Identifying Pathogenic Genes Associated with Adenocarcinoma and Squamous cell carcinoma in Lung Cancer through DNA-Seq Data Analysis.

Abstract Introduction : Next-Generation Sequencing (NGS) has revolutionized genomic research, enabling comprehensive analysis of genetic variations associated with complex diseases like cancer. This research paper details a comprehensive analysis of DNA-Seq data from lung cancer patients, aiming to identify pathogenic genes and genetic variants contributing to the disease. Methodology : The study utilizes a robust bioinformatics pipeline, encompassing raw data quality control, read alignment to a reference genome, variant calling, and functional annotation. Data from germline and somatic samples of lung cancer patients, including normal, squamous cell carcinoma, and adenocarcinoma components, were processed using established tools such as FastQC, fastp, BWA, SAMtools, Picard-tools, GATK (HaplotypeCaller and Mutect2), SnpSift, and Ensembl's Variant Effect Predictor (VEP). Results : The findings highlight the critical role of specific gene variants in lung cancer pathogenesis, providing insights into potential diagnostic biomarkers and therapeutic targets. Conclusion : This study underscores the power of NGS and advanced bioinformatics in unraveling the genetic landscape of cancer, paving the way for personalized medicine approaches.