PD1 treatment using the MC38 model. Compared to any single treatment, combining CX6258 with anti-PD1 significantly slowed MC38 tumor growth. The triple therapy of CX6258, IR, and anti-PD1 delivered the most potent antitumor effects (Fig. 7G).

To examine if CX6258 potentiates the abscopal effects of radiotherapy, we implanted C57BL/6J mice with bilateral subcutaneous MC38 or IR-MC38 tumors and treated them with or without: (i) 15-Gy irradiation to the right flank tumors, and (ii) oral CX6258. Significant growth delay in abscopal tumors was observed in mice treated with both radiotherapy and CX6258 (Fig. 7H-I). To verify whether CX6258 has a similar effect in other cancer types, we used melanoma B16 cells and obtained consistent results (Supplemental Fig. 7G). Moreover, we implanted MC38-luciferase cells into the cecum and MC38 cells into the subcutaneous tissue. The subcutaneous tumors were then treated with radiotherapy or oral CX6258 (Fig. 7J). We found that combining radiotherapy and CX6258 significantly increased complete response (CR) rates in both irradiated (subcutaneous) and abscopal (cecal) tumors (Fig. 7K-M).

To interrogate the underlying immunological mechanisms, we profiled tumor-infiltrating immune cells in MC38 tumors following CX6258 treatment by flow cytometry. CX6258 alone significantly increased DC and CD8+ T cell infiltration, with no significant effects on other immune cells. However, combining CX6258 with radiotherapy further enhanced the infiltration of macrophages, DCs, granulocytes, and CD8+ T cells, while suppressing PMN-MDSC, M-MDSC, and neutrophils. Notably, this combination had no significant impact on B cells, CD4+ T cells, and NK cells (Fig. 7N, Supplemental Fig. 7H). The combination of CX6258 and radiotherapy significantly enhanced CD8+ T cell infiltration and their anti-tumor activity, consistent with our previous findings in irradiated NEK8-deficient tumors (Fig. 7N-O). MC38 tumors treated with irradiation and CX6258 exhibited a significant shift in immune activation profiles, showing markedly elevated effector cytokines (IFN-γ, IL-2, and TNF-α) alongside downregulated exhaustion markers (PD-1, TIM-3, and CTLA-4) compared to the irradiation control group （Supplemental Fig. 7I). We also examined the microenvironment of abscopal tumors. Compared to radiotherapy alone, the combination of CX6258 and radiotherapy significantly increased the infiltration of macrophages, dendritic cells, granulocytes, and CD8+ T cells, while reducing M-MDSC infiltration in abscopal tumors (Supplemental Fig. 7J). Moreover, the cytotoxic activity of CD8+ T cells was markedly enhanced (Supplemental Fig. 7K). The results demonstrated that the antitumor effect of combining NEK8 inhibition with IR depended on adaptive immunity and mirrored the effects seen in NEK8-deficient tumors.

Clinical relevance of NEK8 expression and LDHA Ser196 phosphorylation levels in CRC patients
According to the TCGA-COADREAD datasets, NEK8 expression was significantly upregulated in CRC (Fig. 8A). Examination of NEK8 in an in-house cohort of 54 CRC patients by in situ multi-color immunofluorescence revealed that NEK8 expression in tumor cells was inversely correlated with CD8+ T cell infiltration (Fig. 8B-C). Kaplan–Meier survival analysis of the TCGA-COADREAD datasets revealed that CRC patients with high NEK8 expression had significantly poorer overall survival compared to those with low NEK8 expression (Fig. 8D). IHC showed that the amounts of NEK8 expression, LDHA Ser196 phosphorylation levels and H3K18 lactylation were increased in the radiotherapy-resistant tumors (Fig. 8E-F). NEK8 expression significantly correlated with T stage, TNM stage, and TRG classification but showed no correlation with M stage, histologic grade, or tumor location (Supplemental Table 2). Further analyses demonstrated positive correlations between NEK8 expression, LDHA Ser196 phosphorylation and H3K18 lactylation levels in CRC tissues (Fig. 8G). These findings suggested NEK8 expression and LDHA Ser196 phosphorylation were correlated with clinical radiotherapy resistance to CRC (Fig. 8H).

Methods
Mice
C57BL/6 and BALB/c mouse strains were procured from the Guangdong Medical Laboratory Animal Center, while CD45.1 mice were acquired from Cyagen Biosciences. OT-1 mice were obtained from Shanghai Model Organisms. All experimental animals, aged between 4 and 7 weeks, were maintained in specific pathogen-free (SPF) facilities at Southern Medical University. AOM/ DSS-induced colorectal cancer mice were male and other mice were female. Sex was not considered as a biological variable in the study design and analysis. The study exclusively used female mice to maintain consistency across experiments and reduce variability in immune microenvironment analyses. Male mice were used in the AOM/DSS model as they are more prone to successful modeling. The animal experiments were performed in compliance with the ethical guidelines and protocols approved by the Institutional Animal Care and Use Committee (IACUC) of Southern Medical University in accordance with the ARRIVE guidelines (Approval No. SMUL202404004).

Clinical specimens
Between January 2017 and January 2022, we collected 54 pathological specimens from colorectal cancer (CRC) patients at the Department of Pathology, Nanfang Hospital, Southern Medical University. Specimens were obtained from pre-treatment colonoscopy biopsies from patients undergoing neoadjuvant chemoradiotherapy, with no prior anti-tumor therapies. Therapeutic responses were evaluated using the tumor regression grading (TRG) system from the 8th edition of the American Joint Committee on Cancer (AJCC) 52. Patients with TRG 0 or TRG 1 were classified as responders, whereas those with TRG 2 or TRG 3 were considered non-responders. All specimens were collected with written informed consent from the patients. The study was approved by the Ethics Committee of Nanfang Hospital, Southern Medical University (Guangzhou, China), in accordance with the Declaration of Helsinki (Approval No. NFEC-2024-507).

Establishment of radioresistance mouse models and animal studies
To establish an in vivo radiotherapy-resistant model, MC38 cells (5×10⁵) were inoculated into the right flank of mice. When tumors reached a volume of 100 mm³, they were irradiated with 8 Gy in three doses, with a one-day interval between each irradiation. After 7 days, mice were euthanized, tumors were dissociated, and tumor cells were sorted using anti-mouse-EPCAM (BioLegend，118213, RRID:AB_1134105) and cultured. This treatment cycle was repeated four more times to obtain radiotherapy-resistant MC38 cells (IR-MC38 cells). The radiosensitivity of these cells was then evaluated using in vitro clonogenic survival assays, CCK8 experiments, and in vivo subcutaneous tumor experiments.

Tumor implantation and treatment：MC38, CT26, IR-MC38, or B16 cells (5 × 10⁵) were injected subcutaneously (unilateral or bilateral). For the tumor fragment model, MC38 tumors were excised, cut into fragments, and implanted subcutaneously into recipient mice. For the orthotopic model, 1×10⁶ MC38-luciferase or IR-MC38-luciferase cells in 25 µL of 100% high-concentration Matrigel (Corning) were implanted into the cecum following the described protocol53. The mouse liver metastasis model was generated by injecting 2×10⁵ MC38-luciferase cells into the spleen. The AOM/DSS-induced colitis-associated CRC model was developed as previously described54. When tumors reached ~100 mm³ (subcutaneous/fragment) or after bioluminescence confirmed engraftment (orthotopic/metastatic), mice were randomized to receive 15-Gy focal radiation or sham. In the FTY720 treatment experiments, FTY720 (TargetMol, 162359-55-9) was administered via gavage at 20 µg per dose daily for 7 days. For CD8+ T cell or macrophage depletion experiments, 200 µg of anti-CD8α (BioXCell, BE0061) or anti-CSF1 (BioXCell, BE0204) antibody was injected intraperitoneally, beginning one day prior to other treatments and continuing twice weekly. For the 2-Deoxy-D-glucose (2-DG), oxamate, and lactate treatment experiments, daily intraperitoneal injections were administered as follows: 2-DG (TargetMol, 154-17-6) at 10 mg/kg, oxamate (TargetMol,565-73-1) at 5 mg/kg, or sodium lactate (Sigma-Aldrich,71718-10G) at 1 g/kg. In the C646 treatment experiments, C646 (TargetMol, 328968-36-1) was administered via intraperitoneal injections at 6 mg/kg per dose daily for 8 days. For the anti-PD1 treatment experiments, 200 µg of anti-PD1 antibody (BioXCell, BE0146) was injected intraperitoneally twice weekly for a total of four doses. For the NEK8 inhibitor treatment, 25 mg/kg of CX6258 (TargetMol, 1202916-90-2) was injected intravenously daily.

Disease monitoring and endpoints：Subcutaneous tumors were measured every 2 days with calipers (volume = length × width²/2). Orthotopic cecal and liver metastasis burden was quantified by bioluminescence imaging (Bruker In-Vivo Xtreme) 10 min after i.p. luciferin (200 µL, 15 mg mL⁻¹). Imaging was performed at baseline and 7 days post-treatment, or weekly until endpoint. For the AOM/DSS model, mice were weighed twice weekly;mice were euthanized and colons were collected for tumor counting after the treatment period.

Endpoint criteria: Animals were euthanized when any of the following was met: (i) subcutaneous tumor volume ≥ 2,000 mm³ or longest diameter ≥ 1.5 cm; (ii) orthotopic/metastatic bioluminescence signal increased ≥ 10-fold over baseline or showed exponential growth despite therapy; (iii) loss of > 20 % body weight from baseline; (iv) signs of intestinal obstruction, ascites, or severe anemia (pale mucous membranes); (v) inability to access food/water, lethargy, or hunched posture persisting > 24 h. These humane endpoints were approved by the Institutional Animal Care and Use Committee and applied across all models.

Single cell RNA-seq (scRNA) analysis
To obtain a sufficient number of CD45+ leukocytes and biological replicates for single-cell RNA sequencing, we isolated CD45+ cells using flow cytometry. Cell viability was assessed by trypan blue staining and confirmed to be over 90%. Single-cell capture and library construction were performed by Novogene Co., Ltd. (Beijing, China). Sequencing was conducted using the Illumina 10x Genomics platform. Raw sequencing reads from each sample were processed using Cell Ranger to generate gene expression matrices.

These processed data were analyzed using R version 4.4.0. The analysis pipeline was implemented with the Seurat package (v5.0.0) and other complementary tools as described below.

To ensure the quality of the single-cell data and remove potential doublets, we employed the DoubletFinder package to identify and remove doublets based on gene expression profiles.

The raw gene expression matrix was cleaned by removing mitochondrial, ribosomal, and hemoglobin genes.

After data integration and batch effect removal by Harmony algorithm, Uniform Manifold Approximation and Projection (UMAP) was used for nonlinear dimensionality reduction, with the first 25 principal components (PCs) as input. Differential gene expression analysis was performed to identify marker genes for each cluster using the FindAllMarkers function, with a log-fold change threshold of 0.25 and a minimum percentage of cells expressing the gene set to 25%.

Cells were annotated based on their expression profiles and known marker genes. This manual annotation process involved comparing the expression patterns of cells to known cell type-specific markers. The annotation was refined iteratively to ensure consistency and accuracy.

Cell culture
In this study, we used three cell lines: two CRC cell lines (MC38 and CT26) , a melanoma cell line (B16) and a breast cancer cell line (4T1) , all obtained from the American Type Culture Collection (ATCC). Cells including MC38, IR-MC38, CT26 ,4T1 and B16 were maintained in DMEM medium (Gibco) supplemented with 10% fetal bovine serum (FBS) and cultured in a humidified incubator at 37°C with 5% CO₂. Mycoplasma contamination was routinely monitored and found to be absent.

Plasmid and cell transfections
The Nek8 and Ldha genes were knocked down using shRNA delivered via a pLKO.1 plasmid and their overexpression was achieved using a pCDH plasmid. The Ldha genes were knocked out using sgRNA delivered via a lentiCRISPR v2 plasmid, and Ldha mutant plasmid including Ldha S196A, and Ldha S196D was achieved using a pCDH plasmid. The shRNA and sgRNA sequences are listed in Supplemental Table 1. Stable MC38 cell lines expressing OVA and luciferase were generated by lentiviral infection. Briefly, Lentivirus was produced by co-transfecting 293T cells with the packaging vectors psPAX2 and pMD2.G using Lipofectamine 3000 (Invitrogen). The viral supernatant was collected after 48 hours, filtered through a 0.45-µm filter (Millipore), and concentrated. The expression of NEK8, LDHA, and OVA was confirmed by Western blot.

Flow cytometry
To investigate immune cell infiltration, we first isolated tumor-infiltrating lymphocytes (TILs). Tumor tissues were dissected, cut into small pieces, and digested in RPMI 1640 medium containing DNase I (100 U/mL, Sigma, D5025), collagenase VI (210 U/mL, Thermo, 17104019), and hyaluronidase (0.5 mg/mL, Sigma, H3506) for 30 minutes at 37°C. The dissociated cells were passed through a 70 µm strainer, and the supernatant was collected and centrifuged at 1000 × g for 10 minutes. The cell pellet was then resuspended and subjected to density gradient centrifugation using 40% and 70% Percoll. The interphase containing the TILs was harvested and centrifuged at 1000 × g for 5 minutes. The isolated TILs were incubated with the indicated antibodies including ACD4 (BioLegend, 100434, RRID: AB_893324), CD8a (BioLegend, 1623043, RRID: AB_2894434), Granzyme B (BioLegend, 515403, RRID: AB_2114575), Perforin (BioLegend, 154304, RRID: AB_2721463), TNF-α(BioLegend, 506339, RRID: AB_2563127), IL-2 (BioLegend, 503825, RRID: AB_10895901), IFN-γ(BioLegend, 505825, RRID: AB_1595591),CD152(BioLegend, 106316, RRID: AB_2564474), TIM-3(BioLegend, 134019, RRID: AB_2814028), PD-1(BioLegend, 109119, RRID: AB_2566640), CD45 (BioLegend, 103116, RRID: AB_312981), CD3ε (BioLegend, 100357, RRID: AB_3662378), FOXP3 (BioLegend, 118904, RRID: AB_2936574), CD25 (BioLegend, 113709, RRID: AB_3674974), TCF7 (BD Biosciences, 566692, RRID: AB_2869822), CCR7 (BioLegend, 120124, RRID: AB_2616688), Ki67 (BioLegend, 151212, RRID: AB_2814055), CD11c (BioLegend, 117343, RRID: AB_10897814), CD11b (BioLegend, 101211, RRID: AB_312794), LY6C (BioLegend, 128005, RRID: AB_10639728), LY6G (BioLegend, 127607, RRID: AB_1186099), IA/IE (BioLegend, 107641, RRID: AB_2565975), F4/80 (BioLegend, 123113, RRID: AB_893478), CD19 (BioLegend, 115549, RRID: AB_3106188), CD45.1 (BioLegend, 110731, RRID: AB_10896425), CD45.2 (BioLegend, 109837, RRID: AB_2561393)then resuspended and analyzed by flow cytometry.

To assess the clearance efficiency of CD8+ T cells, cells were isolated by grinding spleen tissues through 70 µm filters. The cells were then washed twice with PBS, stained with 1:200 dilution of fluorescence-labeled antibodies including CD4 and CD8a for 30 minutes at 4°C in the dark, and analyzed by flow cytometry.

To determine MHC class I expression, cells were stained with the respective primary antibodies followed by APC-conjugated anti-mouse MHC class I (H-2Kb) (BioLegend,116518, RRID:AB_10564404). All data were acquired using a Fortessa cytometer (BD) and analyzed with FlowJo software (Tree Star). The flow cytometry gating strategy is shown in Supplemental Fig.8.

Western blot analysis
Western blotting was performed as previously described55. Antibodies used were: NEK8 (Abcam, ab116721, RRID: AB_1090250, discontinued reagent); α-tubulin (Proteintech, 11224-1-AP, RRID: AB_2210206); LDHA (Proteintech, 19987-1-AP, RRID: AB_10646429); L-Lactyl Lysine(PTMBIO, PTM-1401RM, RRID: AB_2942013); H3K9la (PTMBIO, PTM-1419RM, RRID: AB_3076695); H3K14la (PTMBIO, PTM-1414RM, RRID: AB_3076697); H3K18la (PTMBIO, PTM-1427RM, RRID: AB_3076698); Histone H3 (PTMBIO, PTM-1001RM, RRID: AB_3676032); H4K5la (PTMBIO, PTM-1407RM, RRID: AB_3096309); H4K8la (PTMBIO, PTM-1415RM, RRID: AB_3101829); H4K12la (PTMBIO, PTM-1411RM, RRID: AB_2941896), H4K16la (PTMBIO, PTM-1417RM, RRID: AB_3101830); Histone H4 (PTMBIO, PTM-1015RM, RRID: AB_3101866); Anti-Rabbit IgG (Cell Signaling Technology, 7074) , Anti-Rabbit LDHA (Ser96) (HUABIO, Homemade) and HLA-A (Boster, M00194-4).

RT–qPCR
Total RNA was isolated using a TRIzol reagent (Invitrogen, USA). cDNA was synthesized from RNA samples using the HiScript III RT SuperMix for qPCR (+gDNA wiper; Vazyme, R323-01). Quantitative PCR (qPCR) was performed with ChamQ SYBR qPCR Master Mix (Vazyme, Q311-03) on an ABI PRISM 7500 Sequence Detection System (Applied Biosystems, USA). Relative gene expression levels were normalized to GAPDH and calculated using the 2^(-ΔΔCT) method. Primer sequences are listed in Supplemental Table1.

Multiplex immunofluorescence (CmfIHC)
Multiplexed immunofluorescence staining was performed using the Opal™ 4-color Manual IHC kit (PerkinElmer, NEL810001KT) according to the manufacturer’s instructions. Primary antibodies were applied sequentially: anti-CD8 (HUABIO, ET1606-31) and anti-NEK8 (Bioss, bs-7815R). This was followed by incubation with HRP-conjugated secondary antibodies and tyramide signal amplification (TSA). Slides were microwaved after each TSA cycle, and nuclei were stained with DAPI for 30 minutes. Sample scanning, spectral unmixing, and signal quantification were performed using an LSM 880 confocal microscope (Zeiss) and ZEN software (Zeiss). The average fluorescence intensity was calculated by dividing the total fluorescence by the area of interest.

