Research Paper Advance Articles

Prognostic value of immune-related genes in the tumor microenvironment of lung adenocarcinoma and lung squamous cell carcinoma

Yan Qu 1, *, , Bo Cheng 2, *, , Na Shao 3, , Yibin Jia 1, , Qingxu Song 1, , Bingxu Tan 1, , Jianbo Wang 1, ,

  • 1 Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan 250012, Shandong, China
  • 2 Department of Radiation Oncology, Shandong Provincial Cancer Hospital, Jinan 250117, Shandong, China
  • 3 Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan 250021, Shandong, China
* Equal contribution

received: December 16, 2019 ; accepted: February 20, 2020 ; published: March 25, 2020 ;

https://doi.org/10.18632/aging.102871
How to Cite

Copyright © 2020 Qu 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

Non-small cell lung cancer (NSCLC), which consists mainly of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), are the leading cause of cancer deaths worldwide. In this study, we performed a comprehensive analysis of the tumor microenvironmental and genetic factors to identify prognostic biomarkers for NSCLC. We evaluated the immune and stromal scores of patients with LUAD and LUSC using data from The Cancer Genome Atlas database with the ESTIMATE algorithm. Based on these scores, the differentially expressed genes were obtained and immune-related prognostic genes were identified. Functional analysis and protein-protein interaction network further revealed the immune-related biological processes in which these genes participated. Additionally, 22 subsets of tumor-infiltrating immune cells (TIICs) in the tumor microenvironment were analyzed with the CIBERSORT algorithm. Finally, we validated these valuable genes using an independent cohort from the Gene Expression Omnibus database. The associations of the immune and stromal scores with patients’ clinical characteristics and prognosis were positive in LUAD but negative in LUSC and the correlations of TIICs with clinical characteristics were clarified. Several differentially expressed genes were identified to be potential immune-related prognostic genes. This study comprehensively analyzed the tumor microenvironment and presented immune-related prognostic biomarkers for NSCLC.

Abbreviations

LUAD: lung adenocarcinoma; LUSC: lung squamous cell carcinoma; NSCLC: non-small cell lung cancer; LCLC: large cell lung cancer; TCGA: the cancer genome atlas; TIICs: tumor-infiltrating immune cells; DEGs: differentially expressed genes; TME: tumor microenvironment; ECM: extracellular matrix; TILs: tumor-infiltrating lymphocytes; OS: overall survival; ESTIMATE: Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data; PPI: protein-protein interaction; GO analysis: Gene ontology analysis; BP: biological processes; MF: molecular functions; CC: cellular components; KEGG: Kyoto Encyclopedia of Genes and Genomes; Tfh: T follicular helper cells; Tgd cells: gamma delta T cells; Tregs cells: regulatory T cells; NK cells: natural killer cells; CAMs: cell adhesion molecules.