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dc.creatorGray, Phillip N.
dc.creatorVuong, Huy
dc.creatorTsai, Pei
dc.creatorLu, Hsaio-Mei
dc.creatorMu, Wenbo
dc.creatorHsuan, Vickie
dc.creatorHoo, Jayne
dc.creatorShah, Swati
dc.creatorUyeda, Lisa
dc.creatorFox, Susanne
dc.creatorPatel, Harshil
dc.creatorJanicek, Mike
dc.creatorBrown, Sandra
dc.creatorDobrea, Lavinia
dc.creatorWagman, Lawrence
dc.creatorPlimack, Elizabeth
dc.creatorMehra, Ranee
dc.creatorGolemis, Erica
dc.creatorBilusic, Marijo
dc.creatorZibelman, Matthew
dc.creatorElliott, Aaron
dc.date.accessioned2023-11-14T17:03:06Z
dc.date.available2023-11-14T17:03:06Z
dc.date.issued2016-09-08
dc.identifier.citationGray PN, Vuong H, Tsai P, Lu H, Mu W, Hsuan V, et al. TumorNext: A comprehensive tumor profiling assay that incorporates high resolution copy number analysis and germline status to improve testing accuracy. Oncotarget. 2016 Aug 8;7:68206-68228. doi:10.18632/oncotarget.11910.
dc.identifier.issn1949-2553
dc.identifier.urihttp://hdl.handle.net/20.500.12613/9235
dc.description.abstractThe development of targeted therapies for both germline and somatic DNA mutations has increased the need for molecular profiling assays to determine the mutational status of specific genes. Moreover, the potential of off-label prescription of targeted therapies favors classifying tumors based on DNA alterations rather than traditional tissue pathology. Here we describe the analytical validation of a custom probe-based NGS tumor panel, TumorNext, which can detect single nucleotide variants, small insertions and deletions in 142 genes that are frequently mutated in somatic and/or germline cancers. TumorNext also detects gene fusions and structural variants, such as tandem duplications and inversions, in 15 frequently disrupted oncogenes and tumor suppressors. The assay uses a matched control and custom bioinformatics pipeline to differentiate between somatic and germline mutations, allowing precise variant classification. We tested 170 previously characterized samples, of which > 95% were formalin-fixed paraffin embedded tissue from 8 different cancer types, and highlight examples where lack of germline status may have led to the inappropriate prescription of therapy. We also describe the validation of the Affymetrix OncoScan platform, an array technology for high resolution copy number variant detection for use in parallel with the NGS panel that can detect single copy amplifications and hemizygous deletions. We analyzed 80 previously characterized formalin-fixed paraffin-embedded specimens and provide examples of hemizygous deletion detection in samples with known pathogenic germline mutations. Thus, the TumorNext combined approach of NGS and OncoScan potentially allows for the identification of the “second hit” in hereditary cancer patients.
dc.format.extent23 pages
dc.languageEnglish
dc.language.isoeng
dc.relation.ispartofFaculty/ Researcher Works
dc.relation.haspartOncotarget, Vol. 7, No. 42
dc.relation.isreferencedbyImpact Journals
dc.rightsAttribution CC BY
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectTumor profiling
dc.subjectActionable mutations
dc.subjectNext generation sequencing
dc.subjectCopy number variants
dc.subjectGermline mutations
dc.titleTumorNext: A comprehensive tumor profiling assay that incorporates high resolution copy number analysis and germline status to improve testing accuracy
dc.typeText
dc.type.genreJournal article
dc.contributor.groupFox Chase Cancer Center (Temple University)
dc.description.departmentCancer and Cellular Biology
dc.relation.doihttp://dx.doi.org/10.18632/oncotarget.11910
dc.ada.noteFor Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu
dc.description.schoolcollegeLewis Katz School of Medicine
dc.creator.orcidGolemis|0000-0003-3618-3673
dc.creator.orcidBilusic|0000-0003-1020-689X
dc.creator.orcidZibelman|0000-0003-1475-6477
dc.temple.creatorPlimack, Elizabeth
dc.temple.creatorMehra, Ranee
dc.temple.creatorGolemis, Erica A.
dc.temple.creatorBilusic, Marijo
dc.temple.creatorZibelman, Matthew
refterms.dateFOA2023-11-14T17:03:06Z


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