Research Paper Volume 13, Issue 23 pp 25550—25563

A novel immune-related long non-coding RNAs risk model for prognosis assessment of lung adenocarcinoma

Songmei Lu1, , Nan Shan2, , Xingyue Chen1, , Fangliang Peng2, , Yiming Wang1, , Hao Long3, ,

  • 1 Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing, China
  • 2 Department of Gynaecology and Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
  • 3 Department of Biological Immunotherapy, Chongqing University Cancer Hospital, Chongqing, China

Received: August 6, 2021       Accepted: November 23, 2021       Published: December 14, 2021      

https://doi.org/10.18632/aging.203772
How to Cite

Copyright: © 2021 Lu 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.

Abstract

Background: The abundant immune-related long non-coding RNA (IRLNRs) in immune cells and immune microenvironment have the potential to forecast prognosis and evaluate the effect of immunotherapy. IRLNRs analysis will provide a new perspective for LUAC research.

Methods: We calculated the immune score of each sample according to the expression levels of immune-related genes (IRGs) and screened the survival-related IRLNRs (sIRLNRs) by Cox regression analysis. The expression levels of AC068338.3 and AL691432.2 in tissues and cell lines were confirmed by RT-qPCR.

Results: 36 IRLNRs were selected by Pearson correlation analysis. Ten sIRLNRs were significantly correlated with the clinical outcomes of LUAC patients. Five sIRLNRs were identified by multivariate COX regression analysis to establish the immune-related risk score model (IRRS). The overall survival (OS) in the high-risk group was shorter than that in the low-risk group. IRRS could be an independent prognostic factor with significant survival correlation The distributions of immune gene concentrations were different between high-risk group and low-risk group. Furthermore, we further verified that the expression levels of AC068338.3 and AL691432.2 in different LUAC cell lines and tumor tissues were lower than that in Human bronchial epithelial cell (HBE) and adjacent tissues respectively. The lower expression levels of AC068338.3 and AL691432.2 were detected with the more advance T-stages.

Conclusions: Our results highlighted some sIRLNRs with significant clinical correlations and demonstrated their monitored and prognostic values for LUAC patients. The results of this study may provide a new perspective for immunological research and immunotherapy strategies.

Abbreviations

LCa: lung cancer; LUAC: lung adenocarcinoma; TCGA: The Cancer Genome Atlas; GSEA: gene set enrichment analysis; PCA: principal component analysis; TME: tumor microenvironment; IME: immune microenvironment; IRGs: immune-related genes; IRLNRs: immune related long non-coding RNAs; IRRS: immune-related risk score model; LncRNAs: long non-coding RNAs; sIRLNRs: survival-related IRLNRs; OS: overall survival.