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dc.contributor.authorGrant, Adam D
dc.contributor.authorVail, Paris
dc.contributor.authorPadi, Megha
dc.contributor.authorWitkiewicz, Agnieszka K
dc.contributor.authorKnudsen, Erik S
dc.date.accessioned2019-10-09T22:34:38Z
dc.date.available2019-10-09T22:34:38Z
dc.date.issued2019-09-04
dc.identifier.citationGrant, A. D., Vail, P., Padi, M., Witkiewicz, A. K., & Knudsen, E. S. (2019). Interrogating Mutant Allele Expression via Customized Reference Genomes to Define Influential Cancer Mutations. Scientific reports, 9(1), 1-15.en_US
dc.identifier.issn2045-2322
dc.identifier.pmid31484939
dc.identifier.doi10.1038/s41598-019-48967-8
dc.identifier.urihttp://hdl.handle.net/10150/634736
dc.description.abstractGenetic alterations are essential for cancer initiation and progression. However, differentiating mutations that drive the tumor phenotype from mutations that do not affect tumor fitness remains a fundamental challenge in cancer biology. To better understand the impact of a given mutation within cancer, RNA-sequencing data was used to categorize mutations based on their allelic expression. For this purpose, we developed the MAXX (Mutation Allelic Expression Extractor) software, which is highly effective at delineating the allelic expression of both single nucleotide variants and small insertions and deletions. Results from MAXX demonstrated that mutations can be separated into three groups based on their expression of the mutant allele, lack of expression from both alleles, or expression of only the wild-type allele. By taking into consideration the allelic expression patterns of genes that are mutated in PDAC, it was possible to increase the sensitivity of widely used driver mutation detection methods, as well as identify subtypes that have prognostic significance and are associated with sensitivity to select classes of therapeutic agents in cell culture. Thus, differentiating mutations based on their mutant allele expression via MAXX represents a means to parse somatic variants in tumor genomes, helping to elucidate a gene's respective role in cancer.en_US
dc.description.sponsorshipNational Institute of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01CA211878]en_US
dc.language.isoenen_US
dc.publisherNATURE PUBLISHING GROUPen_US
dc.rightsCopyright © The Author(s) 2019. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Cre-ative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not per-mitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/en_US
dc.titleInterrogating Mutant Allele Expression via Customized Reference Genomes to Define Influential Cancer Mutationsen_US
dc.typeArticleen_US
dc.contributor.departmentUniv Arizona, Canc Ctren_US
dc.contributor.departmentUniv Arizona, Dept Mol & Cellular Biolen_US
dc.identifier.journalSCIENTIFIC REPORTSen_US
dc.description.noteOpen access journalen_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal published versionen_US
dc.source.journaltitleScientific reports
refterms.dateFOA2019-10-09T22:34:38Z


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