Disrupting SRSF10-dependent BCAT2 Exon Skipping Reprograms Tumor-Associated Macrophages and Enhances Anti-PD-1 Efficacy in Gastric Cancer

Disrupting SRSF10-dependent BCAT2 Exon Skipping Reprograms Tumor-Associated Macrophages and Enhances Anti-PD-1 Efficacy in Gastric Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Disrupting SRSF10-dependent BCAT2 Exon Skipping Reprograms Tumor-Associated Macrophages and Enhances Anti-PD-1 Efficacy in Gastric Cancer Ping Li, Xiao-Bo Huang, Xin-Peng Yang, zhixiang Chen, Hua-Long Zheng, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7510487/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Aberrant alternative splicing (AS) in cancer generates oncogenic proteomic diversity that drives tumor progression. Given the suboptimal efficacy of immune checkpoint inhibitors (ICIs) in gastric cancer (GC), the therapeutic potential of modulating RNA splicing to augment immunotherapy remains unclear. Here, we demonstrate that the splicing factor SRSF10 is progressively upregulated during gastric tumorigenesis and exhibits elevated expression in ICIs-resistant GC. Utilizing multiple mouse models, we confirmed that SRSF10 ablation with a selective inhibitor 1C8 robustly inhibits GC growth and enhances CD8 + T-cell infiltration via CCL2-mediated reprogramming of tumor-associated macrophages (TAMs). Notably, SRSF10 blockade restricts pre-neoplastic metaplastic cells re-entry the cell cycle and the TAMs reprogramming. Mechanistically, cell-autonomous SRSF10 activates mTOR signaling primarily through inclusion of exon 2 in the BCAA transaminase 2 (BCAT2) mRNA. Pharmacological antagonism of SRSF10 potentiated the therapeutic effect of anti-PD-1 antibody in Tff1-CreERT 2 ; Apc fl/fl ; p53 fl/fl orthotopic GC models. Collectively, our findings revealed that SRSF10 orchestrates mTOR-CCL2 signaling by alternative RNA splicing of BCAT2 to reprogram TAMs, proposing SRSF10 as a tempting therapeutic target for GC immunotherapy. Biological sciences/Cancer/Gastrointestinal cancer/Gastric cancer Biological sciences/Cancer/Cancer microenvironment Serine/Arginine-rich Splicing Factor 10 Alternative Splicing Tumor-Associated Macrophage Immune Checkpoint Inhibitor Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapeutics, emerging as one of the most promising therapeutic strategies[ 1 , 2 ]. Despite approximately 30% of solid tumor patients achieve durable antitumor responses to ICIs treatment, clinical efficacy remains constrained by primary resistance or acquired resistance following initial response[ 1 – 4 ]. Compounding this challenge, gastric cancer (GC) manifests a profoundly heterogeneous malignancy characterized by substantial variability in its responsiveness to immunotherapy[ 5 – 8 ]. This variability underscores the urgent need to decipher the complex molecular underpinnings of ICIs refractoriness. The immunosuppressive tumor microenvironment (TME), characterized by abundant tumor-associated macrophages (TAMs), constitutes a major impediment to ICIs efficacy in malignancies including GC[ 9 , 10 ]. As pivotal components, TAMs encompass two functionally distinct subsets: immunosuppressive M2-polarized macrophages and pro-inflammatory M1 macrophages[ 11 – 13 ]. M2 macrophages perpetuate immunosuppression by secreting cytokines such as IL-10 and TGF-β, thereby dampening immune cell activity[ 11 – 13 ]. Conversely, M1 macrophages potentiate T-cell-mediated anti-tumor responses via molecules including CXCL9 and NOS2, facilitating tumor cell eradication[ 11 – 13 ]. Crucially, the inherent plasticity of macrophages presents a therapeutic opportunity to reprogram these cells toward a pro-inflammatory, antitumoral M1-like state, transforming immunologically "cold" tumors into "hot" tumors and enhancing ICIs responsiveness in GC[ 10 , 13 ]. With advancing comprehension of cancer molecular pathogenesis, there is increasing recognition of the critical function transcriptional reprogramming in both tumor progression and immune evasion[ 14 ]. Notably, we emphasize the discovery of a clinically relevant gene signature associated with immunosuppressive therapy resistance, which holds potential for elucidating the dynamic mechanisms underlying immunotherapy resistance in GC: alternative splicing (AS)[ 15 – 18 ]. AS is a nuclear process involving intron excision from pre-mRNA and exon ligation to generate mature RNAs[ 15 – 18 ]. Previous studies revealed that > 90% of human multi-exon genes undergo AS, establishing it as a critical post-transcriptional mechanism governing gene expression and cellular fate[ 16 – 19 ]. The serine/arginine-rich (SR) family members act as auxiliary splicing regulators by binding exonic/intronic splicing enhancers (ESEs/ISEs) or silencers (ESSs/ISSs) near splice sites[ 18 , 20 , 21 ]. Although SR proteins are evolutionarily conserved, their dysregulation or mutation in cancer drives tumorigenesis by altering pre-mRNA splicing, metabolism, decay, and translation[ 21 , 22 ]. SRSF10, a member of SR family, is frequently overexpressed in human malignancies and promotes oncogenic transformation, with its biological implications increasingly explored[ 23 , 24 ]. However, the role of SRSF10 in gastric tumorigenesis and relevance to immunotherapy remain elusive. Here, by employing conditional transgenic mouse models and extensive human samples, we unveil that elevated SRSF10 correlates with diminished responsiveness to ICIs in GC, exhibiting progressive elevation concomitant with each stage of tumorigenesis. Mechanistically, ablation of SRSF10 potentiates macrophage reprogramming via augmented CCL2 secretion, thereby suppressing neoplastic proliferation. Intriguingly, we demonstrate that SRSF10 orchestrates mTOR signaling activation during tumorigenesis and establishment of the immunosuppressive niche, mediated through regulation of BCAT2 exon 2 alternative RNA splicing. Finally, we propose targeting SRSF10 synergized with anti-PD-1 by reshaping macrophage plasticity, proposing a druggable strategy to overcome GC immunotherapy resistance. METHODS Mice All animal studies and procedures were conducted in accordance with the guidelines of the Animal Protection Committee of Fujian Medical University and were approved by the Ethics Committee of Fujian Medical University/Laboratory Animal Center (No. FJMU IACUC 2021-J-0174). Apc fl/fl (Cat# 029275), p53 fl/fl (Cat# 008462) and Rosa26-LSL-Tdtomato (Cat# 007914) mice were purchased from the Jackson Laboratory (Bar Harbor, Maine, USA). Tff1-CreERT 2 mice were purchased from the Shanghai Model Organisms Center (Shanghai, China). C57BL/6 wild-type mice were purchased from Cyagen Biosciences (Suzhou, China). All mice used were 6–8 weeks of age. Mice were given intraperitoneal injections of tamoxifen (T832955; MACKLIN, Shanghai, China) mixed with sunflower oil at the times shown in the text and/or figures. Samples were analysed at the indicated time points. Statistical analysis All statistical analyses in this study were performed using GraphPad Prism (version 10.2.1, San Diego, California, USA) or SPSS (version 19.0). Quantitative data are presented as the mean ± standard deviation (SD). Comparisons between two groups of variables were conducted using two-tailed Student's t-tests or non-parametric Mann–Whitney U-tests. Patient prognosis was assessed using Kaplan–Meier analysis. Log-rank tests were used to compare differences in survival rates between groups. Univariate and multivariate Cox proportional hazards models were employed to analyze prognostic parameters influencing overall survival (OS), and forest plots were constructed for evaluation. Spearman's correlation analysis was used to assess the relationship between two variables. The chi-squared test was used to investigate the relationship between two categorical variables. Significance levels are indicated as follows: * P < 0.05, ** P < 0.01, and *** P < 0.001. Additional methods are detailed in the online supplementary materials. RESULTS SRSF10 Orchestrates ICIs Resistance and Gastric Tumorigenesis To investigate the heterogeneity of tumor cells in human gastric cancer, single-cell RNA sequencing (scRNA-seq) was performed on ten samples. Following the filtration of low-quality cells and the execution of dimensionality reduction and clustering, the cells were initially classified into 11 cell subpopulations based on marker genes (Fig. 1 A and Supplemental Fig. 1A ). Thereafter, we further subdivided epithelial cell subpopulations into 6 distinct subpopulations based on the expression of specific maker genes (Fig. 1 B-C). Tumor-derived gastric epithelial cells exhibit significant differences from normal cells at the single-cell level. Density distributions reveal that normal tissue primarily consists of mature, differentiated surface epithelial cells and chief cells, whereas tumor tissue is enriched with metaplastic and dysplastic/tumor cell populations (Fig. 1 D and Supplementary Figs. 1B-C ). Subsequently, to delineate regulatory networks governing differential responses to ICIs in GC, we interrogated transcriptome profiles between GC with different responses to ICIs. Leveraging the CIBERSORT algorithm[ 25 ], we uncovered distinct disparities in immune infiltrate composition, particularly diminished CD8⁺ T cell infiltration and pronounced M2-polarized macrophage accumulation in non-responders ( Supplementary Figs. 1D ). Subsequent gene set enrichment analysis (GSEA) using MSigDB Hallmark, Gene Ontology (GO), and KEGG databases revealed enrichment of immune response pathways, particularly involving mTORC1 signaling, spliceosome assembly, and RNA processing ( Supplemental Fig. 1E-F ). Strikingly, spliceosome components (SRSF/THOC families) were differentially upregulated in non-responders (Fig. 1 E), implicating dysregulated RNA processing in T-cell exclusion and TAM polarization. We next intersected the upregulated genes from scRNA-seq (Tumor vs. Normal) and bulk RNA-seq (Non-responder vs. Responder) with spliceosome-related genes, which yielded three consistently candidates: SRSF10, SRSF6 and THOC2 (Fig. 1 F). Among these, SRSF10 demonstrated significantly higher expression in tumor tissues during scRNA-seq (Fig. 1 G-H). Consistent with this, analysis of TCGA-STAD data confirmed elevated SRSF10 expression in tumor tissues (Fig. 1 I). Notably, we identified significant dysregulation of spliceosome components, with SRSF10 demonstrating marked suppression in highly responsive tumors, suggesting its pivotal role in dictating ICIs response for GC patients (Fig. 1 J, M-N). Subsequently, we employed immunohistochemistry (IHC) to