Dataset Information

Identification of Driver Epistatic Gene Pairs Combining Germline and Somatic Mutations in Cancer.

ABSTRACT: Cancer arises from the complex interplay of various factors. Traditionally, the identification of driver genes focuses primarily on the analysis of somatic mutations. We describe a new method for the detection of driver gene pairs based on an epistasis analysis that considers both germline and somatic variations. Specifically, the identification of significantly mutated gene pairs entails the calculation of a contingency table, wherein one of the co-mutated genes can exhibit a germline variant. By adopting this approach, it is possible to select gene pairs in which the individual genes do not exhibit significant associations with cancer. Finally, a survival analysis is used to select clinically relevant gene pairs. To test the efficacy of the new algorithm, we analyzed the colon adenocarcinoma (COAD) and lung adenocarcinoma (LUAD) samples available at The Cancer Genome Atlas (TCGA). In the analysis of the COAD and LUAD samples, we identify epistatic gene pairs significantly mutated in tumor tissue with respect to normal tissue. We believe that further analysis of the gene pairs detected by our method will unveil new biological insights, enhancing a better description of the cancer mechanism.

SUBMITTER: Rocha J

PROVIDER: S-EPMC10253732 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Identification of Driver Epistatic Gene Pairs Combining Germline and Somatic Mutations in Cancer.

Rocha Jairo J Sastre Jaume J Amengual-Cladera Emilia E Hernandez-Rodriguez Jessica J Asensio-Landa Victor V Heine-Suñer Damià D Capriotti Emidio E

International journal of molecular sciences 20230526 11

Cancer arises from the complex interplay of various factors. Traditionally, the identification of driver genes focuses primarily on the analysis of somatic mutations. We describe a new method for the detection of driver gene pairs based on an epistasis analysis that considers both germline and somatic variations. Specifically, the identification of significantly mutated gene pairs entails the calculation of a contingency table, wherein one of the co-mutated genes can exhibit a germline variant. ...[more]

PMID: 37298272

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Project description:ObjectivesIn breast cancer (BC) patients, the frequency of germline BRCA mutations (gBRCA) may vary according to the ethnic background, age, and family history of cancer. Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) is the second most common somatic mutated gene in BC; however, the association of mutations in both genes with cancer has not been thoroughly investigated. Thus, our aims were to investigate gBRCA mutation frequency in a cohort of postmenopausal Brazilian BC patients and the association of gBRCA1/BRCA2 and PIK3CA somatic mutations.MethodsForty-nine postmenopausal (>55 years) and forty-one young (≤35 years) BC patients were included in this study. The postmenopausal group included patients who reported a positive family history of cancer. For these patients, gBRCA1/BRCA2 were sequenced using next-generation sequencing (NGS) or Sanger sequencing. Data for gBRCA in young patients were already available from a previous study. DNA from formalin-fixed, paraffin-embedded (FFPE) tumors was obtained from 27 postmenopausal and 41 young patients for analyzing exons 9 and 20 of PIK3CA. The association between gBRCA1/BRCA2 and somatic mutations in PIK3CA was investigated.ResultsThe overall frequency of gBRCA1/BRCA2 among the 49 postmenopausal patients was 10.2%. The frequencies of somatic mutations in PIK3CA in the postmenopausal and young patients were 37% and 17%, respectively (ns). The most common PIK3CA mutation was found to be E454A. Nonsense and frameshift mutations, which may counteract the oncogenic potential of PIK3CA were also detected. Regardless of age, 25% of BRCA1/BRCA2 mutation carriers and non-carriers , each, had PIK3CA somatic mutations.ConclusionsData obtained indicate that BRCA1/BRCA2 gene testing may be considered for postmenopausal patients with BC who have a family history of cancer. Although some of them are not considered pathogenic, somatic variants of PIK3CA are frequently observed in BC patients, especially in postmenopausal patients.

Project description:MotivationNext-generation sequencing technologies have accelerated the discovery of single nucleotide variants in the human genome, stimulating the development of predictors for classifying which of these variants are likely functional in disease, and which neutral. Recently, we proposed CScape, a method for discriminating between cancer driver mutations and presumed benign variants. For the neutral class, this method relied on benign germline variants found in the 1000 Genomes Project database. Discrimination could, therefore, be influenced by the distinction of germline versus somatic, rather than neutral versus disease driver. This motivates this article in which we consider predictive discrimination between recurrent and rare somatic single point mutations based solely on using cancer data, and the distinction between these two somatic classes and germline single point mutations.ResultsFor somatic point mutations in coding and non-coding regions of the genome, we propose CScape-somatic, an integrative classifier for predictively discriminating between recurrent and rare variants in the human cancer genome. In this study, we use purely cancer genome data and investigate the distinction between minimal occurrence and significantly recurrent somatic single point mutations in the human cancer genome. We show that this type of predictive distinction can give novel insight, and may deliver more meaningful prediction in both coding and non-coding regions of the cancer genome. Tested on somatic mutations, CScape-somatic outperforms alternative methods, reaching 74% balanced accuracy in coding regions and 69% in non-coding regions, whereas even higher accuracy may be achieved using thresholds to isolate high-confidence predictions.Availability and implementationPredictions and software are available at http://CScape-somatic.biocompute.org.uk/.Contactmark.f.rogers.phd@gmail.com or C.Campbell@bristol.ac.uk.Supplementary informationSupplementary data are available at Bioinformatics online.

Dataset Information

Identification of Driver Epistatic Gene Pairs Combining Germline and Somatic Mutations in Cancer.

Publications

Identification of Driver Epistatic Gene Pairs Combining Germline and Somatic Mutations in Cancer.

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