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PMID: 22585170 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencing.

Cancer discovery ·Vol. 2 ·No. 1 ·2012-01-00 ·Pages 82-93

Wagle N, Berger MF, Davis MJ, Blumenstiel B, Defelice M, Pochanard P, Ducar M, Van Hummelen P, Macconaill LE, Hahn WC, Meyerson M, Gabriel SB, Garraway LA

Abstract

Knowledge of "actionable" somatic genomic alterations present in each tumor (e.g., point mutations, small insertions/deletions, and copy-number alterations that direct therapeutic options) should facilitate individualized approaches to cancer treatment. However, clinical implementation of systematic genomic profiling has rarely been achieved beyond limited numbers of oncogene point mutations. To address this challenge, we utilized a targeted, massively parallel sequencing approach to detect tumor genomic alterations in formalin-fixed, paraffin-embedded (FFPE) tumor samples. Nearly 400-fold mean sequence coverage was achieved, and single-nucleotide sequence variants, small insertions/deletions, and chromosomal copynumber alterations were detected simultaneously with high accuracy compared with other methods in clinical use. Putatively actionable genomic alterations, including those that predict sensitivity or resistance to established and experimental therapies, were detected in each tumor sample tested. Thus, targeted deep sequencing of clinical tumor material may enable mutation-driven clinical trials and, ultimately, "personalized" cancer treatment. Despite the rapid proliferation of targeted therapeutic agents, systematic methods to profile clinically relevant tumor genomic alterations remain underdeveloped. We describe a sequencingbased approach to identifying genomic alterations in FFPE tumor samples. These studies affirm the feasibility and clinical utility of targeted sequencing in the oncology arena and provide a foundation for genomics-based stratification of cancer patients.

MeSH Terms
Cell Line, Tumor DNA Mutational Analysis/methods Gene Dosage High-Throughput Nucleotide Sequencing/methods Humans Neoplasms/genetics
Authors & Affiliations
13 authors, click to expand affiliations / ORCID
Wagle Nikhil
Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.
Berger Michael F
Davis Matthew J
Blumenstiel Brendan
Defelice Matthew
Pochanard Panisa
Ducar Matthew
Van Hummelen Paul
Macconaill Laura E
Hahn William C
Meyerson Matthew
Gabriel Stacey B
Garraway Levi A
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Article Info
Journal
Cancer discovery
Abbr.
Cancer Discov
ISSN
2159-8290
Published
2012-01-00
Epub
2011-00-07
Pages
82-93
Language
English
Region
United States
NLM ID
101561693
PMCID
PMC3353152
Subset
IM
Grants
NHGRI NIH HHS · U54 HG003067 · United States
NCI NIH HHS · R33 CA155554-01 · United States
NCI NIH HHS · P01 CA142536 · United States
NCI NIH HHS · R33 CA155554-02 · United States
NCI NIH HHS · T32 CA009172 · United States
NCI NIH HHS · R33 CA126674-04 · United States
NCI NIH HHS · R33 CA126674 · United States
NCI NIH HHS · R33 CA155554 · United States
NCI NIH HHS · R33CA126674 · United States
NCI NIH HHS · U24 CA143867 · United States
NIH HHS · DP2OD002750 · United States
NIH HHS · DP2 OD002750 · United States
NCI NIH HHS · U24CA143867 · United States
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