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Ser MH, Webb M, Thomsen A, Sener U. Isocitrate Dehydrogenase Inhibitors in Glioma: From Bench to Bedside. Pharmaceuticals (Basel) 2024; 17:682. [PMID: 38931350 PMCID: PMC11207016 DOI: 10.3390/ph17060682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 05/16/2024] [Accepted: 05/20/2024] [Indexed: 06/28/2024] Open
Abstract
Isocitrate dehydrogenase (IDH) mutant gliomas are a primary malignancy of the central nervous system (CNS) malignancies, most commonly affecting adults under the age of 55. Standard of care therapy for IDH-mutant gliomas involves maximal safe resection, radiotherapy, and chemotherapy. However, despite good initial responses to multimodality treatment, recurrence is virtually universal. IDH-mutant gliomas represent a life-limiting prognosis. For this reason, there is a great need for novel treatments that can prolong survival. Uniquely for IDH-mutant gliomas, the IDH mutation is the direct driver of oncogenesis through its oncometabolite 2-hydroxygluterate. Inhibition of this mutated IDH with a corresponding reduction in 2-hydroxygluterate offers an attractive treatment target. Researchers have tested several IDH inhibitors in glioma through preclinical and early clinical trials. A phase III clinical trial of an IDH1 and IDH2 inhibitor vorasidenib yielded promising results among patients with low-grade IDH-mutant gliomas who had undergone initial surgery and no radiation or chemotherapy. However, many questions remain regarding optimal use of IDH inhibitors in clinical practice. In this review, we discuss the importance of IDH mutations in oncogenesis of adult-type diffuse gliomas and current evidence supporting the use of IDH inhibitors as therapeutic agents for glioma treatment. We also examine unresolved questions and propose potential directions for future research.
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Affiliation(s)
- Merve Hazal Ser
- Department of Neurology, SBU Istanbul Research and Training Hospital, Istanbul 34098, Turkey
| | - Mason Webb
- Department of Medical Oncology, Mayo Clinic, Rochester, MN 55905, USA; (M.W.); (U.S.)
| | - Anna Thomsen
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ugur Sener
- Department of Medical Oncology, Mayo Clinic, Rochester, MN 55905, USA; (M.W.); (U.S.)
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
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2
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Gao J, Zhao Z, Zhang H, Huang S, Xu M, Pan H. Transcriptomic characterization and construction of M2 macrophage-related prognostic and immunotherapeutic signature in ovarian metastasis of gastric cancer. Cancer Immunol Immunother 2022; 72:1121-1138. [PMID: 36336725 DOI: 10.1007/s00262-022-03316-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 10/25/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Ovarian metastasis (OM) poses a major threat to the outcome of gastric cancer (GC) patients. Recently, immunotherapy emerged as a novel promising therapeutic strategy to treat late-stage GC, whereas its efficacy is influenced by tumor immune microenvironment (TIME). M2 macrophage, a key subset within TIME, plays dual immunosuppressive and pro-tumorigenic roles in cancer progression and is recognized as a potential therapeutic target. However, molecular mechanisms underlying OM remain elusive and the TIME-related prognostic and immunotherapeutic index for these patients is yet to establish. METHODS Differential expressed genes (DEGs) between paired normal mucosa, primary GC and OM of patients from Fudan University Shanghai Cancer Center (FUSCC) cohort (n = 6) were identified by transcriptome sequencing, followed by the functional annotation of enriched hallmark pathways of DEGs between them. CIBERSORT was used to profile the relative expression level of 22 immune cell subsets in normal tissues, primary and metastatic tumors, followed by weighted gene coexpression network analysis (WGCNA) uncovering immune cell-correlated gene sets. The intersected genes between DEGs and M2 macrophage-related genes were processed by least absolute shrinkage and selection operator (LASSO) regression analysis to construct a predictive signature, M2GO, which was further validated by training set and test set of The Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD), GSE62254 and GSE84437 cohorts. GC patients were divided into M2GO-high and -low subgroup according to the optimal cutoff value of the M2GO score. Furthermore, the clinical, molecular and immune features between M2GO-high and -low subgroups were analyzed. Clinical cohorts of immunotherapy were used to validate the predictive value of M2GO in regard to immunotherapy effectiveness. RESULTS Transcriptomic sequencing and follow-up analyses of triple-matched normal tissues, primary and ovarian metastatic tumors identified distinctive sets of DEGs and enriched immune-, cancer- and metastasis-related pathways between them. Of note, M2 macrophage, a major immunosuppressive and pro-tumorigenic component within TIME, was significantly up-regulated in OMs. WGCNA and LASSO regression were applied to establish a novel OM- and M2 macrophage-related predictive signature, M2GO, based on M2 macrophage-related prognostic genes including GJA1, MAGED1 and SERPINE1. M2GO served as an independent prognostic factor of GC patients. Comprehensive molecular and immune characterization of M2GO-based subgroups uncovered their distinctive features in terms of enriched functional pathways, tumor mutation burden, key immune checkpoints, major regulators of natural immune cGAS-STING pathway, infiltrated subsets of immune cells and tumor immune exclusion/dysfunction (TIDE) score. Notably, the M2GO score was significantly lower in responsive group than non-responsive group (P < 0.05) in clinical cohort of metastatic GC patients undergoing immunotherapy. CONCLUSION Transcriptomic characterization of paired normal mucosae, primary and ovarian metastatic tumors revealed their unique molecular and immune features. Follow-up analyses established a novel OM- and M2 macrophage-related signature, M2GO, which served as a promising prognostic and immunotherapeutic biomarker to distinguish the clinical outcome, molecular and immune features of GC patients and predict their differential responses to immunotherapy.
