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Targeted Sequencing of Cancer-Related Genes in Colorectal Cancer Using Next-Generation Sequencing

Overview of attention for article published in PLOS ONE, May 2013
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Title
Targeted Sequencing of Cancer-Related Genes in Colorectal Cancer Using Next-Generation Sequencing
Published in
PLOS ONE, May 2013
DOI 10.1371/journal.pone.0064271
Pubmed ID
Authors

Sae-Won Han, Hwang-Phill Kim, Jong-Yeon Shin, Eun-Goo Jeong, Won-Chul Lee, Kyung-Hun Lee, Jae-Kyung Won, Tae-Yong Kim, Do-Youn Oh, Seock-Ah Im, Yung-Jue Bang, Seung-Yong Jeong, Kyu Joo Park, Jae-Gahb Park, Gyeong Hoon Kang, Jeong-Sun Seo, Jong-Il Kim, Tae-You Kim

Abstract

Recent advance in sequencing technology has enabled comprehensive profiling of genetic alterations in cancer. We have established a targeted sequencing platform using next-generation sequencing (NGS) technology for clinical use, which can provide mutation and copy number variation data. NGS was performed with paired-end library enriched with exons of 183 cancer-related genes. Normal and tumor tissue pairs of 60 colorectal adenocarcinomas were used to test feasibility. Somatic mutation and copy number alteration were analyzed. A total of 526 somatic non-synonymous sequence variations were found in 113 genes. Among these, 278 single nucleotide variations were 232 different somatic point mutations. 216 SNV were 79 known single nucleotide polymorphisms in the dbSNP. 32 indels were 28 different indel mutations. Median number of mutated gene per tumor was 4 (range 0-23). Copy number gain (>X2 fold) was found in 65 genes in 40 patients, whereas copy number loss (<X0.5 fold) was found in 103 genes in 39 patients. The most frequently altered genes (mutation and/or copy number alteration) were APC in 35 patients (58%), TP53 in 34 (57%), and KRAS in 24 (40%). Altered gene list revealed ErbB signaling pathway as the most commonly involved pathway (25 patients, 42%). Targeted sequencing platform using NGS technology is feasible for clinical use and provides comprehensive genetic alteration data.

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Geographical breakdown

Country Count As %
Germany 1 <1%
Netherlands 1 <1%
Korea, Republic of 1 <1%
Sweden 1 <1%
Argentina 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 130 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 23%
Researcher 29 21%
Student > Master 16 12%
Student > Bachelor 9 7%
Other 8 6%
Other 23 17%
Unknown 21 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 30%
Medicine and Dentistry 33 24%
Biochemistry, Genetics and Molecular Biology 24 18%
Engineering 5 4%
Computer Science 3 2%
Other 5 4%
Unknown 26 19%