Ceramide disrupts TM9SF2-PGK1 axis to redirect PD-L1 trafficking and enhance antitumor immunity

Domain: biology
Published: 2026-03-26
Editorial outcome: minor_revision

Abstract
The programmed cell death protein 1 (PD-1) / programmed death-ligand 1 (PD-L1) axis represents a cornerstone of cancer immunotherapy, yet the dynamic shuttling of PD-L1 between endosomal recycling and lysosomal degradation routes limits durable responses. Using a CRISPR screen targeting glycosphingolipid metabolism, we identify transmembrane 9 superfamily member 2 (TM9SF2) as a key regulator of PD-L1 levels. TM9SF2 orchestrates a dual mechanism: it recruits phosphoglycerate kinase 1 (PGK1) to promote PD-L1 recycling to the plasma membrane while dismantling the huntingtin-interacting protein 1-related protein (HIP1R)-mediated lysosomal degradation pathway. Genetic or pharmacological disruption of the TM9SF2-PGK1 complex depletes PD-L1 levels and boosts antitumor immunity. Further, the endogenous ceramide species Cer(d18:1/26:0) destabilizes this complex, triggering PD-L1 lysosomal destruction and potentiating antitumor immunity. These findings delineate a ceramide-gated sorting mechanism within the endosomal network, revealing a druggable metabolic switch to disrupt immune evasion and amplify checkpoint blockade efficacy.

Introduction
Immunotherapy using immune checkpoint inhibitors has recently led to significant advancements in cancer treatment 1-3. Immune checkpoint inhibitors, especially anti-programmed death-1 (PD-1)/PD-1 ligand 1 (PD-L1) agents, have demonstrated promising efficacy and broad applicability across various cancers 4,5. However, not all cancer patients experience substantial benefits from these therapies, and the overall response rates remain relatively low for most cancer types 6. Furthermore, the immune checkpoint inhibitor resistance poses a significant challenge to the clinical success of cancer immunotherapy 7-10.

The intracellular fate of PD-L1 is governed by two competing trafficking pathways: being degraded and eliminated in lysosomes, or accumulating in recycling endosomes and repopulating to the cell membrane 11,12. The disruption of this homeostatic balance often through enhanced recycling or suppressed degradation results in pathological PD-L1 accumulation on tumor cells. This aberrant PD-L1 expression subsequently attenuates T cell effector functions and drives clinical resistance to immunotherapy. Therefore, elucidating the molecular machinery governing PD-L1 intracellular trafficking has become an urgent priority in the field, establishing this process as a crucial regulatory node for improving immune checkpoint blockade (ICB) efficacy 13-15.

Endocytic trafficking of PD-L1—including its sorting into recycling, degradative, or retrograde pathways—is essential for maintaining its balanced distribution and supporting anti-cancer immunity 12,13,16-20. Several key regulators of PD-L1 recycling and degradation have been identified to date, including our most recent work on VPS11/18 21. However, the mechanisms governing its sorting between the degradative and recycling pathways remain unclear. Sphingolipids, major components of eukaryotic membranes, play critical roles in maintaining membrane integrity, endocytosis, protein sorting, and secretion 22,23 They are unevenly distributed within cellular organelles, particularly enriched in the trans-Golgi-PM-endosome axis 24, suggesting a potential link to endosomal transport. As an active sphingolipid, whether ceramide is essential for the selective sorting of internalized PD-L1 to the endosomal membrane or for its lysosomal degradation remains to be determined.

In this study, we identify the TM9SF2-PGK1 complex as a critical hub that governs the intracellular trafficking and recycling of PD-L1. Through a CRISPR screen targeting glycosphingolipid metabolism, TM9SF2 emerged as a key regulator of PD-L1 abundance. Mechanistically, TM9SF2 orchestrates a dual program to control PD-L1 fate: it recruits PGK1 to facilitate PD-L1 recycling to the plasma membrane, while simultaneously dismantling the HIP1R-mediated lysosomal degradation pathway. Disruption of the TM9SF2-PGK1 complex by the endogenous ceramide species Cer(d18:1/26:0) redirects internalized PD-L1 toward lysosomal degradation, thereby potentiating antitumor immunity. This intracellular regulatory axis presents a promising therapeutic strategy to overcome resistance and improve the efficacy of immune checkpoint blockade (ICB) therapy.

Results
TM9SF family members stabilize PD-L1 and suppress CD8+ T cell cytotoxicity
Sphingolipids, critical structural and signaling components of cellular membranes, regulate immune responses through their metabolic intermediates 25,26. To investigate whether sphingolipid synthesis/metabolic pathway mediate PD-L1 expression, we conducted a CRISPR-Cas9 knockout (KO) screen targeting 50 genes involved in the sphingolipid synthesis/metabolic pathway with H460 non-small cell lung cancer (NSCLC) cells (Fig. 1A). After lentiviral transduction and puromycin selection, we isolated the lowest 10% of PD-L1-expressing cells (PD-L1low) by fluorescence-activated cell sorting (FACS) at two time points (day-7 and day-15), followed by next-generation sequencing to quantify sgRNA abundance. Notably, sgRNAs targeting members of the transmembrane 9 superfamily (TM9SF1-4) exhibited significant enrichment in the PD-L1Low populations compared to control cells (Fig. 1B and Fig. S1A), indicating that these genes are essential for maintaining PD-L1 expression in H460 cells.

In mammals, four members of transmembrane 9 superfamily (TM9SF1-4) have been identified 27-29, but the functions of the TM9SF family in PD-L1 regulation are poorly understood. We generated TM9SF1-4 KO H460 cells using two distinct sgRNAs each. Ablation of all four TM9SF genes resulted in a decrease in total PD-L1 protein levels and cell surface expression (Fig. 1C and Fig. S1B-C). Conversely, overexpression of TM9SF1-4 upregulated both total and cell surface PD-L1 levels (Fig. 1D and Fig. S1D). Notably, PD-L1 mRNA levels were not affected by TM9SF1-4 knockout (Fig. S1E). To determine whether TM9SF1-4 influences PD-L1 protein stability, H460 cells were treated with cycloheximide (CHX) which inhibits protein synthesis. An accelerated PD-L1 degradation were observed upon TM9SF1-4 ablation, suggesting that TM9SF1-4 can stabilize PD-L1 at the protein level (Fig. 1E and Fig. S1F).

To determine whether TM9SF2 suppresses tumor immunogenicity, we first established an in vitro co-culture system using primary human T cells and either WT or TM9SF2 KO H460 cells (Fig. 1F and Fig. S1G). Genetic ablation of TM9SF2 significantly enhanced T cell-mediated tumor cell killing, as indicated by reduced viability (Fig. 1G and Fig. S1H) and increased apoptosis (Fig. S1I-J) in TM9SF2 KO cells. Furthermore, TM9SF2-deficient cells induced strong CD8⁺ T cell activation, reflected by elevated IFN-γ production and surface CD107a expression (Fig. 1H-I and Fig. S1K-L). Notably, PD-L1 overexpression in TM9SF2-KO cells reversed the T cell–mediated growth inhibition (Fig. S1M-N), identifying TM9SF2 as a novel regulator of PD-L1–dependent immune evasion.

TM9SF2 promotes PD-L1-mediated immunosuppression in CD8+ T cell
To test in vivo anti-tumor efficacy of TM9SFs, we established Tm9sf1-4-knockdown (KD) models in B16 melanoma and C1498 leukemia cells using shRNA silencing. These immunocompetent murine models provide superior capability for investigating CD8⁺ T cell-mediated immunity in C57BL/6J hosts. Following subcutaneous implantation in C57BL/6J mice, Tm9sf1-4 knockdown consistently suppressed tumor growth in both models (Fig. 2A-C and Fig. S2A-F). Moreover, Tm9sf1-4 KD tumors demonstrated reduced PD-L1 surface levels on cancer and increased infiltration of CD8+ T cells in the tumor microenvironment (TME) (Fig. 2D and Fig. S2G-M). Of note, CD8+ T-cell depletion with an anti-CD8 antibody abrogated the tumor suppression by Tm9sf2 KD (Fig. 2C and Fig. S2D-F), suggesting that the tumor suppression is mediated by CD8+ T cell. CD8+ T cells isolated from Tm9sf1-4 KD tumors displayed elevated cytotoxicity, as indicated by elevated IFN-γ as well as externalized CD107a 30,31 (Fig. 2E-F and Fig. S2N-O). Furthermore, these cells displayed a less exhausted phenotype, consistent with the marked downregulation of the exhaustion markers PD-1 and Tim-3 (Fig. S2P).

We then generated Tm9sf2 overexpression (OE) B16 or C1498 cells and the subcutaneously inoculated Tm9sf2 OE tumors showed increased PD-L1 expression (Fig. 2G and Fig. S2Q-R) and tumor grew more rapidly than the control group (Fig. 2H and Fig. S2S). Meanwhile, tumor-infiltrating CD8+ T cells exhibits decreased amounts of IFN-γ and CD107a, and displayed elevated levels of PD-1 and Tim-3 (Fig. 2I-K and Fig. S2T-V). Strikingly, administration with anti-PD-L1 completely reversed Tm9sf2-OE-driven tumor progression in B16 models (Fig. 2H-K, Fig. S2S and Fig. S2V). Thus, TM9SF2 promote tumor progression by stabilizing PD-L1 and suppressing CD8+ T cell cytotoxicity.

TM9SF2 interacts with PGK1 to suppress CD8+ T cell function
To understand how TM9SF2 regulates PD-L1, we conducted immunoprecipitation coupled with mass spectrometry (IP-MS) analysis with FLAG-tagged TM9SF2 in HEK293T cells. Among the high-confidence interactors identified, phosphoglycerate kinase 1 (PGK1) ranked as the top hit, suggesting it might play a role in TM9SF2-mediated PD-L1 regulation (Fig. 3A).

PGK1 is a classic glycolytic enzyme that drives tumor progression via ATP synthesis, post-transcriptional regulation, and metabolic reprogramming 32,33. However, its role in PD-L1 immune regulation remain unclear. We validated the interaction between TM9SF2 and PGK1 with Co-IP, and this interaction was further potentiated by IFN-γ stimulation (Fig. 3B). Knocking out PGK1 markedly diminished both total cellular and surface PD-L1 levels, whereas PGK1 overexpression resulted in an increased PD-L1 expression (Fig. 3C and Fig. S3A-C). Given PGK1’s canonical role as a glycolytic enzyme, we next evaluated whether the TM9SF2-PGK1 complex regulates PD-L1 via glycolytic activity. Inhibiting glycolysis with 2-deoxy-D-glucose (2-DG) was not able to downregulate PD-L1 as observed in PGK1 KO cells (Fig. S3D), suggesting that PGK1 regulates PD-L1 in a manner independent of its glycolytic function. TM9SF2/PGK1 double KO (DKO) exhibited no additive reduction in PD-L1 levels compared to the single KOs (Fig. S3E), indicating their functional redundancy in regulating PD-L1.

Previous study showed that the phosphorylation at serine 203 (S203) modulates PGK1's subcellular trafficking 34, we generated the phosphorylation-deficient (S203A) and phosphomimetic (S203D) PGK1 mutants using site-directed mutagenesis. PGK1 S203D mutant enhanced TM9SF2 binding capacity and elevated PD-L1 expression, whereas the S203A mutant disrupted this interaction and diminished PD-L1 levels (Fig. 3D-E). We found that PGK1 stabilize PD-L1 through post-translational regulation, as PGK1 KO accelerated PD-L1 protein degradation (Fig. 3F-G and Fig. S3F) without affecting its mRNA abundance (Fig. S3G).

To investigate the pro-tumorigenic functions of PGK1 in vivo, we generated Pgk1 KD B16 and C1498 cells and evaluated their effects on tumor growth in C57BL/6J mice. Pgk1 KD significantly suppressed tumor growth (Fig. 3H and Fig. S3H). Correspondingly, Pgk1 KD tumors exhibited reduced PD-L1 total protein and surface levels and enhanced CD8+ T cell infiltration in the TME (Fig. 3I and Fig. S3H-L). Tumor-infiltrating CD8+ T cells in Pgk1 KD tumors display enhanced effector functions, including higher secretion of IFN-γ and expression of CD107a (Fig. 3J and Fig. S3M), along with reduced levels of the exhaustion markers PD-1 and Tim-3 (Fig. S3N).

DC-PGKI was previously reported to be a potent PGK1 inhibitor 35. Inhibiting PGK1 with DC-PGKI recapitulated Pgk1 knockout phenotypes of reducing intracellular PD-L1 level, suppressing tumor growth, and augmenting T cell-mediated immunity in vivo (Fig. 3K-N and Fig. S3O-U). Conversely, Pgk1 overexpression accelerated tumor growth and impaired CD8+ T cell functionality, underscoring its role in negatively regulating PD-L1-dependent antitumor immunity (Fig. 3O-Q and Fig. S3V-Z). These findings position PGK1 as a potential target for ICB therapy.

TM9SF2-PGK1 maintains PD-L1 expression by facilitating endosomal recycling
To determine the mechanistic basis of TM9SF2-PGK1-mediated PD-L1 regulation, we performed quantitative proteomics following TM9SF2 depletion. Selective dysregulation of endosomal recycling components was enriched in TM9SF2 KD cells, notably the COMMD/CCDC22/CCDC93 (CCC) complexes, which play a critical role in recycling events 36 (Fig. 4A).

Disrupting PD-L1 endosomal trafficking reduces its membrane anchoring and enhances anti-tumor immunity 12,13. We therefore investigated whether the PGK1-TM9SF2 axis operates through a similar mechanism. Using a PD-L1-APC antibody to tract the internalization and recycling of surface PD-L1 12, we found that knockout of PGK1 or TM9SF2 significantly decreased surface PD-L1 levels due to defective endosomal recycling (Fig. 4B-D). Confocal microscopy revealed markedly diminished co-localization of PD-L1 with the recycling endosome marker RAB11 in TM9SF2 or PGK1 KO cells (Fig. 4E). Co-immunoprecipitation of HA-tagged PGK1 confirmed its interaction with TM9SF2 and RAB11 within endosomes, and this binding was enhanced following IFN-γ stimulation (Fig. 4F).

We have confirmed that the phosphorylation of PGK1 at serine 203 is necessary for the interaction between TM9SF2 and PGK1. To investigate whether this post-translational modification regulates PGK1 trafficking, we examined the temporal phosphorylation dynamics following IFN-γ stimulation. Subcellular fractionation into endosomal membrane and cytosolic compartments revealed that S203-phosphorylated PGK1 is selectively enriched in endosomal membranes. This compartment-specific redistribution mirrors the spatial pattern previously observed under EGF stimulation 34, suggesting a conserved mechanism for phosphorylation-dependent membrane localization (Fig. S4A). Strikingly, the phosphomimetic S203D mutant displayed increased interaction with PD-L1 and TM9SF2 in endosomes, whereas the non-phosphorylatable S203A mutant showed the opposite trend (Fig. 4G). These findings indicate that phosphorylation of PGK1 at the S203 site is essential for PD-L1 endosomal recycling, a process regulated by the TM9SF2-PGK1 interaction.

Endocytosed proteins undergo sorting through endosomal pathways for either lysosomal degradation or plasma membrane recycling. To determine whether the TM9SF2-PGK1 axis promotes PD-L1 recycling while preventing lysosomal degradation, we performed live-cell imaging to track PD-L1 spatiotemporal dynamics. Genetic ablation of either TM9SF2 or PGK1 redirected PD-L1 trafficking from recycling to degradative pathways, as evidenced by two complementary findings: reduced PD-L1 surface expression (Fig. S4B) and enhanced lysosomal accumulation quantified through increased co-localization with LAMP1 (Fig. S4C). Given that ubiquitination is a critical signal for the lysosomal degradation of PD-L1 18, we performed immunoprecipitation of PD-L1 in TM9SF2 or PGK1 KO and WT cells, and found that the loss of neither TM9SF2 nor PGK1 altered PD-L1 ubiquitination levels (Fig. S4D-E). Thus, TM9SF2-PGK1 maintains the endocytosed PD-L1 by endosomal recycling instead of lysosomal degradation.

TM9SF2-PGK1 complex hinders lysosomal sorting by degrading the PD-L1 lysosomal carrier HIP1R
To investigate how the TM9SF2-PGK1 axis allows PD-L1 to evade lysosomal trafficking, we conducted quantitative proteomic profiling in PGK1 KO cells. Significant upregulation of lysosomal sorting machinery components, particularly HIP1R—a key adaptor protein responsible for directing PD-L1 to lysosomes—was observed upon PGK1 depletion 19 (Fig. 5A). And the elevated HIP1R protein levels were confirmed in PGK1 and TM9SF2 KO cells with Western blot (Fig. 5B-C and Fig. S5A-B), while HIP1R mRNA expression remained unchanged (Fig. S5C).