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Affiliation(s)
- Jianpeng Gao
- Department of Gastric Surgery, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
| | - Zhenxiong Zhao
- Department of Gastric Surgery, Fudan University Shanghai Cancer Center, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Hena Zhang
- Department of Integrative Oncology, Fudan University Shanghai Cancer Center, and the Shanghai Key Laboratory of Medical Epigenetics, The International Co-Laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Shenglin Huang
- Department of Integrative Oncology, Fudan University Shanghai Cancer Center, and the Shanghai Key Laboratory of Medical Epigenetics, The International Co-Laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Midie Xu
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
- Institute of Pathology, Fudan University, Shanghai, 200032, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
| | - Hongda Pan
- Department of Gastric Surgery, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
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3
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Li G, Li L, Li Y, Qian Z, Wu F, He Y, Jiang H, Li R, Wang D, Zhai Y, Wang Z, Jiang T, Zhang J, Zhang W. An MRI radiomics approach to predict survival and tumour-infiltrating macrophages in gliomas. Brain 2022; 145:1151-1161. [PMID: 35136934 PMCID: PMC9050568 DOI: 10.1093/brain/awab340] [Citation(s) in RCA: 79] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 04/15/2021] [Accepted: 08/18/2021] [Indexed: 01/08/2023] Open
Abstract
Preoperative MRI is one of the most important clinical results for the diagnosis and treatment of glioma patients. The objective of this study was to construct a stable and validatable preoperative T2-weighted MRI-based radiomics model for predicting the survival of gliomas. A total of 652 glioma patients across three independent cohorts were covered in this study including their preoperative T2-weighted MRI images, RNA-seq and clinical data. Radiomic features (1731) were extracted from preoperative T2-weighted MRI images of 167 gliomas (discovery cohort) collected from Beijing Tiantan Hospital and then used to develop a radiomics prediction model through a machine learning-based method. The performance of the radiomics prediction model was validated in two independent cohorts including 261 gliomas from the The Cancer Genomae Atlas database (external validation cohort) and 224 gliomas collected in the prospective study from Beijing Tiantan Hospital (prospective validation cohort). RNA-seq data of gliomas from discovery and external validation cohorts were applied to establish the relationship between biological function and the key radiomics features, which were further validated by single-cell sequencing and immunohistochemical staining. The 14 radiomic features-based prediction model was constructed from preoperative T2-weighted MRI images in the discovery cohort, and showed highly robust predictive power for overall survival of gliomas in external and prospective validation cohorts. The radiomic features in the prediction model were associated with immune response, especially tumour macrophage infiltration. The preoperative T2-weighted MRI radiomics prediction model can stably predict the survival of glioma patients and assist in preoperatively assessing the extent of macrophage infiltration in glioma tumours.
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Affiliation(s)
- Guanzhang Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Lin Li
- Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Engineering Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083, China
| | - Yiming Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Zenghui Qian
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Fan Wu
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Yufei He
- Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Engineering Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083, China
| | - Haoyu Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Renpeng Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Di Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - You Zhai
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Zhiliang Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Tao Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.,Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing 100070, China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, China.,Chinese Glioma Genome Atlas Network and Asian Glioma Genome Atlas Network, Beijing, China
| | - Jing Zhang
- Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Engineering Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083, China
| | - Wei Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.,Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, China.,Chinese Glioma Genome Atlas Network and Asian Glioma Genome Atlas Network, Beijing, China
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Liu J, Gao L, Zhu X, Geng R, Tao X, Xu H, Chen Z. Gasdermin D Is a Novel Prognostic Biomarker and Relates to TMZ Response in Glioblastoma. Cancers (Basel) 2021; 13:cancers13225620. [PMID: 34830775 PMCID: PMC8616249 DOI: 10.3390/cancers13225620] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 11/01/2021] [Accepted: 11/04/2021] [Indexed: 01/25/2023] Open
Abstract
The gasdermin (GSDM) family act as executioners during pyroptosis. However, its expression and biological role in glioma remain to be determined. This study carried out gene expression from six public datasets. Westerns blots and immunohistochemistry (IHC) staining were employed to examine GSDM expression in glioma in an in-house cohort. Kaplan-Meier and Cox regression analyses were performed to evaluate the prognostic role of GSDMs in glioma. Association between gene expression and immune infiltration was assessed by IHC and immunofluorescence (IF) staining of tissue sections. TMZ-induced pyroptosis was assessed by observation of morphological changes, WB and ELISA detection. Only GSDMD expression was upregulated in glioma compared with nontumor brain tissues both in the public datasets and in-house cohort. High GSDMD expression was significantly associated with WHO grade IV, IDH 1/2 wild-type and mesenchymal subtypes. Besides, high GSDMD expression was associated with shorter overall survival and could be used as an independent risk factor for poor outcomes in LGG and GBM. GO enrichment analysis and IHC validation revealed that GSDMD expression might participate in regulating macrophage infiltration and polarization. TMZ treatment induced the pyroptosis in GBM cells and GSDMD expression increased with after treating with TMZ in a time-dependent manner. Moreover, knocking down GSDMD obviously decreased IL-1β expression and reduced TMZ-induced pyroptosis in in vitro. GSDMD was a novel prognostic biomarker, as well as TMZ-treatment response marker in glioma.
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Affiliation(s)
- Junhui Liu
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan 430060, China; (J.L.); (L.G.); (X.Z.); (R.G.); (X.T.); (H.X.)
- Central Laboratory, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Lun Gao
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan 430060, China; (J.L.); (L.G.); (X.Z.); (R.G.); (X.T.); (H.X.)
| | - Xiaonan Zhu
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan 430060, China; (J.L.); (L.G.); (X.Z.); (R.G.); (X.T.); (H.X.)
| | - Rongxin Geng
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan 430060, China; (J.L.); (L.G.); (X.Z.); (R.G.); (X.T.); (H.X.)
| | - Xiang Tao
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan 430060, China; (J.L.); (L.G.); (X.Z.); (R.G.); (X.T.); (H.X.)
| | - Haitao Xu
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan 430060, China; (J.L.); (L.G.); (X.Z.); (R.G.); (X.T.); (H.X.)
| | - Zhibiao Chen
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan 430060, China; (J.L.); (L.G.); (X.Z.); (R.G.); (X.T.); (H.X.)