observe the dynamic changes in SRSF10 expression across normal gastric tissue, intestinal metaplasia (IM), and dysplastic gastric tissue (Fig. 1 K and Supplemental Fig. 2A ). The results further confirmed that SRSF10 expression exhibits a stepwise increase throughout the entire gastric tumorigenesis process. qPCR results further confirmed elevated SRSF10 expression levels in gastric cancer tissues ( Supplementary Fig. 2B ). Assessing SRSF10 dynamics during gastric tumorigenesis, we employed N-methyl-N-nitrosourea (MNU)-induced chemical carcinogenesis, as previously reported[ 26 – 30 ]. We observed substantial SRSF10 upregulation during malignant transformation of gastric epithelium relative to adjacent non-neoplastic tissues (Fig. 1 L). Critically, elevated SRSF10 expression was associated with a poorer prognosis ( Supplementary Fig. 2C ), as indicated by reduced overall survival (OS; Fig. 1 O) and disease-free survival (DFS; Fig. 1 P). According to the univariate/multivariate Cox regression analyses, the BMI, TNM stage, and SRSF10 levels were significantly associated with both OS and DFS (Fig. 1 Q and Supplementary Fig. 2D ), implying, SRSF10 emerged as independent prognostic factors. These results reaffirm the stepwise increase of SRSF10 expression throughout gastric tumorigenesis. Collectively, these findings suggest SRSF10 may function as a modulator central to both the establishment of ICIs-refractory and gastric tumorigenesis, positioning it as a compelling therapeutic target. SRSF10 Inhibition Impairs Growth of GC To further investigate the cell-autonomous effects of SRSF10 on GC progression, we established SRSF10 knockdown and overexpression cell lines in GC cells ( Supplemental Fig. 3A-B ). Utilizing CCK-8 proliferation assays and cell cycle analysis, we demonstrated that SRSF10 significantly enhances in vitro tumor cell proliferation, whereas its depletion exerts an inhibitory effect (Fig. 2 A-D and Supplemental Fig. 3C-D ). Subsequently, we established Srsf10 knockdown cell lines in YTN3 mice GC cells. In vivo xenograft models of C57BL/6 wild-type mice, tumors with Srsf10 knockdown exhibited markedly slower growth rates compared to control grafts. (Fig. 3 E-G). Previously, Shkreta et al.[ 23 , 31 ] identified the 4-pyridinone-benzisothiazole carboxamide compound 1C8 as a selective inhibitor of SRSF10, which mediates antiviral responses. Concurrently, Cai et al.[ 24 ] demonstrated that targeting SRSF10 with 1C8 enhances MYB RNA stability, inhibits lactate production, and consequently augments the response to immunotherapy in hepatocellular carcinoma. Building on this foundation, to investigate the role of SRSF10 inhibition in gastric cancerous events, we crossed Tff1-CreERT 2 alleles with Apc fl/fl , p53 fl/fl , and LSL-tdTomato mice to generate gastric adenocarcinoma models[ 32 ], thereby assessing the functional impact of SRSF10 inhibition via 1C8 on tumorigenesis (Fig. 2 H-I). Notably, gastric tumor areas in 1C8-treated mice were significantly smaller than those in controls (Fig. 2 J). Intriguingly, submucosal tumor cell infiltration was observed in a subset of control mice after 16 weeks of induction, whereas this phenomenon was entirely absent in 1C8-treated mice (Fig. 2 K). To delineate the role of SRSF10 suppression in gastric carcinogenesis, we employed Trop2 as a marker for dysplastic cells. Immunofluorescence analysis revealed robust Trop2 expression in the majority of glands in control mice, contrasting with a reduction in Trop2-positive dysplastic cells in 1C8-treated mice (Fig. 2 L). Additionally, we corroborated diminished CD44v9 (a marker for SPEM) staining in Trop2-positive cells (Fig. 2 L), consistent with previous studies. Thus, SRSF10 propels gastric carcinogenesis by fueling proliferation and dysplastic advancement. Targeting SRSF10 Reprograms the Immunosuppressive Niche via CCL2 To delineate the mechanistic basis of SRSF10-driven GC progression, we performed RNA-seq on SRSF10-depleted GC cells. Differential gene expression analysis revealed that CCL2 (also known as MCP-1) was among the most significantly downregulated genes (Top 10) in the SRSF10 knockdown group (Fig. 3 A). RT-qPCR further validated that CCL2 mRNA expression was significantly reduced upon SRSF10 depletion (Fig. 3 B). Given CCL2's established role in recruiting and polarizing M2-TAMs within the TME[ 33 – 35 ], we corroborated these findings through western blotting, ELISA, and immunofluorescence, collectively confirming diminished intracellular and secreted CCL2 protein (Fig. 3 C-E). To ascertain whether SRSF10 influences the polarization of macrophages through CCL2, THP-1 monocytes were co-cultured with either shSRSF10 or control GC cells. Strikingly, macrophages exposed to shSRSF10 cells exhibited marked suppression of M2 markers (CD206, CD163, TGF-β1) and concomitant upregulation of M1 markers (NOS2, CXCL9, CXCL10) (Fig. 3 F), indicating SRSF10 loss reprograms macrophages toward pro-inflammatory phenotypes. Importantly, we crossed Tff1-CreERT 2 alleles with Apc fl/fl and p53 fl/fl mice to establish a gastric adenocarcinoma model to assess the effects of SRSF10 in TME using a selective inhibitor 1C8. We confirmed that 1C8 efficiently inhibits SRSF10 expression in Tff1-CreERT 2 ; Apc fl/fl ; p53 fl/fl orthotopic GC models (Fig. 3 G). The immunofluorescence results revealed substantially diminished CCL2 expression in the 1C8-treated group than in the control group (Fig. 3 H). Consistently, IHC revealed expanded CD86⁺ M1-macrophages and contracted CD206⁺ M2-macrophages populations (Figs. 3 I-K). To further investigate the communication patterns between SRSF10-positive epithelial cells and the tumor microenvironment, Cell Chat analysis was performed. The results of the study indicated a substantial increase in the interactions between SRSF10-positive cells and various immune or stromal cell types, including fibroblasts, endothelial cells, and macrophages (Fig. 3 L). A notable finding was the observation of substantial ligand-receptor interactions between SRSF10-positive epithelial cells and macrophages via the CCL2–CCR2 signaling pathway (Fig. 3 M). Quantitative analysis further confirmed that CCL2–CCR2 interactions were significantly enhanced in SRSF10-positive epithelial cells compared to SRSF10-negative cells (Fig. 3 N). Further immunofluorescence results revealed significantly enhanced recruitment of GzmB⁺/CD8⁺ T cells in the 1C8-treated group compared to the control group. Collectively, these data establish that SRSF10 inhibition reprograms macrophages in the immunosuppressive TME by ablating CCL2. SRSF10 Blockade Attenuates Pre-neoplastic Metaplastic Cell Proliferation and TAMs Reprogramming To further investigate SRSF10's role in pre-neoplastic metaplastic process, we employed a high-dose tamoxifen (HDT) injury model, which has been extensively utilized by us and others[ 29 , 36 – 38 ]. HDT induces the loss of acid-secreting parietal cells in the gastric corpus and induces the formation of proliferative metaplastic cells ( Supplemental Fig. 4A ), has been called pseudopyloric metaplasia or spasmolytic polypeptide-expressing metaplasia (SPEM)[ 36 , 37 , 39 ]. Notably, 1C8 monotherapy in the naive stomach exerted negligible effects on isthmus mitotic activity (Fig. 4 A-C). Intriguingly, while 1C8 failed to disrupt SPEM initiation, it selectively abrogated the proliferative capacity of HDT-induced SPEM-like cells (Fig. 4 A-C). Immunohistochemical profiling demonstrated that 1C8 significantly reprogrammed the TAM landscape: contracting CD206⁺ M2-like populations while expanding CD86⁺ M1-like macrophages (Figs. 4 D-G). This polarization shift implies SRSF10 inhibition attenuates pre-neoplastic metaplastic immunosuppressive niche. SRSF10 Regulates BCAT2 Exon Skipping to Activates mTORC1 Signaling To elucidate SRSF10’s mechanistic link to CCL2, we bioinformatically scanned the CCL2 pre-mRNA (ENST000002258314) for potential binding sites using the RBP suite algorithm[ 40 ]. However, no clear evidence was found to support a direct interaction between SRSF10 and CCL2 mRNA (Fig. 5 A). Intriguingly, transcriptome-wide GSEA revealed pronounced suppression of mTORC1 signaling upon SRSF10 knockdown (Fig. 5 B and Supplementary Fig. 5A ). Corroborating this, western blot demonstrated concerted attenuation of p-mTOR, CCL2, and stemness factors SOX9/CD44 (Fig. 5 C). Using the Tff1-CreERT 2 ; Apc fl/fl ; p53 fl/fl mice models, we confirmed reduced p-mTOR⁺ gastric epithelial cells (GECs) with 1C8 treatment compared to control group (Fig. 5 D-E), validating the mTORC1 inhibition by SRSF10 ablation. To identify the AS events regulating mTOR signaling, we intersected genes that underwent AS (junction count-only method) with differential expression genes (DEGs; P < 0.05, LogFC < -1). We found 13 AS events (Fig. 5 F and Supplementary Fig. 5B ). Among these AS events, BCAT2 have been reported to activate the mTOR signaling[ 41 , 42 ]. Encouragingly, SRSF10 knockdown led to an increased exclusion of exon 2, generating more BCAT2 transcripts with exon 2 exclusion [BCAT2-E2(-)] and fewer BCAT2 transcripts with exon 2 inclusion [BCAT2-E2(+)] compared with the control group (Fig. 5 G-H). Notably, RIP established direct SRSF10 binding to BCAT2 pre-mRNA (Fig. 5 I), while actinomycin D assays proved SRSF10 stabilizes BCAT2 transcripts (Fig. 5 J). Critically, BCAT2 overexpression rescued p-mTOR, CCL2, SOX9, and CD44 expression (Fig. 5 K), affirming functional causality. IHC of human GC tissues revealed SRSF10 levels correlated positively with BCAT2 but relatively weakly correlated with p-mTOR ( Supplementary Fig. 5C ). To this end, we further found minimal p-mTOR in SRSF10-low&BCAT2-low specimens versus maximal activation in SRSF10-high&BCAT2-high cohorts (Fig. 5 L-M), indicating that the activation of p-mTOR by SRSF10 is dependent on BCAT2. Pharmacological Antagonism of SRSF10 Potentiate Anti-PD-1 Therapy Efficacy As we confirmed that SRSF10 inhibition could increase the infiltration of CD8 + T cells and reprogram TAMs and convert them into M1-like TAMs in the TME. To investigate whether targeting SRSF10 enhances the therapeutic effect of anti-PD-1, we administered PD-1 monoclonal antibodies, SRSF10-targeting agent 1C8, IgG in Tff1-CreERT 2 ; Apc fl/fl ; p53 fl/fl mice by administering tamoxifen (Fig. 6 A). The results revealed that the combination therapy of 1C8 and anti-PD-1 significantly reduced gastric tumor burden compared to monotherapy or control treatment alone (Fig. 6 B-E). Notably, survival analysis showed that GC-burdened mice receiving the combined treatment