AUTHOR=Altaf Reem , Ilyas Umair , Ma Anmei , Shi Meiqi 

TITLE=Identification and validation of differentially expressed genes for targeted therapy in NSCLC using integrated bioinformatics analysis

JOURNAL=Frontiers in Oncology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1206768

DOI=10.3389/fonc.2023.1206768

ISSN=2234-943X

ABSTRACT=Background: Despite the high prevalence of lung cancer with only 23% of five-year survival rates the underlying molecular mechanisms of non-small cell lung cancer (NSCLC) remains unknown. It is a high need to identify reliable candidate biomarker genes for early diagnosis and targeted therapeutic strategies to prevent cancer progression.
Methods: In this study, four datasets obtained from Gene Expression Omnibus were evaluated for NSCLC associated differentially expressed genes (DEGs) using bioinformatics analysis. About 10 common significant DEGs were shortlisted based on their p-value and FDR (DOCK4, ID2, SASH1, NPR1, GJA4, TBX2, CD24, HBEGF, GATA3 and DDR1).  The expression of significant genes were validated using experimental data obtained for TCGA and The Human Protein Atlas database. The human proteomic data for post translational modifications was used to interpret the mutations of these genes. 
Results: The validation of DEGs revealed significant difference in the expression of hub genes in normal and tumorous tissues. The mutational analysis revealed 22.69%, 48.95% and 47.21% sequence predicted disordered region of DOCK4, GJA4 and HBEGF, respectively. The miRNA prediction presented specific miRNA targets hsa-miR-302c-5p, hsa-miR-4531, hsa-miR-11181-5p for DOCK4, SASH1 and ID2, respectively, that have shown association with NSCLC. The system level network showed important interaction of these genes and the drug interaction network showed that these genes are affected by several types of chemicals that could serve as potential drug targets. 
Conclusion: The study demonstrates the importance of system genetics in identifying potential drug targeted therapy for NSCLC. The integrative system level approach shall aid in better understanding of disease etiology and can accelerate the drug discovery outcomes for many cancer types.