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Gene ; 641: 94-104, 2018 Jan 30.
Article in English | MEDLINE | ID: mdl-29054765

ABSTRACT

Compared with numerous studies of somatic mutations using sporadic lung cancer, the research into germline mutations using familial lung cancer (FLC) is limited. In the present study, we used FLC samples obtained from the Chinese population in highly air-polluted regions to screen for novel germline mutations in lung cancer. Through a whole genome sequencing (WGS) analysis of the nine subjects (four lung cancer patients and five normal family members of FLC), we obtained a whole genome dataset of DNA alterations in FLC samples. A total of 1218 genes were identified with mutations of multiple types. Subsequently, the top 12 highly mutated genes were selected for validation by polymerase chain reaction and DNA sequencing in an expanded sample set including FLC, sporadic lung cancer, and healthy population. Mutations of the five genes (ARHGEF5, ANKRD20A2, ZNF595, ZNF812, MYO18B) may be potential germline mutations of lung cancer. We also analyzed specific mutations within the 12 genes and found that some specific mutations within the MUC12, FOXD4L3 and FOXD4L5 genes showed higher frequencies in the samples of FLC and/or lung cancer tissue, compared with the healthy population. Moreover, some genes with copy number variation may be potentially associated with a predisposition to lung cancer. Furthermore, non-coding DNA alterations of the WGS data in FLC were systematically analyzed and arranged. Interestingly, we found that germline mutations also occurred in many genes of non-coding RNA. This study uncovered the mutation spectrum in FLC and provided important clues for the evaluation of the genetic susceptibility to lung cancer.


Subject(s)
Carcinogenesis/chemically induced , Carcinogenesis/genetics , Genetic Predisposition to Disease/genetics , Germ-Line Mutation/genetics , Lung Neoplasms/genetics , Air Pollution , China , Female , Gene Frequency/genetics , Genome, Human/genetics , Humans , Male , Middle Aged , Smoking/adverse effects , Whole Genome Sequencing
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