exhibited a significant survival advantage over all other treatment groups (Fig. 6 C). We further conducted Immunofluorescence evaluation of TROP2 (marker of intramucosal dysplasia) and CD44v9/SOX9 (marker for metaplastic lineage) to elucidate alterations in metaplastic or dysplastic cells following combination therapy. Notably, the combined regimen of 1C8 and anti-PD-1 antibody demonstrated significant efficacy in suppressing the emergence of TROP2 + dysplastic cells (Fig. 6 F-G), concomitant with a marked reduction in SOX9 + /CD44v9 + metaplastic cell populations ( Fig. 6 H and Supplemental Fig. 6A ). The effect of the combination therapy of 1C8 and anti-PD-1 on macrophage phenotype was evaluated by IHC. Our data showed that more cells expressed CD86 + M1-type TAMs, but less cells expressed CD206 + M2-type TAMs in gastric tissue in combined regimen groups (Figs. 6 I-J). As expected, combination treatment synergistically promoted intra tumoral CD8 + T cells expansion in Tff1-CreERT 2 ; Apc fl/fl ; p53 fl/fl mice. Collectively, our data revealed that SRSF10 is a key target of the immunotherapy response in GC, and provided proof of concept the blockade of SRSF10 is a potentially effective approach for improving the efficacy of immunotherapy in GC. DISCUSSION Advanced GC remains a lethal disease with a poor ICIs response and prognosis, necessitating urgent elucidation of the mechanisms underlying its immune escape, and developing effective therapeutic strategies[ 5 , 43 , 44 ]. Recent studies have revealed the pivotal function of AS in tumor progression and immune regulation[ 20 ], yet the role of AS and immunotherapy response in GC remains unclear. Our study establishes splicing factor SRSF10 as a master regulator orchestrating both tumor-intrinsic growth and immunosuppressive niche formation. We revealed that SRSF10 regulates exon skipping of the BCAT2 gene, thereby influencing mTOR activation and CCL2-mediated macrophage polarization, and ultimately promoting immune escape and tumor progression. Pharmacological antagonism of SRSF10 synergized with anti-PD-1 by reshaping macrophage plasticity, proposing a druggable strategy to overcome GC immunotherapy resistance. Transcriptomic profiling of ICIs responders versus non-responders revealed SRSF10 as one of the most differentially expressed spliceosome component, exhibiting pronounced elevation in therapy-resistant GC. Critically, its progressive upregulation during the metaplasia-dysplasia-carcinoma sequence, suggesting SRSF10 acts a duality gene by potentiating both malignant transformation and immune escape. This aligns with emerging evidence that spliceosome generate neoantigens while paradoxically fostering T-cell exhaustion[ 45 , 46 ]. Notably, SRSF10 expression inversely correlated with GC patient survival outcomes, establishing it as an independent prognostic factor—a finding consistent with its oncogenic roles in hepatocellular carcinoma and cervical cancer[ 23 , 24 ]. A vital revelation of our study is the SRSF10-CCL2 axis as a driver of TAM polarization. SRSF10 knockdown drastically reduced CCL2 transcription and secretion, shifting macrophages from immunosuppressive M2 (CD206⁺/CD163⁺/TGF-β⁺) to pro-inflammatory M1 phenotypes (CD86⁺/CXCL9⁺/NOS2⁺). This reprogramming enhanced intratumoral CD8⁺ T-cell infiltration and granzyme B production, effectively converting immune-deserted tumors into immunoreactive niches. CCL2 (MCP-1) is a well-established chemokine recruiting CCR2⁺ monocytes and polarizing them toward M2 states[ 47 ]. Our data extend this paradigm by implicating SRSF10 as an upstream transcriptional regulator of CCL2, thereby positioning splicing machinery as a key modulator of chemokine-driven immune evasion. Intriguingly, we revealed that SRSF10’s regulation of CCL2 is indirect, mediated through mTORC1 activation via BCAT2 exon 2 inclusion. BCAT2, a metabolic enzyme in branched-chain amino acid (BCAA) catabolism, has been reported to activate mTORC1 in colorectal cancer progression[ 48 ]. We demonstrated that SRSF10 binds BCAT2 pre-mRNA, enforcing exon 2 inclusion [BCAT2-E2(+)] and enhancing transcript stability. Harnessing innate antitumor immunity has emerged as a pivotal therapeutic component of combinatorial immunotherapy regimens[ 49 ]. In this study, we showed that pharmacologically targeting SRSF10, using a small-molecule inhibitor 1C8, significantly reduced tumor burden and improved survival in a spontaneous GC mouse model. The combination therapy not only suppressed tumor cell proliferation but also further reduced expression of SOX9 and CD44v9, suggesting that dual targeting of SRSF10 and immune checkpoints may be an effective strategy to overcome resistance and eradicate stem-like tumor cells. In conclusion, our study provides insight into the prominent role of SRSF10 in reprograming the tumor immunosuppressive niche, driven by BCAT2-dependent mTOR activation and CCL2-mediated TAMs polarization. Pharmacological inhibition of SRSF10 reshapes TAMs and synergizes with PD-1 blockade, providing a compelling rationale for clinical translation. As aberrant splicing emerges as a hallmark of cancer immune-resistance, targeting spliceosome nodes like SRSF10 offers a precision approach to reignite antitumor immunity. Declarations Acknowledgements This study was supported by the Natural Science Foundation of Fujian Province (No.2021J02039); Fujian provincial health technology project (No.2024QNA014); Joint Funds for the innovation of Science and Technology, Fujian province (No. 2024Y9320); the National Natural Science Foundation of China (No. 82473061); the National Natural Science Foundation of China (No. 82473120). We gratefully acknowledge the experimental technical support provided by the Public Technology Service Center of Fujian Medical University and the Key Laboratory of the Ministry of Education for Gastrointestinal Cancer. Conflict of Interest The authors declare that they have no competing interests. Author Contributions X.-B.H., X.-P.Y., Z.-X.C., and H.-L.Z. contributed equally to this work and should be considered co-first authors. P.L., Q.-Y.C., and C.-M.H. (senior co-authors) had full access to all data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. C.-Y.J., X.-J.G., L.-Q.W., and B.L. contributed to concept and design. Q.H., Y.-X.G., Y.-F.L., Y.L., X.-Q.Y., J.-B.W., J.-W.X., J.-X.L., and C.-H.Z. performed acquisition, analysis, and interpretation of data. C.-Y.J., X.-J.G., L.-Q.W., B.L., and Q.H. drafted the manuscript. J.-B.W., J.-W.X., J.-X.L., and C.-H.Z. performed statistical analysis. X.-B.H., X.-P.Y., Z.-X.C., H.-L.Z., C.-Y.J., X.-J.G., L.-Q.W., B.L., Q.H., Y.-X.G., Y.-F.L., Y.L., X.-Q.Y., J.-B.W., J.-W.X., J.-X.L., and C.-H.Z. provided administrative, technical, or material support. X.-B.H., X.-P.Y., Z.-X.C., and H.-L.Z. performed supervision. Data Availability Statement The data supporting the findings of this study are available from the corresponding author on request. Ethics Approval The Research Ethics Committee of the Fujian Medical University Union Hospital reviewed and approved the study (No. FJMU IACUC 2021-J-0174; 2021KJT036). All study participants provided written informed consent. Patient consent for publication: Obtained. References A. Ribas, J.D. Wolchok, Cancer immunotherapy using checkpoint blockade, Science, 359 (2018) 1350-1355. D.S. Chen, I. Mellman, Elements of cancer immunity and the cancer-immune set point, Nature, 541 (2017) 321-330. X. He, C. Xu, Immune checkpoint signaling and cancer immunotherapy, Cell Res, 30 (2020) 660-669. R. Cristescu, R. Mogg, M. Ayers, A. Albright, E. Murphy, J. Yearley, X. Sher, X.Q. Liu, H. Lu, M. Nebozhyn, C. Zhang, J.K. Lunceford, A. Joe, J. Cheng, A.L. Webber, N. Ibrahim, E.R. Plimack, P.A. Ott, T.Y. 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SupplementaryTable2.ListofprimersusedforqPCR.pdf Supplementary Table 2. List of primers used for qPCR SupplementalMaterialsandMethods.pdf Supplemental Materials and Methods Originaldata.pdf Original data FigureS1.pdf FigureS2.pdf FigureS3.pdf FigureS4.pdf FigureS5.pdf FigureS6.pdf SupplementaryFigureLegends.pdf Supplementary Figure Legends Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: revise 27 Oct, 2025 Review # 2 received at journal 26 Oct, 2025 Review # 1 received at journal 22 Oct, 2025 Reviewer # 2 agreed at journal 13 Oct, 2025 Reviewer # 1 agreed at journal 06 Oct, 2025 Reviewers invited by journal 02 Oct, 2025 Submission checks completed at journal 03 Sep, 2025 First submitted to journal 03 Sep, 2025 Unknown event 02 Sep, 2025 Editor assigned by journal 01 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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08:04:08","extension":"html","order_by":33,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":174805,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/e2b58750dc48f51a54ea5cb3.html"},{"id":93660312,"identity":"bff68bec-79f9-4d6b-8030-9f19e8d343bf","added_by":"auto","created_at":"2025-10-16 08:04:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1973029,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSRSF10 Orchestrates ICIs Resistance and Gastric Tumorigenesis. \u003c/strong\u003e(A) UMAP visualization of gastric single-cell transcriptomes showing major cell populations. (B) Subclustering of epithelial cells identifies six distinct subsets. (C) Dot plot showing representative marker genes used to define epithelial subsets. (D) Density plots of epithelial cells in normal and tumor samples. (E) Bulk RNA-seq gene set enrichment analysis (GSEA) comparing non-responders versus responders to immune checkpoint inhibitors (ICIs), showing enrichment of spliceosome and RNA processing pathways. (F) Venn diagram of upregulated genes from scRNA-seq (Tumor vs. Normal), bulk RNA-seq (Non-responder vs. Responder), and spliceosome-related gene sets, identifying three overlapping candidates: \u003cem\u003eSRSF10\u003c/em\u003e, \u003cem\u003eSRSF6\u003c/em\u003e, and \u003cem\u003eTHOC2\u003c/em\u003e. (G) UMAP plot showing distribution of SRSF10-positive cells (blue) and SRSF10-negative cells (grey), with enrichment of SRSF10-positive cells in tumor populations. (H) Violin plot showing \u003cem\u003eSRSF10\u003c/em\u003e expression in tumor compared with normal tissues. (I)The relative SRSF10 mRNA expression levels of SRSF10 in tumor and normal tissues in TCGA-STAD. (J) The relative SRSF10 expression in responder and non-responder Groups. (K) The bar chart showing the fraction of samples with low or high SRSF10 expression across different tissue types (normal, intestinal metaplasia, dysplasia/cancer). (L) A schematic diagram of the MNU-induced gastric cancer (GC) mouse model timeline, from induction to euthanasia (above). IHC images of SRSF10 in gastric dysplasia tissue and normal tissue of mice (below). (M) IHC images of SRSF10 in gastric cancer tissues from immunotherapy responder and non-responder. (N) Distribution of SRSF10 expression levels in responder and non-responder groups. (O) Kaplan–Meier overall survival (OS) curves comparing patients with high versus low SRSF10 expression. (P) Kaplan–Meier disease-free survival (DFS) curves comparing patients with high versus low SRSF10 expression. (Q) Univariate and multivariate Cox regression analyses for OS. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ***\u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001. Scale bars in L, M, 100 μm.\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/3341b9316676aef8f1876298.png"},{"id":93662869,"identity":"53e8e949-4092-489d-a241-4a2409e1e705","added_by":"auto","created_at":"2025-10-16 08:28:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2821068,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSRSF10 Inhibition Impairs Growth of GC. \u003c/strong\u003e(A) Cell proliferation curves of AGS-shNC and AGS-shSRSF10 cells assessed by CCK-8 assay. (B) Cell proliferation curves of AGS cells overexpressing SRSF10 and the control cells were assessed via a CCK-8 assay. (C) Cell cycle analysis of AGS-shNC and AGS-shSRSF10 cells by flow cytometry. (D) Flow cytometry was conducted to assess the cell cycle of AGS cells overexpressing SRSF10 and control cells. (E) Representative images of subcutaneous tumors from C57BL/6 wild-type mice injected with gastric cancer cells transduced with shNC or shSrsf10. (F) Growth curves of subcutaneous tumors derived from shNC and shSrsf10 cells in C57BL/6 wild-type mice. (G) Tumor weight comparison between shNC and shSrsf10 groups at the end of the experiment. (H) The experimental strategy for genetic recombination in the \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; Apc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; p53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; LSL-tdTomato\u003c/em\u003e mice model. (I) Tamoxifen and 1C8 treatment schematic. (J) Macroscopic images of gastric tumors in 1C8 and control-treated mice are shown in the figure (left). The total area occupied by gastric tumors in each mouse is shown in the graph (right). (K) Representative images and haematoxylin and eosin (H\u0026amp;E) staining of gastric cancer nodules in \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; Apc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; p53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; LSL-tdTomato\u003c/em\u003e mice, 16 weeks after infection with tamoxifen and 1C8, or the control treatment. (L) Representative images and quantitative analysis of TROP2\u003csup\u003e+\u003c/sup\u003e cells in the gastric tissue of mice that were treated with either 1C8 or the control treatment(left). The proportion of TROP2\u003csup\u003e+\u003c/sup\u003e glands in all gastric glands in the stomach tissues of mice receiving 1C8 or control treatment(right). *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01; ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. Scale bars in K, L, 100 μm.\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/047e391123b63c3a690b1a84.png"},{"id":93661586,"identity":"eafab1c7-e7bf-4021-af15-97364dfe96db","added_by":"auto","created_at":"2025-10-16 08:20:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2818204,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTargeting SRSF10 Reprograms the Immunosuppressive Niche via CCL2. \u003c/strong\u003e(A) A volcano plot displaying the results of gene expression differential analysis is produced by combining RNA-seq sequencing data from the shCtrl and shSRSF10 AGS cell lines. (B) The expression levels of mRNA for the top 10 differentially expressed genes were validated via real-time fluorescent quantitative reverse transcription polymerase chain reaction (RT-qPCR). (C) Western blotting demonstrates the impact of SRSF10 on the expression of the CCL2 protein. (D) ELISA demonstrates the impact of SRSF10 on the secretion of the CCL2 protein. (E) Cell Fluorescence showing the effect of SRSF10 on CCL2 protein expression. (F) Co-culturing SRSF10-knockdown or control gastric cancer cells with THP-1 cells revealed alterations in the expression of M1 and M2 macrophage markers in the THP-1 cells. (G) Immunohistochemistry (IHC) analysis of SRSF10 expression in gastric tissues from \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; Apc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; p53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; LSL-tdTomato\u003c/em\u003e mice treated with vehicle or 1C8.\u0026nbsp; (H) Immunofluorescence staining of DAPI, CCL2, Ki67, and E-cadherin in gastric tissues from vehicle- or 1C8-treated mice(left). The percentage of CCL2\u003csup\u003e+\u003c/sup\u003e cells among total GECs is shown(right). (I-J) Immunohistochemistry of CD206 (M2 macrophage marker) and CD86 (M1 macrophage marker) in gastric tissues from vehicle- or 1C8-treated mice. (K) Quantitative analysis of CD206\u003csup\u003e+\u003c/sup\u003e cells/mm² and CD86\u003csup\u003e+\u003c/sup\u003e cells/mm² in gastric cancer tissues. (L) The cell-cell interaction network reveals interactions between SRSF10-positive epithelial cells (red) and SRSF10-negative cells (blue) with immune cells (macrophages, T/NK cells) and mesenchymal cells (fibroblasts, endothelial cells, smooth muscle cells). (M) Schematic diagram of the CCL2-CCR2 signaling pathway, illustrating interactions between SRSF10-positive epithelial cells and macrophages. (N) Quantitative Analysis of CCL2-CCR2 Interaction Probability. (O) Immunofluorescence staining of CD8 and Granzyme B (GzmB) in gastric tissues from vehicle- or 1C8-treated mice. Quantification of GzmB⁺CD8⁺/CD8⁺ cell percentages in gastric cancer tissues. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. Scale bars in E, G,H, I, J, O, 100 μm.\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/527caf123f344dd5b2065b3b.png"},{"id":93661587,"identity":"9feeccea-149e-4687-8aad-b273546052b9","added_by":"auto","created_at":"2025-10-16 08:20:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4190544,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSRSF10 Blockade Attenuates Pre-neoplastic Metaplastic Cell Proliferation and TAMs Reprogramming. \u003c/strong\u003e(A) Representative immunofluorescence staining of mouse gastric tissues for DAPI, GIF, GS-II, and Ki67 across four treatment groups: vehicle, 1C8, HDT 72 h, and 1C8 + HDT 72 h. (B) Quantification of chief cells, neck cells, and SPEM cells per gastric unit in mice treated with vehicle, 1C8, HDT 72 h, or combination of 1C8 + HDT 72 h. (C) Quantification of Ki67⁺GIF⁺ proliferating chief cells and Ki67⁺GS-II⁺ proliferating SPEM cells per gastric unit under different treatment conditions. (D) Representative IHC staining images of CD86 in Vehicle, 1C8, HDT 72h, and 1C8 + HDT 72h groups. (E) Quantification of CD86\u003csup\u003e+\u003c/sup\u003e cells/HPF in different groups. (F) Representative IHC staining images of CD206 in Vehicle, 1C8, HDT 72h, and 1C8 + HDT 72h groups. (G) Quantification of CD206\u003csup\u003e+\u003c/sup\u003e cells/HPF in different groups. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. Scale bars in A,100 μm.\u003c/p\u003e","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/294114cb60efe4741de5736a.png"},{"id":93661255,"identity":"269aedc9-b794-49e2-84d6-21a92423d31a","added_by":"auto","created_at":"2025-10-16 08:12:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2246165,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSRSF10 Regulates BCAT2 Exon Skipping to Activates mTORC1 Signaling. \u003c/strong\u003e(A) Schematic of the CCL2 mRNA transcript (ENST000002258314) structure with sequence segment scores indicating potential SRSF10 binding sites across 8 segments. (B) Gene Set Enrichment Analysis (GSEA) of hallmark pathways in AGS cells upon SRSF10 knockdown. (C) Western blot analysis showing the expression levels of SRSF10, CD44, SOX9, CCL2, BCAT2, and p-mTOR in AGS cells with or without SRSF10 knockdown. (D) Immunohistochemistry (IHC) analysis of p-mTOR expression in gastric tissues from \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; Apc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; p53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; LSL-tdTomato\u003c/em\u003e mice treated with vehicle or 1C8. (E) Proportion of p-mTOR\u003csup\u003e+\u003c/sup\u003e cells in GECs under Vehicle or 1C8 treatment. (F) Percentages of AS events (SE, MXE, A5SS, A3SS, RI) detected by rMATS analysis in SRSF10-knockdown versus control cells. (G) Sashimi plot showing BCAT2 exon 2 (chr19: 48807000–48807074) inclusion rates, decreased in shSRSF10 compared to shCtrl. Arcs indicate junction reads. (H) RT-PCR validation of BCAT2-E2(+) and BCAT2-E2(−) isoforms in control and SRSF10-knockdown cells(left). Spliced-out ratio (SOR) of BCAT2-E2 in shCtrl versus shSRSF10 cells(right). (I) RNA immunoprecipitation (RIP). (J) BCAT2 mRNA decay curves in shCtrl and shSRSF10 AGS cells following Actinomycin D treatment (0-8 h). (K) Western blot analysis of SRSF10, BCAT2, p-mTOR, CCL2, SOX9 and CD44 in gastric cancer cells under different conditions (shCtrl, shSRSF10, Control, BCAT2). (L) Immunohistochemistry (IHC) staining of BCAT2 and p-mTOR in gastric cancer tissues with low and high SRSF10 expression. (M) Box plots showing the p-mTOR HC scores in different groups based on SRSF10 and BCAT2 expression levels. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. Scale bars in D, L, 100 μm.