To understand how HIP1R is regulated by PGK1, we performed the CHX chase assay and found that PGK1 deficiency significantly extended HIP1R protein half-life, whereas PGK1 overexpression accelerated its degradation (Fig. 5D and Fig. S5D). Ectopic HA-PGK1 expression enhanced HIP1R polyubiquitination, which was further amplified under IFN-γ stimulation (Fig. 5E). Importantly, phosphorylation of PGK1 at S203 was crucial for its regulation of HIP1R ubiquitin-dependent degradation, S203A mutation abolished the PGK1-HIP1R interaction and diminished HIP1R ubiquitination (Fig. 5F and Fig. S5E).

PGK1 has been reported to recognize the dileucine-based sorting signal that directs endosomal EGFR to the lysosome 34. Notably, HIP1R (966–979) possesses a similar dileucine motif 19. To further examine whether PGK1 can recognize HIP1R through the dileucine motif, we constructed plasmids expressing both full-length HIP1R and a truncated version lacking residues HIP1R (966–979). Co-IP assays revealed that PGK1 specifically binds to the dileucine motif of HIP1R, as this interaction was abolished upon motif deletion (Fig. 5G). Furthermore, IFN-γ stimulation significantly enhanced PGK1-HIP1R binding (Fig. 5G), suggesting IFN-γ-induced phosphorylation of PGK1 may also participate in the interaction with HIP1R and its functional execution. To assess the functional relevance of this interaction, we overexpressed GFP-tagged constructs containing either the wild-type dileucine motif (GFP-S1) or a mutant version with leucine-to-alanine substitutions (GFP-S2) (Fig. 5H). Strikingly, PGK1 deficiency markedly stabilized GFP-S1 but had no effect on GFP-S2 (Fig. 5I and Fig. S5F), indicating that PGK1 selectively targets the dileucine motif for degradation. These findings collectively demonstrate that PGK1 regulates HIP1R stability through direct recognition of its dileucine motif, mirroring its known role in EGFR trafficking.

Cer(d18:1/26:0) dissociates the TM9SF2-PGK1 complex to suppress PD-L1 expression and promote antitumor immunity
Given that PGK1 and TM9SF2 are both involved in sphingolipid metabolism 37,38, we hypothesized that specific sphingolipid intermediates might regulate TM9SF2-PGK1 complex assembly and downstream pathways. Targeted lipidomic profiling of TM9SF2-knockdown H460 cells versus wild-type controls identified 12 ceramide species with differential abundance (Fig. 6A). To interrogate this lipid-protein interplay, we treated H460 cells with commercially available ceramide standards (or their metabolically stable analogs) for 40 hours. Strikingly, Cer(d18:1/26:0) induced the most dramatic reduction in PD-L1 protein levels (Fig. 6B-C). Ceramides are synthesized by ceramide synthase enzymes (CERS), which exhibit distinct specificity for their acyl-CoA substrates 39. We generated CERS1-6 knockout H460 cell lines and evaluated PD-L1 levels (Fig. S6A). Depletion of CERS3, responsible for synthesizing Cer(d18:1/26:0), produced the most pronounced changes in PD-L1 levels, while overexpression of CERS3 significantly downregulated PD-L1 levels (Fig. S6A-B). CHX chase assays showed that Cer(d18:1/26:0) treatment or CERS3 overexpression reversed the PD-L1 stabilization and restored HIP1R degradation induced by TM9SF2/PGK1 overexpression (Fig. 6D-E and Fig. S6C-G). Importantly, although TM9SF2 has been linked to ganglioside GM3 (Gb3) synthesis 37, we found that Gb3 does not contribute to TM9SF2-mediated PD-L1 regulation, underscoring the specificity of the ceramide-dependent pathway described here (Fig. S6H).

To investigate whether Cer(d18:1/26:0) disrupts the interaction between TM9SF2 and PGK1, thereby affecting PD-L1, we performed Co-IP and found that Cer(d18:1/26:0) treatment weakened the TM9SF2-PGK1 interaction (Fig. 6F). In addition, we analyzed the subcellular localization of PD-L1 using immunofluorescence labeling. Cer(d18:1/26:0) treatment reduced the colocalization of PD-L1 with recycling endosome markers (RAB11 and CD147) while increasing its association with the lysosomal marker LAMP1 (Fig. 6G and Fig. S6I-J). These findings suggest that Cer(d18:1/26:0) disrupts the PGK1-TM9SF2 interaction, thereby redirecting PD-L1 from recycling endosomes (RAB11/CD147) to lysosomes (LAMP1) and promoting its degradation.

We further examined the anti-tumor effects of Cer(d18:1/26:0) in B16 melanoma and C1498 acute myeloid leukemia (AML) models in vivo (Fig. 6H and Fig. S6K). Compared to the vehicle group, Cer(d18:1/26:0) treatment significantly inhibited tumor growth (Fig. 6I and Fig. S6L-M). Consistent with the reduced tumor burden, ex vivo analysis revealed lower PD-L1 levels on cancer cells and a higher percentage of CD8+ T cells in the TME following Cer(d18:1/26:0) treatment (Fig. 6J and Fig. S6N-Q). Furthermore, tumor-infiltrating CD8+ T cells exhibited increased effector functions, including enhanced IFN-γ secretion and CD107a expression, compared to those in untreated parental tumors (Fig. 6K and Fig. S6R).

Therapeutic potential for targeting TM9SF2-PGK1 complex in human lung cancer
Our findings suggest that the TM9SF2-PGK1 complex functions as a ceramide-responsive signaling hub, regulating PD-L1 sorting within the endosomal system and contributing to cancer immune evasion. To further investigate the clinical association between members of the TM9SF family and cancer prognosis, we compared their expression between normal cells and tumors in the Cancer Genome Atlas (TCGA) database. Bioinformatic analyses across multiple cancer types revealed that the TM9SF1-4 gene signature is upregulated in lung adenocarcinoma (LUAD) and exhibits a negative correlation with overall survival in AML patients (Fig. 7A-B and Fig. S7A-B). Additionally, PGK1 expression was upregulated while HIP1R was downregulated in LUAD (Fig. 7A and Fig. S7A). Immunofluorescent staining of LUAD tissue microarrays further demonstrated a positive correlation of TM9SF2 with PD-L1 expression levels (Fig. 7C and Fig. S7C). To evaluate the potential clinical therapeutic value of these findings, tumor cells were isolated from lung cancer patients and treated with DC-PGKI or Cer(d18:1/26:0) (Fig. 7D). Western blot and flow cytometry analyses revealed that treatment with DC-PGKI and Cer(d18:1/26:0) resulted in a significant reduction of PD-L1 and an increase in HIP1R levels (Fig. 7E-F and Fig. S7D). To verify whether the reduction of PD-L1 expression by the two aforementioned compounds occurs through the TM9SF2-PGK1 complex-mediated pathway, we labeled PD-L1 to monitor its intracellular trafficking from the plasma membrane to endosomal or lysosomal compartments. Following treatment with Cer(d18:1/26:0) or DC-PGKI, a reduction in PD-L1 colocalization with RAB11 and plasma membrane markers was observed, accompanied by an increase in colocalization with the lysosomal marker LAMP1 (Fig. 7G and Fig. S7E). Collectively, these results suggest therapeutic potential to enhance antitumor immune responses by targeting TM9SF2-PGK1 complex formation to modulate PD-L1 trafficking and recycling (Fig. 7H).

Methods
Ethics statement
For mice: Eight-week-old C57BL/6J male mice were obtained from Beijing Vital River Laboratory Animal Technology Co., Ltd. (China). They were maintained in individually ventilated cages at the Shandong University Model Animal Research Center, with a standard 14:10-h light: dark cycle, ambient temperature of 23-25 °C, humidity levels of 40-70% and full access to water and facility chow, following the guidelines set forth by the Animal Care and Utilization Committee of Shandong University, China. All animal studies were conducted in accordance with protocols approved by the Ethics Committee of Shandong University (Approval No. SYXK (Lu) 20230003). According to the approved protocol, the maximum allowable size for any solid tumor is 20 mm in any single dimension. This study strictly adhered to these requirements. Mice were humanely euthanized via carbon dioxide inhalation.

For patient samples: All human lung cancer specimens analyzed in this study were collected from surgical resections performed at the Second Hospital of Shandong University. The use of these clinical samples was reviewed and approved by the Institutional Ethics Committee of the Second Hospital of Shandong University (Approval No. KYLL2025362), and all procedures were conducted in full compliance with the relevant ethical regulations.

Cell culture and treatment
HEK293T cells (Procell Corporation, #CL-0005), B16-F10 cells (Procell Corporation, #CL-0319), H460 cells (Procell Corporation, #CL-0299), and mouse AML cells (C1498) (ATCC, #TIB-49) were incubated in Dulbecco’s Modified Eagle’s Medium (DMEM, containing 10% fetal bovine serum (FBS) as well as 1% penicillin-streptomycin) (37 °C, 5% CO2). For IFN-γ treatment, cells were administered IFN-γ (100 ng/mL) for 48 hours unless indicated otherwise. All ceramide standards (or their metabolically stable analogs) were given at 31.25 μM for 40 hours unless indicated otherwise. The reagents used in this study are listed in Supplementary Dataset 1.

Plasmids
To produce the pLenti-CRISPRv2-sgRNA plasmids for sphingolipid metabolic pathway related CRISPR-Cas9 knockout screen and PGK1 knockout, we allowed sgRNAs to cool naturally to room temperature after heating to 95 °C for 5 minutes in an annealing buffer. We cloned the annealed sgRNAs into a BsmBⅠ-digested pLenti-CRISPRv2 vector (#52961, Addgene, USA). The sgRNAs were designed using crispor.tefor.net. CRISPR sgRNA sequences for TM9SF1-4/PGK1/CERS1-6 knockout are listed in Supplementary Dataset 2 and sgRNA sequences for sphingolipid metabolic pathway related CRISPR-Cas9 knockout screen are listed in Supplementary Dataset 3.

For the FLAG-tagged TM9SF1-4, CERS3 and CD274 plasmids, we purchased FLAG-tagged TM9SF3 plasmid (#P56344) and FLAG-tagged TM9SF4 plasmid (#P58124) from MIAOLING BIOLOGY. We inserted human TM9SF1, CERS3 and CD274 PCR products into pcDNA3.1-3×FLAG vector (#182494, Addgene, USA) and inserted TM9SF2 products into the HindⅢ and EcoRⅠ sites of pCMV-T7-MCS-3×FLAG-Neo vector (#P1303, MIAOLING BIOLOGY, China).

To generate constructs for HA-tagged PGK1, PCR fragments underwent digestion with EcoRⅠ and XhoⅠ before being inserted into the pcDNA3.1-HA vector (#128034, Addgene, USA). The pCDH-Pgk1 plasmids were produced by inserting the synthesized cDNA coding mouse Pgk1 into pCDH-CMV-MCS-EF1-mcherry-T2A-puro vector (#IGV-LV-a-003, Guangzhou IGE Biotechnology Co., Ltd., China) using EcoRⅠ/BamHⅠ MCS.

For the construction of plasmids encoding PGK1 variants, including phosphorylation mutants (S203A and S203D) and PAM locus mutants, pcDNA3.1-HA-PGK1p.Ser203Ala and pcDNA3.1-HA-PGK1p.Ser203Asp were developed using a Mut Express II Fast Mutagenesis Kit V2 (#C214-01, Vazyme, China), with pcDNA3.1-HA-PGK1 serving as the template. These constructs were subsequently employed as templates to generate the pcDNA3.1-HA-PGK1p.Ser203Ala, c.978G>A and pcDNA3.1-HA-PGK1p.Ser203Asp, c.978G>A plasmids, designed to block PAM detection by mutating the NGG site to a sequence compatible with specificity-modified Cas9.

The MYC-tagged HIP1R construct was generated by inserting the PCR product into the pcDNA3.1-MYC vector (#176045, Addgene, USA). For the GFP-tagged HIP1R construct, the fragments were inserted into the XbaⅠ-EcoRⅠ region of pCDH-CMV-MCS-EF1-Blast-EGFP.

The GFP-S1 plasmid was acquired from Tsingke Biotechnology Co., Ltd. by cloning cDNA with an HA-tag and the designated peptide (S1) into pEGFP-C1 via the Bgl II/EcoR I multiple cloning sites. To generate the leucine-to-alanine mutant, GFP-S2 was developed using a Mut Express II Fast Mutagenesis Kit V2, with GFP-S1 as a template. Similarly, the GFP-tagged HIP1RΔ966-979 mutant was generated with HIP1R-GFP as a template.

We amplified the TM9SF2, PGK1, HIP1R, and CD274 genes from A549 cDNA, Pgk1 from L929 cDNA, TM9SF1 from the pCMV-SPORT6-TM9SF1 plasmid (#P4018, MIAOLING BIOLOGY, China), and CERS3 from the pCDNA3.1-HA-CERS3 plasmid (#P2224, MIAOLING BIOLOGY, China). All primers were procured from Sangon Biotech, and plasmid sequences were confirmed through DNA sequencing. Primer sequences are listed in Supplementary Dataset 4.

Hairpin shRNAs targeting the coding sequences of mouse Tm9sf1-4 and Pgk1, transcripts were also generated by Tsingke Biotechnology Co., Ltd. and inserted into the pLKO.1-mCherry-Puro vector. Short hairpin sequences are provided in Supplementary Dataset 5.

Stable cell line generation
To generate TM9SF1-4 or PGK1 knockout (KO) clones, CRISPR-Cas9 technology was employed as previously described 52. pLenti-CRISPRv2-sgRNA plasmids were introduced into HEK293T cells grown in 6-well plates via polyethylenimine (PEI) transfection, along with packaging plasmids PMD2.G and PSPAX at a ratio of 0.25:0.15:0.20 to produce lentivirus. Viral extracts were harvested at 24 h and 48 h after transfection and applied to H460 cells supplemented with polybrene (10 μg/mL). Puromycin selection (2 μg/mL) was subsequently performed for several days to isolate transduced cells.

For generating TM9SF2/PGK1 double-knockout (dKO) clones, TM9SF2 KO H460 cells (3×10⁴ cells/well) were plated in 12-well plates, and then they were transduced using lentiviral particles (pLenti-CRISPRv2-sgRNA PGK1) in the presence of polybrene to facilitate PGK1 knockout. Single-cell clones were generated from polyclonal populations using limiting dilution and validated by immunoblotting to confirm the loss of TM9SF2 and PGK1 protein expression. For Pgk1 overexpression (OE) in B16 and C1498 cells, pCDH-Pgk1 plasmids, along with packaging plasmids, were transfected into HEK293T cells to produce lentiviruses. B16 and C1498 cells underwent infection with the produced lentiviruses with polybrene, and subsequently, puromycin selection was applied. Tm9sf2 OE B16 and C1498 cells were generated using LV-Tm9sf2 viral filtrate (#63315-22, GeneChem Co., Ltd.).

For knockdown (KD) of mouse Tm9sf1-4 or Pgk1, lentiviral vectors expressing the respective shRNAs were transfected into HEK293T cells to produce control and knockdown lentiviruses. B16 and C1498 cells were infected twice with lentivirus-containing culture medium and polybrene at 37 °C for 24 and 48 hours. To maximize KD efficiency, infected cells underwent puromycin selection for several days and were characterized using confocal microscopy.

Puromycin-resistant KD, KO, or OE clones were extracted via single-cell dilution cloning from polyclonal groups and validated by immunoblotting for the respective proteins.

Mouse subcutaneous tumor-bearing model
For syngeneic melanoma or AML models, 1 × 10⁶ B16 or C1498 cells modified with the indicated shRNAs or overexpression constructs were resuspended in 100 μL of saline and introduced subcutaneously into the flanks of C57BL/6J mice to produce tumors. On the day of inoculation with tumor cells, mice were administered with anti-CD8 monoclonal antibody (mAb), anti-PD-L1 mAb, DC-PGKI, or Cer(d18:1/26:0).

For checkpoint therapy, mice received intraperitoneal injections of 200 μg anti-CD8 mAb or 200 μg anti-PD-L1 mAb (or isotype control) on the 0, 3rd, 6th, 9th, and 12th day.

For PGK1 inhibitor treatment, mice received intraperitoneal injections of DC-PGKI which was formulated in a solution of 10% DMSO and 90% PBS at 10 and 5 mg/kg/day, respectively, or a control solution consisting of 10% DMSO in PBS (v/v), for one week.

For treatment with Cer(d18:1/26:0), C57BL/6J mice were injected intraperitoneally with vehicle or Cer(d18:1/26:0) (10 and 20 mg/kg/day) for one week. Cer(d18:1/26:0) was mixed in saline containing sodium carboxymethyl cellulose (0.5%) and Tween 80 (5%), whereas control animals received saline with the same additives.

For C1498 tumors, tumor sizes were evaluated every three days. At the designated time after tumor cell inoculation, mice were euthanized and their tumors were collected for subsequent analysis.

Preparation of ceramide: cholPC
Our approach had slight modifications from a previous protocol 53. Ceramides and cholPC were solubilized in pure chloroform at a concentration of 12.5 mM. ceramide and cholPC were combined at 1:1, dried with nitrogen, and rehydrated using PBS to attain a final concentration of 3.125 mM for each lipid (3.125 mM Cer:3.125 mM cholPC or cholPC: blank). Rehydrated lipids were sonicated for approximately 1 hour until fully dissolved (55 °C). Lipid mixtures were mixed with cell cultures at a 1:100 dilution, making a final level of 31.25 μM for each ceramide.

CRISPR screen
H460 cells were infected with a focused sgRNA library designed to target genes involved in phospholipid metabolism, with 4 sgRNAs per gene. At 48 hours post-infection, cells were enriched for transduced populations via selection with 2 μg/mL puromycin for 72 hours. PD-L1low cells, low 10% of the population, were enriched via two fluorescence-activated cell sorting (FACS) rounds on days 7 and 15 following library transduction. For the first sort, at least 2 × 10⁷ cells were obtained with trypsin, stained on ice for 15 minutes using an APC anti-human PD-L1 antibody, and washed with PBS. Cells exhibiting low PD-L1 expression were isolated using a BD Influx flow cytometer. Genomic DNA (gDNA) was isolated from sorted and unselected populations of mutagenized cells on day 15 by Genomic DNA Purification Kit (#B518251, Sangon Biotech, China) and sent to Novogene for sequencing.

Immunoblotting
Whole-cell or tissue lysates were prepared using RIPA buffer (Solarbio, China) with a 1% protease inhibitor cocktail and 1 mM PMSF. The samples were kept on ice for 10min before centrifuge (10,000 × g, 4 °C, 15 min). Tissue samples were pre-minced and ground in lysis buffer prior to extraction. Proteins were quantified using a bicinchoninic acid (BCA) assay kit (#BL1673A, Biosharp, China). Cell lysates were combined with 5× loading buffer containing 10% 2-mercaptoethanol and heated for 5min for denaturation at 100 °C, except for TM9SF1-4 detection, where samples were denatured at 4 °C for 30 minutes. Forty micrograms of protein per sample were isolated by 10% SDS-PAGE gel and transferred to a polyvinylidene fluoride (PVDF) membrane (Millipore). The membrane was incubated with blocking buffer (EpiZyme, Shanghai, China) for 1 hour at room temperature, then probed with the primary antibody overnight at 4 °C (for details, see Supplementary Dataset 1). Following three sequential 5-minute washes in TBST, the membranes were probed with HRP-associated secondary antibodies (goat anti-rabbit IgG or goat anti-mouse IgG) (1:10,000 dilution in TBST), with incubation proceeding for 60 min (room temperature). Bands were observed using an ECL western blot detection substrate (#32106, Thermo Fisher). For fluorescent detection, Goat anti-Rabbit IgG H&L (IRDye® 800CW) or Goat anti-Mouse IgG H&L (IRDye® 800CW) (1:10,000) were used, and membranes underwent scanning with an Odyssey CLx Imaging System (LI-COR Biosciences). Gray intensity quantification was performed using ImageJ (Fiji).

Immunoaffinity purification-mass spectrometry (IP-MS)
HEK293T cells were plated in triplicate 10 cm culture dishes and introduced alongside FLAG-tagged TM9SF2 plasmid using PEI. Following a 48-hour incubation period, cellular material was collected and homogenized in lysis solution supplemented with 1% protease inhibitor cocktail and 1 mM PMSF. The lysate was subsequently subjected to centrifugation (13,000 × g, 15 minutes, 4 °C) to remove cellular debris. Clarified supernatants were mixed with 30 μL anti-FLAG beads (Sigma) for overnight conjugation at 4 °C. After extensive washing (3 ×) with chilled lysis buffer, the immobilized protein complexes were flash-frozen in liquid nitrogen and subjected to LC-MS/MS analysis.

Coimmunoprecipitation and ubiquitination assays
To investigate protein-protein interactions, HEK293T or H460 cells were transiently transfected with specified plasmids through PEI-mediated transfection for 48h. After transfection, cells were harvested and subjected to immunoprecipitation with magnetic affinity beads conjugated to FLAG, HA, MYC, or GFP antibodies (Cell Signaling Technology) at 4 °C. Antibody-associated complexes were extensively washed (3 ×) with ice-cold lysis buffer, followed by incubation with loading buffer adding 10% β-mercaptoethanol, and 5 min boiling (100 °C) minutes prior to immunoblotting. For TM9SF2 detection, proteins were eluted from beads using 3 × FLAG or HA peptides and denatured without boiling. For Cer(d18:1/26:0) treatment, HEK293T cells expressing FLAG-tagged TM9SF2 and HA-tagged PGK1 were treated with 31.25 μM Cer(d18:1/26:0) for 40 hours, followed by coimmunoprecipitation analysis.

Ubiquitination assays were conducted on co-immunoprecipitation (Co-IP) lysates. Specifically, HEK293T or H460 cells were transfected with various plasmids, with or without stimulation by IFN-γ (100 ng/mL). MYC-tagged protein complexes were immobilized on MYC affinity beads and subsequently washed sequentially with chilled lysis buffer. Immunoblot analysis was performed using an anti-ubiquitin antibody to detect ubiquitinated proteins.

Immunofluorescence imaging
H460 cells, subjected to genetic or pharmacological disruption, including the depletion of PGK1 and TM9SF2 and treatment with ceramide, were utilized in this study. Additionally, cancer cells isolated from lung cancer patients were treated with either DC-PGKI or Cer(d18:1/26:0). All cell types subsequently underwent the following procedures:

The cells were fixed with 4% paraformaldehyde and permeabilized with 0.1% Triton X-100. Non-specific binding sites were blocked with 5% BSA for 1 hour. Cells were then incubated with primary antibodies in PBST (phosphate-buffered saline containing 0.01% Tween-80) under gentle agitation at 4 °C for 16 hours. Following three successive 5-minute rinses with PBST, samples were exposed to species-matched secondary antibodies in the dark for 1 hour at 25 °C. After rinsing, cells were counterstained with DAPI (1 μg/mL) for 10 minutes. Finally, fluorescence signals were captured using a confocal laser scanning microscope (Andor Dragonfly 200) at a resolution of 1024 × 1024 pixels with a 63 × oil immersion objective. Colocalization assessment was performed using ImageJ. Briefly, the red and green traces in the curves correspond to their respective fluorescence channels. Fluorescence intensity values were quantified using the Plot Profile tool in ImageJ along annotated white lines in merged immunofluorescence images, allowing assessment of how red and green fluorophore signal intensities vary with distance.

Characterization of PD-L1 on cell surfaces
H460 cells were trypsinized and rinsed twice using ice-cold PBS. Cells were stained using APC anti-human CD274 antibody under gentle rotation at 4 °C for 60 min in light-protected conditions. Following two additional washes with chilled PBS, antibody-labeled cells were analyzed using flow cytometry.

RNA isolation and qRT-PCR analysis
Total RNA was isolated using a NcmSpin Cell/Tissue RNA Kit (#M5105, NCM Biotech, China). First-strand cDNA synthesis followed a SPARKscript ⅡRT SuperMix for qPCR (#AG0305-B, Sparkjade, China) following the manufacturer’s directions. We performed RT-qPCR analysis on a qRT-PCR system using SYBR. Quantitative analysis was performed via comparative threshold cycle (2−∆∆CT) method with data normalized to GAPDH housekeeping gene expression levels. The primer sequences for qRT-PCR were as follows:
human CD274: forward, 5'-TCACTACACAGCCCTCCTAA-3',
reverse, 5'-ACACCAGAATATGGCCAAGAG-3';
human HIP1R: forward, 5'-AGATGCTGTGCGGAGGATTGAG-3',
reverse, 5'-TGCAGGCTAGTGGATGTCGTCA-3';
human GAPDH: forward, 5'-GAGTCCACTGGCGTCTTCAC-3',
reverse, 5'-TTCACACCCATGACGAACAT-3'.

T cell-mediated tumor cell lethality
T cells were negatively enriched from healthy donor peripheral blood mononuclear cells (PBMCs) employing an EasySep™ isolation system (#17951, STEMCELL Technologies) via negative selection. The isolated T cells were maintained in RPMI 1640 medium. Polyclonal activation was achieved via co-stimulation using ImmunoCult™ CD3/CD28/CD2 T Cell Activator (#10970, STEMCELL Technologies) and recombinant human IL-2 (1000 U/mL, #78036, STEMCELL Technologies) for 3 days. For cell apoptosis assays: sgNTC and sgTM9SF2 H460 cells were plated using 1 × 105 cells/well in 12-well plates, and PBMC-derived effector T cells were included at an effector-to-target ratio of 2:1. After 48-hour co-incubation, cells were collected. After dual PBS washing cycle, cells were subjected to the Annexin V-FITC/7-AAD Apoptosis Detection Kit (#40311ES60, Yeasen, China) at 4 °C for 15 min in light-protected conditions to differentiate early from late apoptotic, as well as necrotic cells. Flow cytometry quantified apoptosis based on the proportion of Annexin V-positive and 7-AAD-positive cells. Anti-PD-L1 treatment served as a positive control. Data attainment was carried out with the BD FACSymphony™ A3 Cell Analyzer, and analysis was conducted with FlowJo software.

For crystal violet staining, sgNTC and sgTM9SF2 H460 cells were co-cultured with T cells sorted from PBMCs (effector-to-target ratio of 2:1) for 48 hours. Residual living cancer cells were assessed using crystal violet staining.

For the CCK-8 assay, sgNTC and sgTM9SF2 H460 cells were placed into 96-well plates with 100 μL culture medium per well, then co-cultured with activated T cells (1:2 ratio) for 48 hours. Residual cancer cells were characterized using CCK-8 staining. Specifically, 10 μL of CCK-8 solution was administered into each well and incubated for 2 hours at 37 °C/5% CO₂, after which absorbance at 450 nm, corresponding to formazan product formation, was determined.

T cells analysis was performed using flow cytometric techniques. Cell viability was assessed with Fixable Viability Dye. For surface marker evaluation, cells were washed and incubated with Brilliant Violet 421 anti-human CD8α and Brilliant Violet 785 anti-human CD107a.

Intracellular interferon gamma (IFN-γ) detection involved cell fixation/permeabilization with the True-Nuclear™ Transcription Factor Buffer Set (#424401, BioLegend, USA), followed by staining with PE-IFN-γ following the producer’s protocol. Isolates were acquired on a BD LSR Fortessa Cell Analyzer (BD Biosciences). Data were analyzed using FlowJo v10 (Treestar Inc.) and GraphPad Prism 9.0.

Tissue microarray analysis
A paraffin-embedded LUAD tissue microarray was obtained from Bioaitech Co. (R076Lu01). All tissues were collected under strict ethical standards with complete donor informed consent. Immunofluorescence analysis of PD-L1 and TM9SF2 expression was performed as described above.

Tumor cell isolation
Single-cell suspensions were generated from lung cancer patient-derived tumor samples through rapid and gentle mechanical dissociation, enzymatic digestion using collagenase IV for 1 h at 37 °C, and subsequent filtration. Tumor cells were then isolated using a tumor cell isolation kit and grown in DMEM (containing 10% FBS and 1% penicillin-streptomycin).

Tumor inoculation and dissection
For tumor dissection, B16 or C1498 tumor tissues were dissected, imaged, and digested using Liberase TM (7.7 mg/mL) and DNase I (100 mg/mL). Tumor fragments were strained using 70-μm strainers (BD Biosciences) to generate single-cell isolates for flow cytometric analysis.

For tumor-infiltrating lymphocytes (TILs), single cell isolates were Fc receptor-blocked using TruStain FcX (1:100) for 15 min, and stained using: AF700-CD45.2 (1:200), PE-Cy7-CD3 (1:1000), BV786-CD8 (1:1000), PerCP-CD4 (1:300), BV421-IFN-γ (1:300), PE-CD107a (1:300), PE-TOX (1:100), PE-Tim-3 (1:200), BV605-PD-1 (1:300) and Fixable Viability Dye (1:1000). We first used Fixable Viability Dye to exclude dead cells in flow cytometry data. Data acquisition was performed on the BD FACSymphony™ A3 Cell Analyzer, and assessment was performed using FlowJo. The gating strategy is detailed in Supplementary Fig. 8.

For PD-L1 expression on tumor cells, single-cell isolates were Fc-blocked, stained using APC-PD-L1 (1:300), and analyzed using the same workflow.

Antibodies used in this study are listed in Supplementary Dataset 1.

Endocytosis and recycling assays
To evaluate PD-L1 recycling, a recycling assay was performed as previously outlined 54. In short, sgNTC and sgTM9SF2/PGK1 H460 cells were Fc-blocked (1:100 dilution) and labeled with a purified anti-human PD-L1 antibody (1:500 dilution) for 0.5 h at 4 °C. After labeling, cells were rinsed with chilled medium and incubated at 37 °C for 30 minutes to facilitate internalization of antibody-bound PD-L1. Surface-bound antibodies were removed using a low pH buffer (IMDM with 1× Pen/Strep and 50 mM sodium, pH 3.5), followed by two PBS washes and incubation in complete medium. Baseline internalized PD-L1 levels were measured immediately after washing (t0), and the recycling pool was quantified after incubation at 37 °C for designated time points (tx). Surface-recycled PD-L1 was detected using an APC-conjugated goat anti-mouse IgG secondary antibody (1:200). The total residual PD-L1 assembly was assessed after fixation and permeabilization, followed by incubation with the same secondary antibody for 45 minutes at room temperature. Cells were rinsed and assessed via flow cytometry.

PD-L1 recycling levels were determined by the ratio of recycled surface PD-L1 to the total residual pool.
To study PD-L1 storage after internalization, H460 cells were detached with TrypLE Express, incubated on ice, and rinsed using RPMI medium (5% FCS, 30 mM HEPES). Surface PD-L1 was labeled using anti-PD-L1 antibody for one hour, washed twice, and resuspended in RPMI. A baseline sample (t0) was collected. Cells were then incubated at 37 °C to allow PD-L1 internalization. At designated time points, samples were diluted in ice-cold PBS, washed, and stained using Alexa Fluor-647-conjugated anti-mouse secondary antibody over 0.5 h. After washing, samples were analyzed via flow cytometry.

Surface PD-L1 at baseline (t0) = S(t0) / A(t0) (1)
Surface PD-L1 at a time point (tx) = S(tx) / A(tx) (2)
PD-L1 Recycling efficiency = [S(tx) / A(tx)] - [S(t0) / A(t0)] (3)

Subcellular fractionation
To separate cellular fractions, H460 cells, either treated or untreated with IFN-γ, were suspended in homogenization buffer consisting of 20 mM HEPES-KOH (pH 7.4), 250 mM sucrose, 1 mM EDTA, and protease inhibitors. Cell lysis was achieved by repeated passage through a 25-gauge needle, followed by centrifugation of the clarified lysates at 800 × g for 5 minutes to remove unbroken cells. The resulting supernatants were further centrifuged (13,000 × g, 10min) to isolate large membrane fractions. Remaining supernatants underwent velocity centrifugation at 100,000 × g for 1 hour, separating light membranes containing endosomal fractions from the cytosolic fraction. All fractions (1:1) were electrophoresed via SDS-PAGE and evaluated by Western blotting.

Lipidomics
Lipidomic profiling of shTM9SF2 and shNC H460 cells was conducted by PTM-biolab Co., Inc. Briefly, cell samples were thawed on ice and extracted using a solvent mixture containing internal standards. After centrifugation, the upper organic layer was collected, dried under vacuum, and reconstituted in a solution (ACN:IPA = 1:1, v/v). Metabolite analysis was performed using LC-ESI-MS/MS with an ExionLC AD coupled to a QTRAP® 6500+ mass spectrometer. Data were log2-transformed, mean-centered, and validated through a permutation test with 200 iterations.

Proteomics
For proteomic profiling, H460 cells with TM9SF2 knockdown or PGK1 knockout were collected and processed by Spectra Biotechnologies (Shanghai). Briefly, peptides were separated using an UltiMate 3000 LC system coupled to a timsTOF Pro 2 mass spectrometer, with elution over a 60-minute gradient on a C18 column at a flow rate of 400 nL/min. Data-independent acquisition (DIA) was performed in diaPASEF mode using variable isolation windows and mobility-dependent collision energy. Raw data were processed in Spectronaut against a human UniProt database, with false discovery rate (FDR) filtering set at 1% and label-free quantification performed using MaxLFQ.