Immunohistochemistry (IHC)
IHC staining was performed as previously described using specific antibodies55. Primary antibodies used included CD8α Rabbit mAb (cell signaling technology, 98941), CD3ε Rabbit mAb (cell signaling technology, 78588), H3K18la (PTMBIO, PTM-1406RM, RRID: AB_2909438), Anti-Rabbit LDHA (Ser96) (HUABIO, Homemade) and NEK8 mAb (Bioss, 7815R). Staining intensity was scored as follows: 0 (no staining), 1 (weak, light yellow), 2 (moderate, yellow-brown), and 3 (strong, brown). The proportion of positive tumor cells was scored as: 0 (<25%), 1 (26–50%), 2 (51–75%), and 3 (>75%). The staining index was calculated by multiplying the intensity score by the proportion score. Results were independently reviewed and scored by two observers. The density of CD3+ T cells and CD8+ T cells in tumor and stromal regions was assessed by counting the number of positive cells under a 40× objective lens.

Radiation clonogenic assay
The radiation clonogenic assay was performed as previously described18. Briefly, cells were seeded in six-well plates at densities of 4×10², 8×10², 1×10³, 5×10³, and 8×10³ cells per well and exposed to 0, 2, 4, 6, and 8 Gy of radiation, respectively. After 14 days of incubation at 37°C, cells were washed with PBS, fixed with 4% paraformaldehyde for 30 minutes, and stained with crystal violet for 20 minutes. Colonies were then manually counted. The surviving fraction (SF) was calculated and plotted as a dose-response curve, which was fitted to the multi-target single-hit model using the formula: SF = 1- (1-e^(-D/D₀))^N.

Cell counting kit-8 (CCK-8) assay
Cell proliferation in the indicated groups was assessed using the CCK-8 assay (Glpbio, GK10001) according to the manufacturer's instructions. After the cells adhered to the culture dish, they were either irradiated with 4 Gy using 6 MV X-rays from a Varian 2300C/D linear accelerator or treated with a gradient concentration of drugs. Subsequently, 10 µL of CCK-8 solution and 90 µL of DMEM medium (total 100 µL) were added to each well, and the cells were cultured for an additional 2 hours. The absorbance (OD value) of each well was measured daily for 5 consecutive days.

Immunofluorescence
Paraformaldehyde (4%) was used to fix the cells for approximately 10 min, followed by incubation with 0.1% Triton X-100 for approximately 30 min. All samples were placed in a 1% BSA solution and closed on a horizontal shaker for 30 min. The primary antibody (axoneme marker: acetylated tubulin (sigma, T7451), a basal body marker: Gamma-tubulin (Boster, BM4273)) solution and incubated overnight at 4 °C. The corresponding fluorescent dye-conjugated secondary antibody was added and incubated in the dark for 1 h, and 10 μL DAPI was added for 15 min. Finally, images were collected using fluorescence microscopy or confocal microscopy.

T-cell co-culture assay
NEK8 knockdown or overexpressing MC38-OVA tumor cells were seeded in a 96-well plate with or without 4 Gy irradiation 24 hours prior and pre-incubated for 2 hours. OT-1 CD8+ T cells were isolated from OT-1 mouse spleens using the EasySep Mouse CD8+ T Cell Isolation Kit (Stemcell, 19853A). Purified OT-1 CD8+ T cells were co-cultured with tumor cells at a 10:1 ratio for 24 hours in a complete medium containing IL-2. Four hours before collection, Brefeldin A (BioLegend, 420601) was added to inhibit cytokine secretion. T cells were then washed, resuspended in a staining buffer, and stained with anti-CD8a-PE (BioLegend, 162304) for 30 minutes on ice. After washing, intracellular staining was performed with anti-Perforin-APC (BioLegend, 154304) and anti-Granzyme B-FITC (BioLegend, 515403) as previously described. For other treatments, L-lactic acid sodium (20 mM) or oxamate (10 mM) was added to the co-culture of tumor cells and T cells.

Co-Immunoprecipitation (Co-IP) assays
Cell lysates were prepared from the indicated cells using lysis buffer (150 mM NaCl, 10 mM HEPES, pH 7.4, 1% NP-40). Lysates were then incubated with anti-NEK8 or anti-LDHA rabbit antibodies and protein G-conjugated agarose beads, or with Flag affinity agarose (Sigma–Aldrich) at 4°C overnight. The beads containing the affinity-bound proteins were washed six times with IP wash buffer (150 mM NaCl, 10 mM HEPES, pH 7.4, 0.1% NP-40) and eluted with 1 M glycine (pH 3.0). The eluates were neutralized, mixed with sample buffer, denatured, and analyzed by Western blotting.

Mass spectrometry (MS) analysis
To identify NEK8-binding proteins, MC38 and CT26 cells were transfected with Flag-tagged NEK8. Lysates were immunoprecipitated using flag beads. The beads containing affinity-bound proteins were washed six times with wash buffer (150 mM NaCl, 10 mM HEPES, pH 7.4, 0.1% NP-40) and eluted with 1 M glycine (pH 3.0). The eluates were analyzed by mass spectrometry (MS), and the data were deposited in the NGDC database (accession No. OMIX009338). Supplemental Data 3 provided peptide counts and detailed information on NEK8-binding protein identified by IP/MS, as well as a comprehensive list of enriched pathways for NEK8-interacting proteins.

Protein expression and purification
BL21 derivative competent cells (Rosetta) infected with human Bub1 baculovirus were harvested 48 hours post-infection and lysed by sonication. His6-Bub1740–1085 was purified and incubated with tobacco etch virus (TEV) protease and 1 mM ATP overnight at 4°C. The phosphorylated Bub1740–1085 was further purified using Resource S and Superdex 200 columns (GE Healthcare). Bub1740–1085 mutants were expressed and purified using the same protocol. The purified Bub1740–1085 was then incubated with 10 mM ATP in storage buffer (20 mM Tris-HCl [pH 7.7], 150 mM NaCl, 10 mM MgCl , 10 mM DTT) for 30 minutes at room temperature and concentrated to 6 mg/ml for crystallization.

In vitro NEK8 kinase assay
The in vitro kinase assay was performed as previously described37. Briefly, LDHA protein was purchased from Abcam (ab93699), and NEK8-His kinase and kinase inactive NEK8 (NEK8 Lys33Met) were expressed in BL21 (Rosetta) competent cells and purified using Ni²⁺-NTA resin (QIAGEN). Recombinant LDHA was incubated with NEK8-His in a kinase buffer (25 mM Tris-HCl [pH 7.5], 5 mM beta-glycerophosphate, 2 mM DTT, 0.1 mM Na₃VO₄, and 10 mM MgCl₂) containing 10 mM ATP in a 50 µL reaction mixture at 37°C for 20 minutes. The reaction was terminated with a sample buffer and analyzed by MS. The data were deposited in the NGDC database (accession No. OMIX009336).

In addition, another in vitro kinase assay was performed by Nanjing RuiGan Biotechnology Co., Ltd (Nanjing, China) as previously described56. Briefly, the 2 μg of NEK8 or kinase-inactive NEK8 (NEK8 Lys33Met), and 4 μg of LDHA proteins were incubated in the kinase reaction buffer (20 mM Tris-HCl, pH7.5, 20 mM MgCl , 5 mM EDTA, 1 mM DTT and 100 μM ATP) in the presence of 5 μCi [32P]-γ-ATP for 2 hours at room temperature with or without kinase inhibitor. The reactions were stopped by adding SDS sample buffer, and protein phosphorylation was visualized by autoradiography (Typhoon 9410) in 10% SDS-PAGE. In vitro phosphorylation kinetics of the NEK8 by LDHA. Two μg of NEK8 were incubated with 0, 0.1, 0.2, 0.5, 1, 2.5, and 5 μM LDHA for 5 minutes. Phosphorylation was detected by autoradiography, and band intensities were quantified using ImageJ. Km and Vmax were determined by fitting the data to the Michaelis–Menten equation in GraphPad Prism 9.

Luciferase-coupled ATP assay
A luciferase-based luminescence assay was used to measure the ATPase activity of NEK8, following the manufacturer's protocols (Beyotime, S0150M). Briefly, NEK8 protein was incubated with 10mM ATP, in the presence or absence of CX6258, at 37°C in kinase buffer (25 mM Tris-HCl [pH 7.5], 5 mM beta-glycerophosphate, 2 mM DTT, 0.1 mM Na₃VO₄, and 10 mM MgCl₂). The reaction was terminated by adding Kinase-Glo reagent (Beyotime, S0150M), and ATPase activity was assessed via luminescence measurements using a microplate reader.

Lactic dehydrogenase (LDH) activity assay
LDH activity was measured using an LDH assay kit (Abbkine KTB1110) according to the manufacturer's instructions. Briefly, 50 µL of cell lysis buffer or tissue lysis buffer was added to each well of a 96-well plate. Then, 50 µL of LDH working reagent was added to each well and incubated for 30 minutes. All standards and samples were prepared in triplicate, and the assays were performed three times.

Lactate concentration assay
Following the manufacturer's protocol, cell supernatant, cell lysis buffer, or tissue lysis buffer was processed using a CheKine™ Lactate Assay Kit (Abbkine, KTB1100). Lactate concentration was measured by absorbance at 450 nm.

Surface plasmon resonance (SPR) assay
The interaction between CX6258 and NEK8 was quantified using surface plasmon resonance (SPR) technology on a BIAcore T200 system (GE Healthcare). NEK8 proteins were covalently immobilized onto CM5 sensor chips, and the resulting binding kinetics were analyzed using the BIAcore T200 evaluation software, following the manufacturer's recommended protocols.

Cut&Tag and Cut&Tag qPCR
The Cut&Tag assay was performed using the hyperactive in situ ChIP Library Prep Kit for Illumina (pG-Tn5) (Vazyme Biotech, TD904) according to the manufacturer’s instructions. Briefly, cells were collected after experimental treatment and bound to concanavalin A beads. The samples were then incubated with an anti-H3K18la primary antibody (PTM Bio, PAP™-599-16), followed by secondary antibodies. The pA-Tn5 transposase was added, and Tn5 transposase-mediated transposition was activated. DNA was extracted and amplified to construct the library, which was purified using VAHTS DNA Clean Beads (Vazyme Biotech, N411). The library was quantified using the VAHTS Library Quantification Kit for Illumina (Vazyme Biotech) and sequenced on the Illumina NovaSeq platform with 150-bp paired-end reads. Data analysis was performed by Epibiote (Guangzhou, China).

For qPCR, immunoprecipitated DNA fragments were purified and subjected to RT-qPCR using primers specific to the promoters of Tapbp, Psmb4, and Calr. IgG was used as a negative control. Primer sequences were listed in Supplemental Table 1.

Bioinformatics analysis
Gene expression data and corresponding clinical information were retrieved from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/) and The Cancer Genome Atlas (TCGA) database (https://www.cancer.gov/ccg/research/genome-sequencing/tcga). To evaluate CD8+ T-cell-mediated antitumor immunity in TCGA-COADREAD patients, we computed a score reflecting CD8+ T-cell infiltration and immune response for each sample. This score was generated through single-sample Gene Set Enrichment Analysis (ssGSEA) on the GenePattern platform (https://cloud.genepattern.org/), utilizing previously published gene sets associated with CD8+ T-cell activity31. Differential gene expression analysis was performed between colorectal cancer (CRC) tumors exhibiting high (top 10%, n = 64) and low (bottom 10%, n = 64) CD8+ T-cell scores.

Our study analyzed two GEO cohorts (GSE133057 and GSE119409) to identify differentially expressed genes (DEGs) in IR-resistant samples compared to IR-sensitive samples. Additionally, we used the Kaplan–Meier and log-rank tests, implemented with the R package survival to evaluate the association between NEK8 expression and overall survival in the TCGA-COADREAD cohort.

To investigate the correlation between NEK8 and radiosensitivity, the radiosensitivity index (RSI) was calculated using the reported formula32: RSI = −0.0098009 × AR + 0.0128283 × JUN + 0.0254552 × STAT1 − 0.0017589 × PRKCB − 0.0038171 × RELA + 0.1070213 × ABL1 − 0.0002509 × SUMO − 0.0092431 × CDK1 + 0.0204469 × HDAC1 − 0.0441683 × IRF1. The RSI was calculated, and patients were divided into RSI-low and RSI-high groups according to the median RSI value in TCGA-COADREAD.

To investigate the correlation between NEK8 and immune infiltration in CRC, the TIMER algorithm was used to estimate immune cell proportions and generate immune scores for each patient in the TCGA-COADREAD cohort.

To determine whether NEK8 binds to LDHA, the structures of LDHA and NEK8 proteins were obtained from the UniProt database. Molecular docking of LDHA and NEK8 was performed using the HDOCK server (http://hdock.phys.hust.edu.cn/). The interactions within the LDHA-NEK8 protein complex were analyzed in detail using PDBePISA and visualized with PyMOL software.

RNA sequencing and dataset analysis
Tumor-bearing C57BL/6J mice transplanted with shNC or shNEK8 tumors were subjected to 15 Gy radiation and then anesthetized. Tumors and cells were collected, and RNA was extracted using Trizol. RNA sequencing was performed as previously described18. Gene read counts were determined using Feature Counts, and differential gene expression analysis was conducted using the limma R package to compare MC38 and IR-MC38 groups, as well as shNC+IR and shNek8+IR tumors. Volcano plots of DEGs were generated using the ggplot2 package, and the expression of the top 30 DEGs was visualized in a heatmap created with the pheatmap package.

High-throughput virtual screening (HTVS)
To identify potential NEK8 inhibitors, this study performed a computer-based virtual screening targeting the ATP-binding site of human NEK8 protein (UniProt database), focusing on key amino acids VAL10, VAL18, and LYS33. The protein was prepared using the Protein Preparation Wizard module, which added hydrogen atoms and optimized energy (OPLS2005 force field, RMSD = 0.3 Å). A receptor grid centered on residues VAL10, VAL18, and LYS33 was generated with a box size of 20 Å × 20 Å × 20 Å. The 2D structures of 50,000 compounds from the MCE 50K Diversity Library were processed using the LigPrep module in Schrödinger software for hydrogenation and energy optimization, then converted to 3D structures for virtual screening. The screening process involved three stages: (1) HTVS mode to screen the initial 50,000 compounds; (2) SP mode to screen the top 10% from HTVS; and (3) XP mode to screen the top 10% from SP, yielding the final ranking of small molecules. The top 5 molecules with the highest absolute docking scores were selected as candidates for further experimental validation (Supplemental Fig. 7A). A higher absolute docking score indicated stronger binding affinity. The 2D and 3D docking modes were visualized using PyMOL.

