Identification and validation of novel prognostic biomarkers and therapeutic targets for non-small cell lung cancer

Abstract

Background: Despite the significant survival benefits of anti-PD-1/PD-L1 immunotherapy, non-small cell lung cancer (NSCLC) remains one of the most common tumors and major causes of cancer-related deaths worldwide. Thus, there is an urgent need to identify new therapeutic targets for this refractory disease.Methods: In this study, microarray datasets GSE27262, GSE75037, GSE102287, and GSE21933 were integrated by Venn diagram. We performed functional clustering and pathway enrichment analyses using R. Through the STRING database and Cytoscape, we conducted protein-protein interaction (PPI) network analysis and identified the key genes, which were verified by the GEPIA2 and UALCAN portal. Validation of actin-binding protein anillin (ANLN) was performed by quantitative real-time polymerase chain reaction and Western blotting. Additionally, Kaplan-Meier methods were used to compute the survival analyses.Results: In total, 126 differentially expressed genes were identified, which were enriched in mitotic nuclear division, mitotic cell cycle G2/M transition, vasculogenesis, spindle, and peroxisome proliferator-activated receptor signaling pathway. 12 central node genes were identified in the PPI network complex. The survival analysis revealed that high transcriptional levels were associated with inferior survival in NSCLC patients. The clinical implication of ANLN was further explored; its protein expression showed a gradually increasing trend from grade I to III.Conclusion: These Key genes may be involved in the carcinogenesis and progression of NSCLC, which may serve as useful targets for NSCLC diagnosis and treatment.

Advances in Genomic Data and Biomarkers: Revolutionizing NSCLC Diagnosis and Treatment

“…Below is a general methodology for discovering new biomarkers using bioinformatics tools [ 79 , 101 , 102 ]: Genomic data identification: The first step is to gather relevant genomic data for the study. This may include publicly available datasets from genomic databases, such as GenBank or the Human Genome Project Repository, or internally generated data from experiments.…”

“…Protein–protein interaction (PPI) network analysis identified central node genes, and their potential prognostic value was confirmed through survival analysis. The markers predicted in this study are listed below [ 101 ]: ANLN: ANLN is observed to be overexpressed in multiple tumor types, including pancreatic, brain, breast, and lung cancers. It is involved in cell proliferation, and its inhibition can impede cancer cell division, migration, and invasion.…”

“…Below is a general methodology for discovering new biomarkers using bioinformatics tools [79,101,102]:…”

“…Protein-protein interaction (PPI) network analysis identified central node genes, and their potential prognostic value was confirmed through survival analysis. The markers predicted in this study are listed below [101] BUB1: BUB1 is a serine/threonine-protein kinase that plays a critical role in oncogenesis, chromosome arrangement, and spindle assembly.…”