Examination of Targetable Mutations by Smoking Status in The Cancer Genome Atlas (TCGA)

Authors: Arasada R PhD, Harris R MD PhD, Carbone DP MD PhD, Bittoni M PhD

Category: Early Detection & Risk Prediction
Conference Year: 2023

Abstract Body:
Purpose: The Cancer Genome Atlas (TCGA) database provides publicly available genomic data for many cancers. This report describes predictive models examining smoking status, demographic, and clinical factors, including race, age, gender, stage and vital status, and their associations with several lung cancer specific mutations, such as ALK, EGFR, ROS1, RET and KRAS. Methods: The data source for this study was the TCGA database, in which data from 522 histologically confirmed lung cancer cases (adenocarcinoma) were analyzed using multiple logistic regression to examine associations between genetic alterations (ALK, ROS1, EGFR, KRAS and RET) by smoking status (current, former, never) and gender, race, age at diagnosis, vital status and stage. Results: Of 522 cases, over half were female, 86% were white, with mean age 66 years, and 61% former smokers, 23% current smokers and 16% who never smoked. Adjusted logistic regression models revealed almost a 5-fold increased odds of EGFR for nonsmokers (versus current and former smokers; p<0.001), and almost a 2-fold increased odds for males (p<0.05). White race showed a 2.5 higher odds of ALK mutation, which approached significance (p=0.07), with former and current smokers showing a 3- and 4-fold increased odds of EGFR, respectively (p<0.05). Current smokers showed a 6.5 higher odds of ROS1 mutation versus nonsmokers (p=0.004). Similarly, current and former smokers exhibited a 3- and 5-fold increased odds of KRAS mutation, respectively, versus nonsmokers (p<0.05). No significant differences were found for RET mutation. Conclusions: This report showed diverse patterns of association between smoking and lung cancer-related mutations. Never smokers had a higher odds of EGFR, which is consistent with past findings, but current and/or former smokers showed a strong increased odds of developing most other mutations. White race showed potential associations with ALK only and males showed associations with EGFR. Overall, these results shed new light on current, former and never smoking as possible predictive factors for several genetic alterations, which has implications for treatment and warrants further research. Future research with larger, more diverse populations is needed to further refine and quantify these results

Keywords: Key words: lung cancer, smoking, genetic alterations