\u003c/p\u003e","description":"","filename":"fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/b75d3a813a48c769c8885bca.png"},{"id":93661256,"identity":"d514c140-728a-4ff2-ae15-b481bf0b51d7","added_by":"auto","created_at":"2025-10-16 08:12:07","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":4320861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePharmacological Antagonism of SRSF10 Potentiate Anti-PD-1 Therapy Efficacy. \u003c/strong\u003e(A) Experimental timeline and drug administration diagram for the \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; Apc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; p53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e; LSL-tdTomato\u003c/em\u003e mice model. (B) Macroscopic tumor morphology comparison of gastric tissue from mice in different treatment groups. (C) Kaplan-Meier survival curves of mice in each treatment group. (D) H\u0026amp;E-stained sections of gastric tissue were examined from each group of mice. (E) Quantitative analysis of tumor area in different treatment groups. (F) Immunofluorescence staining images of gastric tissue from mice in different treatment groups (vehicle, 1C8, anti-PD-1 and anti-PD-1+1C8). TROP2 (green), CD44v9 (red), Ki67 (white) and DAPI (blue). (G) Quantitative analysis of the proportion of TROP2-positive glands. (H) The proportion of SOX9\u003csup\u003e+\u003c/sup\u003e CD44v9\u003csup\u003e+\u003c/sup\u003edouble-positive cells in total GECs. (I) Immunohistochemistry (IHC) analysis of CD86, CD206 and CD8 expression in gastric tissues from mice in different treatment groups (vehicle, 1C8, anti-PD-1 and anti-PD-1+1C8). (J) Quantification of CD86⁺ M1-like macrophages per high-power field (HPF)(above). Quantification of CD206⁺ M2-like macrophages per HPF (in between). Quantification of CD8\u003csup\u003e+\u003c/sup\u003e T cells per HPF (below). *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. Scale bars in D, F, I, 100 μm.\u003c/p\u003e","description":"","filename":"fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/3e72edb7639cc62efc24bd66.png"},{"id":93663083,"identity":"7d882ab6-9bc9-4cbe-b63a-89929f88b060","added_by":"auto","created_at":"2025-10-16 08:36:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":19380044,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/9b3dbbe1-3fe9-4da9-b59e-e3c1b32fc1d4.pdf"},{"id":93660313,"identity":"601fc253-6b84-45e9-91cb-ec0113093397","added_by":"auto","created_at":"2025-10-16 08:04:07","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":105438,"visible":true,"origin":"","legend":"Supplementary Table 1. Antibodies application and dilution.","description":"","filename":"SupplementaryTable1.Antibodiesapplicationanddilution.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/3c44a8ce9736a3f90f2c4226.pdf"},{"id":93660314,"identity":"042f7628-f792-411a-8c71-5d72259ed9d8","added_by":"auto","created_at":"2025-10-16 08:04:07","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":166408,"visible":true,"origin":"","legend":"Supplementary Table 2. List of primers used for qPCR","description":"","filename":"SupplementaryTable2.ListofprimersusedforqPCR.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/eb76c0fde3a3832b176cfa37.pdf"},{"id":93661258,"identity":"12a1b313-ed0e-4463-a110-a6f53c2a9678","added_by":"auto","created_at":"2025-10-16 08:12:07","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":184814,"visible":true,"origin":"","legend":"Supplemental Materials and Methods","description":"","filename":"SupplementalMaterialsandMethods.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/eef8c59b1ccef09295aeed3d.pdf"},{"id":93660318,"identity":"c8a1f3ae-f20d-4c2d-9cc1-d28268e342b4","added_by":"auto","created_at":"2025-10-16 08:04:07","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":529348,"visible":true,"origin":"","legend":"Original data","description":"","filename":"Originaldata.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/672f5eb5e4da204fdffc6ff6.pdf"},{"id":93660325,"identity":"35411087-e76e-4d26-9cf9-133f0a7225a0","added_by":"auto","created_at":"2025-10-16 08:04:07","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":6034637,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/2450ba25910f2ca5170ffc89.pdf"},{"id":93661267,"identity":"6f87682c-f0c9-4309-aa77-f0b4623a02dd","added_by":"auto","created_at":"2025-10-16 08:12:08","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":5478569,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/1e365219982a714c2a4b998b.pdf"},{"id":93660337,"identity":"b3aa2702-bf1c-4c5d-be1c-c84ba91ef4aa","added_by":"auto","created_at":"2025-10-16 08:04:08","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":202061,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/f32980dabc60a23a8de7128b.pdf"},{"id":93660345,"identity":"3ed3ac2e-3b75-414c-8a51-532ba0211cb5","added_by":"auto","created_at":"2025-10-16 08:04:09","extension":"pdf","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":20239198,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/8662b6f1447a03f96f0dba1e.pdf"},{"id":93660324,"identity":"5b39e54e-25d9-4ab4-a9cc-454f827f4384","added_by":"auto","created_at":"2025-10-16 08:04:07","extension":"pdf","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":423757,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS5.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/caefa580d40e17ad1d058255.pdf"},{"id":93660339,"identity":"829fa3ac-1dfb-430d-8053-a7d9954a14fa","added_by":"auto","created_at":"2025-10-16 08:04:08","extension":"pdf","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":20898620,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS6.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/1d1c645ce86fa5e79b217966.pdf"},{"id":93661268,"identity":"a58b37bb-8f72-4f6f-b5cd-4c0d8cec2241","added_by":"auto","created_at":"2025-10-16 08:12:08","extension":"pdf","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":138809,"visible":true,"origin":"","legend":"Supplementary Figure Legends","description":"","filename":"SupplementaryFigureLegends.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7510487/v1/3ceb961c877cf942a2cf00c1.pdf"}],"financialInterests":"(Not answered)","formattedTitle":"Disrupting SRSF10-dependent BCAT2 Exon Skipping Reprograms Tumor-Associated Macrophages and Enhances Anti-PD-1 Efficacy in Gastric Cancer","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eImmune checkpoint inhibitors (ICIs) have revolutionized cancer therapeutics, emerging as one of the most promising therapeutic strategies[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Despite approximately 30% of solid tumor patients achieve durable antitumor responses to ICIs treatment, clinical efficacy remains constrained by primary resistance or acquired resistance following initial response[\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Compounding this challenge, gastric cancer (GC) manifests a profoundly heterogeneous malignancy characterized by substantial variability in its responsiveness to immunotherapy[\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This variability underscores the urgent need to decipher the complex molecular underpinnings of ICIs refractoriness.\u003c/p\u003e\u003cp\u003eThe immunosuppressive tumor microenvironment (TME), characterized by abundant tumor-associated macrophages (TAMs), constitutes a major impediment to ICIs efficacy in malignancies including GC[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. As pivotal components, TAMs encompass two functionally distinct subsets: immunosuppressive M2-polarized macrophages and pro-inflammatory M1 macrophages[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. M2 macrophages perpetuate immunosuppression by secreting cytokines such as IL-10 and TGF-β, thereby dampening immune cell activity[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Conversely, M1 macrophages potentiate T-cell-mediated anti-tumor responses via molecules including CXCL9 and NOS2, facilitating tumor cell eradication[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Crucially, the inherent plasticity of macrophages presents a therapeutic opportunity to reprogram these cells toward a pro-inflammatory, antitumoral M1-like state, transforming immunologically \"cold\" tumors into \"hot\" tumors and enhancing ICIs responsiveness in GC[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWith advancing comprehension of cancer molecular pathogenesis, there is increasing recognition of the critical function transcriptional reprogramming in both tumor progression and immune evasion[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Notably, we emphasize the discovery of a clinically relevant gene signature associated with immunosuppressive therapy resistance, which holds potential for elucidating the dynamic mechanisms underlying immunotherapy resistance in GC: alternative splicing (AS)[\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. AS is a nuclear process involving intron excision from pre-mRNA and exon ligation to generate mature RNAs[\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Previous studies revealed that \u0026gt;\u0026thinsp;90% of human multi-exon genes undergo AS, establishing it as a critical post-transcriptional mechanism governing gene expression and cellular fate[\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The serine/arginine-rich (SR) family members act as auxiliary splicing regulators by binding exonic/intronic splicing enhancers (ESEs/ISEs) or silencers (ESSs/ISSs) near splice sites[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Although SR proteins are evolutionarily conserved, their dysregulation or mutation in cancer drives tumorigenesis by altering pre-mRNA splicing, metabolism, decay, and translation[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. SRSF10, a member of SR family, is frequently overexpressed in human malignancies and promotes oncogenic transformation, with its biological implications increasingly explored[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, the role of SRSF10 in gastric tumorigenesis and relevance to immunotherapy remain elusive.\u003c/p\u003e\u003cp\u003eHere, by employing conditional transgenic mouse models and extensive human samples, we unveil that elevated SRSF10 correlates with diminished responsiveness to ICIs in GC, exhibiting progressive elevation concomitant with each stage of tumorigenesis. Mechanistically, ablation of SRSF10 potentiates macrophage reprogramming via augmented CCL2 secretion, thereby suppressing neoplastic proliferation. Intriguingly, we demonstrate that SRSF10 orchestrates mTOR signaling activation during tumorigenesis and establishment of the immunosuppressive niche, mediated through regulation of BCAT2 exon 2 alternative RNA splicing. Finally, we propose targeting SRSF10 synergized with anti-PD-1 by reshaping macrophage plasticity, proposing a druggable strategy to overcome GC immunotherapy resistance.