Quantification and statistical analysis
All results shown were representative of at least three independent experiments. Statistical analyses were performed using GraphPad Prism 9.0 and IBM SPSS Statistics 20. Comparisons between the two groups were made using two-tailed unpaired Student’s t-tests. One-way or two-way ANOVA followed by Tukey’s multiple comparisons test was used for multiple comparisons. Tumor growth curves were analyzed using repeated-measures two-way ANOVA (mixed model) with Tukey’s multiple comparisons test. Correlation coefficients were calculated using Spearman's rank correlation test. Survival curves were plotted using the Kaplan–Meier method and compared with the log-rank test. Significance levels: *p < 0.05, **p < 0.01, ***p < 0.001, ns = not significant.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Liang et al. investigated the role of NEK8 in modulating radiotherapy (RT) efficacy and CD8⁺ T cell infiltration, which is informative to the clinical combined therapy of radio-immunotherapy. The authors provide mechanistic insights showing that NEK8 increases lactate production and promotes H3K18 lactylation, which can suppress MHC-I gene transcription. This reduces immune therapy efficacy by inhibiting CD8⁺ T cell infiltration and weakening abscopal effects.\n\nThe overall experimental plan and conduct are reasonable and comprehensive. It establishes a correlation between NEK8 expression, radiation resistance, and T cell infiltration using both radiation-resistant animal models and patient tumor sequencing data. Functional validation through NEK8 overexpression and knockdown in multiple cell lines and mouse models further supports the proposed mechanisms, demonstrating NEK8's role in reducing T cell infiltration and cytotoxicity, and attenuating abscopal responses. Thus, the axis of the NEK8-MHC-I pathway is a potential therapeutic target to raise cancer sensitivity to the radio-immunotherapy.\n\nThe manuscript holds the merit of defining a novel pathway of radiation-induced immunosuppressive target by presenting compelling data in the NEK8 downstream signaling pathway, which has a potential high clinical application. The current conclusion would be further supported by using radioresistant cells or tumors.\n\n1. NEK8 was the sole molecule selected when radioresistant cells were compared with the parental MC38 cells because NEK8 was overexpressed in the radioresistant cells or inhibited in the potential cells. This is a rare case in omics analysis. The risk of such a low rate needs to be validated and discussed.\n2. In addition to untreated parental MC38 cells, data of IR-MC38 cells need to be included, which would better support the hypothesis that NEK8 emerges as a promising target to enhance tumor response and abscopal effects, since it is rare to see an abscopal effect after a single dose of irradiation. IR-recurrent tumor models with related clinical samples are to be included.\n3. In repeated in vivo transplantation, the merits or weaknesses of using tumor tissue or flow-selected cells used in this study may be discussed, since immune cells are not selected in the later approach.\n4. Some experiments lack appropriate non-IR controls. For example, in Figure 2J, NEK8 knockdown alone significantly affects cell proliferation. However, upon IR treatment, shNEK8 tumors (shNEK8+IR/ shNEK8) do not exhibit increased sensitivity compared to shNC tumors(shNC+IR/ shNC).\n\nMinor:\n1. Double-check all references for accuracy and formatting, e.g., line 32.\n2. Ensure that all abbreviations are defined upon first use. e.g., line 40.\n3. Review and revise the sentence in line 426 for clarity and grammar.\n4. Provide justification for the use of B16 melanoma cells in the study.\n5. In Figure 2G, the plotted points and trend lines appear inconsistent. Please clarify whether curve fitting was performed and how the data were processed.\n6. In line 518, specify that the MS analysis was conducted post-IP.\n7. Clarify the differences between Figures 5D and 5E, and clearly indicate the IR doses used.\n8. Assess whether LDHA phosphorylation alters its enzymatic activity—this analysis is currently missing.\n9. In line 563, reconsider using the term “restored”; verify if it accurately reflects the experimental outcome. In Figure 8G, it is unclear how the scoring was conducted, given that no data for N=54 patients are shown, which is to be described\n10. The Discussion section lacks depth. It primarily reiterates the results without offering sufficient mechanistic interpretation or contextualizing the findings within the broader field.", "reviewer_2": "In the context of colorectal cancer and its clinical treatment, and using RNA-seq, the authors observe that the expression of the gene coding for NIMA-family protein kinase NEK8 is upregulated in radiotherapy-resistant tumors (i.e. in IR-resistant MC38 cells vs the parental MC38 cells). Patient data suggests that elevated NEK8 expression is associated with increased radioresistance in colorectal cancer and knock down of NEK8 seems to enhance radiotherapy efficacy in a mice model. Therefore, NEK8 seems to be involved in tumor radioresistance and data in the manuscript suggest that its inhibition may boost radiotherapy efficiency in cancer patients. Mechanistically it is proposed that NEK8 regulates lactate production through the phosphorylation of LDHA and that this negatively affects anti-tumor activity and systemic effects (abscopal effect).\n\nI am not an expert in CRC or radiotherapy nor an immunologist and I will leave to other reviewers the comments on the clinical and immunological aspects of the manuscript.Regarding NEK8:\n1/ My major concern with the manuscript is mechanistic and conceptual. Although as the authors point out there have been some reports relating NEK8 levels with tumor progression (as, I should say, there are for many other if not the majority of protein kinases), there is ample consensus that NEK8 is a ciliary kinase, part of the INVC complex, a well defined protein complex that defines a region at the proximal zone of the cilium and is involved in signaling during left-rigt determination and tissue development. I find it quite surprising that the relation between NEK8 and the cilia is mentioned just in passing in the manuscript and that it contains no data in relation to the cilium or any sort of discussion about it.\nDo CRC cells, and specifically MC38 cells, have cilia? Is NEK8 located there? May NEK8 ciliary signaling be related to the suppression of CD8+ T-cell infiltration and antitumor immune responses? to radiation resistance? Is there any data relating cilia signaling and the control of lactate levels? Or is the role of NEK8 in radioresistant CRC cilia-independent? These questions should at least be discussed. And, minimally, immunofluorescence data describing the subcellular localization of NEK8 together with cilia markers in MC38 cells should be provided.\n2/ Regarding the possibility that LDHA might be a NEK8 substrate, I have strong doubts about the way the experiments have been done:\n- NEK8 is expressed in bacteria. Is the kinase properly folded and active? That would be quite remarkable, being a ~700-residue enzyme. Coomassie and western blots of the preps should be shown and the presence of protein kinase activity should be confirmed using a model substrate such as histone H1, α- or ß-casein and [γ-32P]-ATP (see for example Zalli et al. (2012) Hum Mol Genet 21: 1155–71 or Czarnecki et al (2015) Nat Commun 6: 6023). NEK8 autophosphorylation would also expected.\n- Importantly, kinase-inactive NEK8 (e.g. NEK8 Lys33Met) should be used as a negative control to ensure that the activity detected is not due to a contaminating (bacterial) kinase.\n- There is no consensus in the field whether isolated recombinant NEK8 is active, and ANKS6 has been shown to act as a (possibly necessary) NEK8 activator (Czarnecki et al (2015) Nat Commun 6: 6023). Bacterial NEK8 preps would not contain ANKS6, will the presence of this protein increase the activity of NEK8 expressed in bacteria?\n- Once the ability of NEK8 to phosphorylate model substrates has been confirmed, the phosphorylation LDHA by the kinase should be better characterized using [γ-32P]-ATP. Coomassie staining of the proteins (or WB) should be shown. An approximate stoichiometry of the reaction should be calculated (a bona fide substrate would be expected to be phosphorylated significantly in vitro).\n- 10 mM ATP is quite a big concentration for an in vitro kinase assay. The authors should justify why they used it and not other described concentrations in the µm range.\n- MS determination of sites should be ideally done when the substrate is being modified at a linear rate. The authors used a 20 minutes time point at this may be adequate, but this could be assessed by doing a time course of LDHA phosphorylation using [γ-32P]-ATP.\n3/ Putative NEK8 inhibitors such as CX6258 should be directly confirmed to negatively affect NEK8 protein kinase activity towards model substrates and/or LDHA. ATP consumption (Fig 7C and 7D) may suggest that that is the case, but this should be directly confirmed using a proper protein kinase assay (importantly, and as mentioned above, with kinase-inactive NEK8 as a negative control).\n\nOther comments:\n- Are NEK8 protein amounts increased in radiotherapy-resistant tumors? This should be explored.\n- In NEK8 and LDHA immunoprecipitations (Figure 5B), which percentage of the input do the IPs represent?\n- Figure 5F: western blots should be done several times and quantified. It is not clear to me that NEK8 downregulation effectively reduces LDHA Serine-196 phosphorylation.\n- Is Ser196 phosphorylation increasing LDHA activity? This could be tested in vitro using either an LDHA mutant or preincubating LDHA with NEK8 and ATP/Mg2+.\n- The promoters of the Anks6 gene, coding for one of the main described regulators of NEK8 activity, show H3K18la changes upon NEK8 downregulation. Could this indicate corregulation of the two proteins?\n- Similarly for the Nphp3 gene.\n\nMinor:\n- Gene names should be in italics. Upper case for humans, first letter capitalized followed by lowercase for mice.\n- Western blots like these shown in Figure 5B and 5F, Figure 6A and 6B, Supp Fig 2B or Supp Fig 4F etc should show molecular weights.\n- NEK8 does not regulate primary cilia structure (as stated in the discussion, line 705). Its role at the cilium is not completely understood but most probably participates in cilia signalling.", "reviewer_3": "This is an interesting study assessing the role of NEK8 in modulating the efficacy of radiotherapy (RT) in colorectal cancer (CRC), with a particular focus on CD8⁺ T cell infiltration and the abscopal effect. The authors propose that NEK8 regulates LDHA activity via phosphorylation, thereby enhancing lactate production, which in turn modulates tumor immune infiltration. The identification of CX6258 as a NEK8 inhibitor capable of enhancing anti-tumor immunity in vivo is particularly compelling. However, some aspects of the study remain unclear, leading on one hand to ambiguous interpretation of the results by the authors, and on the other hand to the proposed mechanism of action being only partially supported by the current experimental evidence.\n\nMajor Points\n• Figure 2E: The reported correlation coefficient of 0.292 is weak, not strong. The authors should revise their interpretation accordingly.\n• Figures 2I–K: Tumor growth reduction is observed even without IR upon NEK8 knockdown, suggesting that NEK8 may contribute to basal tumor growth, not only RT resistance. Can authors clarify this point.\n• Related to previous, Figures 2G–H: What is the effect of NEK8 knockdown on in vitro tumor cell proliferation in the absence of immune cells? This would clarify whether NEK8 affects tumor-intrinsic growth pathways.\n• Figure 3A–B: The experimental setups appear similar, yet plotting styles and color codes differ, making interpretation to the reader very difficult. Please harmonize or clarify the differences in design and plotting.\n• NEK8 Protein Expression: Please show endogenous NEK8 protein levels in the different models IR resistant vs. non-resistant cells, in control and after IR.\n• Figure 5C: There is a reduction in intracellular lactate upon NEK8 knockdown, but the change in extracellular lactate is modest. Can the authors comment on this discrepancy?\n• Normalization in Figure 5: Please specify how lactate levels (both intra- and extracellular) were normalized (e.g., per cell number or per protein content). This is crucial for accurate interpretation, especially if/when cell proliferation is altered (upon changes in NEK8 levels, i.e.).\n• Figure 5D–E: If the model assumes NEK8 regulates LDHA activity via phosphorylation, these assays should be normalized to LDHA protein levels, not only global protein.\n• LDHA Phosphorylation (S196): Is this based on the custom polyclonal antibody developed in this study? Please provide validation, e.g.: This point is key.\no Loss of signal upon S196 mutation\no Evidence from mass spectrometry confirming NEK8-mediated phosphorylation\n• Figure 5F: Contrary to the authors' interpretation, no clear change in LDHA phosphorylation is evident upon NEK8 knockdown. Please revise interpretation.\n• LDHA KD/OE experiments: Since LDHA manipulation alone can affect tumor growth, can authors interpret data with that in consideration, or provide (in vitro) data to evaluate this.\n• Figure 6L: The interpretation is not consistent with the results shown; NEK8 overexpression does not seem to increase H3K18 lactylation. Please revise.\n• Figure 8: H3K18 lactylation is shown in the cytoplasm, which is inconsistent with its nuclear role. This raises concerns about antibody specificity. Reassess interpretations in this and earlier figures using the same antibody. This is a key point as well\n• Figure 8G: Correlation plots appear to be based on discrete data with few data points, though 54 patients are said to be analyzed. Clarify the nature of the data and sample size. Information in this regard is missing in figure legend.\n• Histone lactylation specificity: Given concerns about antibody specificity, consider measuring histone acetylation as well. Lactate-derived acetyl-CoA can affect chromatin accessibility, offering an alternative or co-occurring mechanism.\n• General: NEK8 and CD8⁺ T cell infiltration: While lactate appears to inhibit CD8⁺ infiltration, which is inline with previous research, the link between NEK8 and lactate is modest (see comment antibody validation and Mass Spec).\n\nMinor Points\n• Figure 1B: Myeloid cell subsets appear heterogeneous? This could be interesting. Please comment on and or annotate the (sub) populations shown.\n• Line 432: Clarify the term DEG (likely “differentially expressed genes”).\n• Figure 1, RNA-seq setup: Clarify which conditions were used (resistant vs. non-resistant tumors, with or without IR?).\n• Figure legends: Ensure that all figure legends are complete, clearly describing conditions, replicates, and normalization methods and statistical methods, for a meaningful and fair interpretation of the panels.", "reviewer_4": "The article Blocking NEK8 enhances radiation-induced antitumor immunity and abscopal effect by inhibiting lactate metabolism in colorectal cancer characterizes the role of NEK8 as a radio resistance mediator in CRC. Their findings highlight the importance of CD8+ T activation for converting radiotherapeutic cytotoxicity into effective antitumor immunity. According to their proposed mechanism, NEK8 inhibits antigen presentation and CD8+ T cell function by promoting lactate production through the phosphorylation of LDHA. The authors highlight the therapeutic potential of inhibiting NEK8 to improve the outcome of radiotherapy. Although the study is novel and presents a potential therapeutic angle, the authors need to address the major and minor concerns outlined below.\n\nMAJOR COMMENTS\n• The steps they follow are often poorly argued and the logic behind them is not clear:\n- For example, why do the authors decide to specifically focus on CD8+ T cells and not T regulatory cells? In Line 408, the authors claim that the infiltration of CD8+ T cells shows the most pronounced difference. However, the decrease in Foxp3+ Treg cells is at least as significant (Fig 1D).\n- Why do the authors focus on histone lactylation? Did the authors test other possible fate of lactate as a signaling molecule or as a metabolite intermediate?\n• A more detailed profiling of CD8⁺ T cells beyond GzmB and perforin should be included in Figure 1J. Additionally, the observed increase in the naïve-like and proliferative states should be further validated.\n• The authors decide to focus on NEK8 after comparing common genes between two datasets for DEG in IR-resistant vs IR-sensitive CRC tumors and DEGs between high and low CD8+ T CRC tumors. Between the two different datasets there are only two genes in common. How did the authors choose these datasets? How can they explain the divergence between them? In addition, the correlations on which they base the relevance of NEK8 are rather weak (Fig 2E and Fig S2).\n• In cell survival curves (Fig 2G, Fig S1E) the curve fitting does not seem correct.\n• In Fig S2B the levels of NEK8 in the vector and shNC conditions should be comparable. However, the expression seems much higher in the shNC condition. Could the authors please explain why is this difference found?\n• In Fig 4A it would make sense to compare also shNEK8 vs shNEK8-IR to establish the impact of radiotherapy. The difference in the percentage of CD8+ T cells seems actually larger when no radiotherapy is applied compared to the corresponding shNC control. Wouldn’t this go against the hypothesis that NEK8 is a key driver of CD8+ T cell migration in the context of IR?\n• In Fig 4C, the authors should provide evidence for the efficacy of FTY720. The drug's effect appears to be primarily associated with radiotherapy rather than NEK8 knockdown, as it also leads to increased tumor growth in the control group. Therefore, the authors should clearly demonstrate how NEK8 knockdown specifically results in an increased CD8⁺ T cell population.\n• In Fig 4D, the expression of GZMB and perforin appears to be absent under control conditions. Can the authors explain these results? Did the authors stimulate the cells with PMA and ionomycin prior to FACS staining? Same in Figure 4D. This is surprising as the exposure to the OVA peptide should induce TCR stimulation.\n• The authors claim that: The results showed that NEK8 knockdown significantly reduced LDHA Serine-196 phosphorylation, while NEK8 overexpression significantly increased it (Fig.5F). This effect was even more pronounced under radiotherapy conditions (Fig.5F). However, in the WB shown in Fig 5F there seems to be no difference in phospho-LDHA between shNC and shNEK8 when radiotherapy is not applied. Related to this, in Line 552 authors say: These findings further confirm that LDHA is a critical downstream target of NEK8. According to the WB this would only be the case when radiotherapy is applied. Quantification of WB should be added to the figures.\n• A large part of the work is based on the use of a single shRNA against NEK8. It would be interesting to show similar effects using a different shRNA to overrule potential off-target effects.\n• In the discussion the authors mention that: During radiotherapy, pancreatic cancer cells ramp up glycolysis and secrete more lactate. However, the results in Fig. 5C seem to contradict this (in CRC cells).