- Correspondence:
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5
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Lv L, Zhang Y, Zhao Y, Wei Q, Zhao Y, Yi Q. Effects of 1p/19q Codeletion on Immune Phenotype in Low Grade Glioma. Front Cell Neurosci 2021; 15:704344. [PMID: 34335194 PMCID: PMC8322528 DOI: 10.3389/fncel.2021.704344] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 06/23/2021] [Indexed: 01/05/2023] Open
Abstract
Background: Chromosome 1p/19q codeletion is one of the most important genetic alterations for low grade gliomas (LGGs), and patients with 1p/19q codeletion have significantly prolonged survival compared to those without the codeletion. And the tumor immune microenvironment also plays a vital role in the tumor progression and prognosis. However, the effect of 1p/19q codeletion on the tumor immune microenvironment in LGGs is unclear. Methods: Immune cell infiltration of 281 LGGs from The Cancer Genome Atlas (TCGA) and 543 LGGs from the Chinese Glioma Genome Atlas (CGGA) were analyzed for immune cell infiltration through three bioinformatics tools: ESTIMATE algorithm, TIMER, and xCell. The infiltrating level of immune cells and expression of immune checkpoint genes were compared between different groups classified by 1p/19q codeletion and IDH (isocitrate dehydrogenase) mutation status. The differential biological processes and signaling pathways were evaluated through Gene Set Enrichment Analysis (GSEA). Correlations were analyzed using Spearman correlation. Results: 1p/19q codeletion was associated with immune-related biological processes in LGGs. The infiltrating level of multiple kinds of immune cells and expression of immune checkpoint genes were significantly lower in 1p/19q codeletion LGGs compared to 1p/19q non-codeletion cohorts. There are 127 immune-related genes on chromosome 1p or 19q, such as TGFB1, JAK1, and CSF1. The mRNA expression of these genes was positively correlated with their DNA copy number. These genes are distributed in multiple immune categories, such as chemokines/cytokines, TGF-β family members, and TNF family members, regulating immune cell infiltration and expression of the immune checkpoint genes in tumors. Conclusion: Our results indicated that 1p/19q codeletion status is closely associated with the immunosuppressive microenvironment in LGGs. LGGs with 1p/19q codeletion display less immune cell infiltration and lower expression of immune checkpoint genes than 1p/19q non-codeletion cases. Mechanistically, this may be, at least in part, due to the deletion of copy number of immune-related genes in LGGs with 1p/19q codeletion. Our findings may be relevant to investigate immune evasion in LGGs and contribute to the design of immunotherapeutic strategies for patients with LGGs.
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Affiliation(s)
- Lei Lv
- Anhui Cancer Hospital, West Branch of the First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yuliu Zhang
- Department of Thoracic Surgery, Dingyuan County General Hospital of Chuzhou City in Anhui, Anhui, China
| | - Yujia Zhao
- School of Basic Medical Sciences, Anhui Medical University, Hefei, China
| | - Qinqin Wei
- School of Basic Medical Sciences, Anhui Medical University, Hefei, China
| | - Ye Zhao
- School of Basic Medical Sciences, Anhui Medical University, Hefei, China
| | - Qiyi Yi
- School of Basic Medical Sciences, Anhui Medical University, Hefei, China
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Ma W, Zhang K, Bao Z, Jiang T, Zhang Y. SAMD9 Is Relating With M2 Macrophage and Remarkable Malignancy Characters in Low-Grade Glioma. Front Immunol 2021; 12:659659. [PMID: 33936093 PMCID: PMC8085496 DOI: 10.3389/fimmu.2021.659659] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 03/19/2021] [Indexed: 12/14/2022] Open
Abstract
Immunoreactions regulated by TAMs (Tumor-associated macrophages) play a pivotal role in tumorigenesis and metastasis. In recent decades, treatments based on immune regulation have achieved revolutionary breakthroughs in cancer targeted therapies. The phenotypes of TAMs in gliomas are more heterogeneous and inherently complex than can be simply defined by classification into the M1 and M2 polarized states. The detailed mechanisms surrounding infiltrating macrophage phenotype and glioma characteristics remain undefined. SAMD9 (Sterile Alpha Motif Domain-Containing Protein 9) was found to be highly expressed in glioma and closely related to histological and genetic features in CGGA and TCGA databases. Simultaneously, we present evidence to show that there was a positive association between SAMD9 and malignancy characters in LGG. Univariable and Multivariate proportional hazard Cox analysis showed that SAMD9 was an independent prognostic factor for LGG. Surprisingly, Gene Ontology (GO) analysis showed SAMD9 expression level was remarkably well correlated with immunological responses and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis supported the connection with immune responses and tumorigenesis. Immune infiltration analysis demonstrated that high SAMD9 expression resulted in an accumulation of macrophages by CIBERSORT and TIMER databases, especially positively related to macrophage total marker gene AIF1 and Macrophage M2 marker gene CD163. IHC staining further indicated a high correlation of SAMD9 with those specific macrophage markers in the immune response. Human THP-1 cells were induced into M2 macrophages, which were then co-cultured with LN229 cells. Silencing of SAMD9 by shRNA in LN229 cells attenuated the infiltration abilities of M2 macrophage. SAMD9 explored immune response via relating of M2 macrophage in vitro. Our results revealed SAMD9 acted as the malignancy characters in LGG, enrichment with M2 macrophage.
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Affiliation(s)
- Wenping Ma
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Glioma Genome Atlas Network (CGGA) and Asian Glioma Genome Atlas Network (AGGA), Beijing, China
| | - Kenan Zhang
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Zhaoshi Bao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Chinese Glioma Genome Atlas Network (CGGA) and Asian Glioma Genome Atlas Network (AGGA), Beijing, China
| | - Tao Jiang
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Chinese Glioma Genome Atlas Network (CGGA) and Asian Glioma Genome Atlas Network (AGGA), Beijing, China
| | - Ying Zhang
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Chinese Glioma Genome Atlas Network (CGGA) and Asian Glioma Genome Atlas Network (AGGA), Beijing, China
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Yuan HY, Lv YJ, Chen Y, Li D, Li X, Qu J, Yan H. TEAD4 is a novel independent predictor of prognosis in LGG patients with IDH mutation. Open Life Sci 2021; 16:323-335. [PMID: 33889755 PMCID: PMC8042920 DOI: 10.1515/biol-2021-0039] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 12/21/2020] [Accepted: 01/20/2021] [Indexed: 12/27/2022] Open
Abstract
TEA domain family members (TEADs) play important roles in tumor progression. Till now, the genomic status of TEADs in patients with glioma has not been well investigated. To confirm whether the genomic status of TEADs could affect the prognosis of patients with glioma, the copy number variation (CNV), mutation and expression data of glioma cohorts in The Cancer Genome Atlas, Gene Expression Omnibus and Chinese Glioma Genome Atlas were comprehensively analyzed. Results showed that TEAD CNV frequency in lower grade gliomas (LGGs) was higher than in glioblastoma multiforme (GBM). Multivariate cox regression analysis showed that TEAD4 CNV increase was significantly associated with overall survival (OS) and disease-free survival (DFS) in LGGs (OS p = 0.022, HR = 1.444, 95% CI: 1.054–1.978; DFS p = 0.005, HR = 1.485, 95% CI: 1.124–1.962), while not in GBM. Patients with TEAD4 CNV increase showed higher expression level of TEAD4 gene. In LGG patients with IDH mutation, those with higher TEAD4 expression levels had shorter OS and DFS. Integrating TEAD4 CNV increase, IDH mutations, TP53 mutation, ATRX mutation and 1p19q co-deletion would separate patients with LGG into four groups with significant differences in prognosis. These study results suggested that TEAD4 variations were independent predictive biomarkers for the prognosis in patients with LGG with IDH mutation.