Statistical analysis
All data are presented as mean ± SD. Two-tailed student’s t-test was used to compare all experimental groups against the control group. Significance levels were defined as *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001 in the figures. Statistical analyses were conducted using GraphPad Prism 10.1.2, and all experiments were independently repeated at least three times.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The work by Zheng et al demonstrates that PDL-1 trafficking to lysosomes is controlled by the TM9SF2-PGK1 axis which can be disrupted by the ceramide species Cer(d18:1/26:0). The work is important as it adds value to understanding how co-receptors and their respective ligands such as PDL-1 are regulated within the tumor cells. Although several key aspects of tumor biology and relevant immunity related data is shown in the manuscript, there is a marked terseness in explaining the results. The manuscript would substantially benefit from increasing clarity through explaining their dataset. Also, it is not clear how blocking ceramide and increasing PD-L1 degradation can enhance ICB efficacy, it does provide a new therapeutic pathway to enhance anti-tumor immunity since PD-1 on effector T cells will not have a cognate ligand available to bind and dampen effector responses inhibiting tumour escape. A further explanation on how the authors envision this process would enhance clarity of their reasoning.\nIn Figure 1, the authors perform a CRISPR-Cas9 KO to screen for genes involved in the sphingolipid synthesis pathway within the H46- non small cell lung cancer cell lines. Using this approach they find TM9SF2 to be a key target in PDL1 protein maintenance. Several western blots are shown in Fig. 1c, e, g, h. All of these western data need to be quantified in order to clearly show the effect of TM9SF proteins on PDL1 protein regulation. For flow cytometry data, isotype controls for PDL1 staining should be included. The authors suggest that increased IFN-g and CD107a indicates activated T cells, although other T cell activation markers are not shown. Again in S1G, a unstim control for IFNg and a FMO or isotype control for S1H is required along with quantification of the MFI or frequency of CD107a. It is not clear what Relative CD107 level means in Fig.1K? Could this be clarified? In S1D, a better labelling of the images would be helpful. In the text, the authors state that PDl1 neturalization showed tumor growth inhibition in S1E-F. E and F are apoptosis assays with Annexin. Need more clarity here on whether there is a in-vivo dataset that is missing or this is an explanation/discussion of the downstream outcome of the data shown in Fig. S1E-F.\nFigure 2, the study utilises B16 and C1498 cells as in-vivo models while the lung cancer cell line used for initial identification of TM9SF2 is not utilised. An explanation for the choice of the in-vivo models would be helpful. I presume this is because B16 is a very good model of PDL1/PD1 mediated tumor escape and hence was chosen. This section requires better clarity. Fig.2A-E not just represents tumor volume and clinical data, it also incorporates an anti-CD8 blocking regimen suggesting that CD8s are important for tumor inhibition. It is not clear how PDL1 regulation in the tumors can affect CD8 T cell function without knowing the PD1 expression on CD8s or the phenotype of the CD8+ T cells such as are the T cell less exhausted? Please expand on this data if possible. The authors then continue to overexpress TM9SF2 and then measure the expression of PDL1, tumor size with anti-PDL1 and some T cell efficacy markers. The western blots in S2 needs to be quantified.\nFigure 3, The westerns need quantification prior to concluding on these observations. Not clear what Relative PDL1 level means in K, is this MFI or frequency? Isotype controls are required in D, E and K. Similar issues prevail throughout figure 3 and figure 4, making it hard to definitively conclude the observations. Include CD8 exhaution markers to demonstrate enhance CD8 T cell activity, PD1 expression on CD8s is not shown throughout the ms which is key to enhanced immunity.\nIn figure 4, the images need to be quantified in 4E,similar issues with western blots. Similar issues with quantifications in Fig.5 for observations to be valid. In Figure 6L, what groups are being compared for stats, similar queries regarding m and n. Quantify data in 7E and include isotype control in 7F.\nThere are several interesting observations here in this manuscript which is important for both understanding the regulation of PDL1 protein and for tumor immunity, but it is overshadowed by lack of appropriate controls. Adding controls, enhancing the characterisation of the CD8+ T cell subsets will significantly improve the clarity of the manuscript.", "reviewer_2": "Summary\nThe authors present a compelling study delineating the role of the TM9SF2–PGK1 axis in regulating PD-L1 trafficking and anti-tumor immunity. Through a combination of genetic, biochemical, and in vivo approaches, the study reveals that ceramide treatment disrupts the TM9SF2–PGK1 interaction, promoting PD-L1 lysosomal degradation and enhancing CD8+ T cell-mediated responses. The study introduces a novel regulatory mechanism of immune checkpoint trafficking and has potential translational relevance.\nThe manuscript is generally well-conducted and well-written, but several points require clarification, additional analysis, or experimental validation.\nMajor Comments\n1. Fig. 1G, Line 89) While the data show reduced PD-L1 levels following TM9SF2 deletion, it remains unclear whether this is due to impaired stability or reduced translation. The authors should provide evidence distinguishing between these possibilities.\n2. Fig. 1I) It would be important to clarify whether the genetic deletion of TM9SF2 impacts tumor cell viability in the absence of T cells. This would help determine whether the observed phenotype is immune-mediated or includes cell-autonomous effects.\n3. Figs. 2F and 2J) Please replace the bar graphs representing MFI or PD-L1 positive cell frequency to make consents with representative histogram plot.\n4. Fig. 2K) TM9SF2-overexpressing tumor cells show increased PD-L1, which theoretically should enhance responsiveness to anti–PD-L1 therapy. However, this was not observed. The authors should provide an explanation for this discrepancy—possibly related to PD-L1 trafficking/localization or compensatory immune-suppressive mechanisms.\n5. Line 110) The rationale for selecting TM9SF2 as the overexpressed target in tumor cells should be explicitly explained. Was this based on expression patterns, functional data, or screening results?\n6. Lines 113–114) The manuscript states that tumor-infiltrating CD8+ T cells exhibit decreased CD107a in TM9SF2-OE tumors, but Figure S2T shows increased CD107a expression. Please reconcile this discrepancy and revise the text accordingly.\n7. Lines 114–115) To support the claim that anti–PD-L1 treatment restores T cell function in TM9SF2-OE tumors, please provide statistical analysis comparing TM9SF2-OE with and without anti–PD-L1 treatment.\n8. Lines 168) Clarify why the authors came up with IFN-γ stimulation, and its biological meaning.\n9. Specificity of TM9SF2–PGK1–PD-L1 Axis\n• Would the regulatory effect of the TM9SF2–PGK1 axis be abolished in PD-L1 KO tumors? Since lysosomal degradation is a general pathway, it is worth discussing whether other immune-related surface proteins, especially pro-tumorigenic molecules, might also be regulated by this axis.\n• Furthermore, does this axis modulate the ubiquitination of PD-L1 prior to lysosomal targeting? If available, ubiquitination assays would be valuable to assess upstream regulation.\n10. Phenotypic Characterization of CD8+ T Cells in TM9SF2-OE Tumors Please demonstrate whether the CD8+ T cells infiltrating TM9SF2-OE tumors are functionally exhausted (e.g., PD-1, Tim-3, and TOX). This would add mechanistic depth to the immune phenotype described.\nMinor Comments\n1. Figure 1F) Consider repositioning the figure to sit adjacent to Figure 1E to improve visual continuity.\n2. Clarify abbreviations (e.g., OE, MFI) and standardize gene/protein symbols throughout the manuscript.\n3. Figure Legends) Add specific descriptions of what each bar graph represents, and include N numbers and statistical test details.\n4. Figure 1J, 1K, 2L, 2M, 3V, 3W, 6M, 6N) Add FACS plot of (%) IFN-γ+, (%) CD107a+ cell to enhance credibility.\n5. Figure 4, 6, 7) Add specific descriptions of what ‘Gray value vs Distance’ and green and red lines represent to aid reader comprehension.", "reviewer_3": "The study identifies the TM9SF2–PGK1 complex as a \"molecular switch\" that sustains PD-L1 plasma-membrane localization by antagonizing HIP1R-mediated lysosomal degradation. It further establishes a novel \"ceramide-gated sorting\" paradigm in which the specific ceramide Cer(d18:1/26:0) dissociates TM9SF2–PGK1, rerouting PD-L1 from recycling to degradation and thereby linking sphingolipid metabolism to immune-checkpoint control. The work is conceptually innovative and clinically relevant, is logically organized, and is written in clear, fluent language. Nevertheless, several issues merit clarification and additional experimentation:\n1. Model selection for in vivo studies\nThe CRISPR screen was initially performed in human non-small-cell lung cancer (NSCLC) H460 cells. However, subsequent mouse experiments employed B16 melanoma and C1498 acute myeloid leukemia (AML) models rather than H460-derived xenografts. The rationale for this choice should be explicitly stated; in particular, whether immunodeficient hosts are required for H460 engraftment, or whether B16/C1498 cells provide unique advantages for studying CD8^+ T cell–mediated immunity in fully immunocompetent C57BL/6J mice.\n2. Documentation of PGK1 phosphorylation\nThe manuscript proposes that IFN-γ-induced phosphorylation of PGK1 at Ser203 governs its subcellular trafficking and interaction with TM9SF2. Key figures (e.g., Fig. 3B, 3F, 3G) should therefore include direct assessment of phospho-Ser203-PGK1 levels by immunoblot or phospho-specific antibodies to substantiate this mechanistic claim.\n3. Molecular mechanism of Cer(d18:1/26:0)-mediated disruption\nThe precise mechanism by which Cer(d18:1/26:0) uncouples TM9SF2–PGK1 remains undefined. Future work should:\n(i) Employ liposome pull-down assays to test whether Cer(d18:1/26:0) binds directly to defined domains of TM9SF2 (e.g., transmembrane regions) or PGK1 (e.g., vicinity of Ser203).\n(ii) Investigate whether ceramide enrichment alters the partitioning of TM9SF2/PGK1 within lipid rafts or other membrane microdomains.\n4. Validation in patient-derived organoids (PDOs)\nWhile Figure 7 uses patient-derived lung cancer cells, the translational impact would be strengthened by testing DC-PGKI or Cer(d18:1/26:0) in matched patient-derived tumor organoids co-cultured with autologous T cells. Such PDO–T-cell co-culture systems can more faithfully model the human tumor microenvironment and provide a platform for evaluating whether these compounds overcome resistance to PD-1/PD-L1 blockade.", "reviewer_4": "This manuscripts reveals that ceramide enhances anti-tumor immunity by disrupting the TM9SF2-PGK1 axis, which normally promotes PD-L1 recycling. This disruption redirects PD-L1 to the lysosomes for degradation, hence offering a potential therapeutic target to enhance the efficacy of cancer immunotherapies. This manuscript is well written and the experiments are both comprehensive and rigorous. Nevertheless, I have several concerns that I would like the authors to address.\n1. The starting point of this study is the anti-PD-L1 resistance, which indeed poses major challenges for immune checkpoint inhibitor therapies. But the role of PD-L1 recycling on clinical resistance seems neither dominant nor clearly defined in the text: Clinically, resistance refers to an initial tumor response followed by disease progression after months of treatment—driven by multifactorial processes such as T cell exclusion, exhaustion, or other immunosuppressive mechanisms. By contrast, PD-L1 trafficking occurs on much shorter, cellular timescales that may not directly correlate with the onset of clinical relapse.\nI suggest the authors should clarify such conceptual ambiguity and provide evidence for whether PD-L1 recycling elevation is primary or acquired after receiving the therapy for a certain period time. If necessary, the motivation of the study should be reframed to distinguish between these two scenarios.\n2. While the genetic and pharmacological perturbations of TM9SF2 convincingly show its role in sustaining PD-L1 levels and mediating immune evasion, the manuscript lacks a critical experiment. Specifically, the authors should perform a PD-L1 add-back rescue in TM9SF2-knockout cells (or tumors) to demonstrate that re-expression of PD-L1 restores surface expression, reverses enhanced T cell killing, and rescues the tumor growth phenotype. Without this experiment, the causal link “TM9SF2→PD-L1→immune suppression” remains incomplete.\n3. Could the authors clarify why TM9SF2 was specifically selected for investigation, rather than other members of the TM9SF gene family? If there is a particular rationale (e.g., prior evidence, differential expression, unique function), it would be helpful to state it clearly. If not, a brief discussion on this choice—acknowledging the potential roles of other family members—would still strengthen the manuscript, either in the main text or the Discussion section.\n4. The flow cytometry analysis of PD-L1 following therapeutic anti–PD-L1 antibody treatment requires careful epitope selection to avoid artifactual signal loss due to competition or masking by the therapeutic antibody. The current manuscript and figure legends (Figure 2F, J) do not specify which detection clone was used, nor whether it binds a non-overlapping epitope. I recommend the authors (1) identify and validate a PD-L1 detection antibody clone that does not compete with the therapeutic anti–PD-L1, (2) clearly annotate this information in the Methods and figure legends to ensure that measured PD-L1 changes reflect true expression dynamics rather than epitope masking.\n5. In Fig. 1B, most of the differentially detected screens show positive LFC values, with only a small number exhibiting negative LFCs. The authors should double-check the analysis to ensure this asymmetry is not due to technical or statistical bias. If the skew is genuine, it warrants explanation—e.g., whether it reflects a biological trend or a limitation of the screening method.\nAdditionally, for improved clarity and context, the figure could include the total number of screens analyzed as well as the number of hits that passed the significance threshold (e.g., p < 0.05). This would help readers better interpret the robustness and distribution of the findings.\n5. there are also some minor expression issues, such as (1) indicate R packages and their versions used in the analysis instead of vaguely say \"analyzed using R software\" in Line 1023; (2) \"Similary\" should be \"Similarly\" in Line 415; (3) \"remains\" in Line 320 .", "reviewer_5": "In this manuscript, the authors identified TM9SF2 as a key regulator of PD-L1 levels using a CRISPR screen targeting glycosphingolipid metabolism. It was demonstrated here that TM9SF2 recruits PGK1 to promote PD-L1 recycling to the plasma membrane, while dismantling the HIP1R-mediated lysosomal degradation pathway. Genetic or pharmacological disruption of the TM9SF2-PGK1 complex depleted PD-L1 levels and enhanced antitumor immunity. Moreover, the endogenous ceramide species Cer(d18:1/26:0) destabilized this complex, triggering PD-L1 lysosomal destruction and potentiating antitumor immunity. These findings suggest that a ceramide-gated sorting mechanism within the endosomal network plays a role in PD-L1 recycling, revealing a druggable metabolic switch that can disrupt immune evasion and enhance checkpoint blockade efficacy.\nAlthough this manuscript provides some interesting data, the mechanistic aspects of how TM9SF2 regulates ceramide synthesis and how ceramide is involved in PD-L1 regulation remain unknown. For example, TM9SF2 is known to regulate the synthesis of ganglioside GM3 (Gb3). However, the role of Gb3 in PD-L1 expression in response to TM9SF2 alterations was not examined in this manuscript. Although there is an interesting upregulation of some ceramides, including C18:1-ceramide, in response to TM9SF2 knockdown, whether this is due to any ceramide synthase function was not described. This is a missed opportunity, as a recent publication (Wofford et al., Cell Reports, 2024) has shown that alterations in C18-ceramide synthesis by CerS4 induce PD-L1 internalization and signaling for cancer metastasis. To this end, the quantification of ceramides and expression levels of ceramide-synthesizing enzymes also need to be provided in these studies.\nAnother point that needs to be addressed is the effects of anti-PD-L1 antibody on tumor growth inhibition and anti-tumor immunity in response to TM9SF2 knockdown versus overexpression. For example, authors demonstrated that an anti-PD-L1 antibody phenocopied the effects of TM9SF2 knockdown in inducing apoptosis (Fig. S1D-F). However, they also showed that the anti-PD-L1 antibody induced immunity in TM9SF2 overexpressing tumors, which may be attributed to higher surface expression levels of PD-L1. These in vitro vs. in vivo effects of anti-PD-L1 antibody on cell death vs immunity in response to TM9SF2 regulation and involvement of ceramide in these effects need to be determined.\nThere are also some minor but important points, particularly the lack of quantification in some Western blots (e.g., Figs. 1E-G).\nNevertheless, this is an interesting study."}, "author_response": "Dear Reviewers,\nWe are grateful to the reviewers for their valuable feedback, which has been\ninstrumental in improving our manuscript. In response, we have carefully revised the\ntext to ensure precise alignment with our experimental findings and have incorporated\nadditional experiments to strengthen our conclusions.\nBelow, we provide detailed responses to each of your comment.\nPoint-by-point Response\nReviewer #1 (Remarks to the Author):\nThe work by Zheng et al demonstrates that PD-L1 trafficking to lysosomes is controlled\nby the TM9SF2-PGK1 axis which can be disrupted by the ceramide species\nCer(d18:1/26:0). The work is important as it adds value to understanding how co-\nreceptors and their respective ligands such as PDL-1 are regulated within the tumor\ncells. Although several key aspects of tumor biology and relevant immunity related data\nis shown in the manuscript, there is a marked terseness in explaining the results. The\nmanuscript would substantially benefit from increasing clarity through explaining their\ndataset. Also, it is not clear how blocking ceramide and increasing PD-L1 degradation\ncan enhance ICB efficacy, it does provide a new therapeutic pathway to enhance anti-\ntumor immunity since PD-1 on effector T cells will not have a cognate ligand available\nto bind and dampen effector responses inhibiting tumour escape. A further explanation\non how the authors envision this process would enhance clarity of their reasoning.\n1. In Figure 1, the authors perform a CRISPR-Cas9 KO to screen for genes involved in\nthe sphingolipid synthesis pathway within the H460- non small cell lung cancer cell\nlines. Using this approach they find TM9SF2 to be a key target in PDL1 protein\nmaintenance. Several western blots are shown in Fig. 1c, e, g, h. All of these western\ndata need to be quantified in order to clearly show the effect of TM9SF proteins on\nPDL1 protein regulation.\nResponse: Thank you for your suggestion. We have performed quantitative analysis of\nall western blot results presented in Fig. 1c, e, g, and h (See Reviewer Figure 1).\nAccordingly, we have included these quantitative data in the revised manuscript as Fig.\n1I, S1A, S1C and S1F.\nReviewer Figure 1. (A) PD-L1 expression in sgNTC and sgTM9SF1-4 H460 cells was\nanalyzed by Western blot. Right: Quantitative analysis. NTC: No Template Control. (B)\nWestern blot assessment to evaluate PD-L1 expression in H460 cells overexpressing\nFLAG-tagged TM9SF1-4 versus empty vector (EV). FLAG antibody is used for the\ndetection of TM9SF1/3/4. TM9SF2 antibody is used for the detection of TM9SF2.\nRight: Quantitative analysis. (C) The lifetime (top) and quantification (bottom) of PD-\nL1 was assessed in sgNTC and sgTM9SF1-4 H460 cells administered cycloheximide\n(CHX, 25 µg/mL) over time. PD-L1 levels were standardized to GAPDH. (D) Western\nblot analysis (left) and quantification (right) of TM9SF2 and PD-L1 protein levels in\nsgTM9SF2 and sgNTC H460 cells. GAPDH was used as a loading control.\n2. For flow cytometry data, isotype controls for PDL1 staining should be included. The\nauthors suggest that increased IFN-g and CD107a indicates activated T cells, although\nother T cell activation markers are not shown.\nResponse: Thank you for your suggestion. For all PD-L1 surface FACS assays, we\nhave included matched isotype control, and the corresponding representative flow\ncytometry plots have been updated in the revised manuscript. In addition to the\npreviously measured T cell activation markers (IFN-γ and CD107a), we have further\nassessed the exhaustion phenotype of CD8+ T cells by examining the expression of PD-\n1, Tim-3, and TOX. Compared to control tumors, TM9SF1-4-knockdown B16 tumors\nexhibited significantly reduced proportions of PD-1+, Tim-3+, and TOX+ CD8+ T cells\n(Reviewer Figure 2A). Similarly, PGK1-knockdown B16 tumors also showed a marked\ndecrease in PD-1⁺, Tim-3⁺, and TOX⁺ CD8⁺ T cell infiltration (Reviewer Figure 2B).\nWe have included these results in the revised manuscript as Fig. S2P and 3P.\nReviewer Figure 2. (A) Flow cytometry analysis of PD-1, Tim-3 and TOX levels in\ntumor-permeating CD8+ T cells in control and TM9SFs-knockdown B16 tumors (n =\n5). (B) Flow cytometry analysis of PD-1, Tim-3 and TOX levels in tumor-permeating\nCD8+ T cells in control and PGK1-knockdown B16 tumors (n=5).\n3. Again in S1G, a unstim control for IFNg and a FMO or isotype control for S1H is\nrequired along with quantification of the MFI or frequency of CD107a. It is not clear\nwhat Relative CD107 level means in Fig.1K? Could this be clarified?\nResponse: We thank the reviewer for this question. In response, we have included the\nunstimulated controls for IFN-γ and the FMO/isotype controls for CD107a in our flow\ncytometry analysis (Reviewer Figure 3). These data are now presented as Fig. S1J-K,\nrespectively, in the revised manuscript. Furthermore, to prevent any ambiguity, we have\nreplaced the \"Relative CD107a level\" with the specific metric of \"CD107a MFI (Mean\nFluorescence Intensity)\" in the updated Fig. S2U.\nReviewer Figure 3. For A-C, activated T cells were co-cultured with H460 cells\ntransduced using TM9SF2-targeting sgRNA or control sgRNA. (A) Representative dot\nplots of IFN-γ expression in CD8+ T cells (n = 5). (B) Representative histograms of\nCD107a expression in CD8+ T cells (n = 5). (C) Quantitative analysis of (B).\n4. In S1D, a better labelling of the images would be helpful.\nResponse: We apologize for the lack of clarity in the labeling in Figure S1D. The labels\nand annotations have been revised to improve clarity and are presented in Fig. S1G in\nthe revised manuscript (see Reviewer Figure 4).\nReviewer Figure 4. Crystal violet staining assay showing T-cell cytotoxicity in\nTM9SF2-knockout H460 cells following activated T cells co-culture. NTC: No\nTemplate Control.\n5. In the text, the authors state that PD-L1 neutralization showed tumor growth\ninhibition in S1E-F. E and F are apoptosis assays with Annexin. Need more clarity here\non whether there is a in-vivo dataset that is missing or this is an explanation/discussion\nof the downstream outcome of the data shown in Fig. S1E-F.\nResponse: We thank the reviewer for this comment. In response, we have clarified the\ndescription of the co-culture model in Figures S1E-F. In this system, CD8⁺ T cells\nisolated from PBMCs were co-cultured with H460 tumor cells to evaluate cytotoxicity\nin the presence or absence of PD-L1 blockade. We found that both anti-PD-L1 treatment\nand TM9SF2 knockout reduced PD-L1 levels on tumor cells, thereby enhancing\nimmune-mediated tumor recognition and killing. This methodological approach is\nconsistent with previously established models (Huang et al, Signal transduction and\ntargeted therapy, 2023; Peng et al, Journal of extracellular vesicles, 2021; Man et al,\nBlood, 2023). Accordingly, the main text has been revised for clarity and now reads:\n\"Of note, PD-L1 neutralization with a clinically validated antibody phenocopied\nTM9SF2 knockout, achieving T cell-mediated tumor growth inhibition (Fig. S1H-I),\nthereby positioning TM9SF2 as a novel PD-L1-dependent immune evasion regulator.\"\n6. Figure 2, the study utilizes B16 and C1498 cells as in-vivo models while the lung\ncancer cell line used for initial identification of TM9SF2 is not utilized. An explanation\nfor the choice of the in-vivo models would be helpful. I presume this is because B16 is\na very good model of PDL1/PD1 mediated tumor escape and hence was chosen. This\nsection requires better clarity.\nResponse: We appreciate the reviewer's comment, which aligns with our consideration.\nAccordingly, we have revised the main text to provide a stronger rationale for our model\nselection.\n7. Fig.2A-E not just represents tumor volume and clinical data, it also incorporates an\nanti-CD8 blocking regimen suggesting that CD8s are important for tumor inhibition. It\nis not clear how PDL1 regulation in the tumors can affect CD8 T cell function without\nknowing the PD1 expression on CD8s or the phenotype of the CD8+ T cells such as are\nthe T cell less exhausted? Please expand on this data if possible. The authors then\ncontinue to overexpress TM9SF2 and then measure the expression of PDL1, tumor size\nwith anti-PDL1 and some T cell efficacy markers.\nResponse: We thank the reviewer for this question. We would like to clarify that the\nantitumor immune regulation mediated by TM9SF2 is strictly dependent on the\npresence of CD8⁺ T cells. This was demonstrated by the observation that the\nimmunostimulatory effect resulting from TM9SF2 knockout was completely abolished\nupon CD8⁺ T cell depletion. Furthermore, we have supplemented these findings with\nadditional experiments in the B16 tumor model, which showed that TM9SF2 knockout\nled to elevated CD8⁺ T cell activation (assessed by IFN-γ production and CD107a\nsurface expression) (revised Fig. S2N-O) and reduced T cell exhaustion, as evidenced\nby downregulated expression of markers including PD-1, Tim-3, and TOX (Reviewer\nFigure 5A). Importantly, the immunoregulatory function of TM9SF2 was also\nabrogated upon PD-L1 antibody treatment, suggesting that its role is mediated through\nthe regulation of PD-L1 expression (Reviewer Figure 5B-F).\nReviewer Figure 5. (A) Flow cytometry analysis of PD-1, Tim-3 and TOX levels in\ntumor-permeating CD8+ T cells in control and TM9SFs-knockdown B16 tumors (n =\n5). (B) Schematic of experimental procedures: For C-F, C57BL/6J mice\nsubcutaneously injected with B16 cells overexpressing TM9SF2 or EV control, with or\nwithout Anti-PD-L1 antibody treatment (200 μg on days 0, 3, 6, 9, and 12). (C)\nRepresentative images and tumor weights of B16 tumors isolated from mice with or\nwithout Anti-PD-L1 antibody treatment (n = 5). (D) Proportions of tumor-permeating\nCD8+ T cells in B16 tumors isolated from mice with or without Anti-PD-L1 antibody\ntreatment (n = 5). (E) Flow cytometry analysis of IFN-γ and CD107a levels in tumor-\npermeating CD8+ T cells in B16 tumors isolated from mice with or without Anti-PD-\nL1 antibody treatment (n = 5). (F) Flow cytometry analysis of PD-1, Tim-3 and TOX\nlevels in tumor-permeating CD8+ T cells in B16 tumors isolated from mice with or\nwithout Anti-PD-L1 antibody treatment (n = 5).\n8. The western blots in S2 needs to be quantified. Figure 3, The westerns need\nquantification prior to concluding on these observations.\nResponse: Thank you for your suggestion. We have performed quantitative analysis of\nall Western blot results presented in Fig. S2 and Fig. 3 (See Reviewer Figure 6).\nAccordingly, we have updated these data in Fig. S2H, S2L, S2R, 3C-D, 3K, S3H, S3Q\nand S3V.\nReviewer Figure 6. (A) Western blot analysis and quantification of PD-L1\nconcentrations in tumors from indicated mice. C57BL/6J mice received subcutaneous\ninjections of C1498 or B16 cells transduced with TM9SF2-targeting shRNA or control\nshRNA. CD8-depleting antibodies (200 μg per day) were administered 0, 3, 6, 9, and\n12 days in the treatment group. (B) Western blot analysis and quantification of PD-L1\nconcentrations in tumors from indicated mice. C57BL/6J mice were transplanted with\nB16 or C1498 cells transduced with shRNA targeting TM9SFs or control. (C) Western\nblot analysis and quantification of PD-L1 concentrations in tumors from indicated mice.\nC57BL/6J mice were transplanted with C1498 overexpressing TM9SF2 or EV control.\n(D-E) Western blot analysis and quantification of PGK1 and PD-L1 in H460 cells\ntransduced with PGK1 sgRNAs versus sgNTC or H460 cells overexpressing HA-\ntagged PGK1. (F-G) The half-life and quantification of PD-L1 was assessed in H460\ncells with PGK1 depletion or overexpression following treatment with cycloheximide\n(CHX, 25 µg/mL). (H) PD-L1 expression in control and PGK1-knockdown C1498 or\nB16 tumors analyzed using Western blot. (I) PD-L1 levels in tumor tissues from the\nindicated mice was analyzed by Western blot. C57BL/6J mice were subcutaneously\ninoculated with C1498 or B16 cells followed by daily intraperitoneal administration of\nDC-PGKI (5 and 10 mg/kg) for one week. (J) PD-L1 levels in C1498 tumors\noverexpressing PGK1 or EV were analyzed by Western blot.\n9. Not clear what Relative PDL1 level means in K, is this MFI or frequency? Isotype\ncontrols are required in D, E and K. Similar issues prevail throughout figure 3 and figure\n4, making it hard to definitively conclude the observations. Include CD8 exhaution\nmarkers to demonstrate enhance CD8 T cell activity, PD1 expression on CD8s is not\nshown throughout the ms which is key to enhanced immunity.\nResponse: We sincerely apologize for any lack of clarity. In Fig. 3K, the term “Relative\nPD-L1 level” refers to the fold change in PD-L1 expression normalized to the control\ngroups and we have revised the axis label to \"Normalized MFI\" (Chen et al, Cell, 2023).\nIsotype controls have been added to Fig. 3 and Fig. 4 (Reviewer Figure 7A-C). The\nrevised figures are now included in the updated manuscript as Fig. 3E, 3F, and 3M.\nFurthermore, to better assess the functional state of CD8⁺ T cells within the tumor\nmicroenvironment, we conducted additional flow cytometry analyses examining\nexhaustion markers (PD-1, Tim-3, and TOX) on CD8⁺ TILs from in vivo experiments\n(Reviewer Figure 7D-E).\nReviewer Figure 7. (A) Flow cytometry analysis of PD-L1 expression in control and\nPGK1-knockdown B16 tumors (n=5). (B-C) Representative histograms depicting PD-\nL1 surface expression in H460 cells transduced with PGK1 sgRNAs versus sgNTC or\nH460 cells overexpressing HA-tagged PGK1. (D) Flow cytometry analysis of PD-1,\nTim-3 and TOX levels in tumor-permeating CD8+ T cells in control and TM9SFs-\nknockdown B16 tumors (n = 5). (E) Flow cytometry analysis of PD-1, Tim-3 and TOX\nlevels in tumor-permeating CD8+ T cells in control and PGK1-knockdown B16 tumors\n(n=5).\n10. In figure 4, the images need to be quantified in 4E, similar issues with western blots.\nSimilar issues with quantifications in Fig.5 for observations to be valid. In Figure 6L,\nwhat groups are being compared for stats, similar queries regarding m and n.\nQuantify data in 7E and include isotype control in 7F. There are several interesting observations\nhere in this manuscript which is important for both understanding the regulation of\nPDL1 protein and for tumor immunity, but it is overshadowed by lack of appropriate\ncontrols. Adding controls, enhancing the characterization of the CD8+ T cell subsets\nwill significantly improve the clarity of the manuscript.\nResponse: We thank the reviewer for these valuable suggestions. In response, we have\nperformed the following additional analyses:\n(1) We have now demonstrated quantitative analysis of the immunofluorescence\nimages in Fig. 4 to better illustrate the colocalization of PD-L1 with CD147, RAB11,\nand LAMP1 (Reviewer Figure 8A-C). These updated figures are included in the revised\nmanuscript as Fig. 4E and 4H-I.\n(2) Densitometric quantification has been performed for the Western blot bands shown\nin Fig. 5 (Reviewer Figure 8D-H), and the results are now included in Fig. S5A-B, S5D\nand S5F of the revised manuscript.\n(3) In Fig. 6L, 6M, and 6N, all statistical comparisons were performed against the\nvehicle-treated control group. This has been explicitly stated in the revised figure\nlegends.\n(4) We have supplemented the Western blot data in Fig. 7E with quantitative bar charts\n(Reviewer Figure 8I-J), which are now included as Fig. S7D. Additionally, isotype\ncontrol FACS histograms have been added to Fig. 7F in the revised manuscript\n(Reviewer Figure 8K-L).\nReviewer Figure 8. (A) Immunofluorescence showing PD-L1 colocalization with\nRAB11 in sgPGK1 or sgTM9SF2 H460 cells versus sgNTC (PD-L1 in green, RAB11\nin red, DAPI in blue). Scale bar: 5 μm. The right panels display intensity profiles of\nPD-L1 versus RAB11 following the white line. (B-C) Immunofluorescence showing\ncolocalization of PD-L1 with plasma membrane marker CD147 (B) or lysosomal\nmarker LAMP1 (C) in sgPGK1 or sgTM9SF2 H460 cells versus sgNTC (PD-L1 in\ngreen, CD147/LAMP1 in red, DAPI in blue). Scale bars: 2 μm and 5 μm. Right panels\ndisplay the intensity profiles of PD-L1 versus CD147 and PD-L1 versus LAMP1 along\nthe white line. (D-E) Western blot analysis and quantitative analysis of HIP1R levels in\nsgPGK1 and sgTM9SF2 H460 cells versus sgNTC cells. (F) Half-life analysis (Top)\nand quantification (Bottom) of HIP1R abundance in CHX (25 μg/mL)-treated H460\ncells with PGK1 depletion or HA-PGK1 overexpression. (G-H) CHX-chase assay and\nquantification showing GFP-S1 and GFP-S2 protein levels over time in sgPGK1 or\nsgNTC H460 cells treated with CHX (25 μg/mL). (I) The expression of PD-L1,\nTM9SF2, PGK1, and HIP1R was analyzed via Western blot in cancer cells (T) treated\nwith DC-PGKI and Cer(d18:1/26:0). Cancer cells were isolated from lung cancer\npatients. (J) Quantification of (I). (K-L) Representative histograms and bar plots of\nsurface PD-L1 expression in cancer cells (T) treated with DC-PGKI and\nCer(d18:1/26:0).\nReviewer #2 (Remarks to the Author):\nSummary\nThe authors present a compelling study delineating the role of the TM9SF2–PGK1 axis\nin regulating PD-L1 trafficking and anti-tumor immunity. Through a combination of\ngenetic, biochemical, and in vivo approaches, the study reveals that ceramide treatment\ndisrupts the TM9SF2–PGK1 interaction, promoting PD-L1 lysosomal degradation and\nenhancing CD8+ T cell-mediated responses. The study introduces a novel regulatory\nmechanism of immune checkpoint trafficking and has potential translational relevance.\nThe manuscript is generally well-conducted and well-written, but several points require\nclarification, additional analysis, or experimental validation.\nMajor Comments\n1. Fig. 1G, Line 89) While the data show reduced PD-L1 levels following TM9SF2\ndeletion, it remains unclear whether this is due to impaired stability or reduced\ntranslation. The authors should provide evidence distinguishing between these\npossibilities.\nResponse: We thank the reviewer for their valuable suggestion. To determine whether\nthe observed decrease in PD-L1 expression following TM9SF2 knockout results from\nreduced protein stability or impaired translation, we performed a cycloheximide (CHX)\nchase assay in both sgTM9SF2 and sgNTC cells (Reviewer Figure 9, including\nquantification). The results revealed a significantly shortened half-life of PD-L1 in\nTM9SF2-deficient cells. To further elucidate the mechanism underlying this impaired\nstability, we examined the intracellular trafficking of PD-L1 using an antibody-based\ninternalization and recycling assay (revised Fig. 4B-D). We found that TM9SF2\ndeficiency specifically disrupts PD-L1 recycling from endosomes to the plasma\nmembrane, thereby redirecting it toward lysosomal degradation. Collectively, these\nresults demonstrate that TM9SF2 deletion attenuates PD-L1 expression primarily by\nperturbing its endosomal recycling and promoting lysosomal degradation, rather than\nby affecting its translation.\nReviewer Figure 9. The lifetime (top) and quantification (bottom) of PD-L1 was\nassessed in sgNTC and sgTM9SF1-4 H460 cells administered cycloheximide (CHX,\n25 µg/mL) over time. PD-L1 levels were standardized to GAPDH.\n2. Fig. 1I It would be important to clarify whether the genetic deletion of TM9SF2\nimpacts tumor cell viability in the absence of T cells. This would help determine\nwhether the observed phenotype is immune-mediated or includes cell-autonomous\neffects.\nResponse: We thank the reviewer for raising this important point. To determine whether\nTM9SF2 deletion exerts any cell-autonomous effects on tumor cell survival, we\ncompared the viability of sgNTC and sgTM9SF2 H460 cells under standard culture\nconditions in the absence of T cells. As shown in Reviewer Figure 10, no significant\ndifference in cell viability was observed. This result rules out cell-autonomous pro-\nsurvival effects of TM9SF2 and confirms that the previously observed enhancement in\nT cell-mediated cytotoxicity is indeed immune-dependent.\nReviewer Figure 10. Cell viability showing T-cell cytotoxicity in H460 cells with\nTM9SF2 depletion following activated T cells co-culture.\n3. Figs. 2F and 2J) Please replace the bar graphs representing MFI or PD-L1 positive\ncell frequency to make consents with representative histogram plot.\nResponse: We thank the reviewer for raising this point. We have replaced the bar graphs\nrepresenting MFI (see Reviewer Figure 11).We have updated the figure as Fig. 2F in\nthe revised manuscript.\nReviewer Figure 11. Flow cytometry analysis of PD-L1 expression in B16 tumors\nisolated from immunocompetent mice and CD8+ T cell-depleted mice (n = 5).\nC57BL/6J mice subcutaneously injected with B16 cells transduced with TM9SF2-\ntargeting shRNA or control, with or without CD8-depleting antibody treatment (200 μg\non days 0, 3, 6, 9, and 12).\n4. Fig. 2K) TM9SF2-overexpressing tumor cells show increased PD-L1, which\ntheoretically should enhance responsiveness to anti–PD-L1 therapy. However, this\nwas not observed. The authors should provide an explanation for this discrepancy—\npossibly related to PD-L1 trafficking/localization or compensatory immune-suppressive\nmechanisms.\nResponse: We thank the reviewer for raising this important question. Considering the\npossibility that the initial antibody dosage might have been insufficient to fully\nneutralize the PD-L1 upregulation induced by TM9SF2 overexpression, we repeated\nthe experiment with an increased dose of anti-PD-L1 antibody, escalating from 50 µg\nto 200 µg per mouse. At this higher dose, anti-PD-L1 treatment significantly reduced\ntumor volume, enhanced CD8⁺ T cell activity, and alleviated CD8⁺ T cell exhaustion in\nboth EV and TM9SF2-OE groups (Reviewer Figure 12). Crucially, no differences in\ntumor size, CD8⁺ T cell function, or exhaustion markers were detected between the anti-\nPD-L1-treated groups with or without TM9SF2 overexpression (Reviewer Figure 12).\nThese results collectively confirm that TM9SF2 promotes tumor immune evasion by\nstabilizing PD-L1 protein and consequently suppressing CD8⁺ T cell cytotoxicity.\nAccordingly, these data have been incorporated into the main text as Fig. 2J-N.\nReviewer Figure 12. (A) Schematic of experimental procedures: For B-F, C57BL/6J\nmice subcutaneously injected with B16 cells overexpressing TM9SF2 or EV control,\nwith or without Anti-PD-L1 antibody treatment (200 μg on days 0, 3, 6, 9, and 12). (B)\nRepresentative images and tumor weights of B16 tumors isolated from mice with or\nwithout Anti-PD-L1 antibody treatment (n = 5). (C) Proportions of tumor-permeating\nCD8+ T cells in B16 tumors isolated from mice with or without Anti-PD-L1 antibody\ntreatment (n = 5). (D) Flow cytometry analysis of IFN-γ and CD107a levels in tumor-\npermeating CD8+ T cells in B16 tumors isolated from mice with or without Anti-PD-\nL1 antibody treatment (n = 5). (E) Flow cytometry analysis of PD-1, Tim-3 and TOX\nlevels in tumor-permeating CD8+ T cells in B16 tumors isolated from mice with or\nwithout Anti-PD-L1 antibody treatment (n = 5).\n5. Line 110) The rationale for selecting TM9SF2 as the overexpressed target in tumor\ncells should be explicitly explained. Was this based on expression patterns, functional\ndata, or screening results?\nResponse: We thank the reviewer for this question. Our decision to focus on TM9SF2\nfor in-depth mechanistic investigation was based on the following key considerations:\nIn our initial genome-wide CRISPR/Cas9 screen targeting sphingolipid pathway genes,\nTM9SF2 emerged as a significantly enriched hit affecting PD-L1 surface expression\n(Reviewer Figure 13A-B). Subsequent validation confirmed that genetic ablation of\nTM9SF2 produced the most substantial reduction in PD-L1 levels among all TM9SF\nfamily members (TM9SF1-4) in H460 cells (Reviewer Figure 13C).\nTo directly compare the functional relevance of different TM9SF members in tumor\nimmune evasion, we performed parallel knockdown studies in immunocompetent\nmouse models. As shown in Fig. S2I-L of the revised manuscript, TM9SF2 knockdown\nexhibited superior antitumor efficacy and PD-L1 suppression compared to targeting\nother TM9SF members, establishing its dominant role in regulating PD-L1-mediated\nimmune evasion (Reviewer Figure 13D-E).\nReviewer Figure 13. (A) sgRNA representation in H460 cells before and after FACS\nsorting. (B) Significant hits identified from cellular screens are shown. LFC: The log2\nfold change of sgRNA. (C) PD-L1 expression in sgNTC and sgTM9SF1-4 H460 cells\nwas analyzed by Western blot. Right: Quantitative analysis. For D-E, a mouse tumor\nmodel using C57BL/6J mice transplanted with C1498 or B16 cells transduced with\nshRNA targeting TM9SFs or control. (D) Flow cytometry analysis of PD-L1 expression\nin control and TM9SFs-knockdown B16 tumors or C1498 tumors (n = 5). (E) PD-L1\nconcentrations in tumors from indicated mice were analyzed by Western blot.\n6. Lines 113–114) The manuscript states that tumor-infiltrating CD8+ T cells exhibit\ndecreased CD107a in TM9SF2-OE tumors, but Figure S2T shows increased CD107a\nexpression. Please reconcile this discrepancy and revise the text accordingly.\nResponse: We thank the reviewer for pointing this out. Upon thorough re-analysis of\nthe raw data, we identified an error in the group labeling in the original figure and\nsincerely apologize for this oversight. We have now corrected the labeling and\nreorganized the figure panels to accurately reflect the experimental groups (Reviewer\nFigure 14). The revised figure has replaced the original version and is now presented\nas Fig. S2U in the main text.\nReviewer Figure 14. Flow cytometry analysis of CD107a levels in tumor-permeating\nCD8+ T cells in C1498 tumors overexpressing TM9SF2 or EV (n = 5).\n7. Lines 114–115) To support the claim that anti–PD-L1 treatment restores T cell\nfunction in TM9SF2-OE tumors, please provide statistical analysis comparing\nTM9SF2-OE with and without anti–PD-L1 treatment.\nResponse: We thank the reviewer for this suggestion. As this point is consistent with\nthe fourth comment raised earlier, we have repeated the animal experiments with an\nadjusted anti-PD-L1 antibody dose. Specifically, we increased the dosage from 50 µg\nto 200 µg per mouse. At this elevated dose, anti-PD-L1 treatment significantly\nsuppressed tumor growth, enhanced CD8⁺ T cell activity, and alleviated T cell\nexhaustion in both EV and TM9SF2-OE groups (Reviewer Figure 15). Importantly, no\ndifferences in tumor size, CD8⁺ T cell function, or exhaustion marker expression were\nobserved between anti-PD-L1-treated groups with or without TM9SF2 overexpression\n(Reviewer Figure 15). Furthermore, anti-PD-L1 treatment effectively restores T cell\nfunction in TM9SF2-OE tumors (Reviewer Figure 15E-F). These results collectively\nconfirm that TM9SF2 promotes tumor immune evasion by stabilizing PD-L1 and\nconsequently suppressing CD8⁺ T cell-mediated cytotoxicity.\nReviewer Figure 15. (A) Schematic of experimental procedures: For B-E, C57BL/6J\nmice subcutaneously injected with B16 cells overexpressing TM9SF2 or EV control,\nwith or without Anti-PD-L1 antibody treatment (200 μg on days 0, 3, 6, 9, and 12). (B)\nRepresentative images and tumor weights of B16 tumors isolated from mice with or\nwithout Anti-PD-L1 antibody treatment (n = 5). (C) Proportions of tumor-permeating\nCD8+ T cells in B16 tumors isolated from mice with or without Anti-PD-L1 antibody\ntreatment (n = 5). (D) Flow cytometry analysis of IFN-γ and CD107a levels in tumor-\npermeating CD8+ T cells in B16 tumors isolated from mice with or without Anti-PD-\nL1 antibody treatment (n = 5). (E) Flow cytometry analysis of PD-1, Tim-3 and TOX\nlevels in tumor-permeating CD8+ T cells in B16 tumors isolated from mice with or\nwithout Anti-PD-L1 antibody treatment (n = 5).\n8. Lines 168) Clarify why the authors came up with IFN-γ stimulation, and its biological\nmeaning.\nResponse: We thank the reviewer for raising this important question regarding the use\nof IFN-γ stimulation in our study. Our rationale is based on the well-established role of\nIFN-γ as a primary inducer of PD-L1 expression within the tumor microenvironment\n(Blank et al, Cancer research, 2004; Spranger et al, Science translational medicine,\n2013; Abiko et al, Clinical cancer research, 2013). In our investigation, we sought not\nonly to examine the effect of TM9SF2 on basal PD-L1 levels in tumor cells but also to\nexplore its impact on inducible PD-L1 upregulation, thereby assessing the generality of\nits regulatory function over PD-L1 expression.\n9. Specificity of TM9SF2–PGK1–PD-L1 Axis\n• Would the regulatory effect of the TM9SF2–PGK1 axis be abolished in PD-L1 KO\ntumors? Since lysosomal degradation is a general pathway, it is worth discussing\nwhether other immune-related surface proteins, especially pro-tumorigenic molecules,\nmight also be regulated by this axis.\n• Furthermore, does this axis modulate the ubiquitination of PD-L1 prior to lysosomal\ntargeting? If available, ubiquitination assays would be valuable to assess upstream\nregulation.\nResponse: Thank you for your suggestion. We have addressed your question by\ninvestigating two key aspects: the specificity of PD-L1 regulation by the TM9SF2-\nPGK1 axis, and its potential dependence on ubiquitination-mediated degradation.\n(1) Since PGK1 has been reported to modulate the endosomal-lysosomal sorting of\nEGFR (Chu et al, Nature communications, 2024), we first evaluated whether the\nTM9SF2–PGK1 axis regulates EGFR degradation. Following EGF stimulation, we\nobserved that depletion of either TM9SF2 or PGK1, as well as Cer(d18:1/26:0)\ntreatment, significantly impaired EGFR degradation (Reviewer Figure 16B-C). This\nindicates that the TM9SF2-PGK1 axis broadly regulates membrane protein trafficking,\naffecting not only PD-L1 but also EGFR.\nTo further evaluate whether the effect of the TM9SF2-PGK1 axis depends specifically\non PD-L1, we examined tumor responses to anti-PD-L1 treatment. At an elevated dose,\nanti-PD-L1 significantly suppressed tumor growth, enhanced CD8⁺ T cell activity, and\nreduced T cell exhaustion in both EV and TM9SF2-OE groups (Reviewer Figure 16B-\nF). Notably, no differences were observed in tumor size, CD8⁺ T cell function, or\nexhaustion markers between TM9SF2-overexpressing and control groups after anti-\nPD-L1 treatment (Reviewer Figure 16B-F). These results confirm that TM9SF2\npromotes immune evasion primarily by stabilizing PD-L1 and thereby inhibiting CD8⁺\nT cell-mediated antitumor immunity.\n(2) To determine whether the TM9SF2–PGK1 axis regulates PD-L1 stability through\npre-lysosomal ubiquitination, we performed PD-L1 immunoprecipitation in TM9SF2-\nknockout, PGK1-knockout, and wild-type cells. The results showed that neither\nTM9SF2 nor PGK1 deficiency altered PD-L1 ubiquitination levels (Reviewer Figure\n16G-H), indicating that this axis does not regulate PD-L1 via pre-lysosomal\nubiquitination. Corresponding updates have been made in the results as Fig. S4B-C,\nmethods, and figure legends of the revised manuscript.\nReviewer Figure 16. (A) EGFR degradation kinetics in H460 cells following EGF\nstimulation under various pretreatment conditions. Cells were pre-treated for 40 hours\nby depleting PGK1/TM9SF2 (via sgRNA transduction) or by supplementing with\nCer(d18:1/26:0) (31.25 μM, cholPC-loaded), followed by EGF treatment for the\nindicated time points. (B) Schematic of experimental procedures: For C-F, C57BL/6J\nmice subcutaneously injected with B16 cells overexpressing TM9SF2 or EV control,\nwith or without Anti-PD-L1 antibody treatment (200 μg on days 0, 3, 6, 9, and 12). (C)\nRepresentative images and tumor weights of B16 tumors isolated from mice with or\nwithout Anti-PD-L1 antibody treatment (n = 5). (D) Proportions of tumor-permeating\nCD8+ T cells in B16 tumors isolated from mice with or without Anti-PD-L1 antibody\ntreatment (n = 5). (E) Flow cytometry analysis of IFN-γ and CD107a levels in tumor-\npermeating CD8+ T cells in B16 tumors isolated from mice with or without Anti-PD-\nL1 antibody treatment (n = 5). (F) Flow cytometry analysis of PD-1, Tim-3 and TOX\nlevels in tumor-permeating CD8+ T cells in B16 tumors isolated from mice with or\nwithout Anti-PD-L1 antibody treatment (n = 5). (G-H) Western blot analyses of PD-L1\nubiquitination in H460 cells with or without PGK1 or TM9SF2 depletion treated with\n10 μM MG132 for 8 hours.\n10. Phenotypic Characterization of CD8+ T Cells in TM9SF2-OE Tumors Please\ndemonstrate whether the CD8+ T cells infiltrating TM9SF2-OE tumors are functionally\nexhausted (e.g., PD-1, Tim-3, and TOX). This would add mechanistic depth to the\nimmune phenotype described.\nResponse: Thank you for your suggestion. We have supplemented the experiments with\nPD-1, Tim-3, and TOX staining of CD8⁺ tumor-infiltrating lymphocytes (TILs) and\nperformed quantitative analysis (Reviewer Figure 17). These data indicate that,\ncompared to normal tissues, TM9SF2-OE tumor tissues exhibit a higher proportion of\nPD-1⁺, Tim-3⁺, and TOX⁺ CD8⁺ T cells, suggesting that CD8⁺ T cells in TM9SF2-OE\ntumors display a more pronounced exhausted phenotype. Notably, anti-PD-L1\ntreatment effectively reversed this enhanced exhaustion phenotype in TM9SF2-OE\ntumors. Together, these findings suggest that TM9SF2 promotes tumor progression by\nstabilizing PD-L1 and impairing CD8⁺ T cell-mediated cytotoxicity. The corresponding\nfigures have been updated as Fig. 2N of the revised manuscript.\nReviewer Figure 17. Flow cytometry analysis of PD-1, Tim-3 and TOX levels in\ntumor-permeating CD8+ T cells in B16 tumors isolated from mice with or without anti-\nPD-L1 antibody treatment (n = 5). C57BL/6J mice subcutaneously injected with B16\ncells overexpressing TM9SF2 or EV control, with or without anti-PD-L1 antibody\ntreatment (200 μg on days 0, 3, 6, 9, and 12).\nMinor Comments\n1. Figure 1F) Consider repositioning the figure to sit adjacent to Figure 1E to improve\nvisual continuity.