\n• Could the increased T cell infiltration be related to elevated MHC I expression? Is radiotherapy generally more effective in cancers with high MHC I levels? What about other cancer types beyond CRC, for example, breast cancer?\n• What is the effect of CX6258 on the immune cells residing in the tumor upon treatment?\n• Besides measuring effector markers, it would be interesting to assess if the knockdown of NEK8 in MC38 affects T cell-mediated killing.\n\nMINOR COMMENTS\n• The manuscript needs thorough proofreading. There are spelling mistakes (for instance perforin is consistently misspelled as “preforin” in the figures and in Fig. 7M “control” is misspelled as “cotrol”) and the grammar of some sentences must be improved (e.g.: Line 439: A positive correlation between NEK8 expression and the Radiosensitivity Index (RSI) 37 in the TCGA-READCOAD datasets (Fig.2E), suggesting that elevated NEK8 expression is associated with increased radioresistance in CRC).\n• The inconsistent order of MC38 and IR-MC38 in the plots and throughout the text is confusing and should be standardized. MC38 should be presented consistently as the control group.\n• No rationale is provided on why the B16 model is used in Fig 2.\n• The figure legend should include OE to indicate overexpression\n• Figure captions are not informative enough in many cases.\n• In Figure 1A and others, the authors use the term proportion, but they are actually indicating percentages, not proportions.\n• Figure 3A is confusing and should be better represented\n• Figure arrangement could be improved, especially for Figures 5 and 7. Some elements overlap in these figures, which makes them less reader-friendly. Axis labels in Fig. 5J and L are hardly understandable.\n• Some words are capitalized when they should not (e.g.: Lactate).\n• In Fig 4H the number of events seems very different between the two plots.\n• In Fig 4E, the statistic is not correctly displayed. Is there a significant different between shNEK8 IR and shNEK8 IR + anti-CD8?\n• It is not possible to interpret the data of Fig. 5G as many lines are presents and overlap\n• The number of significant figures for the kd reported seems too high. The authors should review it. Line 634: 4443.454 1/Ms, and the dissociation rate constant (kd) was 0.015018875 1/s\n• Throughout the paper, flow cytometry data is plotted differently. It would be better to choose the same type of plot, unless there is a valid reason not to do it.", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Authors’ responses to reviewers\nReviewer #1 (Remarks to the Author); expert in cancer and irradiation resistance:\nLiang et al. investigated the role of NEK8 in modulating radiotherapy (RT) efficacy and CD8⁺\nT cell infiltration, which is informative to the clinical combined therapy of radio-immunotherapy.\nThe authors provide mechanistic insights showing that NEK8 increases lactate production and\npromotes H3K18 lactylation, which can suppress MHC-I gene transcription. This reduces immune\ntherapy efficacy by inhibiting CD8⁺ T cell infiltration and weakening abscopal effects.\nThe overall experimental plan and conduct are reasonable and comprehensive. It establishes a\ncorrelation between NEK8 expression, radiation resistance, and T cell infiltration using both\nradiation-resistant animal models and patient tumor sequencing data. Functional validation through\nNEK8 overexpression and knockdown in multiple cell lines and mouse models further supports the\nproposed mechanisms, demonstrating NEK8's role in reducing T cell infiltration and cytotoxicity,\nand attenuating abscopal responses. Thus, the axis of the NEK8-MHC-I pathway is a potential\ntherapeutic target to raise cancer sensitivity to the radio-immunotherapy.\nThe manuscript holds the merit of defining a novel pathway of radiation-induced\nimmunosuppressive target by presenting compelling data in the NEK8 downstream signaling\npathway, which has a potential high clinical application. The current conclusion would be further\nsupported by using radioresistant cells or tumors.\n1. NEK8 was the sole molecule selected when radioresistant cells were compared with the parental\nMC38 cells because NEK8 was overexpressed in the radioresistant cells or inhibited in the potential\ncells. This is a rare case in omics analysis. The risk of such a low rate needs to be validated and\ndiscussed.\nResponse: Thanks for your suggestion. We identified NEK8 through two independent,\ncomplementary screens. First, RNA sequencing of IR-resistant versus parental MC38 cells revealed\na set of differentially expressed genes, among which NEK8 was significantly up-regulated. To\ncorroborate this finding, we performed a second screen in which CD8⁺ T cell-associated genes from\nTCGA-COAD/READ were intersected with the upregulated differentially expressed genes (log₂FC >\n0, P < 0.05) between IR-resistant and IR-sensitive tumours in GSE133057 and GSE119409. This\nstringent intersection uniquely highlighted NEK8 as the only gene convergently identified by both\napproaches, prompting us to prioritise it for subsequent investigation.\nTo clarify the issue raised, we revised the second screening strategy. CD8⁺ T cell–associated\ngenes from the TCGA-COAD/READ cohort were intersected with differentially expressed genes\n(P < 0.05) between IR-resistant and IR-sensitive samples in GSE133057 and GSE119409. This\nrefined analysis now identifies NEK8 and CELSR3, as illustrated in the updated Fig. 2D. CELSR3\nwas down-regulated in IR-resistant samples. And NEK8 was the sole gene convergently identified\nby both screens and up-regulated in IR-resistant samples, so we focused our study on NEK8.\n2. In addition to untreated parental MC38 cells, data of IR-MC38 cells need to be included, which\nwould better support the hypothesis that NEK8 emerges as a promising target to enhance tumor\nresponse and abscopal effects, since it is rare to see an abscopal effect after a single dose of\nirradiation. IR-recurrent tumor models with related clinical samples are to be included.\nResponse: Thanks for your suggestion. we generated NEK8-knockdown IR-MC38 cells and\nconfirmed stable silencing by Western blotting (Supplemental Fig. 2C). The radiosensitizing effect\nof NEK8 depletion was then validated in vitro by clonogenic survival assays (Supplemental Fig.\n2D–E) and in vivo using subcutaneous xenograft models (Fig. 2D). To examine abscopal effects,\nwe employed bilateral subcutaneous (Supplemental Fig. 3C–D) and orthotopic-plus-subcutaneous\ntumor models (Supplemental Fig. 3E-I) established with IR-MC38 and IR-MC38-shNek8 cells;\nNEK8 knockdown markedly augmented the abscopal response elicited by localized irradiation.\nFlow-cytometric analyses further demonstrated that NEK8 deficiency increased both the abundance\nand effector function of CD8⁺ T cells within irradiated tumors and at distant, non-irradiated sites\n(Supplementary Fig. 4C, E; Fig. 4H–I).\nWe detected the expression level of NEK8 in colonoscopic biopsy tissues from patients\nundergoing neoadjuvant chemoradiotherapy before treatment and found that NEK8 was\nsignificantly overexpressed in patients with radiotherapy resistance (Fig. 8E).Owing to the current\ntreatment standard: surgical resection following neoadjuvant chemoradiotherapy, clinical specimens\nfrom locally recurrent, radioresistant colorectal cancers remain scarce, limiting our ability to procure\nhuman samples for direct validation.\n3. In repeated in vivo transplantation, the merits or weaknesses of using tumor tissue or flow-\nselected cells used in this study may be discussed, since immune cells are not selected in the later\napproach.\nResponse: We thank the reviewer for the advice. Serial in-vivo passaging of intact tumor fragments\nmarkedly accelerates model establishment and allows the consideration of other factors such as the\nmicroenvironment; however, it precludes dissection of whether radioresistance arises from intrinsic\ntumor-cell properties or from extrinsic microenvironmental cues. Conversely, derivation of tumor\ncells by fluorescence-activated cell sorting demands additional time, yet yields a genetically stable,\nintrinsically radioresistant population. Moreover, each sorted generation can be cryopreserved,\nensuring reproducibility and long-term availability of the model.\n4. Some experiments lack appropriate non-IR controls. For example, in Figure 2J, NEK8\nknockdown alone significantly affects cell proliferation. However, upon IR treatment, shNEK8\ntumors (shNEK8+IR/ shNEK8) do not exhibit increased sensitivity compared to shNC\ntumors(shNC+IR/ shNC).\nResponse: Thanks very much for your suggestion. We re-conducted the experiments and\nsupplemented with appropriate non-IR control groups in Fig.2H and Fig.3A. In Fig.2I and in Fig.\n2J,MC38 and CT26 cells are intrinsically radiosensitive, so both shNek8 tumors\n(shNek8+IR/shNek8) and shNC tumors (shNC+IR/shNC) already respond markedly to radiotherapy.\nNevertheless, NEK8 depletion in these radiosensitive lines (MC38 and CT26) yields even more\npronounced therapeutic benefit, indicating that NEK8 can serve as a potential target for enhancing\nthe efficacy of radiotherapy. Furthermore, in radiotherapy-resistant IR-MC38 tumors, shNek8\ntumors (shNek8+IR/shNek8) now display substantially heightened IR sensitivity compared with\nshNC controls (shNC+IR/shNC), with no significant difference in shNC+IR vs shNC (Fig.2K).\nMinor:\n1. Double-check all references for accuracy and formatting, e.g., line 32.\nResponse: According to your suggestion, we have corrected it.\n2. Ensure that all abbreviations are defined upon first use. e.g., line 40.\nResponse: Thanks for your suggestion. We have corrected it.\n3. Review and revise the sentence in line 426 for clarity and grammar.\nResponse: Thanks for your suggestion. The manuscript has been improved by professional\nlanguage polishing agencies and native English experts.\n4. Provide justification for the use of B16 melanoma cells in the study.\nResponse: Thanks for your suggestion. we sought to determine whether NEK8 exerts a comparable\nfunction beyond colorectal cancer and whether CX6258 retains its efficacy in other tumor contexts.\nTo this end, we incorporated experiments using murine melanoma B16 cells. The following\nstatements have been appended:\nLines 487–488: “To establish the generalizability of NEK8’s role, we extended our\ninvestigation to melanoma B16 cells and observed concordant results (Supplemental Fig. 2G).”\nLines 708–709: “To assess whether CX6258 displays similar activity in an alternative tumor\nmodel, we employed melanoma B16 cells and confirmed consistent efficacy (Supplemental\nFig.7H).”\n5. In Figure 2G, the plotted points and trend lines appear inconsistent. Please clarify whether curve\nfitting was performed and how the data were processed.\nResponse: Thanks for your valuable advice. In Figure 2G, surviving fraction (SF) curves were fitted\nby the multi-target single-hit model with the following formula “SF = 1 − (1 − e−D/D0) N”. Colonies\nconsisting of more than 50 cells were photographed and counted. The surviving fraction was\ncalculated using the following formula: Mean number of colonies formed / (Number of cells seeded\n× Plating efficiency), in which plating efficiency was defined as Mean number of colonies formed /\n(Number of cells seeded for unirradiated control) from 3 independent experiments.\n6. In line 518, specify that the MS analysis was conducted post-IP.\nResponse: Thanks for your careful work. The revisions have been implemented accordingly.\n7. Clarify the differences between Figures 5D and 5E, and clearly indicate the IR doses used.\nResponse: Thanks for your great suggestion. Figure 5D shows the detection of LDH activity 24\nhours after irradiation with 4 Gy in NEK8 stably knocked-down cells, while Figure 5E shows the\ndetection of LDH activity in subcutaneous tumor tissues with NEK8 knockdown. We have clearly\nindicated the IR doses used.\n8. Assess whether LDHA phosphorylation alters its enzymatic activity—this analysis is currently\nmissing.\nResponse: Thanks for your great suggestion. A previous study reported that ULK1 can interact with\nLDHA and phosphorylate LDHA Ser196 under nutrient scarcity, enhancing LDHA activity and\nlactate production [1]. This supports our conclusion that LDHA-S196 is a critical site for regulating\nLDHA activity and lactate production. In addition. We developed LDHA-KO MC38 cell and\nfollowed by expression of either LDHAWT, LDHAS196A, or LDHAS196D (Supplemental Fig.5H) and\ndetected the LDH activity in each cell. The results are shown in the figure below.\n1. Jia M, Yue X, Sun W, et al. ULK1-mediated metabolic reprogramming regulates Vps34 lipid\nkinase activity by its lactylation. Sci Adv 2023; 9(22):eadg4993.\n9. In line 563, reconsider using the term “restored”; verify if it accurately reflects the experimental\noutcome. In Figure 8G, it is unclear how the scoring was conducted, given that no data for N=54\npatients are shown, which is to be described\nResponse: Thanks for your suggestion. We have corrected “restored” to “rescued”. For Figure 8G,\nNEK8, P-LDHA-S196, and H3K18la immunostaining was scored as follows. Intensity: 0 (absent),\n1 (weak, pale yellow), 2 (moderate, yellow–brown), 3 (strong, brown). Percentage of positive tumor\ncells: 0 (<25 %), 1 (26–50 %), 2 (51–75 %), 3 (>75 %). The staining index was the product of the\nintensity and percentage scores. Correlation analyses were performed on these indices. Because\nsome patients had identical scores, the corresponding points in the scatter plot overlap, producing\ndarker dots and causing the displayed symbols to number fewer than the 54 patients analyzed.\n10. The Discussion section lacks depth. It primarily reiterates the results without offering sufficient\nmechanistic interpretation or contextualizing the findings within the broader field.\nResponse: Thanks very much for your great suggestion. We have made extensive revisions to the\nmanuscript according to your above comments in the Discussion section.\nReviewer #2 (Remarks to the Author); expert in NEK proteins:\nIn the context of colorectal cancer and its clinical treatment, and using RNA-seq, the authors observe\nthat the expression of the gene coding for NIMA-family protein kinase NEK8 is upregulated in\nradiotherapy-resistant tumors (i.e. in IR-resistant MC38 cells vs the parental MC38 cells). Patient\ndata suggests that elevated NEK8 expression is associated with increased radioresistance in\ncolorectal cancer and knock down of NEK8 seems to enhance radiotherapy efficacy in a mice model.\nTherefore, NEK8 seems to be involved in tumor radioresistance and data in the manuscript suggest\nthat its inhibition may boost radiotherapy efficiency in cancer patients. Mechanistically it is\nproposed that NEK8 regulates lactate production through the phosphorylation of LDHA and that\nthis negatively affects anti-tumor activity and systemic effects (abscopal effect).\nI am not an expert in CRC or radiotherapy nor an immunologist and I will leave to other reviewers\nthe comments on the clinical and immunological aspects of the manuscript.Regarding NEK8:\n1/ My major concern with the manuscript is mechanistic and conceptual. Although as the authors\npoint out there have been some reports relating NEK8 levels with tumor progression (as, I should\nsay, there are for many other if not the majority of protein kinases), there is ample consensus that\nNEK8 is a ciliary kinase, part of the INVC complex, a well defined protein complex that defines a\nregion at the proximal zone of the cilium and is involved in signaling during left-rigt determination\nand tissue development. I find it quite surprising that the relation between NEK8 and the cilia is\nmentioned just in passing in the manuscript and that it contains no data in relation to the cilium or\nany sort of discussion about it.\nDo CRC cells, and specifically MC38 cells, have cilia? Is NEK8 located there? May NEK8 ciliary\nsignaling be related to the suppression of CD8+ T-cell infiltration and antitumor immune responses?\nto radiation resistance? Is there any data relating cilia signaling and the control of lactate levels? Or\nis the role of NEK8 in radioresistant CRC cilia-independent? These questions should at least be\ndiscussed. And, minimally, immunofluorescence data describing the subcellular localization of\nNEK8 together with cilia markers in MC38 cells should be provided.\nResponse: Thanks for your great suggestion. We have incorporated background information\nregarding NEK8 being a ciliary kinase, a component of the INVC complex, which is a well-defined\nprotein complex that delineates a region at the proximal zone of the cilium and is implicated in\nsignaling during left-right determination and tissue development. And the results of NEK8 co-\nlocalization with cilia were discussed in the discussion section in lines 760-766.\nMoreover, cilia are also present in colorectal cancer cells, where NEK8 can colocalize with\nthem, as shown in the figure below. We discovered that NEK8 can colocalize with cilia, but a\nsignificant amount of NEK8 remains uncolocalized in the cytoplasm, suggesting that NEK8 may\nfunction through other pathways in addition to its role via the cilia signaling. In our study, NEK8\nwas found to directly bind with LDHA, thereby influencing lactate metabolism and\nradiosensitivity. Since LDHA is expressed in the cytoplasm rather than in the cilia within the cells,\nthe above results indicate that the role of NEK8 in radioresistant CRC is independent of cilia.\n2/ Regarding the possibility that LDHA might be a NEK8 substrate, I have strong doubts about the\nway the experiments have been done:\n- NEK8 is expressed in bacteria. Is the kinase properly folded and active? That would be quite\nremarkable, being a ~700-residue enzyme. Coomassie and western blots of the preps should be\nshown and the presence of protein kinase activity should be confirmed using a model substrate such\nas histone H1, α- or ß-casein and [γ-32P]-ATP (see for example Zalli et al. (2012) Hum Mol Genet\n21: 1155–71 or Czarnecki et al (2015) Nat Commun 6: 6023). NEK8 autophosphorylation would\nalso expected.\n- Importantly, kinase-inactive NEK8 (e.g. NEK8 Lys33Met) should be used as a negative control to\nensure that the activity detected is not due to a contaminating (bacterial) kinase.\n- There is no consensus in the field whether isolated recombinant NEK8 is active, and ANKS6 has\nbeen shown to act as a (possibly necessary) NEK8 activator (Czarnecki et al (2015) Nat Commun\n6: 6023). Bacterial NEK8 preps would not contain ANKS6, will the presence of this protein increase\nthe activity of NEK8 expressed in bacteria?\n- Once the ability of NEK8 to phosphorylate model substrates has been confirmed, the\nphosphorylation LDHA by the kinase should be better characterized using [γ-32P]-ATP. Coomassie\nstaining of the proteins (or WB) should be shown. An approximate stoichiometry of the reaction\nshould be calculated (a bona fide substrate would be expected to be phosphorylated significantly in\nvitro).\n- 10 mM ATP is quite a big concentration for an in vitro kinase assay. The authors should justify\nwhy they used it and not other described concentrations in the µm range.\n- MS determination of sites should be ideally done when the substrate is being modified at a linear\nrate. The authors used a 20 minutes time point at this may be adequate, but this could be assessed\nby doing a time course of LDHA phosphorylation using [γ-32P]-ATP.