Background: Nowadays, non-small cell lung cancer (NSCLC) is a common and highly fatal malignancy worldwide. Therefore, identifying the potential prognostic markers and therapeutic targets is urgent for patients. Objective: This study aimed at finding hub targets associated with NSCLC using multiple databases. Methods: Differentially expressed genes (DEGs) from Genome Expression Omnibus (GEO) cohorts were employed for the enrichment analyses of Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genome (KEGG) pathways. Candidate key genes, filtered from the topological parameter 'Degree' and validated using the Cancer Genome Atlas (TCGA) cohort, were analyzed for their association with clinicopathological features and prognosis of NSCLC. Meanwhile, immunohistochemical cohort analyses and biological verification were further evaluated. Results: A total of 146 DEGs were identified following data preprocessing, and a protein-protein interaction (PPI) systematic network was constructed based on them. The top ten candidate core genes were further extracted from the above PPI network by using 'Degree' value, among which COL1A1 was shown to associate with overall survival (OS) of NSCLC as determined by using the Kaplan-Meier analysis (p=0.028), and could serve as an independent prognostic factor for OS in NSCLC patients (HR, 0.814; 95% CI, 0.665-0.996; p=0.046). We then analyzed the clinical stages, PPI, mutations, potential biological functions, and immune regulations of COL1A1 in NSCLC patients using multiple bioinformatics tools, including GEPIA, GeneMANIA, cBioPortal, GESA, and TISIDB. Finally, we further experimentally validated the overexpression of COL1A1 in NSCLC samples and found that inhibition of COL1A1 expression moderately sensitized NSCLC cells to cisplatin. Conclusion: Thus, our results showed that COL1A1 may serve as a potential prognostic marker and therapeutic target in NSCLC.