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Affiliation(s)
- Hai-Yan Yuan
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha 410011, People's Republic of China
| | - Ya-Juan Lv
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, People's Republic of China.,Institute of Clinical Pharmacology, Central South University, Changsha 410078, People's Republic of China
| | - Yi Chen
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, People's Republic of China.,Institute of Clinical Pharmacology, Central South University, Changsha 410078, People's Republic of China
| | - Dan Li
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, People's Republic of China.,Institute of Clinical Pharmacology, Central South University, Changsha 410078, People's Republic of China
| | - Xi Li
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, People's Republic of China.,Institute of Clinical Pharmacology, Central South University, Changsha 410078, People's Republic of China
| | - Jian Qu
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha 410011, People's Republic of China
| | - Han Yan
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha 410011, People's Republic of China
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8
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Zhao L, Zhang J, Xuan S, Liu Z, Wang Y, Zhao P. Molecular and Clinicopathological Characterization of a Prognostic Immune Gene Signature Associated With MGMT Methylation in Glioblastoma. Front Cell Dev Biol 2021; 9:600506. [PMID: 33614641 PMCID: PMC7892978 DOI: 10.3389/fcell.2021.600506] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 01/08/2021] [Indexed: 02/06/2023] Open
Abstract
Background: O6-methylguanine-DNA methyltransferase (MGMT) methylation status affects tumor chemo-resistance and the prognosis of glioblastoma (GBM) patients. We aimed to investigate the role of MGMT methylation in the regulation of GBM immunophenotype and discover an effective biomarker to improve prognosis prediction of GBM patients. Methods: A total of 769 GBM patients with clinical information from five independent cohorts were enrolled in the present study. Samples from the Cancer Genome Atlas (TCGA) dataset were used as the training set, whereas transcriptome data from the Chinese Glioma Genome Atlas (CGGA) RNA-seq, CGGA microarray, GSE16011, and the Repository for Molecular Brain Neoplasia (REMBRANDT) cohort were used for validation. A series of bioinformatics approaches were carried out to construct a prognostic signature based on immune-related genes, which were tightly related to the MGMT methylation status. In silico analyses were performed to investigate the influence of the signature on immunosuppression and remodeling of the tumor microenvironment. Then, the utility of this immune gene signature was analyzed by the development and evaluation of a nomogram. In vitro experiments were further used to verify the immunologic function of the genes in the signature. Results: We found that MGMT unmethylation was closely associated with immune-related biological processes in GBM. Sixty-five immune genes were more highly expressed in the MGMT unmethylated than the MGMT-methylated group. An immune gene-based risk model was further established to divide patients into high and low-risk groups, and the prognostic value of this signature was validated in several GBM cohorts. Functional analyses manifested a universal up-regulation of immune-related pathways in the high-risk group. Furthermore, the risk score was highly correlated to the immune cell infiltration, immunosuppression, inflammatory activities, as well as the expression levels of immune checkpoints. A nomogram was developed for clinical application. Knockdown of the five genes in the signature remodeled the immunosuppressive microenvironment by restraining M2 macrophage polarization and suppressing immunosuppressive cytokines production. Conclusions: MGMT methylation is strongly related to the immune responses in GBM. The immune gene-based signature we identified may have potential implications in predicting the prognosis of GBM patients and mechanisms underlying the role of MGMT methylation.
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Affiliation(s)
- Liang Zhao
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jiayue Zhang
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shurui Xuan
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zhiyuan Liu
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yu Wang
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Peng Zhao
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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9
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Zhang X, Liu S, Zhao X, Shi X, Li J, Guo J, Niedermann G, Luo R, Zhang X. Magnetic resonance imaging-based radiomic features for extrapolating infiltration levels of immune cells in lower-grade gliomas. Strahlenther Onkol 2020; 196:913-921. [PMID: 32025804 DOI: 10.1007/s00066-020-01584-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 01/16/2020] [Indexed: 02/05/2023]
Abstract
PURPOSE To extrapolate the infiltration levels of immune cells in patients with lower-grade gliomas (LGGs) using magnetic resonance imaging (MRI)-based radiomic features. METHODS A retrospective dataset of 516 patients with LGGs from The Cancer Genome Atlas (TCGA) database was analysed for the infiltration levels of six types of immune cells using Tumor IMmune Estimation Resource (TIMER) based on RNA sequencing data. Radiomic features were extracted from 107 patients whose pre-operative MRI data are available in The Cancer Imaging Archive; 85 and 22 of these patients were assigned to the training and testing cohort, respectively. The least absolute shrinkage and selection operator (LASSO) was applied to select optimal radiomic features to build the radiomic signatures for extrapolating the infiltration levels of immune cells in the training cohort. The developed radiomic signatures were examined in the testing cohort using Pearson's correlation. RESULTS The infiltration levels of B cells, CD4+ T cells, CD8+ T cells, macrophages, neutrophils and dendritic cells negatively correlated with overall survival in the 516 patient cohort when using univariate Cox's regression. Age, Karnofsky Performance Scale, WHO grade, isocitrate dehydrogenase mutant status and the infiltration of neutrophils correlated with survival using multivariate Cox's regression analysis. The infiltration levels of the 6 cell types could be estimated by radiomic features in the training cohort, and their corresponding radiomic signatures were built. The infiltration levels of B cells, CD8+ T cells, neutrophils and macrophages estimated by radiomics correlated with those estimated by TIMER in the testing cohort. Combining clinical/genomic features with the radiomic signatures only slightly improved the prediction of immune cell infiltrations. CONCLUSION We developed MRI-based radiomic models for extrapolating the infiltration levels of immune cells in LGGs. Our results may have implications for treatment planning.
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Affiliation(s)
- Xuanwei Zhang
- Department of Radiation Oncology, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaan Xi, China
- Department of Thoracic Oncology, West China Hospital, Chengdu, China
| | - Shuo Liu
- Neurology Department, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Xu Zhao
- Department of Radiation Oncology, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaan Xi, China
| | - Xiaobo Shi
- Department of Radiation Oncology, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaan Xi, China
| | - Jing Li
- Department of Radiation Oncology, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaan Xi, China
| | - Jia Guo
- Department of Radiation Oncology, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaan Xi, China
| | - Gabriele Niedermann
- Department of Radiation Oncology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ren Luo
- Department of Radiation Oncology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
- Faculty of Biology, University of Freiburg, Freiburg, Germany.
| | - Xiaozhi Zhang
- Department of Radiation Oncology, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaan Xi, China.