\nResponse: Thank you for the valuable suggestions or inquiries. To verify that the NEK8 protein\npurified from bacteria is correctly folded and active, the kinase-inactive NEK8 (NEK8 Lys33Met)\nprotein was also purified as a control for in vitro kinase assays. As shown in Figure A below, the\nNEK8 purified from bacteria possesses kinase activity and is capable of autophosphorylation.\nMoreover, in the absence of ANKS6, NEK8 remains significantly viable, suggesting that ANKS6,\nwhich has been shown to act as a NEK8 activator, may not be essential. In addition, we conducted\nkinase reactions using the known NEK8 kinase substrate ß-casein, and the results are shown in\nFigure B below, further confirming that NEK8 purified from bacteria possesses kinase activity.\nAfter confirming NEK8's ability to phosphorylate the model substrate, we used [γ-32P]-ATP\nto better characterize the kinase's phosphorylation of LDHA. As shown in Figure C below, the\nresults further confirmed that LDHA is a kinase substrate of NEK8 (Supplemental Fig.5D).\nThe reason we used 10 mM ATP in the kinase reaction, rather than other described\nconcentrations in the µM range, was primarily to ensure that the kinase reaction was supplied with\nan ample amount of ATP, guaranteeing a more thorough kinase reaction. This approach ensures the\naccuracy of the mass spectrometry analysis results of the kinase reaction products.\nWe evaluated the time course of LDHA phosphorylation using [γ-32P]-ATP and determined\nthat the 20-minute time point was appropriate for MS-based identification of phosphorylation sites,\nas shown in Figure D below (Supplemental Fig.5E).\n3/ Putative NEK8 inhibitors such as CX6258 should be directly confirmed to negatively affect\nNEK8 protein kinase activity towards model substrates and/or LDHA. ATP consumption (Fig 7C\nand 7D) may suggest that that is the case, but this should be directly confirmed using a proper\nprotein kinase assay (importantly, and as mentioned above, with kinase-inactive NEK8 as a negative\ncontrol).\nResponse: Thank you for the valuable suggestions or inquiries. To precisely characterize the NEK8\ninhibitor CX6258, we employed [γ-32P]-ATP and directly demonstrated that it markedly suppressed\nNEK8’s kinase activity against model substrates as shown in the figure below (Fig.7E).\nOther comments:\n- Are NEK8 protein amounts increased in radiotherapy-resistant tumors? This should be explored.\nResponse: We thank you for the advice. Western blotting revealed markedly elevated NEK8 protein\nlevels in radiotherapy-resistant tumors (Supplemental Fig.2D).\n- In NEK8 and LDHA immunoprecipitations (Figure 5B), which percentage of the input do the IPs\nrepresent?\nResponse: We thank you for this question. Three independent co-immunoprecipitation experiments\nwere quantified by grayscale value quantitative analysis. Under our assay conditions, 55.0 ± 12.7 %\nof input LDHA co-precipitated with NEK8, whereas 60.2 ± 3.3 % of input NEK8 was recovered\nwith LDHA, confirming a robust and reciprocal interaction.\n- Figure 5F: western blots should be done several times and quantified. It is not clear to me that\nNEK8 downregulation effectively reduces LDHA Serine-196 phosphorylation.\nResponse: Your suggestions are very important to the manuscript. All western blot experiments\nwere performed multiple times and subjected to quantitative analysis. For Fig.5F, the experiment\nhas been repeated and the panel has been replaced with new data, which clearly demonstrates that\nNEK8 downregulation effectively reduces LDHA Serine-196 phosphorylation.\n- Is Ser196 phosphorylation increasing LDHA activity? This could be tested in vitro using either an\nLDHA mutant or preincubating LDHA with NEK8 and ATP/Mg2+.\nResponse: Thanks for your great suggestion. A previous study reported that ULK1 can interact with\nLDHA and phosphorylate LDHA Ser196 under nutrient scarcity, enhancing LDHA activity and\nlactate production[1]. This supports our conclusion that LDHA-S196 is a critical site for regulating\nLDHA activity and lactate production. In addition. We developed LDHA-KO MC38 cell and\nfollowed by expression of either LDHAWT, LDHAS196A, or LDHAS196D (Supplemental Fig.5H) and\ndetected the LDH activity in each cell. The results are shown in the figure below.\n1. Jia M, Yue X, Sun W, et al. ULK1-mediated metabolic reprogramming regulates Vps34 lipid\nkinase activity by its lactylation. Sci Adv 2023; 9(22):eadg4993.\n- The promoters of the Anks6 gene, coding for one of the main described regulators of NEK8 activity,\nshow H3K18la changes upon NEK8 downregulation. Could this indicate corregulation of the two\nproteins?\n- Similarly for the Nphp3 gene.\nResponse: Thanks for your questions. Down-regulation of NEK8 elicits prominent H3K18la\nchanges at the Anks6 and Nphp3 promoters, indicating that NEK8 may govern ANKS6 and NPHP3\ntranscription via modulation of H3K18 lactylation, thereby establishing a negative-feedback loop.\nMinor:\n- Gene names should be in italics. Upper case for humans, first letter capitalized followed by\nlowercase for mice.\nResponse: Sorry for the errors. We have corrected them as suggested.\n- Western blots like these shown in Figure 5B and 5F, Figure 6A and 6B, Supp Fig 2B or Supp Fig\n4F etc should show molecular weights.\nResponse: Thanks for your careful review. We have already shown the molecular weights in all\nwestern blots.\n- NEK8 does not regulate primary cilia structure (as stated in the discussion, line 705). Its role at\nthe cilium is not completely understood but most probably participates in cilia signalling.\nResponse: Thanks for your careful review. we have corrected the text as suggested in line 763-768\nin the section of the discussion.\nReviewer #3 (Remarks to the Author); expert in colorectal cancer, metabolism and epigenetics:\nThis is an interesting study assessing the role of NEK8 in modulating the efficacy of radiotherapy\n(RT) in colorectal cancer (CRC), with a particular focus on CD8⁺ T cell infiltration and the abscopal\neffect. The authors propose that NEK8 regulates LDHA activity via phosphorylation, thereby\nenhancing lactate production, which in turn modulates tumor immune infiltration. The identification\nof CX6258 as a NEK8 inhibitor capable of enhancing anti-tumor immunity in vivo is particularly\ncompelling. However, some aspects of the study remain unclear, leading on one hand to ambiguous\ninterpretation of the results by the authors, and on the other hand to the proposed mechanism of\naction being only partially supported by the current experimental evidence.\nMajor Points\n• Figure 2E: The reported correlation coefficient of 0.292 is weak, not strong. The authors\nshould revise their interpretation accordingly.\nResponse: Thanks for your suggestion. We re-analyzed the data, calculated the radiosensitivity\nindex (RSI), and divided patients into RSI-low and RSI-high groups based on the median RSI value\nin TCGA-COADREAD, then analyzed the expression level of NEK8 in the RSI-low and RSI-high\ngroups in new Fig.2E. And we have revised our interpretation accordingly.\n• Figures 2I–K: Tumor growth reduction is observed even without IR upon NEK8\nknockdown, suggesting that NEK8 may contribute to basal tumor growth, not only RT resistance.\nCan authors clarify this point.\nResponse: We thank you for this question. Both our in vivo animal experiments and in vitro CCK8\nassays indicated that the knockdown of NEK8 alone can significantly inhibit tumor growth,\nsuggesting that NEK8 itself can influence the growth of tumor cells. Previous studies have shown\nthat NEK8-mediated colorectal cancer cell proliferation depends on the phosphorylation of c-MYC\nat the serine 405 sites[1]. In addition, NEK8 is involved in regulating the ATR-mediated replication\nstress response and S-phase CDK activity[2]. Therefore, we speculate that NEK8 may influence the\ngrowth of colorectal cancer cells by affecting cyclin or c-myc protein.\n1. Cao B, Zhang K, Pan C, et al. NEK8 regulates colorectal cancer progression via phosphorylating\nMYC. Cell Commun Signal 2023; 21(1):209.\n2. Choi HJ, Lin JR, Vannier JB, et al. NEK8 links the ATR-regulated replication stress response and\nS phase CDK activity to renal ciliopathies. Mol Cell 2013; 51(4):423-439.\n• Related to previous, Figures 2G–H: What is the effect of NEK8 knockdown on in vitro tumor cell\nproliferation in the absence of immune cells? This would clarify whether NEK8 affects tumor-\nintrinsic growth pathways.\nResponse: We thank you for this question. NEK8 knockdown inhibits the proliferation of tumor\ncells in vitro in the absence of immune cells, which may affect the growth of colorectal cancer cells\nby influencing cyclin or c-myc proteins.\n• Figure 3A–B: The experimental setups appear similar, yet plotting styles and color codes differ,\nmaking interpretation to the reader very difficult. Please harmonize or clarify the differences in\ndesign and plotting.\nResponse: Thanks for your valuable suggestions. We have re-conducted the experiment in Figure\n3A to ensure the design and plotting are consistent with Figure 3B.\n• NEK8 Protein Expression: Please show endogenous NEK8 protein levels in the different models\nIR resistant vs. non-resistant cells, in control and after IR.\nResponse: We thank you for the advice. Western blotting revealed that the expression level of\nNEK8 was higher in the radiotherapy-resistant IR-MC38 compared to the relatively radiotherapy-\nsensitive MC38 tumor, and its elevation was more significant 24 hours after 4Gy radiotherapy.\n(Supplemental Fig.2B).\n• Figure 5C: There is a reduction in intracellular lactate upon NEK8 knockdown, but the change in\nextracellular lactate is modest. Can the authors comment on this discrepancy?\nResponse: Thanks for your questions. In the initial Figure 5C, the decline in intracellular lactate\nwas markedly greater than that observed extracellularly. This discrepancy likely arose from the\nactive export of lactate into the extracellular milieu, a process that both acidifies the\nmicroenvironment and attenuates extracellular fluctuations. Upon re-examination, the revised\nFigure 5C demonstrated that NEK8 silencing significantly lowers lactate concentrations in both the\nintracellular compartment and the conditioned medium.\n• Normalization in Figure 5: Please specify how lactate levels (both intra- and extracellular) were\nnormalized (e.g., per cell number or per protein content). This is crucial for accurate interpretation,\nespecially if/when cell proliferation is altered (upon changes in NEK8 levels, i.e.).\nResponse: We appreciate you for bringing these issues to our attention. Lactate concentrations were\ncalculated strictly according to the kit’s protocol and normalized to 1 × 10⁵ cells or the same tumor\nweight(0.01g), which we also annotated in the revised Fig. 5C and J and Supplemental Fig.5B and\nN.\n• Figure 5D–E: If the model assumes NEK8 regulates LDHA activity via phosphorylation, these\nassays should be normalized to LDHA protein levels, not only global protein.\nResponse: We appreciate you for bringing these issues to our attention. In Figure 5D–E, LDH\nactivity were calculated strictly according to the kit’s protocol and normalized to 1 × 10⁵ cells or\nthe same tumor weight (0.1ug), which we also annotated in the revised Fig. 5D and E. In other WB\nexperiments detecting the phosphorylation level of LDHA, we have adjusted to normalized LDHA\nprotein levels in revised Fig.5F and Supplemental Fig. 5H and L.\n• LDHA Phosphorylation (S196): Is this based on the custom polyclonal antibody developed in this\nstudy? Please provide validation, e.g.: This point is key.\no Loss of signal upon S196 mutation\no Evidence from mass spectrometry confirming NEK8-mediated phosphorylation\nResponse: Thanks for your valuable advice. The anti-phospho-LDHA (Ser196) antibody employed\nin this study matched the reagent specified in the literature (Science Advances 2023; 9(22):\neadg4993) [1], both of which were manufactured by HUABIO. To verify its specificity and sensitivity,\nwe generated LDHA-knockout MC38 cells and reconstituted them with either wild-type\nLDHA (LDHAWT), the non-phosphorylatable mutant (LDHAS196A), or the phospho-mimetic\nmutant (LDHAS196D). Immunoblotting with this antibody revealed corresponding changes in\nphospho-Ser196 levels (Supplemental Fig. 5H).\nTo rigorously establish NEK8 as the kinase responsible for LDHA phosphorylation, we\nperformed in vitro kinase assays employing [γ-32P]ATP. Autoradiographic analysis presented in\nSupplemental Fig. 5D-E confirmed that NEK8 directly phosphorylated LDHA, thereby identifying\nLDHA as a bona fide substrate of NEK8.\n1. Jia M, Yue X, Sun W, et al. ULK1-mediated metabolic reprogramming regulates Vps34 lipid\nkinase activity by its lactylation. Sci Adv 2023; 9(22):eadg4993.\n• Figure 5F: Contrary to the authors' interpretation, no clear change in LDHA phosphorylation is\nevident upon NEK8 knockdown. Please revise interpretation.\nResponse: Thanks for your valuable suggestions. We repeated the experiment depicted in Figure\n5F; the new data now reveal a pronounced reduction in LDHA phosphorylation upon NEK8\nknockdown, consistent with our explanation.\n• LDHA KD/OE experiments: Since LDHA manipulation alone can affect tumor growth, can\nauthors interpret data with that in consideration, or provide (in vitro) data to evaluate this.\nResponse: Thanks for your valuable suggestions. Given that LDHA itself can modulate tumor-cell\nproliferation, we wished to determine whether NEK8 regulates colorectal-cancer radiosensitivity\nspecifically via LDHA-Ser196 phosphorylation, independent of any confounding effects\nattributable to altered LDHA abundance. To this end, we ablated endogenous LDHA in NEK8-\noverexpressing MC38 cells and subsequently re-introduced wild-type LDHA (LDHAWT), or the\nnon-phosphorylatable mutant (LDHAS196A). Efficient replacement was confirmed by\nimmunoblotting (Supplemental Fig. 5L). Subcutaneous implantation of these genetically defined\nlines into mice followed by localized irradiation revealed that either LDHA knockout or expression\nof LDHAS196A fully reversed the radioresistance conferred by NEK8 overexpression (Supplemental\nFig. 5M). These data establish that NEK8-mediated phosphorylation of LDHA at Ser196 is both\nnecessary and sufficient for the observed modulation of radiosensitivity.\n• Figure 6L: The interpretation is not consistent with the results shown; NEK8 overexpression does\nnot seem to increase H3K18 lactylation. Please revise.\nResponse: Thanks for your valuable suggestions. The experiment shown in Figure 6L was repeated;\nthe refined data now demonstrate a marked NEK8-dependent enhancement of H3K18 lactylation\nupon overexpression.\n• Figure 8: H3K18 lactylation is shown in the cytoplasm, which is inconsistent with its nuclear role.\nThis raises concerns about antibody specificity. Reassess interpretations in this and earlier figures\nusing the same antibody. This is a key point as well.\nResponse: Sorry for the errors. We verified our antibodies and repurchased the H3K18la antibody\nsuitable for IHC (PTMBIO, PTM-1406RM, RRID: AB_2909438). We re-performed IHC detection\nusing the new antibody in a colorectal cancer radiotherapy cohort, and the results clearly\ndemonstrated that H3K18la is expressed within the nucleus. We also updated the representative\nimages and statistical data（Fig.8E-G）.\n• Figure 8G: Correlation plots appear to be based on discrete data with few data points, though 54\npatients are said to be analyzed. Clarify the nature of the data and sample size. Information in this\nregard is missing in figure legend.\nResponse: Thanks for your suggestion. In Figure 8G, we scored the IHC results for NEK8, P-\nLDHA-S196, and H3K18la. Staining intensity was scored as follows: 0 (no staining), 1 (weak, light\nyellow), 2 (moderate, yellow-brown), and 3 (strong, brown). The proportion of positive tumor cells\nwas scored as: 0 (<25%), 1 (26–50%), 2 (51–75%), and 3 (>75%). The staining index was calculated\nby multiplying the intensity score by the proportion score. The scoring data were subjected to\ncorrelation analysis. Due to overlapping scores from some patients, some points in the scatter plot\ncoincide (resulting in darker color for those points), which leads to fewer than 54 points being\ndisplayed in the figure.\n• Histone lactylation specificity: Given concerns about antibody specificity, consider measuring\nhistone acetylation as well. Lactate-derived acetyl-CoA can affect chromatin accessibility, offering\nan alternative or co-occurring mechanism.\nResponse: Thanks for your valuable suggestion. The H3K18la antibodies employed for both\nimmunoblotting (PTMBIO, PTM-1427RM, RRID: AB_3076698) [1-2] and immunohistochemistry\n(PTMBIO, PTM-1406RM, RRID: AB_2909438) [3-4]have been extensively validated in multiple\nindependent studies, confirming their specificity and reliability.\n[1]Jiao Qiao. et al. Histone H3K18 and Ezrin Lactylation Promote Renal Dysfunction in Sepsis-\nAssociated Acute Kidney Injury[J].Advanced Science.2024.\n[2]Yunjia Zhang. et al. Macrophage MCT4 inhibition activates reparative genes and protects from\natherosclerosis by histone H3 lysine 18 lactylation[J].Cell Reports.2024.\n[3]Li W. et al. Tumor-derived lactate promotes resistance to bevacizumab treatment by facilitating\nautophagy enhancer protein RUBCNL expression through histone H3 lysine 18 lactylation\n(H3K18la) in colorectal cancer. Autophagy. 2024 Jan;20(1):114-130.\n[4]Li F. et al. Positive feedback regulation between glycolysis and histone lactylation drives\noncogenesis in pancreatic ductal adenocarcinoma. Mol Cancer. 2024 May 6;23(1):90.\n• General: NEK8 and CD8⁺ T cell infiltration: While lactate appears to inhibit CD8⁺ infiltration,\nwhich is in line with previous research, the link between NEK8 and lactate is modest (see comment\nantibody validation and Mass Spec).\nResponse: Thanks for your great suggestion.We measured lactate levels in NEK8 stable\noverexpression and knockdown cell lines in vitro. Knockdown of NEK8 significantly reduced\nlactate levels, while overexpression of NEK8 significantly increased lactate production(Fig.5C and\nSupplemental Fig.5B). Additionally, measurements in subcutaneous tumor tissues also\ndemonstrated that NEK8 significantly promotes lactate generation (Supplemental Fig.5N). The\nabove results all indicate that NEK8 regulates lactate metabolism.\nMinor Points\n• Figure 1B: Myeloid cell subsets appear heterogeneous? This could be interesting. Please comment\non and or annotate the (sub) populations shown.\nResponse: Thanks for your valuable suggestion. We have added single-cell analysis of Myeloid\ncell subsets. scRNA-seq resolved myeloid cells into nine transcriptionally defined subsets\n(SupplementaryFig.1E):C01(CCr2+Trem1+M/MdM),C02(Gpnmb+Mph),C03(Ms4a7+Mrc1hiMp\nh),C04(Cd3e+MyeloidCells),C05(Mki67+MyeloidCells),C06(APCs),C07(Ifitm6+Mono),C08(Tnf\nrsf4+Ikzf2+MyeloidCells),C09(S100a9+M/MdM), and a residual C10 (Others). Cluster proportions\ndiverged sharply between conditions (Supplementary Fig. 1F): C02 (Gpnmb⁺ macrophages), C03\n(Ms4a7⁺ Mrc1hi macrophages), and C04 (Cd3e⁺ myeloid cells) showed the greatest shifts in IR-\nMC38 versus MC38 tumors, reflecting radiation-driven remodeling of the myeloid niche.\n• Line 432: Clarify the term DEG (likely “differentially expressed genes”).\nResponse: Thanks for your suggestion, and we have added the content as suggested.\n• Figure 1, RNA-seq setup: Clarify which conditions were used (resistant vs. non-resistant tumors,\nwith or without IR?).\nResponse: Thanks for your suggestion, and we have added the content as suggested in line453-454.\n• Figure legends: Ensure that all figure legends are complete, clearly describing conditions,\nreplicates, and normalization methods and statistical methods, for a meaningful and fair\ninterpretation of the panels.\nResponse: Thanks for your valuable suggestion. We have revised the figure captions to ensure that\nall legends are complete, clearly describing the experimental conditions, number of replicates,\nnormalization methods, and statistical methods.\nReviewer #4 (Remarks to the Author); expert in immunometabolism:\nThe article Blocking NEK8 enhances radiation-induced antitumor immunity and abscopal effect by\ninhibiting lactate metabolism in colorectal cancer characterizes the role of NEK8 as a radio\nresistance mediator in CRC. Their findings highlight the importance of CD8+ T activation for\nconverting radiotherapeutic cytotoxicity into effective antitumor immunity. According to their\nproposed mechanism, NEK8 inhibits antigen presentation and CD8+ T cell function by promoting\nlactate production through the phosphorylation of LDHA. The authors highlight the therapeutic\npotential of inhibiting NEK8 to improve the outcome of radiotherapy. Although the study is novel\nand presents a potential therapeutic angle, the authors need to address the major and minor concerns\noutlined below.\nMAJOR COMMENTS\n• The steps they follow are often poorly argued and the logic behind them is not clear:\n- For example, why do the authors decide to specifically focus on CD8+ T cells and not T regulatory\ncells? In Line 408, the authors claim that the infiltration of CD8+ T cells shows the most pronounced\ndifference. However, the decrease in Foxp3+ Treg cells is at least as significant (Fig 1D).\nResponse: Thanks for your valuable advice. Using flow cytometry, we examined the infiltration of\nFoxp3+ Treg cells and CD8+ T cells in radiotherapy-resistant IR-MC38 tumors and sensitive MC38\ntumors. The results showed that, compared to the control group, the infiltration data of Foxp3+ Treg\ncells significantly increased in the radiotherapy-resistant IR-MC38 tumors (SupplementaryFig.1I，\np = 0.004), while the number of infiltrating CD8+ T cells significantly decreased (Fig.1I, P\n<0.0001). The change in CD8+ T cells was more pronounced, thus we prioritized focusing on CD8+\nT cells for further research. Subsequent studies will also be conducted on Foxp3+ Treg cells.\n- Why do the authors focus on histone lactylation? Did the authors test other possible fate of lactate\nas a signaling molecule or as a metabolite intermediate?\nResponse: We thank you for this question. Lactylation, a recently identified post-translational\nmodification, has emerged as a focal point in contemporary oncology[1]. This process involved the\ncovalent conjugation of lactate to lysine residues on target proteins, thereby modulating their\nfunction and exerting profound effects on tumorigenesis, tumor progression, immune evasion, and\ntherapeutic resistance[2]. Beyond its role as a metabolic by-product, lactate operates as a bona fide\nsignaling molecule that, via lactylation—most notably histone H3 lysine 18 lactylation\n(H3K18la)—orchestrates gene expression through epigenetic reprogramming, thereby governing\ncritical neoplastic phenotypes [3-4].\nOur investigations have revealed that NEK8 overexpression markedly elevated intracellular\nlactate concentrations. Capitalizing on this observation, we focused on studying the novel\nmechanism of lactylation within cells, which contrasts with the classical function. We will continue\nto delve deeper into lactylation metabolism in our subsequent studies.\n1. Zhang D.et al. Metabolic regulation of gene expression by histone lactylation [J]. Nature, 2019,\n574(7779): 575-80.\n2.Li H.et al. Lactylation in cancer: Current understanding and challenges. Cancer Cell. 2024 Oct\n8.\n3.Raychaudhuri D.et al. Histone lactylation drives CD8+ T cell metabolism and function. Nat\nImmunol. 2024 Oct 7.\n4.Zhang C.et al. H3K18 Lactylation Potentiates Immune Escape of Non-Small Cell Lung Cancer.\nCancer Res. 2024 Aug 13.\n• A more detailed profiling of CD8⁺ T cells beyond GzmB and perforin should be included in Figure\n1J. Additionally, the observed increase in the naïve-like and proliferative states should be further\nvalidated.\nResponse: Thanks for your great suggestion. We utilized flow cytometry to assess the infiltration\nof three other types of CD8+ T cells besides C01 in radiation-resistant IR-MC38 and radiation-\nsensitive MC38 tumors. The results revealed that, compared to the control group, the C02 memory-\nlike cluster was significantly reduced in IR-MC38 tumors, while the C03 naive-like cluster and C04\nproliferating-like cluster were significantly increased (Supplementary Fig. 1J).\n• The authors decide to focus on NEK8 after comparing common genes between two datasets for\nDEG in IR-resistant vs IR-sensitive CRC tumors and DEGs between high and low CD8+ T CRC\ntumors. Between the two different datasets there are only two genes in common. How did the authors\nchoose these datasets? How can they explain the divergence between them? In addition, the\ncorrelations on which they base the relevance of NEK8 are rather weak (Fig 2E and Fig S2).\nResponse: Thanks for your suggestion. We identified NEK8 through two independent,\ncomplementary screens. First, RNA sequencing of IR-resistant versus parental MC38 cells revealed\na set of differentially expressed genes, among which NEK8 was significantly up-regulated. To\ncorroborate this finding, we performed a second screen in which CD8⁺ T cell-associated genes from\nTCGA-COAD/READ were intersected with the upregulated differentially expressed genes (log₂FC >\n0, P < 0.05) between IR-resistant and IR-sensitive tumours in GSE133057 and GSE119409. Both\nCEO databases (GSE133057 and GSE119409) consist of transcriptomic data sequenced from\nbiopsy samples prior to neoadjuvant radiotherapy, with clear clinical information on radiotherapy\nresistance and sensitivity. This stringent intersection uniquely highlighted NEK8 as the only gene\nconvergently identified by both approaches, prompting us to prioritise it for subsequent\ninvestigation. In the screening process of the second method, we selected multiple datasets for\nscreening to ensure the accuracy of the target gene identification.\nTo clarify the issue, we revised the second screening strategy. CD8⁺ T cell–associated genes\nfrom the TCGA-COAD/READ cohort were intersected with differentially expressed genes (P <\n0.05) between IR-resistant and IR-sensitive samples in GSE133057 and GSE119409. This refined\nanalysis now identifies NEK8 and CELSR3, as illustrated in the updated Fig. 2D. CELSR3 was\ndown-regulated in IR-resistant samples. And NEK8 was the sole gene convergently identified by\nboth screens and up-regulated in IR-resistant samples, so we focused our study on NEK8.\nWe appreciate the reviewers for noting the moderate correlation coefficient in Fig 2E and Fig\nS2. We would like to point out that in large-scale omics studies, when analyzing in conjunction with\nour wet lab results such as in vivo and in vitro experiments, weak but significant associations are\ncommon and informative.\n• In cell survival curves (Fig 2G, Fig S1E) the curve fitting does not seem correct.\nResponse: Thanks for your valuable advice. In Fig.2G and Fig.S1D, Surviving fraction(SF) curves\nwere fitted by the multi-target single-hit model with the following formula “SF = 1 − (1 − e−D/D0)\nN”. Colonies consisting of more than 50 cells were photographed and counted and the surviving\nfraction was calculated using the following formula: Mean number of colonies formed / (Number\nof cells seeded × Plating efficiency), in which plating efficiency was defined as Mean number of\ncolonies formed / (Number of cells seeded for unirradiated control) from 3 independent experiments.\n• In Fig S2B the levels of NEK8 in the vector and shNC conditions should be comparable. However,\nthe expression seems much higher in the shNC condition. Could the authors please explain why is\nthis difference found?\nResponse: Thanks for your valuable advice. We hypothesize that the cause affecting this situation\nmay be due to improper experimental procedures. To verify our conjecture, we determined the\nexpression level of Nek8 in wild type MC38, vector and shNC by western blot. As shown in the\nfollowing figure, the expression levels of three are the same. In addition, we redesigned and\nconducted three repeated experiments to verify the successful construction of the cell line\n(Supplemental Fig. 2C)\n• In Fig 4A it would make sense to compare also shNEK8 vs shNEK8-IR to establish the impact of\nradiotherapy. The difference in the percentage of CD8+ T cells seems actually larger when no\nradiotherapy is applied compared to the corresponding shNC control. Wouldn’t this go against the\nhypothesis that NEK8 is a key driver of CD8+ T cell migration in the context of IR?\nResponse: Thanks for your great suggestion. The issue you raised might be due to the\nradiosensitivity of MC38 cells themselves. For this reason, we repeated the same experiment using\nradiotherapy-resistant IR-MC38 cells. The infiltration of CD8+ T cells was relatively reduced in the\nshNC+IR group compared to the shNC group, whereas it was significantly increased in the\nshNEK8+IR group compared to the shNEK8 group (Supplemental Fig. 4C). We also compare\nshNEK8 vs shNEK8-IR to establish the impact of radiotherapy in new Fig.4A and Supplemental\nFig.4C. Radiotherapy can promote the infiltration of CD8+ T cells to some extent (shNC vs shNC-\nIR) in MC38 and CT26. When radiotherapy is performed after knocking down NEK8, the\ndifferential analysis of CD8+ T cell infiltration showed a smaller P value, which indicated higher\ncredibility (shNEK8 vs shNEK8-IR), with a smaller P value. These results are consistent with our\nhypothesis that NEK8 controls CD8+ T cell migration and suppressive function in the context of IR.\n• In Fig 4C, the authors should provide evidence for the efficacy of FTY720. The drug's effect\nappears to be primarily associated with radiotherapy rather than NEK8 knockdown, as it also leads\nto increased tumor growth in the control group. Therefore, the authors should clearly demonstrate\nhow NEK8 knockdown specifically results in an increased CD8⁺ T cell population.\nResponse: Thanks for your valuable advice. To validate these findings, we repeated the experiment\nand introduced two additional groups: shNC+FTY720 and shNEK8+FTY720. Subcutaneous\ntumors were dissociated and analyzed by flow cytometry to quantify CD8⁺ T-cell infiltration.\nConsistent with our previous results, administration of FTY720 significantly rescued the reduction\nin tumor volume elicited by NEK8 knockdown (Figure A below) and, notably, abrogated the\nsynergistic tumor-suppressive effect observed when NEK8 depletion was combined with ionizing\nradiation (IR). The on-target activity of FTY720 under these experimental conditions is documented\nin Figure B-C below.\n• In Fig 4D, the expression of GZMB and perforin appears to be absent under control conditions.\nCan the authors explain these results? Did the authors stimulate the cells with PMA and ionomycin\nprior to FACS staining? Same in Figure 4D. This is surprising as the exposure to the OVA peptide\nshould induce TCR stimulation.\nResponse: We thank the reviewer for this insightful observation. The apparent absence of GZMB\nand perforin in the control (shNC) tumors is most likely attributable to the extreme scarcity of\nfunctionally active CD8⁺ T cells within the poorly immunogenic tumor microenvironment\nestablished by our model. Under basal conditions, tumor-infiltrating CD8⁺ T cells are present at very\nlow frequencies, exhibit an exhausted or naïve phenotype, and remain transcriptionally quiescent\nwith respect to cytolytic effector molecules. Consequently, flow cytometry assays fall below the\nlimit of detection for GZMB and perforin. In contrast, NEK8 knockdown or combination with\nionizing radiation markedly increases CD8⁺ T-cell infiltration and reinvigorates their cytotoxic\nprogram, thereby rendering GZMB and perforin readily detectable. In the current study, intracellular\ncytokine staining of CD8⁺ T cells was performed on freshly dissociated subcutaneous tumors\nwithout ex vivo restimulation with PMA and ionomycin. This approach was chosen to preserve the\nin vivo activation state and to avoid artefacts introduced by pharmacological stimulation. In Figure\n4D, we only treated with brefeldin A for 4h, without adding PMA and ionomycin, resulting in the\nabsence of GZMB and perforin expression under control conditions.\n• The authors claim that: The results showed that NEK8 knockdown significantly reduced LDHA\nSerine-196 phosphorylation, while NEK8 overexpression significantly increased it (Fig.5F). This\neffect was even more pronounced under radiotherapy conditions (Fig.5F). However, in the WB\nshown in Fig 5F there seems to be no difference in phospho-LDHA between shNC and shNEK8\nwhen radiotherapy is not applied. Related to this, in Line 552 authors say: These findings further\nconfirm that LDHA is a critical downstream target of NEK8. According to the WB this would only\nbe the case when radiotherapy is applied. Quantification of WB should be added to the figures.\nResponse: Thanks for your valuable suggestions. We repeated the experiment depicted in Figure\n5F; the new data now reveal NEK8 knockdown significantly reduced LDHA Serine-196\nphosphorylation, while NEK8 overexpression significantly increased it. This effect was even more\npronounced under radiotherapy conditions. All WB experiments were repeated three times and\nquantified in the Source Data file.\n• A large part of the work is based on the use of a single shRNA against NEK8. It would be\ninteresting to show similar effects using a different shRNA to overrule potential off-target effects.\nResponse: Thank you for the valuable suggestions or inquiries. In the revised manuscript, we have\nnow included an additional shRNA targeting a different region of NEK8. Some of the in vitro\nexperiments were repeated including in Fig.2G-H, Fig.5C-D, Fig.5F and Fig.6A-B.\n• In the discussion the authors mention that: During radiotherapy, pancreatic cancer cells ramp up\nglycolysis and secrete more lactate. However, the results in Fig. 5C seem to contradict this (in CRC\ncells).\nResponse: Thanks for your careful review. We repeated the experiment in Fig. 5C, and the analysis\nshowed a certain degree of increase in lactate secretion in MC38 cells after radiotherapy, but there\nwas no statistical difference. This may be due to differences in the cancer types.\n• Could the increased T cell infiltration be related to elevated MHC I expression? Is radiotherapy\ngenerally more effective in cancers with high MHC I levels? What about other cancer types beyond\nCRC, for example, breast cancer?\nResponse: Thanks for your questions. Elevated MHC-I expression is strongly associated with\nincreased CD8⁺ T cell infiltration across multiple cancer types, including colorectal cancer. This is\nsupported by studies showing that:1) Inhibition of autophagy proteins (e.g. ATG7) or chloroquine\ntreatment enhances MHC-I expression and CD8⁺ T cell responses [1-2] 2) MHC-I expression\n.correlates significantly with intratumoral T cell infiltration (ITTC) and improved patient survival in\nCRC [1]. In our study, the infiltration of CD8+ T cells was significantly reduced in NEK8-high\nexpressing tumors. On one hand, the significantly increased lactate content in the\nmicroenvironment inhibited the infiltration of CD8+ T cells. On the other hand, tumor cells\nexhibited low expression of MHC class I molecules.\nMoreover, radiotherapy tends to be more effective in tumors with high MHC-I expression, as\nseen in melanoma[3], HNSCC[4], and GBM[5], where MHC-I upregulation promotes CD8⁺ T cell-\nmediated antitumor immunity. Other cancer types,inluding breast cancer[6], SCLC[7], ovarian\ncancer[8], and PDAC[9], underscoring the broad relevance of MHC-I in shaping the tumor immune\nmicroenvironment and response to therapy.\n[1] Loi M, et al. Macroautophagy Proteins Control MHC Class I Levels on Dendritic Cells and\nShape Anti-viral CD8(+) T Cell Responses[J]. Cell Rep, 2016,15(5):1076-1087.\n[2] Zhang W, et al. Inhibition of autophagy-related protein 7 enhances anti-tumor immune response\nand improves efficacy of immune checkpoint blockade in microsatellite instability colorectal\ncancer[J]. J Exp Clin Cancer Res, 2024,43(1):114.\n[3] Constanzo J, et al. MHC-I-Driven Antitumor Immunity Counterbalances Low Absorbed Doses\nof Radiopharmaceutical Therapy[J]. J Nucl Med, 2025,66(5):785-792.\n[4] Lind H T, et al. MHC class I upregulation contributes to the therapeutic response to radiotherapy\nin combination with anti-PD-L1/anti-TGF-β in squamous cell carcinomas with enhanced CD8 T\ncell memory-driven response[J]. Cancer Lett, 2025,608:217347.\n[5] Mondal I, et al. PP2Ac Deficiency Enhances Tumor Immunogenicity by Activating STING-Type\nI Interferon Signaling in Glioblastoma[J]. Cancer Res, 2023,83(15):2527-2542.\n[6] Li J, et al. Inhibition of ATM enhances the immunogenicity of triple-negative breast cancer by\npromoting MHC-I expression[J]. Cell Death Dis, 2025,16(1):624.\n[7] Cui Y, Qiu T, Wang J, et al. IFITM3 enhances immunosensitivity via MHC-I regulation and is\nassociated with the efficacy of anti-PD-1/-L1 therapy in SCLC[J]. Mol Cancer, 2025,24(1):187.\n[8] Alim L, et al. Antigen presentation potential is variable among human ovarian tumour and\nsyngeneic murine models and dictates pre-clinical outcomes of immunotherapy[J]. Biomed\nPharmacother, 2025,187:118141.\n[9] Xing X, et al. B4GALT5 inhibits CD8(+) T-cell response by downregulating MHC-I level through\nERAD pathway in PDAC[J]. J Immunother Cancer, 2025,13(5).\n• What is the effect of CX6258 on the immune cells residing in the tumor upon treatment?\nResponse: We appreciate you for bringing these issues to our attention. We treated OT1 CD8+ T\ncells with a certain concentration gradient of CX6258 for 24 hours and assessed the cytotoxic\ncapacity and exhaustion status of CD8+ T cells using flow cytometry. The results are shown in the\nfigure below. CX6258 had no effect on the cytotoxic capacity of CD8+ T cells but significantly\ninhibited their exhaustion.\n• Besides measuring effector markers, it would be interesting to assess if the knockdown of NEK8\nin MC38 affects T cell-mediated killing.\nResponse: We appreciate you for bringing these issues to our attention. Based on your suggestion,\nNEK8 knockdown MC38-OVA tumor cells were seeded in a 96-well plate with or without 4 Gy\nirradiation 24 hours prior and pre-incubated for 2 hours. Purified OT-1 CD8+ T cells were co-\ncultured with tumor cells at a 10:1 ratio for 24 hours in a complete medium containing IL-2. We\nthen observed the survival of tumor cells under a microscope, and the results are shown in the figure\nbelow. NEK8 knockout tumor cells were significantly killed by CD8+ T cells, while the majority of\nNEK8 knockout tumor cells were eradicated after 4Gy radiotherapy.\nMINOR COMMENTS\n• The manuscript needs thorough proofreading. There are spelling mistakes (for instance perforin is\nconsistently misspelled as “preforin” in the figures and in Fig. 7M “control” is misspelled as “cotrol”)\nand the grammar of some sentences must be improved (e.g.: Line 439: A positive correlation\nbetween NEK8 expression and the Radiosensitivity Index (RSI) 37 in the TCGA-READCOAD\ndatasets (Fig.2E), suggesting that elevated NEK8 expression is associated with increased\nradioresistance in CRC).\nResponse: Thanks for your careful review. We have made the corrections.