Literature DB >> 32829091

Analyses of multi-omics differences between patients with high and low PD1/PDL1 expression in lung squamous cell carcinoma.

Zhengyang Hu1, Guoshu Bi1, Qihai Sui1, Yunyi Bian1, Yajing Du2, Jiaqi Liang1, Ming Li1, Cheng Zhan3, Zongwu Lin4, Qun Wang1.   

Abstract

BACKGROUND: Immunotherapy has achieved excellent results in patients with lung squamous cell carcinoma. However, in which population it can exert the greatest effect is still unknown. Some studies have suggested that its effect is related to the expression level of PD1. Analyzing the relationship between PD1 expression level and genetic differences in lung squamous cell carcinoma patients will be helpful in understanding the underlying causes of this immunotherapy effect and provide a reference for clinical practice.
METHODS: In this study, we used RNA-seq, miRNA-seq, methylation array, mutation profiles, and copy number variation data from the TCGA database and RNA-seq data from the GEO database to analyze the distinctive genomic patterns associated with PD1 and PDL1 expression. RNA-seq data from 44 LUSC patients who underwent surgery at Zhongshan Hospital were also included in the study.
RESULTS: After grouping LUSC patients according to the expression levels of PD1 and PDL1, we found no significant difference in survival between the two groups. However, 178 genes, including IL-21, KLRC3, and KLRC4, were significantly upregulated in both the TCGA and GEO databases in the high expression group, and there was a precise correlation between gene expression and epigenetic changes in the two groups. At the same time, the overall level of somatic mutations was not significantly different between the two groups. It is worth noting that the gene enrichment results showed that the differential pathways were mainly enriched in immune regulation, especially T cell-related immune activities.
CONCLUSION: We found that the differences in gene expression between the two groups were related to immunity, which may affect the effectiveness of immunotherapy. We hope our results can provide a reference for further research and help in finding other targets to improve the efficacy of immunotherapy.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bioinformatics; Lung squamous cell carcinoma; Multiomics; Programmed death 1; Programmed death-ligand 1

Mesh:

Substances:

Year:  2020        PMID: 32829091     DOI: 10.1016/j.intimp.2020.106910

Source DB:  PubMed          Journal:  Int Immunopharmacol        ISSN: 1567-5769            Impact factor:   4.932


  4 in total

1.  Mutations in the TTN Gene are a Prognostic Factor for Patients with Lung Squamous Cell Carcinomas.

Authors:  Sheng Zou; Jiayue Ye; Sheng Hu; Yiping Wei; Jianjun Xu
Journal:  Int J Gen Med       Date:  2022-01-04

2.  Differences in genetics and microenvironment of lung adenocarcinoma patients with or without TP53 mutation.

Authors:  Dejun Zeng; Zhengyang Hu; Yanjun Yi; Besskaya Valeria; Guangyao Shan; Zhencong Chen; Cheng Zhan; Miao Lin; Zongwu Lin; Qun Wang
Journal:  BMC Pulm Med       Date:  2021-10-11       Impact factor: 3.317

3.  Integrative Analysis of Multi-Omics Data-Identified Key Genes With KLRC3 as the Core in a Gene Regulatory Network Related to Immune Phenotypes in Lung Adenocarcinoma.

Authors:  Kai Mao; Yunxi Zhao; Bo Ding; Peng Feng; Zhenqing Li; You Lang Zhou; Qun Xue
Journal:  Front Genet       Date:  2022-03-31       Impact factor: 4.599

4.  Multiomics Differences in Lung Squamous Cell Carcinoma Patients with High Radiosensitivity Index Compared with Those with Low Radiosensitivity Index.

Authors:  Yajing Du; Sujuan Yuan; Xibing Zhuang; Qi Zhang; Tiankui Qiao
Journal:  Dis Markers       Date:  2021-08-30       Impact factor: 3.434

  4 in total

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