Chromatin Separation Regulators Predict the Prognosis and Immune Microenvironment Estimation in Lung Adenocarcinoma

Zhaoshui Li; Zaiqi Ma; Hong Xue; Ruxin Shen; Kun Qin; Yu Zhang; Xin Zheng; Guodong Zhang

doi:10.3389/fgene.2022.917150

Chromatin Separation Regulators Predict the Prognosis and Immune Microenvironment Estimation in Lung Adenocarcinoma

Front Genet. 2022 Jul 8:13:917150. doi: 10.3389/fgene.2022.917150. eCollection 2022.

Authors

Zhaoshui Li^{1

2}, Zaiqi Ma², Hong Xue³, Ruxin Shen¹, Kun Qin¹, Yu Zhang¹, Xin Zheng⁴, Guodong Zhang⁵

Affiliations

¹ Qingdao Medical College, Qingdao University, Qingdao, China.
² Cardiothoracic Surgery Department, Qingdao Hiser Hospital Affiliated to Qingdao University, Qingdao, China.
³ Heart Center Department, Qingdao Hiser Hospital Affiliated to Qingdao University, Qingdao, China.
⁴ Cancer Center Department, Qingdao Hiser Hospital Affiliated to Qingdao University, Qingdao, China.
⁵ Thoracic Surgery Department, Shandong Cancer Hospital Affiliated to Shandong First Medical University, Jinan, China.

Abstract

Background: Abnormal chromosome segregation is identified to be a common hallmark of cancer. However, the specific predictive value of it in lung adenocarcinoma (LUAD) is unclear. Method: The RNA sequencing and the clinical data of LUAD were acquired from The Cancer Genome Atlas (TACG) database, and the prognosis-related genes were identified. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were carried out for functional enrichment analysis of the prognosis genes. The independent prognosis signature was determined to construct the nomogram Cox model. Unsupervised clustering analysis was performed to identify the distinguishing clusters in LUAD-samples based on the expression of chromosome segregation regulators (CSRs). The differentially expressed genes (DEGs) and the enriched biological processes and pathways between different clusters were identified. The immune environment estimation, including immune cell infiltration, HLA family genes, immune checkpoint genes, and tumor immune dysfunction and exclusion (TIDE), was assessed between the clusters. The potential small-molecular chemotherapeutics for the individual treatments were predicted via the connectivity map (CMap) database. Results: A total of 2,416 genes were determined as the prognosis-related genes in LUAD. Chromosome segregation is found to be the main bioprocess enriched by the prognostic genes. A total of 48 CSRs were found to be differentially expressed in LUAD samples and were correlated with the poor outcome in LUAD. Nine CSRs were identified as the independent prognostic signatures to construct the nomogram Cox model. The LUAD-samples were divided into two distinct clusters according to the expression of the 48 CSRs. Cell cycle and chromosome segregation regulated genes were enriched in cluster 1, while metabolism regulated genes were enriched in cluster 2. Patients in cluster 2 had a higher score of immune, stroma, and HLA family components, while those in cluster 1 had higher scores of TIDES and immune checkpoint genes. According to the hub genes highly expressed in cluster 1, 74 small-molecular chemotherapeutics were predicted to be effective for the patients at high risk. Conclusion: Our results indicate that the CSRs were correlated with the poor prognosis and the possible immunotherapy resistance in LUAD.

Keywords: bioinformatics; chromosome segregation regulators; immune environment; lung adenocarcinoma; prognostic signature.