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eMice\u003c/h2\u003e\u003cp\u003e All animal studies and procedures were conducted in accordance with the guidelines of the Animal Protection Committee of Fujian Medical University and were approved by the Ethics Committee of Fujian Medical University/Laboratory Animal Center (No. FJMU IACUC 2021-J-0174). \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e (Cat# 029275), \u003cem\u003ep53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e (Cat# 008462) and \u003cem\u003eRosa26-LSL-Tdtomato\u003c/em\u003e (Cat# 007914) mice were purchased from the Jackson Laboratory (Bar Harbor, Maine, USA). \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e mice were purchased from the Shanghai Model Organisms Center (Shanghai, China). C57BL/6 wild-type mice were purchased from Cyagen Biosciences (Suzhou, China). All mice used were 6\u0026ndash;8 weeks of age. Mice were given intraperitoneal injections of tamoxifen (T832955; MACKLIN, Shanghai, China) mixed with sunflower oil at the times shown in the text and/or figures. Samples were analysed at the indicated time points.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAll statistical analyses in this study were performed using GraphPad Prism (version 10.2.1, San Diego, California, USA) or SPSS (version 19.0). Quantitative data are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Comparisons between two groups of variables were conducted using two-tailed Student's t-tests or non-parametric Mann\u0026ndash;Whitney U-tests. Patient prognosis was assessed using Kaplan\u0026ndash;Meier analysis. Log-rank tests were used to compare differences in survival rates between groups. Univariate and multivariate Cox proportional hazards models were employed to analyze prognostic parameters influencing overall survival (OS), and forest plots were constructed for evaluation. Spearman's correlation analysis was used to assess the relationship between two variables. The chi-squared test was used to investigate the relationship between two categorical variables. Significance levels are indicated as follows: * \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, and *** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e\u003cp\u003eAdditional methods are detailed in the online supplementary materials.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eSRSF10 Orchestrates ICIs Resistance and Gastric Tumorigenesis\u003c/h2\u003e\u003cp\u003eTo investigate the heterogeneity of tumor cells in human gastric cancer, single-cell RNA sequencing (scRNA-seq) was performed on ten samples. Following the filtration of low-quality cells and the execution of dimensionality reduction and clustering, the cells were initially classified into 11 cell subpopulations based on marker genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cb\u003eSupplemental Fig.\u0026nbsp;1A\u003c/b\u003e). Thereafter, we further subdivided epithelial cell subpopulations into 6 distinct subpopulations based on the expression of specific maker genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB-C). Tumor-derived gastric epithelial cells exhibit significant differences from normal cells at the single-cell level. Density distributions reveal that normal tissue primarily consists of mature, differentiated surface epithelial cells and chief cells, whereas tumor tissue is enriched with metaplastic and dysplastic/tumor cell populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD and \u003cb\u003eSupplementary Figs.\u0026nbsp;1B-C\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSubsequently, to delineate regulatory networks governing differential responses to ICIs in GC, we interrogated transcriptome profiles between GC with different responses to ICIs. Leveraging the CIBERSORT algorithm[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], we uncovered distinct disparities in immune infiltrate composition, particularly diminished CD8⁺ T cell infiltration and pronounced M2-polarized macrophage accumulation in non-responders (\u003cb\u003eSupplementary Figs.\u0026nbsp;1D\u003c/b\u003e). Subsequent gene set enrichment analysis (GSEA) using MSigDB Hallmark, Gene Ontology (GO), and KEGG databases revealed enrichment of immune response pathways, particularly involving mTORC1 signaling, spliceosome assembly, and RNA processing (\u003cb\u003eSupplemental Fig.\u0026nbsp;1E-F\u003c/b\u003e). Strikingly, spliceosome components (SRSF/THOC families) were differentially upregulated in non-responders (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE), implicating dysregulated RNA processing in T-cell exclusion and TAM polarization.\u003c/p\u003e\u003cp\u003eWe next intersected the upregulated genes from scRNA-seq (Tumor vs. Normal) and bulk RNA-seq (Non-responder vs. Responder) with spliceosome-related genes, which yielded three consistently candidates: SRSF10, SRSF6 and THOC2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Among these, SRSF10 demonstrated significantly higher expression in tumor tissues during scRNA-seq (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG-H). Consistent with this, analysis of TCGA-STAD data confirmed elevated SRSF10 expression in tumor tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI). Notably, we identified significant dysregulation of spliceosome components, with SRSF10 demonstrating marked suppression in highly responsive tumors, suggesting its pivotal role in dictating ICIs response for GC patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ, M-N). Subsequently, we employed immunohistochemistry (IHC) to observe the dynamic changes in SRSF10 expression across normal gastric tissue, intestinal metaplasia (IM), and dysplastic gastric tissue (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eK and \u003cb\u003eSupplemental Fig.\u0026nbsp;2A\u003c/b\u003e). The results further confirmed that SRSF10 expression exhibits a stepwise increase throughout the entire gastric tumorigenesis process. qPCR results further confirmed elevated SRSF10 expression levels in gastric cancer tissues (\u003cb\u003eSupplementary Fig.\u0026nbsp;2B\u003c/b\u003e). Assessing SRSF10 dynamics during gastric tumorigenesis, we employed N-methyl-N-nitrosourea (MNU)-induced chemical carcinogenesis, as previously reported[\u003cspan additionalcitationids=\"CR27 CR28 CR29\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. We observed substantial SRSF10 upregulation during malignant transformation of gastric epithelium relative to adjacent non-neoplastic tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eL).\u003c/p\u003e\u003cp\u003eCritically, elevated SRSF10 expression was associated with a poorer prognosis (\u003cb\u003eSupplementary Fig.\u0026nbsp;2C\u003c/b\u003e), as indicated by reduced overall survival (OS; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eO) and disease-free survival (DFS; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eP). According to the univariate/multivariate Cox regression analyses, the BMI, TNM stage, and SRSF10 levels were significantly associated with both OS and DFS (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eQ and \u003cb\u003eSupplementary Fig.\u0026nbsp;2D\u003c/b\u003e), implying, SRSF10 emerged as independent prognostic factors. These results reaffirm the stepwise increase of SRSF10 expression throughout gastric tumorigenesis. Collectively, these findings suggest SRSF10 may function as a modulator central to both the establishment of ICIs-refractory and gastric tumorigenesis, positioning it as a compelling therapeutic target.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSRSF10 Inhibition Impairs Growth of GC\u003c/h3\u003e\n\u003cp\u003eTo further investigate the cell-autonomous effects of SRSF10 on GC progression, we established SRSF10 knockdown and overexpression cell lines in GC cells (\u003cb\u003eSupplemental Fig.\u0026nbsp;3A-B\u003c/b\u003e). Utilizing CCK-8 proliferation assays and cell cycle analysis, we demonstrated that SRSF10 significantly enhances \u003cem\u003ein vitro\u003c/em\u003e tumor cell proliferation, whereas its depletion exerts an inhibitory effect (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-D and \u003cb\u003eSupplemental Fig.\u0026nbsp;3C-D\u003c/b\u003e). Subsequently, we established Srsf10 knockdown cell lines in YTN3 mice GC cells. In vivo xenograft models of C57BL/6 wild-type mice, tumors with Srsf10 knockdown exhibited markedly slower growth rates compared to control grafts. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-G).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePreviously, Shkreta et al.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] identified the 4-pyridinone-benzisothiazole carboxamide compound 1C8 as a selective inhibitor of SRSF10, which mediates antiviral responses. Concurrently, Cai et al.[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] demonstrated that targeting SRSF10 with 1C8 enhances MYB RNA stability, inhibits lactate production, and consequently augments the response to immunotherapy in hepatocellular carcinoma. Building on this foundation, to investigate the role of SRSF10 inhibition in gastric cancerous events, we crossed \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e alleles with \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003ep53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e, and \u003cem\u003eLSL-tdTomato\u003c/em\u003e mice to generate gastric adenocarcinoma models[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], thereby assessing the functional impact of SRSF10 inhibition via 1C8 on tumorigenesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH-I). Notably, gastric tumor areas in 1C8-treated mice were significantly smaller than those in controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ). Intriguingly, submucosal tumor cell infiltration was observed in a subset of control mice after 16 weeks of induction, whereas this phenomenon was entirely absent in 1C8-treated mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eK). To delineate the role of SRSF10 suppression in gastric carcinogenesis, we employed Trop2 as a marker for dysplastic cells. Immunofluorescence analysis revealed robust Trop2 expression in the majority of glands in control mice, contrasting with a reduction in Trop2-positive dysplastic cells in 1C8-treated mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eL). Additionally, we corroborated diminished CD44v9 (a marker for SPEM) staining in Trop2-positive cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eL), consistent with previous studies. Thus, SRSF10 propels gastric carcinogenesis by fueling proliferation and dysplastic advancement.