\n• The inconsistent order of MC38 and IR-MC38 in the plots and throughout the text is confusing\nand should be standardized. MC38 should be presented consistently as the control group.\nResponse: Thanks for your valuable advice. We have made the corrections.\n• No rationale is provided on why the B16 model is used in Fig 2.\nResponse: Thanks for your suggestion. We have moved the figure to Supplementary Figure 2 and\nadded “To verify whether NEK8 has a similar effect in other cancer types, we used melanoma B16\ncells and obtained consistent results (Supplemental Fig.2G).” in lines 486-488.\n• The figure legend should include OE to indicate overexpression\nResponse: Thanks for your valuable advice. We have made the corrections.\n• Figure captions are not informative enough in many cases.\nResponse: Thanks for your careful review. We have made the corrections.\n• In Figure 1A and others, the authors use the term proportion, but they are actually indicating\npercentages, not proportions.\nResponse: Thanks for your careful review. We have corrected “proportion” to “percentages”.\n• Figure 3A is confusing and should be better represented\nResponse: Thanks for your valuable suggestions. We have re-conducted the experiment in Figure\n3A to ensure the design and plotting are consistent with Figure 3B.\n• Figure arrangement could be improved, especially for Figures 5 and 7. Some elements overlap in\nthese figures, which makes them less reader-friendly. Axis labels in Fig. 5J and L are hardly\nunderstandable.\nResponse: Thanks for your valuable advice. We have improved Figure arrangement in revied\nFigures.\n• Some words are capitalized when they should not (e.g.: Lactate).\nResponse: Sorry for the errors. We have corrected them as suggested.\n• In Fig 4H the number of events seems very different between the two plots.\nResponse: Thanks for your careful review. Since the shNEK8+IR group had a higher number of\nCD8+ T cells in the distant non-irradiated tumors, under the same flow cytometry detection duration,\nthe cell count in the right shNEK8+IR group was slightly higher than that in the left group.\n• In Fig 4E, the statistic is not correctly displayed. Is there a significant different between shNEK8\nIR and shNEK8 IR + anti-CD8?\nResponse: Thanks for your great suggestion. We have presented the data analysis results in the\nrevied Fig.4E, showing a significant difference between shNEK8 IR and shNEK8 IR + anti-CD8.\n• It is not possible to interpret the data of Fig. 5G as many lines are presents and overlap\nResponse: Thanks for your valuable advice. Due to the large number of experimental groups, the\ncurves of some groups appear to overlap. We have uploaded the experimental data to the Source\nData file.\n• The number of significant figures for the kd reported seems too high. The authors should review\nit. Line 634: 4443.454 1/Ms, and the dissociation rate constant (kd) was 0.015018875 1/s\nResponse: Thanks for your valuable advice. We have made the corrections.\n• Throughout the paper, flow cytometry data is plotted differently. It would be better to choose the\nsame type of plot, unless there is a valid reason not to do it.\nResponse: We agree that visual consistency is important for clarity. Throughout the manuscript,\nCD8⁺ T-cell infiltration is consistently presented as scatter (dot) plots. Functional assessments of\nthese cells are displayed as overlaid scatter plots with transparent contour lines to preserve both\nsingle-cell resolution and population density. For single-channel MHC-I measurements, we use\noverlaid histograms to emphasize fluorescence intensity distributions. While the formats differ\nslightly, each was selected to convey the relevant information most clearly and is applied uniformly\nacross all comparable datasets. We are, of course, willing to replot any figure in a single style should\nthe reviewers deem it necessary.\nReviewer #5 (Remarks to the Author); ECR:\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is\npart of the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse: Thank you very much for your insightful and constructive review of this manuscript. I\ngreatly appreciate the time and effort you dedicated to evaluating the work, and I found your\ncomments particularly helpful in shaping my own assessment.\nAuthors’ responses to reviewers\nReviewer #1 (Remarks to the Author):\nThe authors have properly addressed the major concerns raised. The finding of NEK8 being a\npotential target for cancer radioimmunotherapy is informative to the fields of combined approaches\nof radiation with checkpoint blockade which is highly clinical relevant.\nResponse: Thank you very much for your insightful and constructive review of this manuscript. I\ngreatly appreciate the time and effort you dedicated to evaluating the work, and I found your\ncomments particularly helpful in shaping my own assessment.\nReviewer #2 (Remarks to the Author):\nThe authors have addressed most of my concerns, and although I still have doubts about the validity\nof some of the manuscript conclusions regarding NEK8, the manuscript has improved substantially.\nSpecifically:\n- The authors now note that NEK8 has been previously described as a ciliary kinase and seek to\nshow in a figure that they don't include in the manuscript that, although NEK8 can be found in the\ncilium in MC38 colorectal cancer cells, most of the kinase is cytoplasmatic. They suggest that the\nrelevant function of NEK8 in the context of this study happens in the cytoplasm, where the kinase\ninteracts with LDHA. Although I think that the figure provided is not ideal to show NEK8\nlocalization (acetylated tubulin staining is suboptimal and I am not even sure that a cilium is visible\nin the provided image; a basal body marker would we needed to clarify this point), I concede that a\nsignificant amount of NEK8 may be cytoplasmatic. In any case I would suggest including the\nmentioned figure as supplementary data to allow the reader to form their own conclusions.\n- Importantly, the authors now show that NEK8 purified from bacteria is active both against a model\nsubstrate and LDHA (while the ATP-binding defective NEK8 K33M mutant is not, as expected).\nThis is now part of figure S5 and supports the hypothesis that LDHA may be a bona fide NEK8\nsubstrate in vivo. It also strengthens the validity of the phosphosite determination experiments\nshown in figures S5 F and G. Moreover, using an [γ-32P]-ATP-based assay the manuscript also\nshows that the NEK8 inhibitor CX6258 suppressed the activity of the kinase against LDHA (figure\n7E).\n- It is now shown that NEK8 protein amounts are increased in radiotherapy-resistant tumors (figure\nS2B).\nResponse: Thank you for the valuable suggestions or inquiries. Immunofluorescence was\nperformed using antibodies against the ciliary basal body marker (Gamma-tubulin) and NEK8. As\nshown in the figure below, we discovered that NEK8 partially co-localized with Gamma-tubulin at\nthe ciliary base. However, a substantial portion of NEK8 signal remains distributed in the cytoplasm\nwithout colocalization. We have included these results in the Supplemental Fig. 2C.\nRemaining concerns:\n- I would like to note that an (approximate) stoichiometry of the phosphorylation reaction in which\nNEK8 modifies LDHA has not been calculated, leaving open the possibility that protein LDHA is\nonly a marginally efficient substrate for NEK8.\nResponse: Thanks for your great suggestion. In vitro phosphorylation kinetics of LDHA by NEK8\nwere assessed. Reactions containing 2μg of NEK8 were incubated with 0, 0.1, 0.2, 0.5, 1, 2.5, and\n5 μM LDHA for 5 minutes. Phosphorylation was detected by autoradiography (Fig A, Supplemental\nFig. 5F), and band intensities were quantified using ImageJ. The data were fitted to the Michaelis–\nMenten equation using GraphPad Prism 9 to determine the kinetic parameters (Fig B, Supplemental\nFig. 5G). The analyses yielded a Km of 0.35 μM and a Vmax of 919,695 signal units per 5min,\nindicating that protein LDHA is a high-affinity substrate for NEK8.\n- I still think that (multiple) western blots in figure 5F should be quantified to unequivocally be able\nto affirm that “Nek8 knockdown significantly reduced LDHA Serine-196 phosphorylation, while\nNek8 overexpression significantly increased it. This effect was even more pronounced under\nradiotherapy conditions”.\nResponse: We appreciate your valuable advice. The experiment was repeated in three times in\nNEK8-knockdown MC38 cells, and was also performed in NEK8-knockdown IR-MC38 cells\nfollowed by quantitative analysis of the results (see figure below). These findings confirm that\n\"Nek8 knockdown significantly reduced LDHA Serine-196 phosphorylation, while Nek8\noverexpression markedly increased it. This effect was further enhanced under radiotherapy\nconditions.\".\n- The anti-NEK8 antibody used “Abcam, ab116721, RRID: AB_1090250” is not easily found with\nthe information provided; please note in the manuscript that it is a discontinued reagent,\nResponse: Thank you for pointing this our. We have added a note in the manuscript (line 213) to\nindicate that the anti-NEK8 antibody (Abcam, ab116721, RRID: AB_1090250) is a discontinued\nreagent.\nReviewer #3 (Remarks to the Author):\nThe authors have properly revised the manuscript and most of the concerns are now resolved.\nThere are a couple/few unresolved points that need attention. See attachment.\nResponse:Thank you for your constructive review. I greatly appreciate the time and effort you\ndedicated to evaluating the work, and I found your comments particularly helpful in shaping my\nown assessment. Black text corresponds to the initial response, while blue text represents the current,\nrevised response.\nRelated to previous, Figures 2G–H: What is the effect of NEK8 knockdown on in vitro tumor cell\nproliferation in the absence of immune cells? This would clarify whether NEK8 affects\ntumorintrinsic growth pathways.\nResponse: We thank you for this question. NEK8 knockdown inhibits the proliferation of tumor\ncells in vitro in the absence of immune cells, which may affect the growth of colorectal cancer cells\nby influencing cyclin or c-myc proteins.\n1) For this question and the previous one, I appreciate that you share this information but this should\nbe clearly stated in the manuscript as well, at least in the discussions section, as it indicates\nalternative mechanisms of action of NEK8 in CRC.\nResponse: Thanks for your suggestion. We have added it at lines 807-808 in the discussions section.\nFigure 5F: Contrary to the authors' interpretation, no clear change in LDHA phosphorylation is\nevident upon NEK8 knockdown. Please revise interpretation.\nResponse: Thanks for your valuable suggestions. We repeated the experiment depicted in Figure\n5F; the new data now reveal a pronounced reduction in LDHA phosphorylation upon NEK8\nknockdown, consistent with our explanation.\n2) I am afraid I am not able to fully agree with the authors, below the figure you refer\nto.Overexpression seems to increase LDHA phosphorylation, but there is no effect, or extremely\nmild on NEK8 knockdown, which is consistent with the figure panel in first submission. Adjust\nyour interpretation or provide alternative methods to assess this.\nResponse: We appreciate your good advice. The experiment was repeated three times in NEK8-\nknockdown MC38 cells and also conducted in NEK8-knockdown IR-MC38 cells, followed by\nquantitative analysis of the results (see figure below). The data confirm that \"Nek8 knockdown\nsignificantly reduced LDHA Serine-196 phosphorylation, while Nek8 overexpression markedly\nincreased it. This effect was further enhanced under radiotherapy conditions.\".\nFigure 8G: Correlation plots appear to be based on discrete data with few data points,though 54\npatients are said to be analyzed. Clarify the nature of the data and sample size.Information in this\nregard is missing in figure legend.\nResponse: Thanks for your suggestion. In Figure 8G, we scored the IHC results for NEK8,\nPLDHAS196,and H3K18la. Staining intensity was scored as follows: 0 (no staining), 1 (weak, light\nyellow),2 (moderate, yellow-brown), and 3 (strong, brown). The proportion of positive tumor cells\nwas scored as: 0 (<25%), 1 (26–50%), 2 (51–75%), and 3 (>75%). The staining index was calculated\nby multiplying the intensity score by the proportion score. The scoring data were subjected to\ncorrelation analysis. Due to overlapping scores from some patients, some points in the scatter plot\ncoincide (resulting in darker color for those points), which leads to fewer than 54 points being\ndisplayed in the figure.\n3) 3)Indicate in the figure panel and/or legend what lighter and darker blue means.\nResponse: Thanks for your suggestion. We have added “Light blue represents the score of a single\npatient, while dark blue indicates identical scores from multiple patients.” at lines 1294-1295 in the\nfigure legend.\nReviewer #4 (Remarks to the Author):\nWe have carefully reviewed the revised manuscript by Li et al. and believe that the authors have not\nadequately addressed several of our previously raised concerns. Below we summarize the main\nissues.\n1. Lack of experimental validation\nIn many cases, the authors responded to our comments by citing literature rather than providing\nexperimental evidence. For example, when asked why they focused exclusively on histone\nlactylation without investigating other possible fates of lactate, they justified their choice by stating\nthat histone lactylation is a recently discovered and therefore interesting mechanism. However, this\nargument does not explain why alternative, and potentially more relevant, biological contexts were\nexcluded. The authors should demonstrate experimentally that histone lactylation, rather than other\nlactate pathways, is the key driver of the observed phenotype. A similar issue arises with our request\nto test their findings in additional cancer models (e.g., breast cancer), which was not addressed\nexperimentally.\nResponse: Thanks for your valuable advice. Our data demonstrate that NEK8 overexpression\nrobustly increases both intra- and extracellular lactate levels. The lactate secreted from NEK8-high\ntumor cells enters the circulation, influencing distal tumors and inhibiting the abscopal effect (Fig5C,\nFig5G-I and FigS5Q). Intracellularly, NEK8 overexpression markedly elevated intracellular lactate\nconcentration and lactylation serves as a key mechanism through which elevated lactate exerts its\noncogenic effects. Pan-lactylation profiling of NEK8-stable cell lines revealed enhanced\nmodification predominantly in proteins of ~15 kDa, consistent with histone size (Fig6A and\nFigS6A), leading us to hypothesized that NEK8 modulates histone lactylation to influence\nradiotherapy response. Indeed, NEK8 depletion broadly attenuated site-specific histone lactylation\n(Fig6B and FigS6B). Among these modifications, we focused on H3K18la—a critical mark\nimplicated in tumorigenesis, immune regulation, and metabolic-epigenetic reprogramming[1,2]—and\ninvestigated its role in mediating NEK8’s effects (Fig6C-M).\nTo further establish whether NEK8 affects radiotherapy efficacy through histone lactylation,\nwe conducted additional experiments (see Figure A-B below, FigS6E-F). Pharmacologic inhibition\nof the histone acetyltransferase p300 with C646 fully reversed the NEK8-driven increase in\nH3K18la and restored MHC-I expression in NEK8-high MC38 cells, confirming a causal link\nbetween NEK8-induced histone lactylation and antigen-presentation capacity (FigS6E). Moreover,\ntreatment of MC38-Vector and MC38-NEK8 subcutaneous tumor models with C646 showed that\nC646 significantly reversed NEK8-mediated radioresistance and its combination with radiotherapy\nmarkedly suppressed tumor growth (Fig S6F).\nFor broader validation ,we established stable NEK8-knockdown cell lines in the breast cancer\nmodel 4T1. The results were consistent with those in CRC, showing analogous effects on\nlactyplation and radiotherapy responses (see Figure C-D below, FigS2D and FigS6D).\nGiven that radiotherapy efficacy is often correlated with high MHC-I expression, we examined\nMHC-I levels in MC38, irradiated-resistant IR-MC38, and 4T1 cells. Radiation-sensitive MC38\ncells exhibited the highest MHC-I expression, while IR-MC38 showed the lowest. 4T1 cells also\ndemonstrated relatively low MHC-I expression (Figure E below). Correspondingly, a subcutaneous\n4T1 tumor model in mice confirmed significant radioresistance (Figure F-G below).\n1.Raychaudhuri D.et al. Histone lactylation drives CD8+ T cell metabolism and function. Nat\nImmunol. 2024 Oct 7.\n2.Zhang C, Zhou L, Zhang M, et al. H3K18 Lactylation Potentiates Immune Escape of Non-Small\nCell Lung Cancer [J]. Cancer Res, 2024, 84 (21):3589-3601.\n2. Poor quality of key experiments\nSome of the most critical experiments were performed inadequately. For instance, the cytotoxicity\n(killing) assay, central to supporting their conclusions, was presented only as a low-resolution image\nin the rebuttal letter, without quantification or mention of biological replicates. Similarly, in\nresponse to our request to test the effect of CX6258 on tumor-infiltrating immune cells, the authors\nlimited their analysis to GZMB, perforin, and TIM-3 expression in CD8⁺ T cells. This narrow scope\nignores other important lymphocyte populations. Moreover, when we asked for validation beyond\nGZMB and perforin, we expected confirmation of additional effector markers (e.g., IFN-γ, IL-2,\nTNF-α) and exhaustion markers (e.g., PD-1, TIM-3), which was not provided.\nResponse: Thanks for your careful review. We repeated the cytotoxicity (killing) assay using\nMC38-OVA cells transfected with a luciferase reporter gene. NEK8 knockdown MC38-OVA tumor\ncells were seeded in a 96-well plate, and where indicated, received 4 Gy irradiation 24 hours prior\nto the assay. After a 2-hour pre-incubation, purified OT-1 CD8+ T cells were added at a 10:1\neffector-to-target ratio and co-cultured for 24 hours in complete medium containing IL-2. Tumor\ncell survival was first assessed microscopically, followed by measurement of luciferase activity after\nsubstrate addition. These results are shown in the figure A below.\nTo evaluate the effect of CX6258 on TIL function, we treated isolated TILs with a concentration\ngradient of CX6258 for 12 hours. The cytotoxic capacity of CD8+ T cells, CD4+T cells and NK\ncells, as well as the exhaustion status of CD8+ T cells, were assessed by flow cytometry (Figure B-\nD). CX6258 did not affect the cytotoxic capacity of CD8+ T cells (Figure B), CD4+ T cells, or NK\ncells (Figure C-D). However, it significantly reduced the exhaustion of CD8+ T cells (Figure B).\nWe further analyzed additional immune markers in two models: irradiated NEK8-deficient\nMC38 tumors and irradiated MC38 tumors treated with CX6258. Flow cytometry analysis revealed\nthat irradiated NEK8-dificient tumors exhibited increased levels of effector cytokines (IFN-γ, IL-2\nand TNF-α) and decreased levels of exhaustion markers (PD-1, TIM-3 and CTLA4) compared to\ncontrols (Figure E below, FigS4F). Similarly, the combination of irradiation and CX6258\ntreatment led to a significant increase in effector cytokines and a concomitant decrease in exhaustion\nmarkers compared to irradiation alone (Figure F below, FigS7I).\n3. Concerns about reproducibility\nSome issues were addressed with new experiments, but these now show results that differ\nsubstantially from those in the original submission, raising concerns about reproducibility. For\nexample, discrepancies are evident in protein expression patterns on western blots and in the\nglycolytic phenotype. It remains unclear whether the original biological replicates were excluded,\nand if so, why.