A four-gene signature-derived risk score for glioblastoma: prospects for prognostic and response predictive analyses

<b>Objective</b> Glioblastoma (GBM) is the most common primary malignant brain tumor regulated by numerous genes, with poor survival outcomes and unsatisfactory response to therapy. Therefore, a robust, multi-gene signature-derived model is required to predict the prognosis and treatment...

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Main Authors: Mianfu Cao, Juan Cai, Ye Yuan, Yu Shi, Hong Wu, Qing Liu, Yueliang Yao, Lu Chen, Weiqi Dang, Xiang Zhang, Jingfang Xiao, Kaidi Yang, Zhicheng He, Xiaohong Yao, Yonghong Cui, Xia Zhang, Xiuwu Bian
Format: Article
Language:English
Published: China Anti-Cancer Association 2019-09-01
Series:Cancer Biology & Medicine
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Online Access:http://www.cancerbiomed.org/index.php/cocr/article/view/1457
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language English
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author Mianfu Cao
Juan Cai
Ye Yuan
Yu Shi
Hong Wu
Qing Liu
Yueliang Yao
Lu Chen
Weiqi Dang
Xiang Zhang
Jingfang Xiao
Kaidi Yang
Zhicheng He
Xiaohong Yao
Yonghong Cui
Xia Zhang
Xiuwu Bian
spellingShingle Mianfu Cao
Juan Cai
Ye Yuan
Yu Shi
Hong Wu
Qing Liu
Yueliang Yao
Lu Chen
Weiqi Dang
Xiang Zhang
Jingfang Xiao
Kaidi Yang
Zhicheng He
Xiaohong Yao
Yonghong Cui
Xia Zhang
Xiuwu Bian
A four-gene signature-derived risk score for glioblastoma: prospects for prognostic and response predictive analyses
Cancer Biology & Medicine
Differentially expressed genes
gene set enrichment analysis
glioblastoma prognosis
radiotherapy
temozolomide chemotherapy
author_facet Mianfu Cao
Juan Cai
Ye Yuan
Yu Shi
Hong Wu
Qing Liu
Yueliang Yao
Lu Chen
Weiqi Dang
Xiang Zhang
Jingfang Xiao
Kaidi Yang
Zhicheng He
Xiaohong Yao
Yonghong Cui
Xia Zhang
Xiuwu Bian
author_sort Mianfu Cao
title A four-gene signature-derived risk score for glioblastoma: prospects for prognostic and response predictive analyses
title_short A four-gene signature-derived risk score for glioblastoma: prospects for prognostic and response predictive analyses
title_full A four-gene signature-derived risk score for glioblastoma: prospects for prognostic and response predictive analyses
title_fullStr A four-gene signature-derived risk score for glioblastoma: prospects for prognostic and response predictive analyses
title_full_unstemmed A four-gene signature-derived risk score for glioblastoma: prospects for prognostic and response predictive analyses
title_sort four-gene signature-derived risk score for glioblastoma: prospects for prognostic and response predictive analyses
publisher China Anti-Cancer Association
series Cancer Biology & Medicine
issn 2095-3941
2095-3941
publishDate 2019-09-01
description <b>Objective</b> Glioblastoma (GBM) is the most common primary malignant brain tumor regulated by numerous genes, with poor survival outcomes and unsatisfactory response to therapy. Therefore, a robust, multi-gene signature-derived model is required to predict the prognosis and treatment response in GBM.<b>Methods</b> Gene expression data of GBM from TCGA and GEO datasets were used to identify differentially expressed genes (DEGs) through DESeq2 or LIMMA methods. The DEGs were then overlapped and used for survival analysis by univariate and multivariate COX regression. Based on the gene signature of multiple survival-associated DEGs, a risk score model was established, and its prognostic and predictive role was estimated through Kaplan–Meier analysis and log-rank test. Gene set enrichment analysis (GSEA) was conducted to explore high-risk score-associated pathways. Western blot was used for protein detection.<b>Results</b> Four survival-associated DEGs of GBM were identified: OSMR, HOXC10, SCARA3, and SLC39A10. The four-gene signature-derived risk score was higher in GBM than in normal brain tissues. GBM patients with a high-risk score had poor survival outcomes. The high-risk group treated with temozolomide chemotherapy or radiotherapy survived for a shorter duration than the low-risk group. GSEA showed that the high-risk score was enriched with pathways such as vasculature development and cell adhesion. Western blot confirmed that the proteins of these four genes were differentially expressed in GBM cells.<b>Conclusions</b> The four-gene signature-derived risk score functions well in predicting the prognosis and treatment response in GBM and will be useful for guiding therapeutic strategies for GBM patients.
topic Differentially expressed genes
gene set enrichment analysis
glioblastoma prognosis
radiotherapy
temozolomide chemotherapy
url http://www.cancerbiomed.org/index.php/cocr/article/view/1457
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spelling doaj-882fd41e94bf40198ab694ff3d1896a22020-11-25T02:11:17ZengChina Anti-Cancer AssociationCancer Biology & Medicine2095-39412095-39412019-09-0116359560510.20892/j.issn.2095-3941.2018.02772018000277A four-gene signature-derived risk score for glioblastoma: prospects for prognostic and response predictive analysesMianfu Cao0Juan Cai1Ye Yuan2Yu Shi3Hong Wu4Qing Liu5Yueliang Yao6Lu Chen7Weiqi Dang8Xiang Zhang9Jingfang Xiao10Kaidi Yang11Zhicheng He12Xiaohong Yao13Yonghong Cui14Xia Zhang15Xiuwu Bian16Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaDepartment of Kidney, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, ChinaInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Key Laboratory of Tumor Immunopathology, Ministry of Education of China, Chongqing 400038, China<b>Objective</b> Glioblastoma (GBM) is the most common primary malignant brain tumor regulated by numerous genes, with poor survival outcomes and unsatisfactory response to therapy. Therefore, a robust, multi-gene signature-derived model is required to predict the prognosis and treatment response in GBM.<b>Methods</b> Gene expression data of GBM from TCGA and GEO datasets were used to identify differentially expressed genes (DEGs) through DESeq2 or LIMMA methods. The DEGs were then overlapped and used for survival analysis by univariate and multivariate COX regression. Based on the gene signature of multiple survival-associated DEGs, a risk score model was established, and its prognostic and predictive role was estimated through Kaplan–Meier analysis and log-rank test. Gene set enrichment analysis (GSEA) was conducted to explore high-risk score-associated pathways. Western blot was used for protein detection.<b>Results</b> Four survival-associated DEGs of GBM were identified: OSMR, HOXC10, SCARA3, and SLC39A10. The four-gene signature-derived risk score was higher in GBM than in normal brain tissues. GBM patients with a high-risk score had poor survival outcomes. The high-risk group treated with temozolomide chemotherapy or radiotherapy survived for a shorter duration than the low-risk group. GSEA showed that the high-risk score was enriched with pathways such as vasculature development and cell adhesion. Western blot confirmed that the proteins of these four genes were differentially expressed in GBM cells.<b>Conclusions</b> The four-gene signature-derived risk score functions well in predicting the prognosis and treatment response in GBM and will be useful for guiding therapeutic strategies for GBM patients.http://www.cancerbiomed.org/index.php/cocr/article/view/1457Differentially expressed genesgene set enrichment analysisglioblastoma prognosisradiotherapytemozolomide chemotherapy