Predictive Panel for Immunotherapy in Lower-Grade Glioma.

Lower-grade gliomas biomarkers immune checkpoint blockade neoantigens

Journal

World neurosurgery
ISSN: 1878-8769
Titre abrégé: World Neurosurg
Pays: United States
ID NLM: 101528275

Informations de publication

Date de publication:
10 Jan 2024
Historique:
received: 25 10 2023
revised: 04 01 2024
accepted: 05 01 2024
medline: 13 1 2024
pubmed: 13 1 2024
entrez: 12 1 2024
Statut: aheadofprint

Résumé

The main treatment of lower-grade glioma (LGG) is still surgical resection followed by radiotherapy and/or chemotherapy, which has certain limitations, including side effects and drug resistance. Immunotherapy is a promising treatment for LGG, but it is generally hindered by the tumor microenvironment with the limited expression of tumor antigens. We integrated RNA sequencing data sets and clinical information and conducted consistent cluster analysis to explore the most suitable patients for immune checkpoint therapy. Gene set enrichment analysis, UMAP analysis, mutation correlation analysis, TIMER analysis and TIDE analysis were used to identify the immune characteristics of three immune subtypes and the feasibility of five antigens as immune checkpoint markers. We analyzed the isolation and mutation of homologous recombination repair genes（HRR） of the three immune subtypes, and the HRR genes of the three subtypes were obviously segregated. Among them, IS2 subtype has a large number of HRR gene mutations, which increases the immunogenicity of tumors, which is consistent with the results of tumor mutation load analysis of three immune subtypes. Then we evaluated the immune cell infiltration of immune subtypes and found that IS2 and IS3 subtypes were rich in immune cells. It is worth noting that there are many Treg cells and NK cells in IS1 subtype. In addition, when analyzing the immune checkpoint gene expression of the three subtypes, we found that they were up-regulated most in IS2 subtypes compared with other subtypes. Then when we further confirmed the role of immune-related genes in LGG, through TIDE analysis and TISIDB analysis, we obtained five markers that can predict the efficacy of ICB in patients with LGG. In addition, we confirmed that they were associated with poor prognosis through survival analysis. We obtained three reliable immune subtypes, and patients with the IS2 subtype are suitable for immunotherapy, in which NAMPT, SLC11A1, TNC, VIM, and SPP1 are predictive panel markers for ICB in the LGG group. Our findings provide a rationale for immunotherapy selection and prediction of patient prognosis in LGG patients.

Sections du résumé

BACKGROUND BACKGROUND
The main treatment of lower-grade glioma (LGG) is still surgical resection followed by radiotherapy and/or chemotherapy, which has certain limitations, including side effects and drug resistance. Immunotherapy is a promising treatment for LGG, but it is generally hindered by the tumor microenvironment with the limited expression of tumor antigens.
METHODS METHODS
We integrated RNA sequencing data sets and clinical information and conducted consistent cluster analysis to explore the most suitable patients for immune checkpoint therapy. Gene set enrichment analysis, UMAP analysis, mutation correlation analysis, TIMER analysis and TIDE analysis were used to identify the immune characteristics of three immune subtypes and the feasibility of five antigens as immune checkpoint markers.
RESULTS RESULTS
We analyzed the isolation and mutation of homologous recombination repair genes（HRR） of the three immune subtypes, and the HRR genes of the three subtypes were obviously segregated. Among them, IS2 subtype has a large number of HRR gene mutations, which increases the immunogenicity of tumors, which is consistent with the results of tumor mutation load analysis of three immune subtypes. Then we evaluated the immune cell infiltration of immune subtypes and found that IS2 and IS3 subtypes were rich in immune cells. It is worth noting that there are many Treg cells and NK cells in IS1 subtype. In addition, when analyzing the immune checkpoint gene expression of the three subtypes, we found that they were up-regulated most in IS2 subtypes compared with other subtypes. Then when we further confirmed the role of immune-related genes in LGG, through TIDE analysis and TISIDB analysis, we obtained five markers that can predict the efficacy of ICB in patients with LGG. In addition, we confirmed that they were associated with poor prognosis through survival analysis.
CONCLUSIONS CONCLUSIONS
We obtained three reliable immune subtypes, and patients with the IS2 subtype are suitable for immunotherapy, in which NAMPT, SLC11A1, TNC, VIM, and SPP1 are predictive panel markers for ICB in the LGG group. Our findings provide a rationale for immunotherapy selection and prediction of patient prognosis in LGG patients.

Identifiants

DOI: 10.1016/j.wneu.2024.01.039 PMID: 38216032
pubmed: 38216032
pii: S1878-8750(24)00049-4
doi: 10.1016/j.wneu.2024.01.039
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Auteurs

Qingqing Lv (Q)

Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China, 410013; The Key Laboratory of Carcinogenesis of the Chinese Ministry of Health; The Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education; Cancer Research Institute, Central South University, Changsha, 410008, Hunan, China.

Zhaoyu Zhang (Z)

Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China, 410013; The Key Laboratory of Carcinogenesis of the Chinese Ministry of Health; The Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education; Cancer Research Institute, Central South University, Changsha, 410008, Hunan, China.

Haijuan Fu (H)

Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China, 410013; The Key Laboratory of Carcinogenesis of the Chinese Ministry of Health; The Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education; Cancer Research Institute, Central South University, Changsha, 410008, Hunan, China.

Danyang Li (D)

Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China, 410013; The Key Laboratory of Carcinogenesis of the Chinese Ministry of Health; The Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education; Cancer Research Institute, Central South University, Changsha, 410008, Hunan, China.

Yihao Liu (Y)

Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China, 410013; The Key Laboratory of Carcinogenesis of the Chinese Ministry of Health; The Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education; Cancer Research Institute, Central South University, Changsha, 410008, Hunan, China.

Yingnan Sun (Y)

Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China, 410013.

Minghua Wu (M)

Hunan Cancer Hospital/the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China, 410013; The Key Laboratory of Carcinogenesis of the Chinese Ministry of Health; The Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education; Cancer Research Institute, Central South University, Changsha, 410008, Hunan, China. Electronic address: wuminghua554@aliyun.com.

Classifications MeSH