Abstract
Lung adenocarcinoma (LUAD) is the most common malignancy, leading to more than 1 million related deaths each year. Due to low long-term survival rates, the exploration of molecular mechanisms underlying LUAD progression and novel prognostic predictors is urgently needed to improve LUAD treatment. In our study, cancer-specific differentially expressed genes (DEGs) were identified using the robust rank aggregation (RRA) method between tumor and normal tissues from six Gene Expression Omnibus databases (GSE43458, GSE62949, GSE68465, GSE115002, GSE116959, and GSE118370), followed by a selection of prognostic modules using weighted gene co-expression network analysis. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were applied to identify nine hub genes (CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6) that constructed a prognostic risk model. The RNA expressions of nine hub genes were validated in tumor and normal tissues by RNA-sequencing and single-cell RNA-sequencing, while immunohistochemistry staining from the Human Protein Atlas database showed consistent results in the protein levels. The risk model revealed that high-risk patients were associated with poor prognoses, including advanced stages and low survival rates. Furthermore, a multivariate Cox regression analysis suggested that the prognostic risk model could be an independent prognostic factor for LUAD patients. A nomogram that incorporated the signature and clinical features was additionally built for prognostic prediction. Moreover, the levels of hub genes were related to immune cell infiltration in LUAD microenvironments. A CMap analysis identified 13 small molecule drugs as potential agents based on the risk model for LUAD treatment. Thus, we identified a prognostic risk model including CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6 as novel biomarkers and validated their prognostic and predicted values for LUAD.
Highlights
Lung cancer—with 1,800,000 new lung cancer cases worldwide each year—is the most malignant cancer in males and females (Torre et al, 2015; Sung et al, 2021)
Our findings suggested a prognostic risk model including CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6 serves as a novel biomarker and uncovered their prognostic and predictive values to provide molecular evidence of new potential clinical strategies for Lung adenocarcinoma (LUAD)
There were 665 LUAD and 141 normal tissues analyzed in our work to explore the differentially expressed genes (DEGs)
Summary
Lung cancer—with 1,800,000 new lung cancer cases worldwide each year—is the most malignant cancer in males and females (Torre et al, 2015; Sung et al, 2021). Acetyl-CoA acetyltransferase inhibits the proliferation and migration of clear cell renal cell carcinoma cells in vitro and has been validated as a prognostic and progression biomarker via significant correlation with overall survival (OS) and disease-free survival rates (Chen et al, 2019). It was uncovered a nine-gene signature comprising MET, KLK10, COL17A1, CEP55, ANKRD22, ITGB6, ARNTL2, MCOLN3, and SLC25A45 has been identified as predicting the survival of pancreatic cancer (Wu M. et al, 2019), providing possible therapies. It is urgent to discover molecular markers highly associated with survival to contribute to improving the effect of targeted therapeutic approaches
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