Prognostic implications of autophagy-associated gene signatures in non-small cell lung cancer

Abstract

Autophagy, a highly conserved cellular proteolysis process, has been involved in non-small cell lung cancer (NSCLC). We tried to develop a prognostic prediction model for NSCLC patients based on the expression profiles of autophagy-associated genes. Univariate Cox regression analysis was used to determine autophagy-associated genes significantly correlated with overall survival (OS) of the TCGA lung cancer cohort. LASSO regression was performed to build multiple-gene prognostic signatures. We found that the 22-gene and 11-gene signatures could dichotomize patients with significantly different OS and independently predict the OS in TCGA lung adenocarcinoma (HR=2.801, 95% CI=2.252-3.486, P<0.001) and squamous cell carcinoma (HR=1.105, 95% CI=1.067-1.145, P<0.001), respectively. The prognostic performance of the 22-gene signature was validated in four GEO lung cancer cohorts. Moreover, GO, KEGG, and GSEA analyses unveiled several fundamental signaling pathways and cellular processes associated with the 22-gene signature in lung adenocarcinoma. We also constructed a clinical nomogram with a concordance index of 0.71 to predict the survival possibility of NSCLC patients by integrating clinical characteristics and the autophagy gene signature. The calibration curves substantiated fine concordance between nomogram prediction and actual observation. Overall, we constructed and verified a novel autophagy-associated gene signature that could improve the individualized outcome prediction in NSCLC.

Identification of an autophagy-related gene expression prognostic model in endometrial carcinoma patients

“…Based on TCGA nonsmall cell lung cancer (NSCLC) data, Liu et.al also develop a 22-gene prognostic prediction model for NSCLC patients based on the expression profiles of autophagy-associated genes. In addition, they also validated the evaluation efficacy of the model using GEO NSCLC dataset [22]. The above studied underlined the significance of ARGs in cancer progression and proved the effectiveness of combining certain ARGs to building a gene expression-based model to estimated patients' prognosis.…”

Identification of an autophagy-related gene expression prognostic model in endometrial carcinoma patients

“…Based on TCGA non-small cell lung cancer (NSCLC) data, Liu et.al also develop a 22-gene prognostic prediction model for NSCLC patients based on the expression pro les of autophagy-associated genes. In addition, they also validated the evaluation e cacy of the model using GEO NSCLC dataset [22]. The above studied underlined the signi cance of ARGs in cancer progression and proved the effectiveness of combining certain ARGs to building a gene expression-based model to estimated patients' prognosis.…”

Identification and Validation of an Individualized Autophagy-Clinical Prognostic Index in Gastric Cancer Patients

“…Gene signatures based on ATGs have been reported in a variety of cancers, such as serous ovarian cancer, breast cancer, colon cancer and glioma [24][25][26][27]. For example, Liu and colleagues recently reported a 14 autophagy related signature (NRG1, itga3, map1lc3a) based on relapse free survival in patients with non-small cell lung cancer [28].…”