Non-small Cell Carcinoma Genomic Biomarkers: Smoking Factors and Associated Biological Pathways

Non-small cell lung carcinoma (NSCLC) is a major health concern contributing to 84% of all lung cancers diagnosed in 2023. Drug resistance and the lack of diagnostic and therapeutic biomarkers result in high mortality rates, which are expected to rise due to increasing global tobacco consumption. This study aims to identify genomic biomarkers and biological pathways of disease metastasis and drug resistance in NSCLC. We retrieved and analyzed whole-exome sequencing data from 38 NSCLC patients using the COSMIC database. Based on smoking history, 8 patients were allocated into a subgroup. OncodriveCLUSTL identified driver genes with significant clustering. Clinical significance of clustered mutations was assessed by CancerVar based on AMP/CAP/ASCO guidelines. Oncogenicity prediction by artificial intelligence (OPAI) calculated oncogenicity scores for each mutation. Lastly, a filtered driver gene list was exploited to determine enriched biological pathways using g.Profiler. Clustering process identified 30 possible drivers with CTNND1, KRAS, and IKZF1 already included in cancer gene census. CancerVar categorized most mutations in Tier III, but they show high oncogenic potential as in SNRPN, TLE3 having the highest oncogenicity scores by OPAI. Pathway analysis revealed disrupted neuron apoptotic processes and calcium signaling pathways, such as voltage-gated calcium channel activity. The cellular components of zonula adherens enriched in the smoking subgroup revealed possible therapeutic targets. Future investigation on these findings will help to develop targeted therapies for these pathways.