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10
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Lin X, Wang Z, Yang G, Wen G, Zhang H. YTHDF2 correlates with tumor immune infiltrates in lower-grade glioma. Aging (Albany NY) 2020; 12:18476-18500. [PMID: 32986017 PMCID: PMC7585119 DOI: 10.18632/aging.103812] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 07/20/2020] [Indexed: 01/24/2023]
Abstract
Immunotherapy is an effective treatment for many cancer types. However, YTHDF2 effects on the prognosis of different tumors and correlation with tumor immune infiltration are unclear. Here, we analyzed The Cancer Genome Atlas and Gene Expression Omnibus data obtained through various web-based platforms. The analyses showed that YTHDF2 expression and associated prognoses may depend on cancer type. High YTHDF2 expression was associated with poor overall survival in lower-grade glioma (LGG). In addition, YTHDF2 expression positively correlated with expression of several immune cell markers, including PD-1, TIM-3, and CTLA-4, as well as tumor-associated macrophage gene markers, and isocitrate dehydrogenase 1 in LGG. These findings suggest that YTHDF2 is a potential prognostic biomarker that correlates with LGG tumor-infiltrating immune cells.
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Affiliation(s)
- Xiangan Lin
- Department of Cancer Chemotherapy, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University, Guangzhou 510000, China
| | - Zhichao Wang
- Department of Cancer Chemotherapy, Zengcheng District People’s Hospital of Guangzhou, Guangzhou 511300, China
| | - Guangda Yang
- Department of Cancer Chemotherapy, Zengcheng District People’s Hospital of Guangzhou, Guangzhou 511300, China
| | - Guohua Wen
- Department of Cancer Chemotherapy, Zengcheng District People’s Hospital of Guangzhou, Guangzhou 511300, China
| | - Hailiang Zhang
- Department of Cancer Chemotherapy, Zengcheng District People’s Hospital of Guangzhou, Guangzhou 511300, China
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11
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A novel signature based on microvascular invasion predicts the recurrence of HCC. J Transl Med 2020; 18:272. [PMID: 32631357 PMCID: PMC7336478 DOI: 10.1186/s12967-020-02432-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 06/20/2020] [Indexed: 12/31/2022] Open
Abstract
Background and objectives In hepatocellular carcinoma (HCC) patients, microvascular invasion (MVI) is associated with worse outcomes regardless of treatment. No single reliable preoperative factor exists to predict MVI. The aim of the work described here was to develop a new MVI− based mRNA biomarker to differentiate between high and low risk patients. Methods Using The Cancer Genome Atlas (TCGA) database, we collected data from 315 HCC patients, including mRNA expression and complete clinical data. We generated a seven-mRNA signature to predict patient outcomes. The mRNA signature was validated using the GSE36376 cohort. Finally, we tested the formula in our own 53 HCC patients using qPCR for the seven mRNAs and analyzing the computed tomography (CT) features. Results This seven‐mRNA signature significantly correlated with length of recurrence-free survival (RFS) and overall survival (OS) for both the training and validation groups. RFS and OS were briefer in high risk versus low risk patients. A Kaplan–Meier analysis also indicated that survival time was significantly shortened in the high risk group versus the low risk group. Time-dependent receiver operating characteristic analysis demonstrated good predictive performance for the seven-mRNA signature. The mRNA signature also acts as an independent factor according to a Multivariate analysis. Our results are consistent with the seven-mRNA formula risk score. Conclusion Our research showed a novel seven-mRNA biomarker based on MVI predicting RFS and OS in HCC patients. This mRNA signature can stratify patients into subgroups based on their risk of recurrence to help guide individualized treatment and precision management in HCC.
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12
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Zhao B, Wang Y, Wang Y, Chen W, Liu PH, Kong Z, Dai C, Wang Y, Ma W. Systematic identification, development, and validation of prognostic biomarkers involving the tumor-immune microenvironment for glioblastoma. J Cell Physiol 2020; 236:507-522. [PMID: 32572951 DOI: 10.1002/jcp.29878] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 05/17/2020] [Accepted: 05/31/2020] [Indexed: 01/31/2023]
Abstract
Gliomas are infiltrative neoplasms with a highly invasive nature. Due to its distinct genomic, genetic and epigenetic features, the immune prognostic signature (IPS) and immune microenvironment of glioblastoma (GBM) merit further research. We aimed to explore prognosis-related immune genes and develop an IPS model for predicting prognosis in GBM. RNA-sequencing data, as well as clinical information, from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) public cohorts were analyzed. To develop the IPS, least absolute shrinkage and selection operator (LASSO) Cox analysis was performed for immune-related genes that were differentially expressed between GBM and normal tissues. Then, interaction effects of the IPS on the immune microenvironment were systematically analyzed; the precise prognostic model was developed based on the IPS and clinical data and was then further validated. A total of 21 immune prognostic genes were identified based on GBM microenvironment status. An 8-gene IPS was established, and the GBM patients were effectively stratified into low- and high-risk groups in the TCGA cohort as a training set. Univariate and multivariate Cox analyses revealed that IPS was an independent prognostic factor, and the prognostic performance of individual IPS genes was systematically illustrated. In addition, a comprehensive and novel nomogram model was initially established to estimate overall survival in TCGA-GBM patients, and high-risk patients had higher levels of dendritic cell and neutrophil infiltration. Furthermore, the nomogram model was developed and validated in the CGGA validation set. The low-risk IPS was linked to a stronger response to anti-PD-L1 immunotherapy and clinical advantages in the IMvigor210 cohort. This novel IPS with promising biomarkers classifies GBM patients into subgroups with distinct clinical outcomes and immunophenotypes. Our findings and this resource may help to characterize the immune microenvironment, inform cancer immunotherapy and facilitate the development of precision immuno-oncology.
