Abstract
Lung cancer remains as the leading cause of cancer-related death worldwide, and lung adenocarcinoma (LUAD) is the most common histological subtype. This study aims to investigate biomarkers associated with cancer progression and prognosis of LUAD. We integrated expression profiles of 668 lung cancer patients in five datasets from the Gene Expression Omnibus (GEO) and identified a panel of differentially expressed genes (DEGs). Function enrichment analysis highlighted that these genes were closely associated with the carcinogenesis of LUAD, such as cell cycle, ECM-receptor interaction and p53 signaling pathway. Cyclin-dependent kinase 1 (CDK1) and MAD2 mitotic arrest deficient-like 1 (MAD2L1), two critical mitotic checkpoint genes, were selected for further study. Elevated expression of CDK1 and MAD2L1 was validated in an independent LUAD cohort. Kaplan-Meier analysis revealed that CDK1 and MAD2L1 expression was negatively correlated with both overall survival (OS) and relapse-free survival (RFS). In conclusion, CDK1 and MAD2L1 were adverse prognostic biomarkers for LUAD whose increased expression could render patients with LUAD a high risk of cancer recurrence and poor survival, suggesting that they might be applied as potential targets for LUAD treatment.
Highlights
Lung cancer is the leading cause of cancer-related death worldwide, of which non-small cell lung cancer (NSCLC) accounts for approximately 85% cases [1]
Kaplan-Meier analysis revealed that Cyclin-dependent kinase 1 (CDK1) and MAD2L1 expression was negatively correlated with both overall survival (OS) and relapse-free survival (RFS)
We found that CDK1 and MAD2L1 were up-regulated in lung adenocarcinoma (LUAD) and directly correlated with the clinical pathological features
Summary
Lung cancer is the leading cause of cancer-related death worldwide, of which non-small cell lung cancer (NSCLC) accounts for approximately 85% cases [1]. An explanation might be that the effects of genes with broad confidence intervals are difficult to confirm using a validation strategy, that is, when genes are identified as significant in one study, they are further tested for significance in separate subsequent studies with smaller sample sizes [9]. To address these issues, validation of the signature genes in several independent studies or distinct patient populations is necessary
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