The underlying molecular mechanisms and prognostic factors of RNA binding protein in colorectal cancer: a study based on multiple online databases

Downregulated RBM5 Enhances CARM1 Expression and Activates the PRKACA/GSK3β Signaling Pathway through Alternative Splicing-Coupled Nonsense-Mediated Decay

Downregulated RNA-binding motif protein 5 (RBM5) promotes the development and progression of various tumors, including bladder cancer (BC). Alternative splicing (AS) plays a crucial role in the progression of cancer by producing protein isomers with different functions or by promoting nonsense-mediated mRNA decay (NMD). However, whether RBM5 modulates the progression of BC through AS-NMD remains unexplored. In this study, we revealed that the downregulation of RBM5 expression promoted the expression of coactivator-associated arginine methyltransferase 1 (CARM1) in BC cells and tissues. Increased expression of CARM1 facilitated the activation of the Wnt/β-catenin axis and cell proliferation, which then contributed to the poor prognosis of patients with BC. Interestingly, RBM5 bound directly to CARM1 mRNA and participated in AS-NMD, downregulating the expression of CARM1. In addition, we revealed that protein kinase catalytic subunit alpha (PRKACA) functioned as a phosphorylated kinase of GSK3β, was regulated by CARM1 at the transcription level, and promoted the growth and progression of BC cells. Furthermore, in this study, we demonstrated a regulatory mechanism of Wnt/β-catenin activation through the RBM5/CARM1/PRKACA axis and identified a novel potential target for treating BC.

Development and Validation of an 8-Gene Signature to Improve Survival Prediction of Colorectal Cancer

Background

Most prognostic signatures for colorectal cancer (CRC) are developed to predict overall survival (OS). Gene signatures predicting recurrence-free survival (RFS) are rarely reported, and postoperative recurrence results in a poor outcome. Thus, we aim to construct a robust, individualized gene signature that can predict both OS and RFS of CRC patients.

Methods

Prognostic genes that were significantly associated with both OS and RFS in GSE39582 and TCGA cohorts were screened via univariate Cox regression analysis and Venn diagram. These genes were then submitted to least absolute shrinkage and selection operator (LASSO) regression analysis and followed by multivariate Cox regression analysis to obtain an optimal gene signature. Kaplan-Meier (K-M), calibration curves and receiver operating characteristic (ROC) curves were used to evaluate the predictive performance of this signature. A nomogram integrating prognostic factors was constructed to predict 1-, 3-, and 5-year survival probabilities. Function annotation and pathway enrichment analyses were used to elucidate the biological implications of this model.

Results

A total of 186 genes significantly associated with both OS and RFS were identified. Based on these genes, LASSO and multivariate Cox regression analyses determined an 8-gene signature that contained ATOH1, CACNB1, CEBPA, EPPHB2, HIST1H2BJ, INHBB, LYPD6, and ZBED3. Signature high-risk cases had worse OS in the GSE39582 training cohort (hazard ratio [HR] = 1.54, 95% confidence interval [CI] = 1.42 to 1.67) and the TCGA validation cohort (HR = 1.39, 95% CI = 1.24 to 1.56) and worse RFS in both cohorts (GSE39582: HR = 1.49, 95% CI = 1.35 to 1.64; TCGA: HR = 1.39, 95% CI = 1.25 to 1.56). The area under the curves (AUCs) of this model in the training and validation cohorts were all around 0.7, which were higher or no less than several previous models, suggesting that this signature could improve OS and RFS prediction of CRC patients. The risk score was related to multiple oncological pathways. CACNB1, HIST1H2BJ, and INHBB were significantly upregulated in CRC tissues.

Conclusion

A credible OS and RFS prediction signature with multi-cohort and cross-platform compatibility was constructed in CRC. This signature might facilitate personalized treatment and improve the survival of CRC patients.