Dataset Information

New lung cancer panel for high-throughput targeted resequencing.

ABSTRACT: We present a new next-generation sequencing-based method to identify somatic mutations of lung cancer. It is a comprehensive mutation profiling protocol to detect somatic mutations in 30 genes found frequently in lung adenocarcinoma. The total length of the target regions is 107 kb, and a capture assay was designed to cover 99% of it. This method exhibited about 97% mean coverage at 30× sequencing depth and 42% average specificity when sequencing of more than 3.25 Gb was carried out for the normal sample. We discovered 513 variations from targeted exome sequencing of lung cancer cells, which is 3.9-fold higher than in the normal sample. The variations in cancer cells included previously reported somatic mutations in the COSMIC database, such as variations in TP53, KRAS, and STK11 of sample H-23 and in EGFR of sample H-1650, especially with more than 1,000× coverage. Among the somatic mutations, up to 91% of single nucleotide polymorphisms from the two cancer samples were validated by DNA microarray-based genotyping. Our results demonstrated the feasibility of high-throughput mutation profiling with lung adenocarcinoma samples, and the profiling method can be used as a robust and effective protocol for somatic variant screening.

SUBMITTER: Kim EH

PROVIDER: S-EPMC4099348 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

New lung cancer panel for high-throughput targeted resequencing.

Kim Eun-Hye EH Lee Sunghoon S Park Jongsun J Lee Kyusang K Bhak Jong J Kim Byung Chul BC

Genomics & informatics 20140630 2

We present a new next-generation sequencing-based method to identify somatic mutations of lung cancer. It is a comprehensive mutation profiling protocol to detect somatic mutations in 30 genes found frequently in lung adenocarcinoma. The total length of the target regions is 107 kb, and a capture assay was designed to cover 99% of it. This method exhibited about 97% mean coverage at 30× sequencing depth and 42% average specificity when sequencing of more than 3.25 Gb was carried out for the norm ...[more]

PMID: 25031567

Similar Datasets

Project description:Background: Recent advanced technologies, such as high-throughput sequencing, have enabled the identification of a broad spectrum of variants. Using targeted-gene-panel resequencing for Parkinson's disease (PD)-associated genes, we have occasionally found several single-nucleotide variants (SNVs), which are thought to be disease-associated, in PD patients. To confirm the significance of these potentially disease-associated variants, we performed genome association analyses, using next-generation target resequencing, to evaluate the associations between the identified SNVs and PD. Methods: We obtained genomic DNA from 766 patients, who were clinically diagnosed with PD, and 336 healthy controls, all of Japanese origin. All data were analyzed using Ion AmpliSeq panel sequences, with 29 PD- or dementia-associated genes in a single panel. We excluded any variants that did not comply with the Hardy-Weinberg equilibrium in the control group. Variant frequencies in the PD and control groups were compared using PLINK. The identified variants were confirmed to a frequency difference of P < 0.05, after applying the Benjamini-Hochberg procedure using Fisher's exact test. The pathogenicity and prevalence of each variant were estimated based on a public gene database. Results: We identified three rare variants that were significantly associated with PD: rs201012663/rs150500694 in SYNJ1 and rs372754391 in DJ-1, which are intronic variants, and rs7412 in ApoE, which is an exonic variant. The variants in SYNJ1 and ApoE were frequently identified in the control group, and rs201012663/rs150500694 in SYNJ1 may play a protective role against PD. The DJ-1 variant was frequently identified in the PD group, with a high odds ratio of 2.2. Conclusion: The detected variants may represent genetic modifiers or disease-related variants in PD. Targeted-gene-panel resequencing may represent a useful method for detecting disease-causing variants and genetic association studies in PD.

Dataset Information

New lung cancer panel for high-throughput targeted resequencing.

Publications

New lung cancer panel for high-throughput targeted resequencing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets