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The CXCL Family Contributes to Immunosuppressive Microenvironment in Gliomas and Assists in Gliomas Chemotherapy

Overview
Journal Front Immunol
Date 2021 Oct 4
PMID 34603309
Citations 15
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Abstract

Gliomas are a type of malignant central nervous system tumor with poor prognosis. Molecular biomarkers of gliomas can predict glioma patient's clinical outcome, but their limitations are also emerging. C-X-C motif chemokine ligand family plays a critical role in shaping tumor immune landscape and modulating tumor progression, but its role in gliomas is elusive. In this work, samples of TCGA were treated as the training cohort, and as for validation cohort, two CGGA datasets, four datasets from GEO database, and our own clinical samples were enrolled. Consensus clustering analysis was first introduced to classify samples based on CXCL expression profile, and the support vector machine was applied to construct the cluster model in validation cohort based on training cohort. Next, the elastic net analysis was applied to calculate the risk score of each sample based on CXCL expression. High-risk samples associated with more malignant clinical features, worse survival outcome, and more complicated immune landscape than low-risk samples. Besides, higher immune checkpoint gene expression was also noticed in high-risk samples, suggesting CXCL may participate in tumor evasion from immune surveillance. Notably, high-risk samples also manifested higher chemotherapy resistance than low-risk samples. Therefore, we predicted potential compounds that target high-risk samples. Two novel drugs, LCL-161 and ADZ5582, were firstly identified as gliomas' potential compounds, and five compounds from PubChem database were filtered out. Taken together, we constructed a prognostic model based on CXCL expression, and predicted that CXCL may affect tumor progression by modulating tumor immune landscape and tumor immune escape. Novel potential compounds were also proposed, which may improve malignant glioma prognosis.

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References
1.
Woroniecka K, Chongsathidkiet P, Rhodin K, Kemeny H, Dechant C, Farber S . T-Cell Exhaustion Signatures Vary with Tumor Type and Are Severe in Glioblastoma. Clin Cancer Res. 2018; 24(17):4175-4186. PMC: 6081269. DOI: 10.1158/1078-0432.CCR-17-1846. View

2.
Nick T, Hardin J . Regression modeling strategies: an illustrative case study from medical rehabilitation outcomes research. Am J Occup Ther. 1999; 53(5):459-70. DOI: 10.5014/ajot.53.5.459. View

3.
Weller M, Wick W, Aldape K, Brada M, Berger M, Pfister S . Glioma. Nat Rev Dis Primers. 2016; 1:15017. DOI: 10.1038/nrdp.2015.17. View

4.
Liu F, Huang J, Liu X, Cheng Q, Luo C, Liu Z . CTLA-4 correlates with immune and clinical characteristics of glioma. Cancer Cell Int. 2020; 20:7. PMC: 6945521. DOI: 10.1186/s12935-019-1085-6. View

5.
Farsaci B, Donahue R, Coplin M, Grenga I, Lepone L, Molinolo A . Immune consequences of decreasing tumor vasculature with antiangiogenic tyrosine kinase inhibitors in combination with therapeutic vaccines. Cancer Immunol Res. 2014; 2(11):1090-102. PMC: 4221465. DOI: 10.1158/2326-6066.CIR-14-0076. View