Impact of mini-driver genes in the prognosis and tumor features of colorectal cancer samples: a novel perspective to support current biomarkers

Abstract

Background Colorectal cancer (CRC) is the second leading cause of cancer-related deaths, and its development is associated with the gains and/or losses of genetic material, which leads to the emergence of main driver genes with higher mutational frequency. In addition, there are other genes with mutations that have weak tumor-promoting effects, known as mini-drivers, which could aggravate the development of oncogenesis when they occur together. The aim of our work was to use computer analysis to explore the survival impact, frequency, and incidence of mutations of possible mini-driver genes to be used for the prognosis of CRC. Methods We retrieved data from three sources of CRC samples using the cBioPortal platform and analyzed the mutational frequency to exclude genes with driver features and those mutated in less than 5% of the original cohort. We also observed that the mutational profile of these mini-driver candidates is associated with variations in the expression levels. The candidate genes obtained were subjected to Kaplan–Meier curve analysis, making a comparison between mutated and wild-type samples for each gene using a p-value threshold of 0.01. Results After gene filtering by mutational frequency, we obtained 159 genes of which 60 were associated with a high accumulation of total somatic mutations with Log2 (fold change) > 2 and p values < 10−5. In addition, these genes were enriched to oncogenic pathways such as epithelium-mesenchymal transition, hsa-miR-218-5p downregulation, and extracellular matrix organization. Our analysis identified five genes with possible implications as mini-drivers: DOCK3, FN1, PAPPA2, DNAH11, and FBN2. Furthermore, we evaluated a combined classification where CRC patients with at least one mutation in any of these genes were separated from the main cohort obtaining a p-value < 0.001 in the evaluation of CRC prognosis. Conclusion Our study suggests that the identification and incorporation of mini-driver genes in addition to known driver genes could enhance the accuracy of prognostic biomarkers for CRC.

Insights from a Computational-Based Approach for Analyzing Autophagy Genes across Human Cancers

“…This is noteworthy because lncRNAs, which are usually located in antisense strands of DNA from original genes, can also be affected by somatic mutations irrespective of their canonical effects. Thus, the combination of somatic mutations and non-coding RNA as potential prognostic markers deserves further attention, as demonstrated in COAD [ 59 ].…”