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eTargeting SRSF10 Reprograms the Immunosuppressive Niche via CCL2\u003c/h2\u003e\u003cp\u003eTo delineate the mechanistic basis of SRSF10-driven GC progression, we performed RNA-seq on SRSF10-depleted GC cells. Differential gene expression analysis revealed that CCL2 (also known as MCP-1) was among the most significantly downregulated genes (Top 10) in the SRSF10 knockdown group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). RT-qPCR further validated that CCL2 mRNA expression was significantly reduced upon SRSF10 depletion (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Given CCL2's established role in recruiting and polarizing M2-TAMs within the TME[\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], we corroborated these findings through western blotting, ELISA, and immunofluorescence, collectively confirming diminished intracellular and secreted CCL2 protein (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-E). To ascertain whether SRSF10 influences the polarization of macrophages through CCL2, THP-1 monocytes were co-cultured with either shSRSF10 or control GC cells. Strikingly, macrophages exposed to shSRSF10 cells exhibited marked suppression of M2 markers (CD206, CD163, TGF-β1) and concomitant upregulation of M1 markers (NOS2, CXCL9, CXCL10) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF), indicating SRSF10 loss reprograms macrophages toward pro-inflammatory phenotypes.\u003c/p\u003e\u003cp\u003eImportantly, we crossed \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e alleles with \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003ep53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e mice to establish a gastric adenocarcinoma model to assess the effects of SRSF10 in TME using a selective inhibitor 1C8. We confirmed that 1C8 efficiently inhibits SRSF10 expression in \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e; \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e; \u003cem\u003ep53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e orthotopic GC models (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG). The immunofluorescence results revealed substantially diminished CCL2 expression in the 1C8-treated group than in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). Consistently, IHC revealed expanded CD86⁺ M1-macrophages and contracted CD206⁺ M2-macrophages populations (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI-K). To further investigate the communication patterns between SRSF10-positive epithelial cells and the tumor microenvironment, Cell Chat analysis was performed. The results of the study indicated a substantial increase in the interactions between SRSF10-positive cells and various immune or stromal cell types, including fibroblasts, endothelial cells, and macrophages (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eL). A notable finding was the observation of substantial ligand-receptor interactions between SRSF10-positive epithelial cells and macrophages via the CCL2\u0026ndash;CCR2 signaling pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eM). Quantitative analysis further confirmed that CCL2\u0026ndash;CCR2 interactions were significantly enhanced in SRSF10-positive epithelial cells compared to SRSF10-negative cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eN). Further immunofluorescence results revealed significantly enhanced recruitment of GzmB⁺/CD8⁺ T cells in the 1C8-treated group compared to the control group. Collectively, these data establish that SRSF10 inhibition reprograms macrophages in the immunosuppressive TME by ablating CCL2.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSRSF10 Blockade Attenuates Pre-neoplastic Metaplastic Cell Proliferation and TAMs Reprogramming\u003c/h3\u003e\n\u003cp\u003eTo further investigate SRSF10's role in pre-neoplastic metaplastic process, we employed a high-dose tamoxifen (HDT) injury model, which has been extensively utilized by us and others[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. HDT induces the loss of acid-secreting parietal cells in the gastric corpus and induces the formation of proliferative metaplastic cells (\u003cb\u003eSupplemental Fig.\u0026nbsp;4A\u003c/b\u003e), has been called pseudopyloric metaplasia or spasmolytic polypeptide-expressing metaplasia (SPEM)[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Notably, 1C8 monotherapy in the naive stomach exerted negligible effects on isthmus mitotic activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-C). Intriguingly, while 1C8 failed to disrupt SPEM initiation, it selectively abrogated the proliferative capacity of HDT-induced SPEM-like cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-C). Immunohistochemical profiling demonstrated that 1C8 significantly reprogrammed the TAM landscape: contracting CD206⁺ M2-like populations while expanding CD86⁺ M1-like macrophages (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD-G). This polarization shift implies SRSF10 inhibition attenuates pre-neoplastic metaplastic immunosuppressive niche.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eSRSF10 Regulates BCAT2 Exon Skipping to Activates mTORC1 Signaling\u003c/h3\u003e\n\u003cp\u003eTo elucidate SRSF10\u0026rsquo;s mechanistic link to CCL2, we bioinformatically scanned the CCL2 pre-mRNA (ENST000002258314) for potential binding sites using the RBP suite algorithm[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. However, no clear evidence was found to support a direct interaction between SRSF10 and CCL2 mRNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Intriguingly, transcriptome-wide GSEA revealed pronounced suppression of mTORC1 signaling upon SRSF10 knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB and \u003cb\u003eSupplementary Fig.\u0026nbsp;5A\u003c/b\u003e). Corroborating this, western blot demonstrated concerted attenuation of p-mTOR, CCL2, and stemness factors SOX9/CD44 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Using the \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e; \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e; \u003cem\u003ep53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e mice models, we confirmed reduced p-mTOR⁺ gastric epithelial cells (GECs) with 1C8 treatment compared to control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD-E), validating the mTORC1 inhibition by SRSF10 ablation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo identify the AS events regulating mTOR signaling, we intersected genes that underwent AS (junction count-only method) with differential expression genes (DEGs; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, LogFC \u0026lt; -1). We found 13 AS events (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF and \u003cb\u003eSupplementary Fig.\u0026nbsp;5B\u003c/b\u003e). Among these AS events, BCAT2 have been reported to activate the mTOR signaling[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Encouragingly, SRSF10 knockdown led to an increased exclusion of exon 2, generating more BCAT2 transcripts with exon 2 exclusion [BCAT2-E2(-)] and fewer BCAT2 transcripts with exon 2 inclusion [BCAT2-E2(+)] compared with the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG-H). Notably, RIP established direct SRSF10 binding to BCAT2 pre-mRNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI), while actinomycin D assays proved SRSF10 stabilizes BCAT2 transcripts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ). Critically, BCAT2 overexpression rescued p-mTOR, CCL2, SOX9, and CD44 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eK), affirming functional causality. IHC of human GC tissues revealed SRSF10 levels correlated positively with BCAT2 but relatively weakly correlated with p-mTOR (\u003cb\u003eSupplementary Fig.\u0026nbsp;5C\u003c/b\u003e). To this end, we further found minimal p-mTOR in SRSF10-low\u0026amp;BCAT2-low specimens versus maximal activation in SRSF10-high\u0026amp;BCAT2-high cohorts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eL-M), indicating that the activation of p-mTOR by SRSF10 is dependent on BCAT2.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePharmacological Antagonism of SRSF10 Potentiate Anti-PD-1 Therapy Efficacy\u003c/h2\u003e\u003cp\u003eAs we confirmed that SRSF10 inhibition could increase the infiltration of CD8\u003csup\u003e+\u003c/sup\u003e T cells and reprogram TAMs and convert them into M1-like TAMs in the TME. To investigate whether targeting SRSF10 enhances the therapeutic effect of anti-PD-1, we administered PD-1 monoclonal antibodies, SRSF10-targeting agent 1C8, IgG in \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e; \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e; \u003cem\u003ep53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e mice by administering tamoxifen (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). The results revealed that the combination therapy of 1C8 and anti-PD-1 significantly reduced gastric tumor burden compared to monotherapy or control treatment alone (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB-E). Notably, survival analysis showed that GC-burdened mice receiving the combined treatment exhibited a significant survival advantage over all other treatment groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe further conducted Immunofluorescence evaluation of TROP2 (marker of intramucosal dysplasia) and CD44v9/SOX9 (marker for metaplastic lineage) to elucidate alterations in metaplastic or dysplastic cells following combination therapy. Notably, the combined regimen of 1C8 and anti-PD-1 antibody demonstrated significant efficacy in suppressing the emergence of TROP2\u003csup\u003e+\u003c/sup\u003e dysplastic cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF-G), concomitant with a marked reduction in SOX9\u003csup\u003e+\u003c/sup\u003e/CD44v9\u003csup\u003e+\u003c/sup\u003e metaplastic cell populations \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH and \u003cb\u003eSupplemental Fig.\u0026nbsp;6A\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eThe effect of the combination therapy of 1C8 and anti-PD-1 on macrophage phenotype was evaluated by IHC. Our data showed that more cells expressed CD86\u003csup\u003e+\u003c/sup\u003e M1-type TAMs, but less cells expressed CD206\u003csup\u003e+\u003c/sup\u003e M2-type TAMs in gastric tissue in combined regimen groups (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI-J). As expected, combination treatment synergistically promoted intra tumoral CD8\u003csup\u003e+\u003c/sup\u003e T cells expansion in \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e; \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e; \u003cem\u003ep53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e mice. Collectively, our data revealed that SRSF10 is a key target of the immunotherapy response in GC, and provided proof of concept the blockade of SRSF10 is a potentially effective approach for improving the efficacy of immunotherapy in GC.