ABSTRACT
Multiple transcript isoforms of genes can be formed by processing and modifying the 5' and 3' ends of RNA. Herein, the aim of this study is to uncover the characteristics of RNA processing modification (RPM) in hepatocellular carcinoma (HCC), and to identify novel biomarkers and potential targets for treatment. Firstly, integrated bioinformatics analysis was carried out to identify risk prognostic RPM regulators (RPMRs). Then, we used these RPMRs to identify subtypes of HCC and explore differences in immune microenvironment and cellular function improvement pathways between the sub-types. Finally, we used the principal component analysis algorithms to estimate RPMscore, which were applied to 5 cohorts. Lower RPMscore among patients correlated with a declined survival rate, increased immune infiltration, and raised expression of immune checkpoints, aligning with the "immunity tidal model theory". The RPMscore exhibited robust, which was validated in multiple datasets. Mechanistically, low RPMscore can create an immunosuppressive microenvironment in HCC by manipulating tumor-associated macrophages. Preclinically, patients with high RPMscore might benefit from immunotherapy. The RPMscore is helpful in clustering HCC patients with distinct prognosis and immunotherapy. Our RPMscore model can help clinicians to select personalized therapy for HCC patients, and RPMscore may act a part in the development of HCC.