\nResponse: Thank you for your suggestion. We have reorganized the figure panels to\nenhance logical flow and readability.\n2. Clarify abbreviations (e.g., OE, MFI) and standardize gene/protein symbols\nthroughout the manuscript.\nResponse: Thank you for your suggestion. We have standardized all abbreviations\nthroughout the manuscript and defined them upon first use.\n3. Figure Legends) Add specific descriptions of what each bar graph represents, and\ninclude N numbers and statistical test details.\nResponse: Thank you for your suggestion. We have updated all figure legends to\ninclude sample sizes, specific statistical tests, and detailed graphical descriptions.\n4. Figure 1J, 1K, 2L, 2M, 3V, 3W, 6M, 6N) Add FACS plot of (%) IFN-γ+, (%)\nCD107a+ cell to enhance credibility.\nResponse: Thank you for your suggestion. We have included FACS gating strategies\nfor IFN-γ⁺, CD107a⁺, TOX+, PD-1+ and Tim-3+ CD8+ T cells in the supplemental\nmaterials corresponding to Fig. 1, Fig. 2, Fig. 3, and Fig. 6 (Reviewer Figure 18).\nReviewer Figure 18. The gating strategy of flow cytometry for IFN-γ⁺, CD107a⁺,\nTOX+, PD-1+ and Tim-3+ CD8+ T cells in tumors.\n5. Figure 4, 6, 7) Add specific descriptions of what ‘Gray value vs Distance’ and green\nand red lines represent to aid reader comprehension.\nResponse: Thank you for your suggestion. We have expanded the\n\"Immunofluorescence Imaging\" section in the Methods to detail our\nimmunofluorescence quantification approach for the intensity-distance curves in Fig. 4,\nFig. 6, and Fig. 7. As described previously (Ren et al, Nature communications, 2021),\nthis analysis utilized ImageJ's Plot Profile tool to measure fluorescence intensity\nvariations along annotated white lines in merged images, assessing co-localization\nthrough spatial distribution patterns of red and green fluorophores.\nReviewer #3 (Remarks to the Author):\nThe study identifies the TM9SF2–PGK1 complex as a \"molecular switch\" that sustains\nPD-L1 plasma-membrane localization by antagonizing HIP1R-mediated lysosomal\ndegradation. It further establishes a novel \"ceramide-gated sorting\" paradigm in which\nthe specific ceramide Cer(d18:1/26:0) dissociates TM9SF2–PGK1, rerouting PD-L1\nfrom recycling to degradation and thereby linking sphingolipid metabolism to immune-\ncheckpoint control. The work is conceptually innovative and clinically relevant, is\nlogically organized, and is written in clear, fluent language. Nevertheless, several issues\nmerit clarification and additional experimentation:\n1. Model selection for in vivo studies\nThe CRISPR screen was initially performed in human non-small-cell lung cancer\n(NSCLC) H460 cells. However, subsequent mouse experiments employed B16\nmelanoma and C1498 acute myeloid leukemia (AML) models rather than H460-derived\nxenografts. The rationale for this choice should be explicitly stated; in particular,\nwhether immunodeficient hosts are required for H460 engraftment, or whether\nB16/C1498 cells provide unique advantages for studying CD8^+ T cell–mediated\nimmunity in fully immunocompetent C57BL/6J mice.\nResponse: We appreciate the reviewer's comment. We employed B16 melanoma and\nC1498 acute myeloid leukemia (AML) models because these murine models provide\nsuperior capability for investigating CD8⁺ T cell-mediated immunity in C57BL/6J hosts.\nAccordingly, we have revised the main text to provide a stronger rationale for our model\nselection.\n2. Documentation of PGK1 phosphorylation\nThe manuscript proposes that IFN-γ-induced phosphorylation of PGK1 at Ser203\ngoverns its subcellular trafficking and interaction with TM9SF2. Key figures (e.g., Fig.\n3B, 3F, 3G) should therefore include direct assessment of phospho-Ser203-PGK1\nlevels by immunoblot or phospho-specific antibodies to substantiate this mechanistic\nclaim.\nResponse: Thank you for this suggestion. To directly address this point, we measured\np-Ser203-PGK1 levels using a phosphorylation-specific antibody against Ser203 of\nPGK1. Our data demonstrate that IFN-γ-induced phosphorylation of PGK1 at Ser203\nenhances its interaction with TM9SF2 and subsequently regulates PD-L1 expression\n(Reviewer Figure 19). These updated results are now presented in Fig. 3B and 3G-H of\nthe revised manuscript.\nReviewer Figure 19. (A) Co-immunoprecipitation assays validating the interactions\nbetween TM9SF2 and PGK1 in H460 cells after 48 hours of IFN-γ stimulation (100\nng/mL). (B) Co-immunoprecipitation assays demonstrating the association between\nTM9SF2 and PGK1 wild-type, S203D (phosphorylation-mimetic mutant), or S203A\n(phosphorylation-deficient mutant). (C) Western blot analysis of PD-L1 levels in\nPGK1-depleted H460 cells transfected with PGK1 wild type or phospho-mutants.\n3. Molecular mechanism of Cer(d18:1/26:0)-mediated disruption\nThe precise mechanism by which Cer(d18:1/26:0) uncouples TM9SF2–PGK1 remains\nundefined. Future work should:\n(i) Employ liposome pull-down assays to test whether Cer(d18:1/26:0) binds directly\nto defined domains of TM9SF2 (e.g., transmembrane regions) or PGK1 (e.g., vicinity\nof Ser203).\n(ii) Investigate whether ceramide enrichment alters the partitioning of TM9SF2/PGK1\nwithin lipid rafts or other membrane microdomains.\nResponse: Thank you for your suggestion. Our current co-immunoprecipitation data\ndemonstrate that Cer(d18:1/26:0) effectively disrupts the TM9SF2-PGK1 protein\ncomplex (revised Fig. 6I), modulates PD-L1 endosomal recycling and expression\n(revised Fig. 6B-C and 6J-L), and enhances anti-tumor immunity in mouse models\n(revised Fig. 6M-Q and S6F-K). We fully acknowledge that the liposome\nimmunoprecipitation approach you mentioned would provide more direct evidence for\ndefining the specific regulatory domains through which Cer(d18:1/26:0) targets the\nTM9SF2-PGK1 complex. However, despite several attempts, we were unable to\nsuccessfully establish the liposome IP technique due to technical limitations. Given the\ntime constraints for revision, we plan to address this important aspect in our future\nstudies.\n4. Validation in patient-derived organoids (PDOs)\nWhile Figure 7 uses patient-derived lung cancer cells, the translational impact would\nbe strengthened by testing DC-PGKI or Cer(d18:1/26:0) in matched patient-derived\ntumor organoids co-cultured with autologous T cells. Such PDO–T-cell co-culture\nsystems can more faithfully model the human tumor microenvironment and provide a\nplatform for evaluating whether these compounds overcome resistance to PD-1/PD-L1\nblockade.\nResponse: We sincerely appreciate your suggestion. We have validated the efficacy of\nCer(d18:1/26:0) and DC-PGKI modulation in patient-derived cells, observing\npromising regulatory effects (revised Fig. 7E-F). However, the establishment of\norganoid models remains beyond our current technical expertise. Although we have\nactively attempted collaborations with several specialized laboratories, we have not yet\nsucceeded in constructing a stable organoid system. We therefore plan to continue\ndeveloping this important capability in our future research.\n5. The authors employed a focused CRISPR sgRNA library that was specifically\ncurated to interrogate genes implicated in sphingolipid metabolism. By integrating\nfluorescence-activated cell sorting (FACS), they sought to identify sphingolipid\nmetabolic regulators governing cell-surface PD-L1 expression. Enrichment of sgRNAs\ntargeting TM9SF in cells exhibiting low PD-L1 levels indicated that these genes are\nindispensable for maintaining PD-L1 abundance in H460 cells. Although the CRISPR\nsgRNA sequences directed against the sphingolipid metabolic pathway are enumerated\nin Table S2, the library comprises only 50 genes. Consequently, it remains uncertain\nwhether this panel provides comprehensive coverage of the entire pathway. Indeed, the\nGO Biological Process Annotations 2025 dataset annotates 80 genes as participating in\nthe sphingolipid metabolic process (GO:0006665). Thus, despite the successful\nidentification of the TM9SF family via the CRISPR/Cas9 screen, the experimental\ndesign is inherently limited by the incomplete representation of sphingolipid metabolic\ngenes within the employed sgRNA library.\nResponse: Thank you for your comment. We acknowledge that our screening library\nwas relatively limited. Nevertheless, the TM9SF family emerged as a phospholipid-\nrelated regulator with significant PD-L1 modulatory activity and considerable\ntherapeutic potential. This finding suggests that phospholipid modulation represents a\npromising candidate strategy for PD-L1 regulation. In future studies, we plan to\nsystematically evaluate other molecules not covered in our initial screening for their\nimmunomodulatory functions.\nReviewer #4 (Remarks to the Author):\nThis manuscripts reveals that ceramide enhances anti-tumor immunity by disrupting\nthe TM9SF2-PGK1 axis, which normally promotes PD-L1 recycling. This disruption\nredirects PD-L1 to the lysosomes for degradation, hence offering a potential therapeutic\ntarget to enhance the efficacy of cancer immunotherapies. This manuscript is well\nwritten and the experiments are both comprehensive and rigorous. Nevertheless, I have\nseveral concerns that I would like the authors to address.\n1. The starting point of this study is the anti-PD-L1 resistance, which indeed poses\nmajor challenges for immune checkpoint inhibitor therapies. But the role of PD-L1\nrecycling on clinical resistance seems neither dominant nor clearly defined in the text:\nClinically, resistance refers to an initial tumor response followed by disease progression\nafter months of treatment—driven by multifactorial processes such as T cell exclusion,\nexhaustion, or other immunosuppressive mechanisms. By contrast, PD-L1 trafficking\noccurs on much shorter, cellular timescales that may not directly correlate with the\nonset of clinical relapse.\nI suggest the authors should clarify such conceptual ambiguity and provide evidence\nfor whether PD-L1 recycling elevation is primary or acquired after receiving the\ntherapy for a certain period time. If necessary, the motivation of the study should be\nreframed to distinguish between these two scenarios.\nResponse: We sincerely thank the reviewer for raising this important question. Our data\nindeed did not directly demonstrate a potential link between PD-L1 intracellular\ntrafficking and therapy resistance. Following a comprehensive literature review, we\nconfirmed that this specific relationship has not been experimentally established in\ncurrently published studies. To prevent potential misunderstanding, we have revised the\nIntroduction section to clarify that PD-L1 homeostasis is primarily regulated through\nsynthesis, endosomal recycling, and lysosomal degradation pathways. We now\nemphasize that disruption of this balance—whether through accelerated recycling or\nimpaired degradation—may lead to pathological PD-L1 accumulation, potentially\ncontributing to T cell dysfunction and immunotherapy resistance.\n2. While the genetic and pharmacological perturbations of TM9SF2 convincingly show\nits role in sustaining PD-L1 levels and mediating immune evasion, the manuscript lacks\na critical experiment. Specifically, the authors should perform a PD-L1 add-back\nrescue in TM9SF2-knockout cells (or tumors) to demonstrate that re-expression of PD-L1\nrestores surface expression, reverses enhanced T cell killing, and rescues the tumor\ngrowth phenotype. Without this experiment, the causal link “TM9SF2→PD-\nL1→immune suppression” remains incomplete.\nResponse: Thank you for your suggestion. In response, we established a T cell-H460\ntumor cell co-culture model. Our results demonstrated that TM9SF2 knockout in H460\ncells downregulated PD-L1 expression, enhanced T cell-mediated tumor cell killing,\nand reduced tumor cell viability. Conversely, these effects were abolished by\nsubsequent PD-L1 overexpression (Reviewer Figure 20A-B).\nIn contrast, TM9SF2 overexpression in H460 cells upregulated PD-L1, attenuated T\ncell-mediated cytotoxicity, and increased tumor cell survival. These effects were\nsimilarly reversed by treatment with an anti-PD-L1 antibody (Reviewer Figure 20C).\nIn vivo, anti-PD-L1 administration significantly inhibited tumor growth, enhanced\nCD8⁺ T cell activity, and alleviated T cell exhaustion in both empty vector and\nTM9SF2-overexpressing groups (Reviewer Figure 20D-H). Notably, no differences\nwere observed in tumor size, CD8⁺ T cell function, or exhaustion markers between\nTM9SF2-overexpressing and control groups after anti-PD-L1 treatment (Reviewer\nFigure 20D-H).\nCollectively, these findings provide compelling evidence supporting the causal\nrelationship “TM9SF2 → PD-L1” in regulating tumor immune evasion.\nReviewer Figure 20. (A) Cell viability showing PD-L1 overexpression reverses\nenhanced T cell-mediated cytotoxicity induced by TM9SF2 deficiency. sgNTC and\nsgTM9SF2 H460 cells were co-cultured with activated T cells and sgTM9SF2 cells\nwere pre-transfected with Flag-PD-L1 or empty vector for 48 hours before co-culture.\n(B) Western blot analysis of TM9SF2 and PD-L1 protein levels in cells in (A). (C) Cell\nviability was measured to assess T cell-mediated cytotoxicity in H460 cells\noverexpressing TM9SF2 or empty vector following co-culture with activated T cells,\nin the presence or absence of Anti-PD-L1 antibody (1 µg/mL). (D) Schematic of\nexperimental procedures: For E-H, C57BL/6J mice subcutaneously injected with B16\ncells overexpressing TM9SF2 or EV control, with or without Anti-PD-L1 antibody\ntreatment (200 μg on days 0, 3, 6, 9, and 12). (E) Representative images and tumor\nweights of B16 tumors isolated from mice with or without Anti-PD-L1 antibody\ntreatment (n = 5). (F) Proportions of tumor-permeating CD8+ T cells in B16 tumors\nisolated from mice with or without Anti-PD-L1 antibody treatment (n = 5). (G) Flow\ncytometry analysis of IFN-γ and CD107a levels in tumor-permeating CD8+ T cells in\nB16 tumors isolated from mice with or without Anti-PD-L1 antibody treatment (n = 5).\n(H) Flow cytometry analysis of PD-1, Tim-3 and TOX levels in tumor-permeating\nCD8+ T cells in B16 tumors isolated from mice with or without Anti-PD-L1 antibody\ntreatment (n = 5).\n3. Could the authors clarify why TM9SF2 was specifically selected for investigation,\nrather than other members of the TM9SF gene family? If there is a particular rationale\n(e.g., prior evidence, differential expression, unique function), it would be helpful to\nstate it clearly. If not, a brief discussion on this choice—acknowledging the potential\nroles of other family members—would still strengthen the manuscript, either in the\nmain text or the Discussion section.\nResponse: We thank the reviewer for this question. Our decision to focus on TM9SF2\nfor in-depth mechanistic investigation was based on the following key considerations:\nIn our initial genome-wide CRISPR/Cas9 screen targeting sphingolipid pathway genes,\nTM9SF2 emerged as a significantly enriched hit affecting PD-L1 surface expression\n(Reviewer Figure 21A-B). Subsequent validation confirmed that genetic ablation of\nTM9SF2 produced the most substantial reduction in PD-L1 levels among all TM9SF\nfamily members (TM9SF1-4) in H460 cells (Reviewer Figure 21C).\nTo directly compare the functional relevance of different TM9SF members in tumor\nimmune evasion, we performed parallel knockdown studies in immunocompetent\nmouse models. As shown in Fig. S2I-L of the revised manuscript, TM9SF2 knockdown\nexhibited superior antitumor efficacy and PD-L1 suppression compared to targeting\nother TM9SF members, establishing its dominant role in regulating PD-L1-mediated\nimmune evasion (Reviewer Figure 21D-E).\nReviewer Figure 21. (A) sgRNA representation in H460 cells before and after FACS\nsorting. (B) Significant hits identified from cellular screens are shown. LFC: The log2\nfold change of sgRNA. (C) PD-L1 expression in sgNTC and sgTM9SF1-4 H460 cells\nwas analyzed by Western blot. Right: Quantitative analysis. For D-E, a mouse tumor\nmodel using C57BL/6J mice transplanted with C1498 or B16 cells transduced with\nshRNA targeting TM9SFs or control. (D) Flow cytometry analysis of PD-L1 expression\nin control and TM9SFs-knockdown B16 tumors or C1498 tumors (n = 5). (E) PD-L1\nconcentrations in tumors from indicated mice were analyzed by Western blot.\n4. The flow cytometry analysis of PD-L1 following therapeutic anti–PD-L1 antibody\ntreatment requires careful epitope selection to avoid artifactual signal loss due to\ncompetition or masking by the therapeutic antibody. The current manuscript and figure\nlegends (Figure 2F, J) do not specify which detection clone was used, nor whether it\nbinds a non-overlapping epitope. I recommend the authors (1) identify and validate a\nPD-L1 detection antibody clone that does not compete with the therapeutic anti–PD-\nL1, (2) clearly annotate this information in the Methods and figure legends to ensure\nthat measured PD-L1 changes reflect true expression dynamics rather than epitope\nmasking.