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PMID: 21931712 已发表 · ppublish 英语

High throughput interrogation of somatic mutations in high grade serous cancer of the ovary.

PloS one ·第 6 卷 ·第 9 期 ·2012-06-08

Matulonis Ursula A, Hirsch Michelle, Palescandolo Emanuele, Kim Eejung, Liu Joyce, van Hummelen Paul, MacConaill Laura, Drapkin Ronny, Hahn William C

摘要

Epithelial ovarian cancer is the most lethal of all gynecologic malignancies, and high grade serous ovarian cancer (HGSC) is the most common subtype of ovarian cancer. The objective of this study was to determine the frequency and types of point somatic mutations in HGSC using a mutation detection protocol called OncoMap that employs mass spectrometric-based genotyping technology.,The Center for Cancer Genome Discovery (CCGD) Program at the Dana-Farber Cancer Institute (DFCI) has adapted a high-throughput genotyping platform to determine the mutation status of a large panel of known cancer genes. The mutation detection protocol, termed OncoMap has been expanded to detect more than 1000 mutations in 112 oncogenes in formalin-fixed paraffin-embedded (FFPE) tissue samples. We performed OncoMap on a set of 203 FFPE advanced staged HGSC specimens. We isolated genomic DNA from these samples, and after a battery of quality assurance tests, ran each of these samples on the OncoMap v3 platform. 56% (113/203) tumor samples harbored candidate mutations. Sixty-five samples had single mutations (32%) while the remaining samples had ≥ 2 mutations (24%). 196 candidate mutation calls were made in 50 genes. The most common somatic oncogene mutations were found in EGFR, KRAS, PDGRFα, KIT, and PIK3CA. Other mutations found in additional genes were found at lower frequencies (<3%).,Sequenom analysis using OncoMap on DNA extracted from FFPE ovarian cancer samples is feasible and leads to the detection of potentially druggable mutations. Screening HGSC for somatic mutations in oncogenes may lead to additional therapies for this patient population.

文献信息
期刊
PloS one
期刊简称
PLoS One
发表日期
2012-06-08
收录日期
2011-09-20
更新日期
2016-10-19
语言
英语
国家/地区
United States
NLM ID
101285081
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