Characterization of RNA Processing Genes in Colon Cancer for Predicting Clinical Outcomes.

Publisher: SAGE Publications Country of Publication: United States NLM ID: 101288638 Publication Model: eCollection Cited Medium: Print ISSN: 1177-2719 (Print) Linking ISSN: 11772719 NLM ISO Abbreviation: Biomark Insights Subsets: PubMed not MEDLINE

Publication: <2016- > : Thousand Oaks, CA : SAGE Publications
Original Publication: Auckland, N.Z. : Libertas Academica Ltd.

Objective: Colon cancer is associated with multiple levels of molecular heterogeneity. RNA processing converts primary transcriptional RNA to mature RNA, which drives tumourigenesis and its maintenance. The characterisation of RNA processing genes in colon cancer urgently needs to be elucidated.
Methods: In this study, we obtained 1033 relevant samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to explore the heterogeneity of RNA processing phenotypes in colon cancer. Firstly, Unsupervised hierarchical cluster analysis detected 4 subtypes with specific clinical outcomes and biological features via analysis of 485 RNA processing genes. Next, we adopted the least absolute shrinkage and selection operator (LASSO) as well as Cox regression model with penalty to characterise RNA processing-related prognostic features.
Results: An RNA processing-related prognostic risk model based on 10 genes including FXR1 , MFAP1 , RBM17 , SAGE1 , SNRPA1 , SRRM4 , ADAD1 , DDX52 , ERI1 , and EXOSC7 was identified finally. A composite prognostic nomogram was constructed by combining this feature with the remaining clinical variables including TNM, age, sex, and stage. Genetic variation, pathway activation, and immune heterogeneity with risk signatures were also analysed via bioinformatics methods. The outcomes indicated that the high-risk subgroup was associated with higher genomic instability, increased proliferative and cycle characteristics, decreased tumour killer CD8 ⁺ T cells and poorer clinical prognosis than the low-risk group.
Conclusion: This prognostic classifier based on RNA-edited genes facilitates stratification of colon cancer into specific subgroups according to TNM and clinical outcomes, genetic variation, pathway activation, and immune heterogeneity. It can be used for diagnosis, classification and targeted treatment strategies comparable to current standards in precision medicine. It provides a rationale for elucidation of the role of RNA editing genes and their clinical significance in colon cancer as prognostic markers.
Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
(© The Author(s) 2024.)

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Keywords: Colon cancer; GEO; RNA processing gene; TCGA; nomogram; prognosis; risk score

Date Created: 20240820 Latest Revision: 20240821

20240821

PMC11331464

10.1177/11772719241258642

39161926