Your browser doesn't support javascript.
loading
Functional studies of lung cancer GWAS beyond association.
Long, Erping; Patel, Harsh; Byun, Jinyoung; Amos, Christopher I; Choi, Jiyeon.
Afiliação
  • Long E; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Patel H; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Byun J; Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, 77030, USA.
  • Amos CI; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, 77030, USA.
  • Choi J; Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, 77030, USA.
Hum Mol Genet ; 31(R1): R22-R36, 2022 10 20.
Article em En | MEDLINE | ID: mdl-35776125
ABSTRACT
Fourteen years after the first genome-wide association study (GWAS) of lung cancer was published, approximately 45 genomic loci have now been significantly associated with lung cancer risk. While functional characterization was performed for several of these loci, a comprehensive summary of the current molecular understanding of lung cancer risk has been lacking. Further, many novel computational and experimental tools now became available to accelerate the functional assessment of disease-associated variants, moving beyond locus-by-locus approaches. In this review, we first highlight the heterogeneity of lung cancer GWAS findings across histological subtypes, ancestries and smoking status, which poses unique challenges to follow-up studies. We then summarize the published lung cancer post-GWAS studies for each risk-associated locus to assess the current understanding of biological mechanisms beyond the initial statistical association. We further summarize strategies for GWAS functional follow-up studies considering cutting-edge functional genomics tools and providing a catalog of available resources relevant to lung cancer. Overall, we aim to highlight the importance of integrating computational and experimental approaches to draw biological insights from the lung cancer GWAS results beyond association.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Estudo de Associação Genômica Ampla / Neoplasias Pulmonares Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Hum Mol Genet Assunto da revista: BIOLOGIA MOLECULAR / GENETICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Estudo de Associação Genômica Ampla / Neoplasias Pulmonares Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Hum Mol Genet Assunto da revista: BIOLOGIA MOLECULAR / GENETICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos