Cancer cells' DNA sequence (i.e., the genome) exhibits many alterations, such as mutations, compared to healthy cells. A typical scientific challenge lies in predicting the few specific mutations providing a selective advantage to cancer cells. Classically, scientists focus on mutations within the parts of the genome that code for proteins. However, most mutations happen in the noncoding portion of the genome. This is where cis-regulatory elements, that act like switches, control when, where, and how much a gene is expressed in different cells and tissues.
The study specifically looked at mutations in these cis-regulatory elements. The authors designed a computational approach to predict mutations likely associated with a cascading effect altering how the genome is regulated. This aspect is important because cancer often occurs when the regulation of genes goes wrong.
Notably, the analysis combined genetic information (i.e., mutations) and data on how the genes are expressed in the cancer cells to show that the mutations are likely to directly impact regulation. This approach differs from other methods that only look at how often mutations occur in cis-regulatory elements.
Overall, this study provides a new understanding of how cancer develops and its effects on key biological pathways. It also highlights the importance of studying mutations in noncoding genome regions.
A. Mathelier says: «Our study provides an innovative foray into exploring patients’ cancer mutations in the noncoding portion of the genome. This study advances our understanding of the disruption of the regulatory program occurring in cancer cells. We believe that such basic research has the potential to directly apply to the analysis of specialized cancer data to enhance the exploration of cancer mutations in the clinic.»
Reference
Castro-Mondragon JA, Aure MR, Lingjærde OC, Langerød A, Martens JWM, Børresen-Dale AL, Kristensen VN, Mathelier A. Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of gene regulatory programs in cancers. Nucleic Acids Res. 2022 Dec 8;50(21):12131–48. Full paper can be found here.
Abstract
Most cancer alterations occur in the noncoding portion of the human genome, where regulatory regions control gene expression. The discovery of noncoding mutations altering the cells' regulatory programs has been limited to a few examples with high recurrence or high functional impact. Here, we show that transcription factor binding sites (TFBSs) have similar mutation loads to those in protein-coding exons. By combining cancer somatic mutations in TFBSs and expression data for protein-coding and miRNA genes, we evaluate the combined effects of transcriptional and post-transcriptional alterations on the regulatory programs in cancers. The analysis of seven TCGA cohorts culminates with the identification of protein-coding and miRNA genes linked to mutations at TFBSs that are associated with a cascading trans-effect deregulation on the cells' regulatory programs. Our analyses of cis-regulatory mutations associated with miRNAs recurrently predict 12 mature miRNAs (derived from 7 precursors) associated with the deregulation of their target gene networks. The predictions are enriched for cancer-associated protein-coding and miRNA genes and highlight cis-regulatory mutations associated with the dysregulation of key pathways associated with carcinogenesis. By combining transcriptional and post-transcriptional regulation of gene expression, our method predicts cis-regulatory mutations related to the dysregulation of key gene regulatory networks in cancer patients.
About The Computational Biology & Gene Regulation Group
The group aims to develop cutting-edge bioinformatics tools with immediate application to real-life biological problems. They focus on gene expression regulation and the mechanisms by which it is disrupted in human diseases such as cancer.