Research Paper Volume 13, Issue 23 pp 25453—25465
A risk model based on autophagy-related lncRNAs for predicting prognosis and efficacy of immunotherapy and chemotherapy in gastric cancer patients
- 1 Department of Gastroenterology, The First Affiliated Hospital, And College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
- 2 Department of Clinical Laboratory, The First Affiliated Hospital, And College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
- 3 Department of Gastrointestinal Surgery, The First Affiliated Hospital, And College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
Received: May 10, 2021 Accepted: September 29, 2021 Published: December 12, 2021https://doi.org/10.18632/aging.203765
How to Cite
Copyright: © 2021 Gao 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.
Long non-coding RNAs (lncRNAs) are a class of non-protein-coding RNAs essential to the occurrence and development of gastric cancer (GC). We aimed to identify critical lncRNA pairs to construct a prognostic model and assess its performances in prognosis and efficacy prediction in GC patients receiving immunotherapy and chemotherapy. We searched transcriptome and clinical data of GC patients from The Cancer Genome Atlas (TCGA) database. Autophagy-related lncRNAs were identified using co-expression network analysis, and lncRNA pairs with prognostic value were selected using pairwise transcriptome analysis. The gene pairs were subjected to LASSO algorithm for identification of optimal gene pairs for risk model construction. Patients were classified into the low-risk and high-risk groups with the RiskScore as a cutoff. Finally, 9 optimal gene pairs were identified in the LASSO algorithm model for construction of a lncRNA prognostic risk model. For predictive performances, it successfully predicted a shorter survival of high-risk patients than that obtained in low-risk individuals (P < 0.001). It showed moderate AUC (area under the curve) values for 1-, 2-, and 3-year overall survival prediction of 0.713 and could serve as an independent predictor for GC prognosis. Compared to the low-risk group, high-risk patients had higher expressions of marker genes for immune checkpoint inhibitors (ICIs) and showed higher sensitivity to the chemotherapy agents, rapamycin, bexarotene, and bicalutamide. Our findings demonstrate a robust prognostic model based on nine autophagy-related lncRNA pairs for GC. It acts as an independent predictor for survival and efficacy prediction of immunotherapy and chemotherapy in GC patients.
lncRNAs: long non-coding RNAs; GC: gastric cancer; TCGA: The Cancer Genome Atlas; AUC: area under the curve; TIME: tumor immune microenvironment; IC50: 50% inhibitory concentration; ICIs: immune checkpoint inhibitors; FDR: false discovery rate; FC: fold change; CAFs: cancer-associated fibroblasts.