Research Paper Volume 15, Issue 6 pp 2293—2307

Construction and validation of a hypoxia-related risk signature identified EXO1 as a prognostic biomarker based on 12 genes in lung adenocarcinoma

Qirui Chen1, , Shuo Chen1, , Jing Wang1, , Yan Zhao1, , Xin Ye1, , Yili Fu1, , Yi Liu1, &, ,

  • 1 Department of Thoracic Surgery, Beijing Chaoyang Hospital, Beijing 100020, China

Received: December 3, 2022       Accepted: March 15, 2023       Published: March 25, 2023
How to Cite

Copyright: © 2023 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Background: Increasing evidence has demonstrated the clinical importance of hypoxia and its related factors in lung adenocarcinoma (LUAD).

Methods: RNA-seq datasets from The Cancer Genome Atlas (TCGA) were analyzed using the differentially expressed genes in hypoxia pathway by the Least Absolute Shrinkage and Selection Operator (LASSO) model. Applying gene ontology (GO) and gene set enrichment analysis (GSEA), a risk signature associated with the survival of LUAD patients was constructed between LUAD and normal tissue.

Results: In total, 166 hypoxia-related genes were identified. Based on the LASSO Cox regression, 12 genes were selected for the development of the risk signature. Then, we designed an OS-associated nomogram that included the risk score and clinical factors. The concordance index of the nomogram was 0.724. ROC curve showed better predictive ability using the nomogram (AUC = 0.811 for 5-year OS). Finally, the expressions of the 12 genes were validated in two external datasets and EXO1 was recognized as a potential biomarker in the progression of LUAD patients.

Conclusions: Overall, our data suggested that hypoxia is associated with the prognosis, and EXO1 acted as a promising biomarker in LUAD.


TCGA: The Cancer Genome Atlas; LUAD: lung adenocarcinoma; LASSO: Least Absolute Shrinkage and Selection Operator; GO: gene ontology; GSEA: gene set enrichment analysis; OS: overall survival; HRGs: hypoxia-related genes; MSigDB: Molecular Signatures Database; KEGG: Encyclopedia of Genes and Genomes; ROC: Receiver operating characteristic; AUC: area under the ROC curve; C-index: concordance index.