\nResponse: We sincerely appreciate you for raising this critical point, which highlight the essential\nprinciple of reproducibility in scientific research. We fully recognize that substantial differences\nbetween original and revised datasets are a legitimate cause for concern, and we apologize for not\nproviding a clearer explanation for this discrepancy initially.\nThe primary issue stemmed from our original anti-phospho-LDHA (Ser196) antibody, which\nwe subsequently identified as exhibiting significant batch-to-batch variability and non-specific\nbinding. These shortcomings became apparent only after we instituted more rigorous validation\nprotocols, including the use of knockout and phosphosite-mutant controls. Consequently, the revised\nimmunoblots were generated using a newly sourced and thoroughly validated antibodies under\noptimized conditions, which yields a more specific and reproducible signal.\nConcerning the biological replicates, we wish to clarify that we did not selectively exclude data\nfrom the original experiments. Instead, we conducted a completely new and independent series of\nexperiments with the appropriate controls, which rendered the original, techinically compromised\ndataset invalid for direct comparison. All raw data corresponding to these new experimental\nreplicates have been made available in the 'Source Data' file for full transparency.\n4. Manuscript clarity\nTo facilitate review, the authors should highlight all changes made to the manuscript, which would\nallow reviewers to clearly identify revisions.\nResponse: Thanks for your valuable advice. In response, we have prepared a tracked-changes\nversion of the revised manuscript in which all modifications are clearly highlighted: newly added\ntext is displayed in red, and removed text is shown with strikethrough. We trust this format will\nfacilitate your review of the revisions made in response to the comments. Should you need any\nany further clarification regarding specific changes, we would be happy to provide additional details.\nConclusion\nGiven these outstanding concerns, insufficient experimental validation, inadequately performed key\nassays, unresolved questions regarding reproducibility, and lack of clarity in revisions, we believe\nthat the manuscript is not yet suitable for publication. Substantial additional work will be required\nbefore it can be reconsidered.\nReviewer #5 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part\nof the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse: Thanks for your insightful and constructive review of this manuscript.\nAuthors’ responses to reviewers\nReviewer #2 (Remarks to the Author):\nAlthough I still have problems seeing cilia and basal bodies in Supplemental Fig. 2C, and doubts\nabout the subcellular localization of NEK8 and its impact on the kinase described function, the\nauthors have addressed the rest of my concerns, further improving the manuscript.\nResponse: We thank the reviewer for your careful re-evaluation of our revised manuscript and for\nacknowledging the improvements we have made. We will further investigate the subcellular\nlocalization of NEK8 and its impact on the kinase described function in subsequent studies.\nReviewer #3 (Remarks to the Author):\nThe points I raised have been adequately addressed in this last version.\nResponse: Thank you very much for your insightful and constructive review of this manuscript.\nReviewer #4 (Remarks to the Author):\nThe authors have addressed most of the reviewers’ comments. However, it remains unclear why\ncertain information was not provided in the previous submission.\nResponse: We thank the reviewer for your positive assessment of our revisions and for\nacknowledging that we have addressed most of the comments. We sincerely apologize for certain\ninformation was not provided in the previous submission. This was an oversight on our part, and we\nappreciate the opportunity to correct it.\nReviewer #5 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part\nof the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse: We thank the co-reviewer for your thorough and constructive feedback on our\nmanuscript.\nAuthors’ responses to reviewers\nReviewer #3 (Remarks to the Author); expert in colorectal cancer, metabolism and\nepigenetics:\nThis is an interesting study assessing the role of NEK8 in modulating the efficacy of radiotherapy\n(RT) in colorectal cancer (CRC), with a particular focus on CD8⁺ T cell infiltration and the abscopal\neffect. The authors propose that NEK8 regulates LDHA activity via phosphorylation, thereby\nenhancing lactate production, which in turn modulates tumor immune infiltration. The identification\nof CX6258 as a NEK8 inhibitor capable of enhancing anti-tumor immunity in vivo is particularly\ncompelling. However, some aspects of the study remain unclear, leading on one hand to ambiguous\ninterpretation of the results by the authors, and on the other hand to the proposed mechanism of\naction being only partially supported by the current experimental evidence.\nReviewer’s comments to Author’s responses are marked in red\nMajor Points\n• Figure 2E: The reported correlation coefficient of 0.292 is weak, not strong. The authors\nshould revise their interpretation accordingly.\nResponse: Thanks for your suggestion. We re-analyzed the data, calculated the radiosensitivity\nindex (RSI), and divided patients into RSI-low and RSI-high groups based on the median RSI value\nin TCGA-COADREAD, then analyzed the expression level of NEK8 in the RSI-low and RSI-high\ngroups in new Fig.2E. And we have revised our interpretation accordingly.\nThe difference is very mild, but ok\n• Figures 2I–K: Tumor growth reduction is observed even without IR upon NEK8\nknockdown, suggesting that NEK8 may contribute to basal tumor growth, not only RT resistance.\nCan authors clarify this point.\nResponse: We thank you for this question. Both our in vivo animal experiments and in vitro CCK8\nassays indicated that the knockdown of NEK8 alone can significantly inhibit tumor growth,\nsuggesting that NEK8 itself can influence the growth of tumor cells. Previous studies have shown\nthat NEK8-mediated colorectal cancer cell proliferation depends on the phosphorylation of c-MYC\nat the serine 405 sites[1]. In addition, NEK8 is involved in regulating the ATR-mediated replication\nstress response and S-phase CDK activity[2]. Therefore, we speculate that NEK8 may influence the\ngrowth of colorectal cancer cells by affecting cyclin or c-myc protein.\n1. Cao B, Zhang K, Pan C, et al. NEK8 regulates colorectal cancer progression via phosphorylating\nMYC. Cell Commun Signal 2023; 21(1):209.\n2. Choi HJ, Lin JR, Vannier JB, et al. NEK8 links the ATR-regulated replication stress response and\nS phase CDK activity to renal ciliopathies. Mol Cell 2013; 51(4):423-439.\n• Related to previous, Figures 2G–H: What is the effect of NEK8 knockdown on in vitro\ntumor cell proliferation in the absence of immune cells? This would clarify whether NEK8 affects\ntumorintrinsic growth pathways.\nResponse: We thank you for this question. NEK8 knockdown inhibits the proliferation of tumor\ncells in vitro in the absence of immune cells, which may affect the growth of colorectal cancer cells\nby influencing cyclin or c-myc proteins.\nFor this question and the previous one, I appreciate that you share this information but this should\nbe clearly stated in the manuscript as well, at least in the discussions section, as it indicates\nalternative mechanisms of action of NEK8 in CRC.\n• Figure 3A–B: The experimental setups appear similar, yet plotting styles and color codes\ndiffer, making interpretation to the reader very difficult. Please harmonize or clarify the differences\nin design and plotting.\nResponse: Thanks for your valuable suggestions. We have re-conducted the experiment in Figure\n3A to ensure the design and plotting are consistent with Figure 3B.\nOK\n• NEK8 Protein Expression: Please show endogenous NEK8 protein levels in the different\nmodels IR resistant vs. non-resistant cells, in control and after IR.\nResponse: We thank you for the advice. Western blotting revealed that the expression level of NEK8\nwas higher in the radiotherapy-resistant IR-MC38 compared to the relatively radiotherapysensitive\nMC38 tumor, and its elevation was more significant 24 hours after 4Gy radiotherapy.\n(Supplemental Fig.2B).\nOK\n• Figure 5C: There is a reduction in intracellular lactate upon NEK8 knockdown, but the\nchange in extracellular lactate is modest. Can the authors comment on this discrepancy?\nResponse: Thanks for your questions. In the initial Figure 5C, the decline in intracellular lactate\nwas markedly greater than that observed extracellularly. This discrepancy likely arose from the\nactive export of lactate into the extracellular milieu, a process that both acidifies the\nmicroenvironment and attenuates extracellular fluctuations. Upon re-examination, the revised\nFigure 5C demonstrated that NEK8 silencing significantly lowers lactate concentrations in both the\nintracellular compartment and the conditioned medium.\nOK\n• Normalization in Figure 5: Please specify how lactate levels (both intra- and extracellular)\nwere normalized (e.g., per cell number or per protein content). This is crucial for accurate\ninterpretation, especially if/when cell proliferation is altered (upon changes in NEK8 levels, i.e.).\nResponse: We appreciate you for bringing these issues to our attention. Lactate concentrations were\ncalculated strictly according to the kit’s protocol and normalized to 1 × 10⁵ cells or the same tumor\nweight(0.01g), which we also annotated in the revised Fig. 5C and J and Supplemental Fig.5B and\nN.\nOK\n• Figure 5D–E: If the model assumes NEK8 regulates LDHA activity via phosphorylation,\nthese assays should be normalized to LDHA protein levels, not only global protein.\nResponse: We appreciate you for bringing these issues to our attention. In Figure 5D–E, LDH\nactivity were calculated strictly according to the kit’s protocol and normalized to 1 × 10⁵ cells or the\nsame tumor weight (0.1ug), which we also annotated in the revised Fig. 5D and E. In other WB\nexperiments detecting the phosphorylation level of LDHA, we have adjusted to normalized LDHA\nprotein levels in revised Fig.5F and Supplemental Fig. 5H and L.\n• LDHA Phosphorylation (S196): Is this based on the custom polyclonal antibody developed\nin this study? Please provide validation, e.g.: This point is key.\no Loss of signal upon S196 mutation o Evidence from mass spectrometry\nconfirming NEK8-mediated phosphorylation\nResponse: Thanks for your valuable advice. The anti-phospho-LDHA (Ser196) antibody employed\nin this study matched the reagent specified in the literature (Science Advances 2023; 9(22):\neadg4993) [1], both of which were manufactured by HUABIO. To verify its specificity and\nsensitivity, we generated LDHA-knockout MC38 cells and reconstituted them with either wild-type\nLDHA (LDHAWT), the non-phosphorylatable mutant (LDHAS196A), or the phospho-mimetic\nmutant (LDHAS196D). Immunoblotting with this antibody revealed corresponding changes in\nphosphoSer196 levels (Supplemental Fig. 5H).\nTo rigorously establish NEK8 as the kinase responsible for LDHA phosphorylation, we\nperformed in vitro kinase assays employing [γ-32P]ATP. Autoradiographic analysis presented in\nSupplemental Fig. 5D-E confirmed that NEK8 directly phosphorylated LDHA, thereby identifying\nLDHA as a bona fide substrate of NEK8.\n1. Jia M, Yue X, Sun W, et al. ULK1-mediated metabolic reprogramming regulates Vps34 lipid kinase\nactivity by its lactylation. Sci Adv 2023; 9(22):eadg4993.\nGood!\n• Figure 5F: Contrary to the authors' interpretation, no clear change in LDHA\nphosphorylation is evident upon NEK8 knockdown. Please revise interpretation.\nResponse: Thanks for your valuable suggestions. We repeated the experiment depicted in Figure\n5F; the new data now reveal a pronounced reduction in LDHA phosphorylation upon NEK8\nknockdown, consistent with our explanation.\nI am afraid I am not able to fully agree with the authors, below the figure you refer\nto.Overexpression seems to increase LDHA phosphorylation, but there is no effect, or extremely\nmild on NEK8 knockdown, which is consistent with the figure panel in first submission. Adjust\nyour interpretation or provide alternative methods to assess this.\n• LDHA KD/OE experiments: Since LDHA manipulation alone can affect tumor growth, can\nauthors interpret data with that in consideration, or provide (in vitro) data to evaluate this.\nResponse: Thanks for your valuable suggestions. Given that LDHA itself can modulate tumor-cell\nproliferation, we wished to determine whether NEK8 regulates colorectal-cancer radiosensitivity\nspecifically via LDHA-Ser196 phosphorylation, independent of any confounding effects attributable\nto altered LDHA abundance. To this end, we ablated endogenous LDHA in NEK8overexpressing\nMC38 cells and subsequently re-introduced wild-type LDHA (LDHAWT), or the non-\nphosphorylatable mutant (LDHAS196A). Efficient replacement was confirmed by immunoblotting\n(Supplemental Fig. 5L). Subcutaneous implantation of these genetically defined lines into mice\nfollowed by localized irradiation revealed that either LDHA knockout or expression of LDHAS196A\nfully reversed the radioresistance conferred by NEK8 overexpression (Supplemental Fig. 5M).\nThese data establish that NEK8-mediated phosphorylation of LDHA at Ser196 is both necessary\nand sufficient for the observed modulation of radiosensitivity.\nOK\n• Figure 6L: The interpretation is not consistent with the results shown; NEK8\noverexpression does not seem to increase H3K18 lactylation. Please revise.\nResponse: Thanks for your valuable suggestions. The experiment shown in Figure 6L was repeated;\nthe refined data now demonstrate a marked NEK8-dependent enhancement of H3K18 lactylation\nupon overexpression.\n• Figure 8: H3K18 lactylation is shown in the cytoplasm, which is inconsistent with its\nnuclear role. This raises concerns about antibody specificity. Reassess interpretations in this and\nearlier figures using the same antibody. This is a key point as well.\nResponse: Sorry for the errors. We verified our antibodies and repurchased the H3K18la antibody\nsuitable for IHC (PTMBIO, PTM-1406RM, RRID: AB_2909438). We re-performed IHC detection\nusing the new antibody in a colorectal cancer radiotherapy cohort, and the results clearly\ndemonstrated that H3K18la is expressed within the nucleus. We also updated the representative\nimages and statistical data（Fig.8E-G）.\nOK\n• Figure 8G: Correlation plots appear to be based on discrete data with few data points,\nthough 54 patients are said to be analyzed. Clarify the nature of the data and sample size.\nInformation in this regard is missing in figure legend.\nResponse: Thanks for your suggestion. In Figure 8G, we scored the IHC results for NEK8, PLDHA-\nS196, and H3K18la. Staining intensity was scored as follows: 0 (no staining), 1 (weak, light yellow),\n2 (moderate, yellow-brown), and 3 (strong, brown). The proportion of positive tumor cells was\nscored as: 0 (<25%), 1 (26–50%), 2 (51–75%), and 3 (>75%). The staining index was calculated by\nmultiplying the intensity score by the proportion score. The scoring data were subjected to\ncorrelation analysis. Due to overlapping scores from some patients, some points in the scatter plot\ncoincide (resulting in darker color for those points), which leads to fewer than 54 points being\ndisplayed in the figure.\nIndicate in the figure panel and/or legend what lighter and darker blue means.\n• Histone lactylation specificity: Given concerns about antibody specificity, consider\nmeasuring histone acetylation as well. Lactate-derived acetyl-CoA can affect chromatin\naccessibility, offering an alternative or co-occurring mechanism.\nResponse: Thanks for your valuable suggestion. The H3K18la antibodies employed for both\nimmunoblotting (PTMBIO, PTM-1427RM, RRID: AB_3076698) [1-2] and immunohistochemistry\n(PTMBIO, PTM-1406RM, RRID: AB_2909438) [3-4]have been extensively validated in multiple\nindependent studies, confirming their specificity and reliability.\n[1]Jiao Qiao. et al. Histone H3K18 and Ezrin Lactylation Promote Renal Dysfunction in\nSepsisAssociated Acute Kidney Injury[J].Advanced Science.2024.\n[2]Yunjia Zhang. et al. Macrophage MCT4 inhibition activates reparative genes and protects from\natherosclerosis by histone H3 lysine 18 lactylation[J].Cell Reports.2024.\n[3]Li W. et al. Tumor-derived lactate promotes resistance to bevacizumab treatment by facilitating\nautophagy enhancer protein RUBCNL expression through histone H3 lysine 18 lactylation\n(H3K18la) in colorectal cancer. Autophagy. 2024 Jan;20(1):114-130.\n[4]Li F. et al. Positive feedback regulation between glycolysis and histone lactylation drives\noncogenesis in pancreatic ductal adenocarcinoma. Mol Cancer. 2024 May 6;23(1):90.\n• General: NEK8 and CD8⁺ T cell infiltration: While lactate appears to inhibit CD8⁺ infiltration,\nwhich is in line with previous research, the link between NEK8 and lactate is modest (see comment\nantibody validation and Mass Spec).\nResponse: Thanks for your great suggestion.We measured lactate levels in NEK8 stable\noverexpression and knockdown cell lines in vitro. Knockdown of NEK8 significantly reduced\nlactate levels, while overexpression of NEK8 significantly increased lactate production(Fig.5C and\nSupplemental Fig.5B). Additionally, measurements in subcutaneous tumor tissues also\ndemonstrated that NEK8 significantly promotes lactate generation (Supplemental Fig.5N). The\nabove results all indicate that NEK8 regulates lactate metabolism.\nOK\nMinor Points\nMinor points are address\n• Figure 1B: Myeloid cell subsets appear heterogeneous? This could be interesting. Please comment\non and or annotate the (sub) populations shown.\nResponse: Thanks for your valuable suggestion. We have added single-cell analysis of Myeloid cell\nsubsets. scRNA-seq resolved myeloid cells into nine transcriptionally defined subsets\n(SupplementaryFig.1E):C01(CCr2+Trem1+M/MdM),C02(Gpnmb+Mph),C03(Ms4a7+Mrc1hiMp\nh),C04(Cd3e+MyeloidCells),C05(Mki67+MyeloidCells),C06(APCs),C07(Ifitm6+Mono),C08(Tnf\nrsf4+Ikzf2+MyeloidCells),C09(S100a9+M/MdM), and a residual C10 (Others). Cluster proportions\ndiverged sharply between conditions (Supplementary Fig. 1F): C02 (Gpnmb⁺ macrophages), C03\n(Ms4a7⁺ Mrc1hi macrophages), and C04 (Cd3e⁺ myeloid cells) showed the greatest shifts in IR-\nMC38 versus MC38 tumors, reflecting radiation-driven remodeling of the myeloid niche.\n• Line 432: Clarify the term DEG (likely “differentially expressed genes”).\nResponse: Thanks for your suggestion, and we have added the content as suggested.\n• Figure 1, RNA-seq setup: Clarify which conditions were used (resistant vs. non-resistant tumors,\nwith or without IR?).\nResponse: Thanks for your suggestion, and we have added the content as suggested in line453-454.\n• Figure legends: Ensure that all figure legends are complete, clearly describing conditions,\nreplicates, and normalization methods and statistical methods, for a meaningful and fair\ninterpretation of the panels.\nResponse: Thanks for your valuable suggestion. We have revised the figure captions to ensure that\nall legends are complete, clearly describing the experimental conditions, number of replicates,\nnormalization methods, and statistical methods."}]

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