Heterogeneous nuclear ribonucleoproteins depict a new predictive risk model for ovarian cancer prognosis and immunotherapy

Heterogeneous nuclear ribonucleoproteins (hnRNPs) are a family of RNA-binding proteins that are highly involved in nucleic-acid metabolism. The pathological effect of a series of hnRNPs family members on ovarian cancer is far from fully elucidated. This study acquired the RNA-seq data of ovarian cancer and imformation about hnRNP from TCGA database and a published study, respectively. The expression, mutation and copy number variation (CNV) of 22 hnRNP genes were analyzed. The hnRNP score, cell cycle and ferroptosis scores of ovarian cancer samples were calculated by ssGSEA. The intersection of hnRNP score related genes with cell cycle related genes or with ferroptosis related genes was taken to construct prognostic risk system by univariate Cox analysis, the Least Absolute Shrinkage and Selection Operator (LASSO)-regression analysis and multivariate Cox regression analysis, to predict the prognosis and response to immunotherapy. A prognostic risk system based on nine hnRNP score-related genes was created, which independently predicted the prognosis of ovarian cancer cases and has been validated and stable in different ovarian cancer cohorts. The expression of the prognostic signature genes in ovarian cancer tissues was verified by immunohistochemistry, and the correlation between their individual expression and the prognosis of ovarian cancer was investigated. To provide functional and mechanistic support beyond bulk transcriptomics, we integrated an independent high-grade serous ovarian cancer (HGSOC) single-cell atlas (GSE154600; 50,086 cells) and found that signature genes such as JCHAIN, S1PR4 and HAMP were expressed in a cell-type-restricted manner. In silico knockout predicted that JCHAIN, HAMP and S1PR4 knockdown perturbs plasma-cell humoral, macrophage antigen-presentation and NK/T-cell programs, respectively, and that HNRNPM loss is linked to extracellular-matrix remodeling. DepMap CRISPR dependency data further indicated that ovarian cancer cell lines depend on HNRNPM (median Chronos score -0.906) and RBM17 (-1.157). Promoter-methylation and m6A analyses suggested an epigenetic layer in the regulation of signature genes. Prognostic risk system was related to tumor immunomodulatory pathway and the activity level of some immune cells in tumor microenvironment (TME), and the expression of immune molecules, and immune score, stromal score. And it has potential ability to predict the response of cases to immunotherapy. We systematically demonstrated the expression of hnRNP gene family in different types of cancer, as well as the genetic variation in ovarian cancer and its potential impact on cancer development. We have created a risk system that effectively and steadily quantifies the prognosis of individual ovarian cancer cases and predicts the response to immunotherapy, which provides insight into hnRNP as a possible indicator to guide clinical decision-making.