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Background & Aims: Cancer stemness and immune evasion are closely associated and play critical roles in tumor development and resistance to immunotherapy. However, little is known about the underlying molecular mechanisms that coordinate this association. Methods: The expressions of heterogeneous nuclear ribonucleoprotein M (HNRNPM) in 240 hepatocellular carcinoma (HCC) samples, public databases, and liver development databases were analyzed. Chromatin immunoprecipitation assays were performed to explore the associations between stem-cell transcription factors and HNRNPM. HNRNPM-regulated alternative splicing (AS) and its binding motif were identified by RNA-seq and RIP-seq. HNRNPM-specific antisense oligonucleotides were developed to explore potential therapeutic targets in HCC. CD8+ T cells that were co-cultured with tumor cells were sorted by flow cytometry assays. Results: We identified an elevated oncofetal splicing factor in HCC, HNRNPM, that unifies and regulates the positive association between cancer stemness and immune evasion. HNRNPM knockdown abolished HCC tumorigenesis and diminished cancer stem cell properties in vitro and in vivo. Mechanistically, HNRNPM regulated the AS of MBD2 by binding its flanking introns, whose isoforms played opposing roles. Although MBD2a and MBD2c competitively bound to CpG islands in the FZD3 promoter, MBD2a preferentially increased FZD3 expression and then activated the WNT/β-catenin pathway. Interestingly, FZD3 and β-catenin further provided additional regulation by targeting OCT4 and SOX2. We found that HNRNPM inhibition significantly promoted CD8+ T cell activation and that HNRNPM- antisense oligonucleotides effectively inhibited WNT/β-catenin to enhance anti-programmed cell death protein-1 immunotherapy by promoting CD8+ T cell infiltration. Conclusions: HNRNPM has a tumor-intrinsic function in generating an immunosuppressive HCC environment through an AS-dependent mechanism and demonstrates proof of the concept of targeting HNRNPM in tailoring HCC immunotherapeutic approaches.

Abstract Background Due to the phenotypic and molecular diversity of hepatocellular carcinomas (HCC), it is still a challenge to determine patients’ prognosis. We aim to identify new prognostic markers for resected HCC patients. Methods 274 patients were retrospectively identified and samples collected from Zhongshan hospital, Fudan University. We analyzed the gene expression patterns of tumors and compared expression patterns with patient survival times. We identified a “9-gene signature” associated with survival by using the coefficient and regression formula of multivariate Cox model. This molecular signature was then validated in three patients cohorts from internal cohort (n = 69), TCGA (n = 369) and GEO dataset (n = 80). Results We identified 9-gene signature consisting of ZC2HC1A, MARCKSL1, PTGS1, CDKN2B, CLEC10A, PRDX3, PRKCH, MPEG1 and LMO2. The 9-gene signature was used, combined with clinical parameters, to fit a multivariable Cox model to the training cohort (concordance index, ci = 0.85), which was successfully validated (ci = 0.86 for internal cohort; ci = 0.78 for in silico cohort). The signature showed improved performance compared with clinical parameters alone (ci = 0.70). Furthermore, the signature predicted patient prognosis than previous gene signatures more accurately. It was also used to stratify early-stage, HBV or HCV-infected patients into low and high-risk groups, leading to significant differences in survival in training and validation (P