Cargando…

Gene methylation biomarkers in sputum as a classifier for lung cancer risk

CT screening for lung cancer reduces mortality, but will cost Medicare ∼2 billion dollars due in part to high false positive rates. Molecular biomarkers could augment current risk stratification used to select smokers for screening. Gene methylation in sputum reflects lung field cancerization that r...

Descripción completa

Detalles Bibliográficos
Autores principales: Leng, Shuguang, Wu, Guodong, Klinge, Donna M., Thomas, Cynthia L., Casas, Elia, Picchi, Maria A., Stidley, Christine A., Lee, Sandra J., Aisner, Seena, Siegfried, Jill M., Ramalingam, Suresh, Khuri, Fadlo R., Karp, Daniel D., Belinsky, Steven A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5609978/
https://www.ncbi.nlm.nih.gov/pubmed/28969046
http://dx.doi.org/10.18632/oncotarget.19255
Descripción
Sumario:CT screening for lung cancer reduces mortality, but will cost Medicare ∼2 billion dollars due in part to high false positive rates. Molecular biomarkers could augment current risk stratification used to select smokers for screening. Gene methylation in sputum reflects lung field cancerization that remains in lung cancer patients post-resection. This population was used in conjunction with cancer-free smokers to evaluate classification accuracy of a validated eight-gene methylation panel in sputum for cancer risk. Sputum from resected lung cancer patients (n=487) and smokers from Lovelace (n=1380) and PLuSS (n=718) cohorts was studied for methylation of an 8-gene panel. Area under a receiver operating characteristic curve was calculated to assess the prediction performance in logistic regressions with different sets of variables. The prevalence for methylation of all genes was significantly increased in the ECOG-ACRIN patients compared to cancer-free smokers as evident by elevated odds ratios that ranged from 1.6 to 8.9. The gene methylation panel showed lung cancer prediction accuracy of 82–86% and with addition of clinical variables improved to 87–90%. With sensitivity at 95%, specificity increased from 25% to 54% comparing clinical variables alone to their inclusion with methylation. The addition of methylation biomarkers to clinical variables would reduce false positive screens by ruling out one-third of smokers eligible for CT screening and could increase cancer detection rates through expanding risk assessment criteria.