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BCL7A as a novel prognostic biomarker for glioma patients

Authors :
Junhui Liu
Lun Gao
Baowei Ji
Rongxin Geng
Jing Chen
Xiang Tao
Qiang Cai
Zhibiao Chen
Source :
Journal of Translational Medicine, Vol 19, Iss 1, Pp 1-16 (2021)
Publication Year :
2021
Publisher :
BMC, 2021.

Abstract

Abstract Background Glioma is the most common primary brain tumor and represents one of the most aggressive and lethal types of human cancer. BCL7 family has been found in several cancer types and could be involved in tumor progression. While the role of BCL7 family in human glioma has remained to be elucidated. Methods Paraffin-embedded tumor samples were obtained to detect BCL7 expression by performing in glioma. Data (including normalized gene expression and corresponding clinical data) were obtained from Gliovis, CGGA, GEO, cBioportal and Oncomine and were used to investigate BCL7 genes expression in glioma. Survival analyses were calculated by Kaplan–Meier methods and Cox regression analysis in TCGA and CGGA. Gene Set Enrichment Analyses (GSEA) and gene ontology (GO) analysis was employed to perform the biological processes enrichment. Results BCL7A expression in glioma tissues was lower compared to non-tumor brain tissues (NBT), and exhibited a negative correlation with glioma grades. Results from immunohistochemical (IHC) staining and public dataset validation demonstrated that BCL7B and BCL7C were highly expressed in glioma tissues compared to NBT. Cox regression analysis identified BCL7A as the only gene in the BCL7 family that was independently associated with the prognosis of lower-grade glioma (LGG) and glioblastoma (GBM). GO and GSEA analyses revealed the potential contribution of BCL7A in adaptive immune response and neutrophil activation in the tumor microenvironment. Moreover, we found that BCL7A had no prognostic effect on the overall survival of GBM patients who received IR only; however, patients who received chemotherapy (TMZ) combined with IR in the high BCL7A group survived longer than patients in the low BCL7A group (HR = 0.346, p

Details

Language :
English
ISSN :
14795876
Volume :
19
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Journal of Translational Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.41a84f7846b84e8bbcdadcca5c58e7b8
Document Type :
article
Full Text :
https://doi.org/10.1186/s12967-021-03003-0