Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma

RNA binding proteins (RBPs) are aberrantly expressed in a tissue-specific manner across many tumors. These proteins, which play a vital role in post-transcriptional gene regulation, are involved in RNA splicing, maturation, transport, stability, degradation, and translation. We set out to establish an accurate risk score model based on RBPs to estimate prognosis in hepatocellular carcinoma (HCC). RNA-sequencing data, proteomic data and corresponding clinical information were acquired from the Cancer Genome Atlas database and the Clinical Proteomic Tumor Analysis Consortium database respectively. We identified 406 differentially expressed RBPs between HCC tumor and normal tissues at the transcriptional and protein level. Overall, 11 RBPs (BRIX1, DYNC1H1, GTPBP4, PRKDC, RAN, RBM19, SF3B4, SMG5, SPATS2, TAF9, and THOC5) were selected to establish a risk score model. We divided HCC patients into low-risk and high-risk groups based on the median of risk score values. The survival analysis indicated that patients in the high-risk group had poorer overall survival compared to patients in the low-risk group. Our study demonstrated that 11 RBPs were associated with the overall survival of HCC patients. These RBPs may represent potential drug targets and can help optimize future clinical treatment.

Automated summary

RBPs are aberrantly expressed in a tissue-specific manner in tumors. A risk score model based on RBPs was established to estimate prognosis in HCC, revealing 11 RBPs associated with overall survival of patients, potentially serving as drug targets.