Stemness Related Genes Revealed by Network Analysis Associated With Tumor Immune Microenvironment and the Clinical Outcome in Lung Adenocarcinoma

Hao Zeng; Jianrui Ji; Xindi Song; Yeqian Huang; Hui Li; Juan Huang; Xuelei Ma

doi:10.3389/fgene.2020.549213

Stemness Related Genes Revealed by Network Analysis Associated With Tumor Immune Microenvironment and the Clinical Outcome in Lung Adenocarcinoma

Front Genet. 2020 Sep 16:11:549213. doi: 10.3389/fgene.2020.549213. eCollection 2020.

Authors

Hao Zeng^{1

2}, Jianrui Ji^{1

2}, Xindi Song², Yeqian Huang², Hui Li², Juan Huang³, Xuelei Ma^{1

2}

Affiliations

¹ State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center for Biotherapy, Chengdu, China.
² West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China.
³ Department of Hematology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.

Abstract

Lung adenocarcinoma (LUAD) is one of the leading fatal malignancy with high morbidity and mortality worldwide. However, due to its complicated mechanism and lack of effective clinical therapeutics, early diagnosis and prognosis are still unsatisfactory. Most of the previous studies focused on cancer stem cells (CSCs), the relationship between cancer stemness (stem-like characteristics) and anti-tumor immunity has not been clearly revealed. Therefore, this study aimed to comprehensively analyze the role of cancer stemness and tumor microenvironment (TME) in LUAD using weighted gene co-expression network analysis (WGCNA). We constructed a gene co-expression network, identified key modules, and hub genes, and further explored the relationship between hub gene expression and cancer immunological characteristics through a variety of algorithms, including Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and Gene Set Enrichment Analysis (GSEA). The hub genes were renamed stemness related genes (SRGs), whose functions were examined at the transcription and protein levels through survival analysis with additional samples, Oncomine database, immunohistochemistry, single cell RNA sequencing (scRNA-seq) and single-sample Gene Set Enrichment Analysis (ssGSEA). Subsequently, Tumor Immune Dysfunction and Exclusion (TIDE) and Connectivity Map (CMap) were implemented for treatment and prognosis analyses. As a result, 15 co-expressed SRGs (CCNA2, CCNB1, CDC20, CDCA5, CDCA8, FEN1, KIF2C, KPNA2, MCM6, NUSAP1, RACGAP1, RRM2, SPAG5, TOP2A, and TPX2) were identified. The overexpression of which was discovered to be associated with reduced immune infiltration in LUAD. It was discovered that there was a general negative correlation between cancer stemness and immunity. The expression of SRGs could probably affect our tumor occurrence, progression, the efficacy of chemotherapy and immunotherapy, and clinical outcomes. In conclusion, the 15 SRGs reported in our study may be used as potential candidate biomarkers for prognostic indicators and therapeutic targets after further validation.

Keywords: cancer stemness cells (CSCs); clinical outcome; single cell RNA sequencing (scRNA-seq); tumor microenvironment (TME); weighted gene co-expression network analysis (WGCNA).