\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eAdvanced GC remains a lethal disease with a poor ICIs response and prognosis, necessitating urgent elucidation of the mechanisms underlying its immune escape, and developing effective therapeutic strategies[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Recent studies have revealed the pivotal function of AS in tumor progression and immune regulation[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], yet the role of AS and immunotherapy response in GC remains unclear. Our study establishes splicing factor SRSF10 as a master regulator orchestrating both tumor-intrinsic growth and immunosuppressive niche formation. We revealed that SRSF10 regulates exon skipping of the BCAT2 gene, thereby influencing mTOR activation and CCL2-mediated macrophage polarization, and ultimately promoting immune escape and tumor progression. Pharmacological antagonism of SRSF10 synergized with anti-PD-1 by reshaping macrophage plasticity, proposing a druggable strategy to overcome GC immunotherapy resistance.\u003c/p\u003e\u003cp\u003eTranscriptomic profiling of ICIs responders versus non-responders revealed SRSF10 as one of the most differentially expressed spliceosome component, exhibiting pronounced elevation in therapy-resistant GC. Critically, its progressive upregulation during the metaplasia-dysplasia-carcinoma sequence, suggesting SRSF10 acts a duality gene by potentiating both malignant transformation and immune escape. This aligns with emerging evidence that spliceosome generate neoantigens while paradoxically fostering T-cell exhaustion[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Notably, SRSF10 expression inversely correlated with GC patient survival outcomes, establishing it as an independent prognostic factor\u0026mdash;a finding consistent with its oncogenic roles in hepatocellular carcinoma and cervical cancer[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA vital revelation of our study is the SRSF10-CCL2 axis as a driver of TAM polarization. SRSF10 knockdown drastically reduced CCL2 transcription and secretion, shifting macrophages from immunosuppressive M2 (CD206⁺/CD163⁺/TGF-β⁺) to pro-inflammatory M1 phenotypes (CD86⁺/CXCL9⁺/NOS2⁺). This reprogramming enhanced intratumoral CD8⁺ T-cell infiltration and granzyme B production, effectively converting immune-deserted tumors into immunoreactive niches. CCL2 (MCP-1) is a well-established chemokine recruiting CCR2⁺ monocytes and polarizing them toward M2 states[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Our data extend this paradigm by implicating SRSF10 as an upstream transcriptional regulator of CCL2, thereby positioning splicing machinery as a key modulator of chemokine-driven immune evasion.\u003c/p\u003e\u003cp\u003eIntriguingly, we revealed that SRSF10\u0026rsquo;s regulation of CCL2 is indirect, mediated through mTORC1 activation via BCAT2 exon 2 inclusion. BCAT2, a metabolic enzyme in branched-chain amino acid (BCAA) catabolism, has been reported to activate mTORC1 in colorectal cancer progression[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. We demonstrated that SRSF10 binds BCAT2 pre-mRNA, enforcing exon 2 inclusion [BCAT2-E2(+)] and enhancing transcript stability.\u003c/p\u003e\u003cp\u003eHarnessing innate antitumor immunity has emerged as a pivotal therapeutic component of combinatorial immunotherapy regimens[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In this study, we showed that pharmacologically targeting SRSF10, using a small-molecule inhibitor 1C8, significantly reduced tumor burden and improved survival in a spontaneous GC mouse model. The combination therapy not only suppressed tumor cell proliferation but also further reduced expression of SOX9 and CD44v9, suggesting that dual targeting of SRSF10 and immune checkpoints may be an effective strategy to overcome resistance and eradicate stem-like tumor cells.\u003c/p\u003e\u003cp\u003eIn conclusion, our study provides insight into the prominent role of SRSF10 in reprograming the tumor immunosuppressive niche, driven by BCAT2-dependent mTOR activation and CCL2-mediated TAMs polarization. Pharmacological inhibition of SRSF10 reshapes TAMs and synergizes with PD-1 blockade, providing a compelling rationale for clinical translation. As aberrant splicing emerges as a hallmark of cancer immune-resistance, targeting spliceosome nodes like SRSF10 offers a precision approach to reignite antitumor immunity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Natural Science Foundation of Fujian Province (No.2021J02039); Fujian provincial health technology project (No.2024QNA014); Joint Funds for the innovation of Science and Technology, Fujian province (No. 2024Y9320); the National Natural Science Foundation of China (No. 82473061); the National Natural Science Foundation of China (No. 82473120). We gratefully acknowledge the experimental technical support provided by the Public Technology Service Center of Fujian Medical University and the Key Laboratory of the Ministry of Education for Gastrointestinal Cancer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eX.-B.H., X.-P.Y., Z.-X.C., and H.-L.Z. contributed equally to this work and should be considered co-first authors. P.L., Q.-Y.C., and C.-M.H. (senior co-authors) had full access to all data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. C.-Y.J., X.-J.G., L.-Q.W., and B.L. contributed to concept and design. Q.H., Y.-X.G., Y.-F.L., Y.L., X.-Q.Y., J.-B.W., J.-W.X., J.-X.L., and C.-H.Z. performed acquisition, analysis, and interpretation of data. C.-Y.J., X.-J.G., L.-Q.W., B.L., and Q.H. drafted the manuscript. J.-B.W., J.-W.X., J.-X.L., and C.-H.Z. \u0026nbsp;performed statistical analysis. X.-B.H., X.-P.Y., Z.-X.C., H.-L.Z., C.-Y.J., X.-J.G., L.-Q.W., B.L., Q.H., Y.-X.G., Y.-F.L., Y.L., X.-Q.Y., J.-B.W., J.-W.X., J.-X.L., and C.-H.Z. \u0026nbsp;provided administrative, technical, or material support. X.-B.H., X.-P.Y., Z.-X.C., and H.-L.Z. \u0026nbsp;performed supervision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the findings of this study are available from the corresponding author on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Research Ethics Committee of the Fujian Medical University Union Hospital reviewed and approved the study (No. FJMU IACUC 2021-J-0174; 2021KJT036). All study participants provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent for publication:\u0026nbsp;\u003c/strong\u003eObtained.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eA. Ribas, J.D. Wolchok, Cancer immunotherapy using checkpoint blockade, Science, 359 (2018) 1350-1355.\u003c/li\u003e\n\u003cli\u003eD.S. Chen, I. 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Yee, Combination of PD-1 Inhibitor and OX40 Agonist Induces Tumor Rejection and Immune Memory in Mouse Models of Pancreatic Cancer, Gastroenterology, 159 (2020) 306-319.e312.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Serine/Arginine-rich Splicing Factor 10, Alternative Splicing, Tumor-Associated Macrophage, Immune Checkpoint Inhibitor","lastPublishedDoi":"10.21203/rs.3.rs-7510487/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7510487/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAberrant alternative splicing (AS) in cancer generates oncogenic proteomic diversity that drives tumor progression. Given the suboptimal efficacy of immune checkpoint inhibitors (ICIs) in gastric cancer (GC), the therapeutic potential of modulating RNA splicing to augment immunotherapy remains unclear. Here, we demonstrate that the splicing factor SRSF10 is progressively upregulated during gastric tumorigenesis and exhibits elevated expression in ICIs-resistant GC. Utilizing multiple mouse models, we confirmed that SRSF10 ablation with a selective inhibitor 1C8 robustly inhibits GC growth and enhances CD8\u003csup\u003e+\u003c/sup\u003e T-cell infiltration via CCL2-mediated reprogramming of tumor-associated macrophages (TAMs). Notably, SRSF10 blockade restricts pre-neoplastic metaplastic cells re-entry the cell cycle and the TAMs reprogramming. Mechanistically, cell-autonomous SRSF10 activates mTOR signaling primarily through inclusion of exon 2 in the BCAA transaminase 2 (BCAT2) mRNA. Pharmacological antagonism of SRSF10 potentiated the therapeutic effect of anti-PD-1 antibody in \u003cem\u003eTff1-CreERT\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e; \u003cem\u003eApc\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e; \u003cem\u003ep53\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e orthotopic GC models. Collectively, our findings revealed that SRSF10 orchestrates mTOR-CCL2 signaling by alternative RNA splicing of BCAT2 to reprogram TAMs, proposing SRSF10 as a tempting therapeutic target for GC immunotherapy.\u003c/p\u003e","manuscriptTitle":"Disrupting SRSF10-dependent BCAT2 Exon Skipping Reprograms Tumor-Associated Macrophages and Enhances Anti-PD-1 Efficacy in Gastric Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-16 08:04:02","doi":"10.21203/rs.3.rs-7510487/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-10-27T10:35:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-10-26T06:09:37+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-10-22T16:47:39+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-14T02:07:33+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-06T15:56:03+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-10-03T01:47:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-03T10:44:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cell Death \u0026 Disease","date":"2025-09-03T08:23:39+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2025-09-02T10:16:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-01T16:35:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fa3bff00-d2ff-4f4b-b9d1-bb2639bfc0f7","owner":[],"postedDate":"October 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":55694775,"name":"Biological sciences/Cancer/Gastrointestinal cancer/Gastric cancer"},{"id":55694776,"name":"Biological sciences/Cancer/Cancer microenvironment"}],"tags":[],"updatedAt":"2026-03-09T13:31:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-16 08:04:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7510487","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7510487","identity":"rs-7510487","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}