Literature DB >> 31588509

MutEx: a multifaceted gateway for exploring integrative pan-cancer genomic data.

Jie Ping1, Olufunmilola Oyebamiji2, Hui Yu2, Scott Ness2, Jeremy Chien2, Fei Ye1, Huining Kang2, David Samuels3, Sergey Ivanov4, Danqian Chen5, Ying-Yong Zhao5, Yan Guo2.   

Abstract

Somatic mutation and gene expression dysregulation are considered two major tumorigenesis factors. While independent investigations of either factor pervade, studies of associations between somatic mutations and gene expression changes have been sporadic and nonsystematic. Utilizing genomic data collected from 11 315 subjects of 33 distinct cancer types, we constructed MutEx, a pan-cancer integrative genomic database. This database records the relationships among gene expression, somatic mutation and survival data for cancer patients. MutEx can be used to swiftly explore the relationship between these genomic/clinic features within and across cancer types and, more importantly, search for corroborating evidence for hypothesis inception. Our database also incorporated Gene Ontology and several pathway databases to enhance functional annotation, and elastic net and a gene expression composite score to aid in survival analysis. To demonstrate the usability of MutEx, we provide several application examples, including top somatic mutations associated with the most extensive expression dysregulation in breast cancer, differential mutational burden downstream of DNA mismatch repair gene mutations and composite gene expression score-based survival difference in breast cancer. MutEx can be accessed at http://www.innovebioinfo.com/Databases/Mutationdb_About.php.
© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  gene expression; somatic mutation; survival

Year:  2020        PMID: 31588509      PMCID: PMC7373173          DOI: 10.1093/bib/bbz084

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  24 in total

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8.  Mutational heterogeneity in cancer and the search for new cancer-associated genes.

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Journal:  Nature       Date:  2013-06-16       Impact factor: 49.962

9.  MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction.

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Journal:  Oncogene       Date:  2018-05-14       Impact factor: 9.867

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5.  Comprehensive Analysis of Co-Mutations Identifies Cooperating Mechanisms of Tumorigenesis.

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  5 in total

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