Evidence map›Paper›PMID 38062391›Full record

ArticleBMC bioinformatics2023

Incorporating mutational heterogeneity to identify genes that are enriched for synonymous mutations in cancer.

Yiyun Rao, Nabeel Ahmed, Justin Pritchard, Edward P O'Brien

Abstract read
In one paragraph

Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yiyun RaoHuck Institute of the Life Sciences, Pennsylvania State University, University Park, State College, PA, 16802, USA.
Nabeel AhmedHuck Institute of the Life Sciences, Pennsylvania State University, University Park, State College, PA, 16802, USA.
Justin PritchardDepartment of Biomedical Engineering, Pennsylvania State University, University Park, State College, PA, 16802, USA. jrp94@psu.edu.
Edward P O'BrienDepartment of Chemistry, Pennsylvania State University, University Park, State College, PA, 16802, USA. epo2@psu.edu.

Funding

Translation Kinetics and their Effects on Protein Structure and Function, mRNA half-lives, and Cellular PhenotypeR35GM124818 · NIGMS · PENNSYLVANIA STATE UNIVERSITY, THE · PI Edward Patrick O'Brien · 2017 to 2026
$4.0M
Model Driven Construction of Dual-switch Selection Gene Drives to Combat Drug ResistanceR21EB026617 · NIBIB · PENNSYLVANIA STATE UNIVERSITY, THE · PI PRITCHARD, JUSTIN · 2019 to 2021
$628k
NIBIB NIH HHS 5R21EB026617NIBIB NIH HHS R21 EB026617NIGMS NIH HHS R35 GM124818NIH HHS R35-GM124818
6 · The paper itself

Abstract

backgroundSynonymous mutations, which change the DNA sequence but not the encoded protein sequence, can affect protein structure and function, mRNA maturation, and mRNA half-lives. The possibility that synonymous mutations might be enriched in cancer has been explored in several recent studies. However, none of these studies control for all three types of mutational heterogeneity (patient, histology, and gene) that are known to affect the accurate identification of non-synonymous cancer-associated genes. Our goal is to adopt the current standard for non-synonymous mutations in an investigation of synonymous mutations.

resultsHere, we create an algorithm, MutSigCVsyn, an adaptation of MutSigCV, to identify cancer-associated genes that are enriched for synonymous mutations based on a non-coding background model that takes into account the mutational heterogeneity across these levels. Using MutSigCVsyn, we first analyzed 2572 cancer whole-genome samples from the Pan-cancer Analysis of Whole Genomes (PCAWG) to identify non-synonymous cancer drivers as a quality control. Indicative of the algorithm accuracy we find that 58.6% of these candidate genes were also found in Cancer Census Gene (CGC) list, and 66.2% were found within the PCAWG cancer driver list. We then applied it to identify 30 putative cancer-associated genes that are enriched for synonymous mutations within the same samples. One of the promising gene candidates is the B cell lymphoma 2 (BCL-2) gene. BCL-2 regulates apoptosis by antagonizing the action of proapoptotic BCL-2 family member proteins. The synonymous mutations in BCL2 are enriched in its anti-apoptotic domain and likely play a role in cancer cell proliferation.

conclusionOur study introduces MutSigCVsyn, an algorithm that accounts for mutational heterogeneity at patient, histology, and gene levels, to identify cancer-associated genes that are enriched for synonymous mutations using whole genome sequencing data. We identified 30 putative candidate genes that will benefit from future experimental studies on the role of synonymous mutations in cancer biology.

Indexed as

NeoplasmsSilent MutationDNA Mutational AnalysisGenome, HumanHumansMutationProto-Oncogene Proteins c-bcl-2RNA, MessengerProto-Oncogene Proteins c-bcl-2RNA, MessengerCancer driverMutSigCVSynonymous mutations

Identifiers

PMID38062391
PMCPMC10704839

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.