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A mutational signature associated with alcohol consumption and prognostically significantly mutated driver genes in esophageal squamous cell carcinoma.


ABSTRACT: Background:Esophageal squamous cell carcinoma (ESCC) is often diagnosed at an advanced and incurable stage. Information on driver genes and prognosticators in ESCC remains incomplete. The objective was to elucidate significantly mutated genes (SMGs), mutational signatures, and prognosticators in ESCC. Patients and methods:Three MutSig algorithms (i.e. MutSigCV, MutSigCL and MutSigFN) and '20/20+' ratio-metric were employed to identify SMGs. Nonnegative matrix factorization was used to decipher mutational signatures. Kaplan-Meier survival analysis, multivariate Cox and logistic regression models were applied to analyze association between mutational features and clinical parameters. Results:We identified 26 SMGs, including 8 novel (NAV3, TENM3, PTCH1, TGFBR2, RIPK4, PBRM1, USP8 and BAP1) and 18 that have been previously reported. Three mutational signatures were identified to be prevalent in ESCC including clocklike C>T at CpG, APOBEC overactive C>T at TpCp[A/T], and a signature featured by T>C substitution. The T>C mutational signature was significantly correlated with alcohol consumption (OR: 3.59; 95% CI: 2.30-5.67; P?

SUBMITTER: Li XC 

PROVIDER: S-EPMC5913594 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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A mutational signature associated with alcohol consumption and prognostically significantly mutated driver genes in esophageal squamous cell carcinoma.

Li X C XC   Wang M Y MY   Yang M M   Dai H J HJ   Zhang B F BF   Wang W W   Chu X L XL   Wang X X   Zheng H H   Niu R F RF   Zhang W W   Chen K X KX  

Annals of oncology : official journal of the European Society for Medical Oncology 20180401 4


<h4>Background</h4>Esophageal squamous cell carcinoma (ESCC) is often diagnosed at an advanced and incurable stage. Information on driver genes and prognosticators in ESCC remains incomplete. The objective was to elucidate significantly mutated genes (SMGs), mutational signatures, and prognosticators in ESCC.<h4>Patients and methods</h4>Three MutSig algorithms (i.e. MutSigCV, MutSigCL and MutSigFN) and '20/20+' ratio-metric were employed to identify SMGs. Nonnegative matrix factorization was use  ...[more]

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