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Affiliation(s)
- Binghao Zhao
- Departments of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Yuekun Wang
- Departments of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Yaning Wang
- Departments of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Wenlin Chen
- Departments of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Peng Hao Liu
- Departments of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Ziren Kong
- Departments of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Congxin Dai
- Departments of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Yu Wang
- Departments of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Wenbin Ma
- Departments of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
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13
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Marinari E, Allard M, Gustave R, Widmer V, Philippin G, Merkler D, Tsantoulis P, Dutoit V, Dietrich PY. Inflammation and lymphocyte infiltration are associated with shorter survival in patients with high-grade glioma. Oncoimmunology 2020; 9:1779990. [PMID: 32923142 PMCID: PMC7458651 DOI: 10.1080/2162402x.2020.1779990] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 06/03/2020] [Indexed: 12/15/2022] Open
Abstract
Glioma represents a serious health burden in terms of morbidity and mortality. The prognostic significance of the lymphoid and myeloid infiltrates in glioma is not clearly determined. Moreover, the characterization of different leukocyte subsets in the tumor microenvironment relies mainly on immunohistochemistry observations, and data about their association with prognosis are contradictory. Here, we performed acomprehensive study of both the tumor-infiltrating and circulating immune compartments of patients with high-grade glioma. Nineteen tumor biopsies and 30 PBMC samples were analyzed by RNA sequencing. Validation was performed on The Cancer Genome Atlas (TCGA) RNA sequencing data from glioma and on additional 39 tumor biopsies analyzed by flow cytometry. We identified prognostic tumor and peripheral immune signatures, which associate increased inflammation, immune infiltration and activation with shorter overall survival in high-grade glioma patients. Importantly, we confirmed our observations by flow cytometry analysis and validated the tumor-signature using the TCGA dataset. In addition, both tumor genotype and grade associated with the degree of glioma immune infiltration. Unlike in the majority of cancers, lymphocyte infiltration at the tumor site is anegative prognostic factor in glioma, suggesting the ambivalent pro-tumorigenic role of immune responses in glioma.
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Affiliation(s)
- Eliana Marinari
- Laboratory of Tumor Immunology, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Center for Translational Research in Onco-Hematology, Division of Oncology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Mathilde Allard
- Laboratory of Tumor Immunology, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Center for Translational Research in Onco-Hematology, Division of Oncology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Robin Gustave
- Laboratory of Tumor Immunology, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Center for Translational Research in Onco-Hematology, Division of Oncology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Valérie Widmer
- Laboratory of Tumor Immunology, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Center for Translational Research in Onco-Hematology, Division of Oncology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Géraldine Philippin
- Laboratory of Tumor Immunology, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Center for Translational Research in Onco-Hematology, Division of Oncology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Doron Merkler
- Department of Pathology and Immunology, Division of Clinical Pathology, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Petros Tsantoulis
- Center for Translational Research in Onco-Hematology, Division of Oncology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
- Oncology Service, Geneva University Hospitals, Geneva, Switzerland
| | - Valérie Dutoit
- Laboratory of Tumor Immunology, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Center for Translational Research in Onco-Hematology, Division of Oncology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Pierre-Yves Dietrich
- Center for Translational Research in Onco-Hematology, Division of Oncology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
- Oncology Service, Geneva University Hospitals, Geneva, Switzerland
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14
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Zhang M, Wang X, Chen X, Zhang Q, Hong J. Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Lower-Grade Glioma. Front Genet 2020; 11:363. [PMID: 32351547 PMCID: PMC7174786 DOI: 10.3389/fgene.2020.00363] [Citation(s) in RCA: 107] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2019] [Accepted: 03/25/2020] [Indexed: 01/08/2023] Open
Abstract
Objective Despite several clinicopathological factors being integrated as prognostic biomarkers, the individual variants and risk stratification have not been fully elucidated in lower grade glioma (LGG). With the prevalence of gene expression profiling in LGG, and based on the critical role of the immune microenvironment, the aim of our study was to develop an immune-related signature for risk stratification and prognosis prediction in LGG. Methods RNA-sequencing data from The Cancer Genome Atlas (TCGA), Genome Tissue Expression (GTEx), and Chinese Glioma Genome Atlas (CGGA) were used. Immune-related genes were obtained from the Immunology Database and Analysis Portal (ImmPort). Univariate, multivariate cox regression, and Lasso regression were employed to identify differentially expressed immune-related genes (DEGs) and establish the signature. A nomogram was constructed, and its performance was evaluated by Harrell’s concordance index (C-index), receiver operating characteristic (ROC), and calibration curves. Relationships between the risk score and tumor-infiltrating immune cell abundances were evaluated using CIBERSORTx and TIMER. Results Noted, 277 immune-related DEGs were identified. Consecutively, 6 immune genes (CANX, HSPA1B, KLRC2, PSMC6, RFXAP, and TAP1) were identified as risk signature and Kaplan–Meier curve, ROC curve, and risk plot verified its performance in TCGA and CGGA datasets. Univariate and multivariate Cox regression indicated that the risk group was an independent predictor in primary LGG. The prognostic signature showed fair accuracy for 3- and 5-year overall survival in both internal (TCGA) and external (CGGA) validation cohorts. However, predictive performance was poor in the recurrent LGG cohort. The CIBERSORTx algorithm revealed that naïve CD4+ T cells were significant higher in low-risk group. Conversely, the infiltration levels of M1-type macrophages, M2-type macrophages, and CD8+T cells were significant higher in high-risk group in both TCGA and CGGA cohorts. Conclusion The present study constructed a robust six immune-related gene signature and established a prognostic nomogram effective in risk stratification and prediction of overall survival in primary LGG.