\nResponse: We sincerely thank the reviewer for raising this critical technical point\nregarding antibody epitope compatibility. In our initial experiments, we employed two\ndistinct anti-mouse PD-L1 clones: the therapeutic blocking antibody InVivoMAb anti-\nmouse PD-L1 (clone 10F.9G2, Bio X Cell #BE0101) for in vivo treatment, and the\ndetection antibody anti-mouse CD274 (clone MIH7, BioLegend #155404) for\nsubsequent flow cytometric analysis. We selected the MIH7 clone based on\nBioLegend's product specifications indicating that \"MIH7 does not block other CD274\nantibodies: clone MIH6 and 10F.9G2,\" which suggested non-overlapping epitopes and\ntheoretical compatibility. Indeed, in our preliminary experiments using a lower\nantibody dose (50 μg), we observed detectable signals that may have resulted from\nincomplete neutralization. However, after consulting with several immunology\nresearch groups, we were unable to obtain conclusive evidence regarding potential\ninterference between these antibody clones. Therefore, to ensure experimental accuracy\nand reliability, we have decided to discontinue this particular PD-L1 detection assay.\n5. In Fig. 1B, most of the differentially detected screens show positive LFC values, with\nonly a small number exhibiting negative LFCs. The authors should double-check the\nanalysis to ensure this asymmetry is not due to technical or statistical bias. If the skew\nis genuine, it warrants explanation—e.g., whether it reflects a biological trend or a\nlimitation of the screening method.\nAdditionally, for improved clarity and context, the figure could include the total number\nof screens analyzed as well as the number of hits that passed the significance threshold\n(e.g., p < 0.05). This would help readers better interpret the robustness and distribution\nof the findings.\nResponse: We thank the reviewer for this valuable comment. We have carefully\ninvestigated the issue raised by the reviewer and determined that the observed effect\nresulted from excessive viral titer, which led to multiple viral particles infecting\nindividual cells. To address this, we repeated the experiment with an adjusted\nmultiplicity of infection (MOI) of 0.3 and performed two rounds of screening using the\nsgRNA library-transduced cells. In the first round, we selected cells with low PD-L1\nexpression, which were then expanded and subjected to a second round of screening to\nconfirm stable PD-L1 downregulation. Sequencing analysis revealed that VPS11 and\nVPS18 were among the top-ranked hits—consistent with our previous research—\nsupporting the reliability of the screening approach. Several TM9SF family members\nwere also identified, which subsequently became the focus of our validation studies\n(Reviewer Figure 22). We have represented the screened genes and significant hits with\n-Log10pValue in Fig. 1B-C of the revised manuscript.\nReviewer Figure 22. (A) sgRNA representation in H460 cells before and after FACS\nsorting. (B) Significant hits identified from cellular screens are shown. LFC: The log2\nfold change of sgRNA.\n6. there are also some minor expression issues, such as (1) indicate R packages and\ntheir versions used in the analysis instead of vaguely say \"analyzed using R software\"\nin Line 1023; (2) \"Similary\" should be \"Similarly\" in Line 415; (3) \"remains\" in Line\n320 .\nResponse: We thank the reviewer for this suggestion and sincerely apologize for any\nconfusion caused. We have now specified the version of the R package used (version\n4.1.0) in the revised manuscript. Additionally, we have carefully reviewed the entire\ntext to correct spelling and grammatical errors.\nReviewer #5 (Remarks to the Author):\nIn this manuscript, the authors identified TM9SF2 as a key regulator of PD-L1 levels\nusing a CRISPR screen targeting glycosphingolipid metabolism. It was demonstrated\nhere that TM9SF2 recruits PGK1 to promote PD-L1 recycling to the plasma membrane,\nwhile dismantling the HIP1R-mediated lysosomal degradation pathway. Genetic or\npharmacological disruption of the TM9SF2-PGK1 complex depleted PD-L1 levels and\nenhanced antitumor immunity. Moreover, the endogenous ceramide species\nCer(d18:1/26:0) destabilized this complex, triggering PD-L1 lysosomal destruction and\npotentiating antitumor immunity. These findings suggest that a ceramide-gated sorting\nmechanism within the endosomal network plays a role in PD-L1 recycling, revealing a\ndruggable metabolic switch that can disrupt immune evasion and enhance checkpoint\nblockade efficacy.\n1. Although this manuscript provides some interesting data, the mechanistic aspects of\nhow TM9SF2 regulates ceramide synthesis and how ceramide is involved in PD-L1\nregulation remain unknown. For example, TM9SF2 is known to regulate the synthesis\nof ganglioside GM3 (Gb3). However, the role of Gb3 in PD-L1 expression in response\nto TM9SF2 alterations was not examined in this manuscript.\nResponse: Thank you for your suggestion. We appreciate the reviewer's insightful\ncomments. Our findings establish that the TM9SF2-PGK1 complex orchestrates PD-\nL1 trafficking by redirecting it to recycling endosomes, thereby bypassing lysosomal\ndegradation. Our study did not investigate whether TM9SF2 affects ceramide synthesis.\nHowever, our results demonstrate that Cer(d18:1/26:0) disrupts the TM9SF2-PGK1\ncomplex and consequently modulates PD-L1 expression levels, and the relevant\nexperimental evidence will be presented in detail in the following question. Considering\nTM9SF2's established role in ganglioside GM3 (Gb3) biosynthesis, we examined its\npotential involvement in TM9SF2-mediated PD-L1 recycling. Following 30-hour\ntreatment with escalating Gb3 concentrations, both wild-type and TM9SF2-KO cells\nexhibited dose-dependent reduction of PD-L1 protein levels with nearly identical\ndegradation kinetics (Reviewer Figure 23). These results demonstrate conclusively that\nTM9SF2 regulates PD-L1 stability through a mechanism independent of Gb3 synthesis.\nThe corresponding data have been incorporated as Fig. S6E in the revised manuscript.\nReviewer Figure 23. Western blot analysis and quantification of PD-L1 levels in\nsgNTC and sgTM9SF2 H460 cells treated with 0, 2, or 10 μM Gb3 for 30h.\n2. Although there is an interesting upregulation of some ceramides, including C18:1-\nceramide, in response to TM9SF2 knockdown, whether this is due to any ceramide\nsynthase function was not described. This is a missed opportunity, as a recent\npublication (Wofford et al., Cell Reports, 2024) has shown that alterations in C18-\nceramide synthesis by CerS4 induce PD-L1 internalization and signaling for cancer\nmetastasis. To this end, the quantification of ceramides and expression levels of\nceramide-synthesizing enzymes also need to be provided in these studies.\nResponse: Thank you for your suggestion. Our study demonstrates that TM9SF2\nknockout significantly elevates Cer(d18:1/26:0) levels, as shown in Fig. 6A of the\nrevised manuscript. To elucidate the functional contribution of ceramide synthases to\nPD-L1 regulation, we systematically knocked out CERS1-6 in H460 cells. Genetic\nknockout of CERS3, the principal synthase responsible for Cer(d18:1/26:0) production,\nmarkedly enhanced PD-L1 protein expression, while CERS3 overexpression\nconversely reduced PD-L1 levels (Reviewer Figure 24A-C). Furthermore, CERS3\noverexpression effectively counteracted both the prolonged PD-L1 half-life and\ncompromised HIP1R stability induced by TM9SF2 or PGK1 overexpression,\nrecapitulating the effects of exogenous Cer(d18:1/26:0) treatment (Reviewer Figure\n24D-I). These findings, presented in Fig. 6D-H and S6A-D with revised legends in the\nrevised manuscript, establish that CERS3-derived Cer(d18:1/26:0) disrupts the\nTM9SF2-PGK1 interaction, thereby inhibiting PD-L1 endosomal recycling and\npromoting its lysosomal degradation.\nReviewer Figure 24. (A-B) PD-L1 levels assessed via Western blot in sgNTC and\nsgCERS1-6 H460 cells. (C) PD-L1 expression analyzed via Western blot in H460 cells\noverexpressing CERS3 compared to vector control. (D-F) Half-life analysis and\nquantification of PD-L1 or HIP1R concentrations in H460 cells overexpressing\nTM9SF2 for the indicated time points following CHX (25 µg/mL) treatment. Cells\nunderwent pre-transfection with CERS3-FLAG for 24 hours or pre-treated using 31.25\nμM cholPC loaded with Cer(d18:1/26:0) for 40 hours. (G-I) Half-life analysis and\nquantification of PD-L1 or HIP1R concentrations in H460 cells overexpressing PGK1\nfor the indicated time points following CHX (25 µg/mL) treatment. The cells were pre-\ntransfection with CERS3-FLAG for 24 hours or pre-treated using 31.25 μM cholPC\nloaded with Cer(d18:1/26:0) for 40 hours.\n3. Another point that needs to be addressed is the effects of anti-PD-L1 antibody on\ntumor growth inhibition and anti-tumor immunity in response to TM9SF2 knockdown\nversus overexpression. For example, authors demonstrated that an anti-PD-L1 antibody\nphenocopied the effects of TM9SF2 knockdown in inducing apoptosis (Fig. S1D-F).\nHowever, they also showed that the anti-PD-L1 antibody induced immunity in TM9SF2\noverexpressing tumors, which may be attributed to higher surface expression levels of\nPD-L1. These in vitro vs. in vivo effects of anti-PD-L1 antibody on cell death vs\nimmunity in response to TM9SF2 regulation and involvement of ceramide in these\neffects need to be determined.\nResponse: Thank you for your question regarding whether the TM9SF2-PGK1 axis\nregulates tumor immune activity in a PD-L1-dependent manner. We have conducted the\nfollowing experiments to address this:\nFirst, in a T cell-H460 tumor cell co-culture model, our results demonstrated that\nTM9SF2 knockout in H460 cells downregulated PD-L1 expression, enhanced T cell-\nmediated tumor cell killing, and reduced tumor cell viability (revised Fig. 1J-N and\nS1F-K). Conversely, these effects were abolished by subsequent PD-L1 overexpression\n(Reviewer Figure 25A-B).\nIn contrast, TM9SF2 overexpression in H460 cells upregulated PD-L1, attenuated T\ncell-mediated cytotoxicity, and increased tumor cell survival. These effects were\nsimilarly reversed by treatment with an anti-PD-L1 antibody (Reviewer Figure 25C).\nFurthermore, in our in vivo mouse studies, anti-PD-L1 treatment significantly\nsuppressed tumor growth, enhanced CD8⁺ T cell activity, and reduced T cell exhaustion\nin both EV and TM9SF2-OE groups. Notably, no differences were observed in tumor\nsize, CD8⁺ T cell function, or exhaustion markers between TM9SF2-overexpressing\nand control groups after anti-PD-L1 treatment (Reviewer Figure 25D-H).\nThese results collectively confirm that TM9SF2 promotes immune evasion primarily\nby stabilizing PD-L1 and thereby inhibiting CD8⁺ T cell-mediated antitumor immunity.\nRegarding the role of Cer(d18:1/26:0) in the TM9SF2-PGK1-PD-L1 regulatory axis,\nwe have provided a comprehensive response to Question 2 above.\nReviewer Figure 25. (A) Cell viability showing PD-L1 overexpression reverses\nenhanced T cell-mediated cytotoxicity induced by TM9SF2 deficiency. sgNTC and\nsgTM9SF2 H460 cells were co-cultured with activated T cells and sgTM9SF2 cells\nwere pre-transfected with Flag-PD-L1 or empty vector for 48 hours before co-culture.\n(B) Western blot analysis of TM9SF2 and PD-L1 protein levels in cells in (A). (C) Cell\nviability was measured to assess T cell-mediated cytotoxicity in H460 cells\noverexpressing TM9SF2 or empty vector following co-culture with activated T cells,\nin the presence or absence of Anti-PD-L1 antibody (1 µg/mL). (D) Schematic of\nexperimental procedures: For E-H, C57BL/6J mice subcutaneously injected with B16\ncells overexpressing TM9SF2 or EV control, with or without Anti-PD-L1 antibody\ntreatment (200 μg on days 0, 3, 6, 9, and 12). (E) Representative images and tumor\nweights of B16 tumors isolated from mice with or without Anti-PD-L1 antibody\ntreatment (n = 5). (F) Proportions of tumor-permeating CD8+ T cells in B16 tumors\nisolated from mice with or without Anti-PD-L1 antibody treatment (n = 5). (G) Flow\ncytometry analysis of IFN-γ and CD107a levels in tumor-permeating CD8+ T cells in\nB16 tumors isolated from mice with or without Anti-PD-L1 antibody treatment (n = 5).\n(H) Flow cytometry analysis of PD-1, Tim-3 and TOX levels in tumor-permeating\nCD8+ T cells in B16 tumors isolated from mice with or without Anti-PD-L1 antibody\ntreatment (n = 5).\n4. There are also some minor but important points, particularly the lack of quantification\nin some Western blots (e.g., Figs. 1E-G).\nResponse: Thank you for your suggestion. We have incorporated quantitative analysis\nof all Western blot results in the revised manuscript and have correspondingly updated\nthe relevant figure legends.\nNevertheless, this is an interesting study."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have addressed all the comments raised.", "reviewer_2": "The authors have made substantial and commendable efforts to address the concerns raised in the initial round of review.\nThe revised manuscript now presents a cohesive and convincing mechanistic framework demonstrating how the TM9SF2–PGK1 axis regulates PD-L1 trafficking through endosomal recycling, and how disruption of this axis—either genetically or via Cer(d18:1/26:0)—promotes lysosomal degradation of PD-L1 and enhances CD8⁺ T cell–mediated antitumor immunity.\nThe authors further demonstrated that the regulatory effect of TM9SF2–PGK1 on membrane protein trafficking is not restricted to PD-L1. The additional experiments substantially reinforce the central conclusions and elevate the overall impact of the work.\nMinor issues:\n1. TOX gating (Reviewer Figure 18) is not convincing\nWhile the authors added gating strategies (Reviewer Figure 18), the TOX positive gate definition is not sufficiently justified.\n2. TIM-3 and PD-1 co-expression needs direct visualization and quantification\nTo better support the conclusion regarding reduced CD8⁺ T cell exhaustion, please quantify the frequency of TIM-3⁺PD-1⁺ double-positive cells among CD8⁺ TILs across all relevant groups (e.g., control vs TM9SF perturbation; control vs PGK1 perturbation; ± anti–PD-L1 if applicable). This should include:\n• a summary bar graph of TIM-3⁺PD-1⁺ (%) in CD8⁺ TILs with statistical testing; and\n• representative bivariate FACS plots (TIM-3 vs PD-1) for each group, with consistent gating and axis scaling, to allow visual validation of the shift in double-positive populations.", "reviewer_3": "The authors have adequately addressed the concerns and the manuscript has been greatly improved. I have no further questions.", "reviewer_4": "The revisions to the Introduction section are well-executed.\nThe authors have successfully performed the requested PD-L1 add-back rescue experiments in TM9SF2-knockout cells.\nThe results clearly demonstrate that re-expressing PD-L1 restores tumor cell survival and reverses the enhanced T-cell mediated cytotoxicity induced by TM9SF2 deficiency. This completes the \"TM9SF2 ->PD-L1 -> immune suppression\" causal chain.\nAlso I appreciate the authors' professional and honest approach regarding the potential for epitope.\nIn conclusion, the authors have addressed all my major and minor concerns with high-quality experimental data and rigorous analysis.", "reviewer_5": "The authors addressed all of my points adequately with additional experiments and new figures in the revised manuscript. I do not have any further comments."}, "author_response": "Dear Reviewers,\nWe are grateful to the reviewers for their valuable feedback, which has been\ninstrumental in improving our manuscript. In response, we have carefully revised the\ntext to ensure precise alignment with our experimental findings.\nBelow, we provide detailed responses to each of your comment.\nPoint-by-point Response\nReviewer #2 (Remarks to the Author):\nMinor issues:\n1. TOX gating (Reviewer Figure 18) is not convincing\nWhile the authors added gating strategies (Reviewer Figure 18), the TOX positive gate\ndefinition is not sufficiently justified.\nResponse: Thank you for your suggestion. We have included the gating strategy using\nisotype control and FMO control, which confirms that the threshold we used to define\nthe TOX-positive population is appropriate (See Reviewer Figure 1).\nReviewer Figure 1. Gating strategy for TOX.\n2. TIM-3 and PD-1 co-expression needs direct visualization and quantification\nTo better support the conclusion regarding reduced CD8⁺ T cell exhaustion, please\nquantify the frequency of TIM-3⁺PD-1⁺ double-positive cells among CD8⁺ TILs across\nall relevant groups (e.g., control vs TM9SF perturbation; control vs PGK1 perturbation;\n± anti–PD-L1 if applicable). This should include:\n• a summary bar graph of TIM-3⁺PD-1⁺ (%) in CD8⁺ TILs with statistical testing; and\n• representative bivariate FACS plots (TIM-3 vs PD-1) for each group, with consistent\ngating and axis scaling, to allow visual validation of the shift in double-positive\npopulations.\nResponse: Thank you for your suggestion. We appreciate the value of directly\nanalyzing the TIM-3⁺PD-1⁺ double-positive cell population for assessing T cell\nexhaustion. Our data show that in the key experimental groups, the frequencies of either\nTIM-3⁺ or PD-1⁺ cells demonstrate significant and consistent trends of change (refer to\nSupplementary Figure 2P, 2V, and 3N), which support our conclusion regarding the\nalteration in the exhaustion state."}]

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