Role of CENPL, DARS2 and PAICS in determining the prognosis in patients with lung adenocarcinoma

Abstract

Abstract Purpose Nonsmall cell lung cancer (NSCLC) accounts for about 85% of lung cancer cases and is the leading cause of tumor-related death, of which Lung adenocarcinoma (LUAD) is the most prevalent histological subtype. At present, the prognosis of LUAD remains poor due to local recurrence and distant metastasis. This study aims to explore the key prognostic biomarkers and investigate the underlying mechanism. Methods GDC TCGA Lung adenocarcinoma (Data Release 18.0, July 8, 2019) was downloaded from the UCSC Xena browser. The dataset of GSE72094 and GSE13213 and the corresponding clinical information were downloaded from GEO database. By analyzing above datasets through DESeq2 R package and Limma R package, differentially expressed genes (DEGs) were found. GO and KEGG analysis were used to analyze the possible enrichment pathways of these DEGs. the protein-protein interaction network was constructed to explore the possible relationship among these DEGs using the STRING database. Survival analysis was performed to identify reliable prognostic genes using Kaplan-Meier method. Multi-omics analysis of the prognostic genes was performed using the GSCA. TIMER database was used to analyze the association of the prognostic genes with immune infiltration. Spearman correlation analysis was conducted to research the correlation between the prognostic genes and drug sensitivity. The multivariate Cox regression was used to identify the independent prognostic factor of LUAD. Finally, a nomogram was constructed using the rms R package . Results Firstly, we screened out 30 DEGs which may be associated with tumor progression. Functional enrichment analysis and PPI network were conducted to reveal the potential enrichment pathways and interactions of these DEGs. Secondly, survival analysis revealed that the expression of CENPL, DARS2 and PAICS was negatively correlated with prognosis of LUAD patients. Multi-omics analysis further disclosed that CENPL, DARS2 and PAICS expressions were significantly higher in LUAD. CENPL, DARS2 and PAICS were all high-expressed in the late groups and M1 stage of LUAD. The correlation analysis indicated that CENPL, DARS2 and PAICS may not be associated with activation or suppression of immune cells. Drug sensitivity analysis for CENPL, DARS2 and PAICS revealed many potentially effective drugs and small molecule compounds. Finally, we successfully constructed a robust and stable nomogram by combining the expression of DARS2 and PAICS with other clinicopathological variables. Conclusion CENPL, DARS2 and PAICS expressions were negatively correlated with LUAD prognosis. The prognostic model including DARS2 and PAICS with other clinicopathological variables could effectively predict prognosis.