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Affiliation(s)
- Mingwei Zhang
- Department of Radiation Oncology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.,Institute of Immunotherapy, Fujian Medical University, Fuzhou, China.,Key Laboratory of Radiation Biology (Fujian Medical University), Fujian Province University, Fuzhou, China.,Fujian Key Laboratory of Individualized Active Immunotherapy, Fuzhou, China.,Fujian Medical University Union Hospital, Fuzhou, China
| | - Xuezhen Wang
- Department of Radiation Oncology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Xiaoping Chen
- Department of Statistics, College of Mathematics and Informatics & FJKLMAA, Fujian Normal University, Fuzhou, China
| | - Qiuyu Zhang
- Institute of Immunotherapy, Fujian Medical University, Fuzhou, China
| | - Jinsheng Hong
- Department of Radiation Oncology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.,Key Laboratory of Radiation Biology (Fujian Medical University), Fujian Province University, Fuzhou, China.,Fujian Key Laboratory of Individualized Active Immunotherapy, Fuzhou, China
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15
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Song LR, Weng JC, Li CB, Huo XL, Li H, Hao SY, Wu Z, Wang L, Li D, Zhang JT. Prognostic and predictive value of an immune infiltration signature in diffuse lower-grade gliomas. JCI Insight 2020; 5:133811. [PMID: 32229719 DOI: 10.1172/jci.insight.133811] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Accepted: 03/25/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUNDLower-grade gliomas (LGGs) vary widely in terms of the patient's overall survival (OS). There is no current, valid method that could exactly predict the survival. The effects of intratumoral immune infiltration on clinical outcome have been widely reported. Thus, we aim to develop an immune infiltration signature to predict the survival of LGG patients.METHODSWe analyzed 1216 LGGs from 5 public data sets, including 2 RNA sequencing data sets and 3 microarray data sets. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to select an immune infiltration signature and build a risk score. The performance of the risk score was assessed in the training set (329 patients), internal validation set (140 patients), and 4 external validation sets (405, 118, 88, and 136 patients).RESULTSAn immune infiltration signature consisting of 20 immune metagenes was used to generate a risk score. The performance of the risk score was thoroughly verified in the training and validation sets. Additionally, we found that the risk score was positively correlated with the expression levels of TGF-β and PD-L1, which were important targets of combination immunotherapy. Furthermore, a nomogram incorporating the risk score, patient's age, and tumor grade was developed to predict the OS, and it performed well in all the training and validation sets (C-index: 0.873, 0.881, 0.781, 0.765, 0.721, and 0.753).CONCLUSIONThe risk score based on the immune infiltration signature has reliable prognostic and predictive value for patients with LGGs and is a potential biomarker for the cotargeting immunotherapy.FUNDINGThis work was supported by The National Natural Science Foundation of China (grant nos. 81472370 and 81672506), the Natural Science Foundation of Beijing (grant no. J180005), the National High Technology Research and Development Program of China (863 Program, grant no. 2014AA020610), and the National Basic Research Program of China (973 Program, grant no. 2014CB542006).
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Affiliation(s)
- Lai-Rong Song
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Jian-Cong Weng
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Cheng-Bei Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xu-Lei Huo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Huan Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Shu-Yu Hao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China
| | - Zhen Wu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Liang Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Da Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Jun-Ting Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Brain Tumor, Beijing, China
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Liu YQ, Wu F, Li JJ, Li YF, Liu X, Wang Z, Chai RC. Gene Expression Profiling Stratifies IDH-Wildtype Glioblastoma With Distinct Prognoses. Front Oncol 2019; 9:1433. [PMID: 31921684 PMCID: PMC6929203 DOI: 10.3389/fonc.2019.01433] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Accepted: 12/02/2019] [Indexed: 12/31/2022] Open
Abstract
Objectives: In the present study, we aimed to determine the candidate genes that may function as biomarkers to further distinguish patients with isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM), which are heterogeneous with respect to clinical outcomes. Materials and Methods: We selected 41 candidate genes associated with overall survival (OS) using univariate Cox regression from IDH-wildtype GBM patients based on RNA sequencing (RNAseq) expression data from the Chinese Glioma Genome Atlas (CGGA, n = 105) and The Cancer Genome Atlas (TCGA, n = 139) cohorts. Next, a seven-gene-based risk signature was formulated according to Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm in the CGGA RNAseq database as a training set, while another 525 IDH-wildtype GBM patient TCGA datasets, consisting of RNA sequencing and microarray data, were used for validation. Patient survival in the low- and high-risk groups was calculated using Kaplan-Meier survival curve analysis and the log-rank test. Uni-and multivariate Cox regression analysis was used to assess the prognosis value. Gene oncology (GO) and gene set enrichment analysis (GSEA) were performed for the functional analysis of the seven-gene-based risk signature. Results: We developed a seven-gene-based signature, which allocated each patient to a risk group (low or high). Patients in the high-risk group had dramatically shorter overall survival than their low-risk counterparts in three independent cohorts. Univariate and multivariate analysis showed that the seven-gene signature remained an independent prognostic factor. Moreover, the seven-gene risk signature exhibited a striking prognostic validity, with AUC of 78.4 and 73.9%, which was higher than for traditional “age” (53.7%, 62.4%) and “GBM sub-type” (57.7%, 52.9%) in the CGGA- and TCGA-RNAseq databases, respectively. Subsequent bioinformatics analysis predicted that the seven-gene signature was involved in the inflammatory response, immune response, cell adhesion, and apoptotic process. Conclusions: Our findings indicate that the seven-gene signature could be a potential prognostic biomarker. This study refined the current classification system of IDH-wildtype GBM and may provide a novel perspective for the research and individual therapy of IDH-wildtype GBM.
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Affiliation(s)
- Yu-Qing Liu
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network, Beijing, China
| | - Fan Wu
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network, Beijing, China
| | - Jing-Jun Li
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network, Beijing, China
| | - Yang-Fang Li
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network, Beijing, China
| | - Xing Liu
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network, Beijing, China
| | - Zheng Wang
- Chinese Glioma Genome Atlas Network, Beijing, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Rui-Chao Chai
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network, Beijing, China
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Di Giorgio E, Paluvai H, Picco R, Brancolini C. Genetic Programs Driving Oncogenic Transformation: Lessons from in Vitro Models. Int J Mol Sci 2019; 20:ijms20246283. [PMID: 31842516 PMCID: PMC6940909 DOI: 10.3390/ijms20246283] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 12/10/2019] [Accepted: 12/11/2019] [Indexed: 12/11/2022] Open
Abstract
Cancer complexity relies on the intracellular pleiotropy of oncogenes/tumor suppressors and in the strong interplay between tumors and micro- and macro-environments. Here we followed a reductionist approach, by analyzing the transcriptional adaptations induced by three oncogenes (RAS, MYC, and HDAC4) in an isogenic transformation process. Common pathways, in place of common genes became dysregulated. From our analysis it emerges that, during the process of transformation, tumor cells cultured in vitro prime some signaling pathways suitable for coping with the blood supply restriction, metabolic adaptations, infiltration of immune cells, and for acquiring the morphological plasticity needed during the metastatic phase. Finally, we identified two signatures of genes commonly regulated by the three oncogenes that successfully predict the outcome of patients affected by different cancer types. These results emphasize that, in spite of the heterogeneous mutational burden among different cancers and even within the same tumor, some common hubs do exist. Their location, at the intersection of the various signaling pathways, makes a therapeutic approach exploitable.
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18
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Su J, Long W, Ma Q, Xiao K, Li Y, Xiao Q, Peng G, Yuan J, Liu Q. Identification of a Tumor Microenvironment-Related Eight-Gene Signature for Predicting Prognosis in Lower-Grade Gliomas. Front Genet 2019; 10:1143. [PMID: 31803233 PMCID: PMC6872675 DOI: 10.3389/fgene.2019.01143] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Accepted: 10/21/2019] [Indexed: 12/15/2022] Open
Abstract
Lower-grade gliomas (LrGG), characterized by invasiveness and heterogeneity, remain incurable with current therapies. Clinicopathological features provide insufficient information to guide optimal individual treatment and cannot predict prognosis completely. Recently, an increasing amount of studies indicate that the tumor microenvironment plays a pivotal role in tumor malignancy and treatment responses. However, studies focusing on the tumor microenvironment (TME) of LrGG are still limited. In this study, taking advantage of the currently popular computational methods for estimating the infiltration of tumor-associated normal cells in tumor samples and using weighted gene co-expression network analysis, we screened the co-expressed gene modules associated with the TME and further identified the prognostic hub genes in these modules. Furthermore, eight prognostic hub genes (ARHGDIB, CLIC1, OAS3, PDIA4, PARP9, STAT1, TAP2, and TAGLN2) were selected to construct a prognostic risk score model using the least absolute shrinkage and selection operator method. Univariate and multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic factor for LrGG. Moreover, time-dependent ROC curves indicated that our model had favorable efficiency in predicting both short- and long-term prognosis in LrGG patients, and the stratified survival analysis demonstrated that our model had prognostic value for different subgroups of LrGG patients. Additionally, our model had potential value for predicting the sensitivity of LrGG patients to radio- and chemotherapy. Besides, differential expression analysis showed that the eight genes were aberrantly expressed in LrGG compared to normal brain tissue. Correlation analysis revealed that the expression of the eight genes was significantly associated with the infiltration levels of six types of immune cells in LrGG. In summary, the TME-related eight-gene signature was significantly associated with the prognosis of LrGG patients. They might act as potential prognostic biomarkers for LrGG patients, offer better stratification for future clinical trials, and be candidate targets for immunotherapy, thus deserving further investigation.
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Affiliation(s)
- Jun Su
- Department of Neurosurgery in Xiangya Hospital, Central South University, Changsha, China
| | - Wenyong Long
- Department of Neurosurgery in Xiangya Hospital, Central South University, Changsha, China
| | - Qianquan Ma
- Department of Neurosurgery in Peking University Third Hospital, Peking University, Beijing, China
| | - Kai Xiao
- Department of Neurosurgery in Xiangya Hospital, Central South University, Changsha, China
| | - Yang Li
- Department of Neurosurgery in Xiangya Hospital, Central South University, Changsha, China
| | - Qun Xiao
- Department of Neurosurgery in Xiangya Hospital, Central South University, Changsha, China
| | - Gang Peng
- Department of Neurosurgery in Xiangya Hospital, Central South University, Changsha, China
| | - Jian Yuan
- Department of Neurosurgery in Xiangya Hospital, Central South University, Changsha, China
| | - Qing Liu
- Department of Neurosurgery in Xiangya Hospital, Central South University, Changsha, China.,Institute of Skull Base Surgery & Neuro-oncology at Hunan, Changsha, China
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19
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Zhang ZY, Zhan YB, Zhang FJ, Yu B, Ji YC, Zhou JQ, Bai YH, Wang YM, Wang L, Jing Y, Duan WC, Sun C, Sun T, Zhao HB, Li K, Wang WQ, Li RY, Sun HW, Zhai G, Wang SK, Wei XT, Yang B, Yan DM, Liu XZ, Wang WW. Prognostic value of preoperative hematological markers combined with molecular pathology in patients with diffuse gliomas. Aging (Albany NY) 2019; 11:6252-6272. [PMID: 31444316 PMCID: PMC6738441 DOI: 10.18632/aging.102186] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Accepted: 08/10/2019] [Indexed: 12/11/2022]
Abstract
The prediction of clinical outcome for patients with infiltrative gliomas is challenging. Although preoperative hematological markers have been proposed as predictors of survival in glioma and other cancers, systematic investigations that combine these data with other relevant clinical variables are needed to improve prognostic accuracy and patient outcomes. We investigated the prognostic value of preoperative hematological markers, alone and in combination with molecular pathology, for the survival of 592 patients with Grade II-IV diffuse gliomas. On univariate analysis, increased neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR), and decreased albumin-to-globulin ratio (AGR), all predicted poor prognosis in Grade II/III gliomas. Multivariate analysis incorporating tumor status based on the presence of IDH mutations, TERT promoter mutations, and 1p/19q codeletion showed that in lower-grade gliomas, high NLR predicted poorer survival for the triple-negative, IDH mutation only, TERT mutation only, and IDH and TERT mutation groups. NLR was an independent prognostic factor in Grade IV glioma. We therefore propose a prognostic model for diffuse gliomas based on the presence of IDH and TERT promoter mutations, 1p/19q codeletion, and NLR. This model classifies lower-grade gliomas into nine subgroups that can be combined into four main risk groups based on survival projections.
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Affiliation(s)
- Zhen-Yu Zhang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Yun-Bo Zhan
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Feng-Jiang Zhang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Bin Yu
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Yu-Chen Ji
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Jin-Qiao Zhou
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Ya-Hui Bai
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Yan-Min Wang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Li Wang
- Department of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Yan Jing
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Wen-Chao Duan
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Chen Sun
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Tao Sun
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Hai-Biao Zhao
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Ke Li
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Wen-Qing Wang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Ruo-Yan Li
- Department of SICU, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Hong-Wei Sun
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Guang Zhai
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Shu-Kai Wang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Xin-Ting Wei
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Bo Yang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Dong-Ming Yan
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Xian-Zhi Liu
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Wei-Wei Wang
- Department of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
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20
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Wang Y, Liu X, Guan G, Xiao Z, Zhao W, Zhuang M. Identification of a Five-Pseudogene Signature for Predicting Survival and Its ceRNA Network in Glioma. Front Oncol 2019; 9:1059. [PMID: 31681595 PMCID: PMC6803554 DOI: 10.3389/fonc.2019.01059] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 09/27/2019] [Indexed: 02/05/2023] Open
Abstract
Background: Glioma is the most common primary brain tumor with a dismal prognosis. It is urgent to develop novel molecular biomarkers and conform to individualized schemes. Methods: Differentially expressed pseudogenes between low grade glioma (LGG) and glioblastoma multiforme (GBM) were identified in the training cohort. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox proportional hazards regression analyses were used to select pseudogenes associated with prognosis of glioma. A risk signature was constructed based on the selected pseudogenes for predicting the survival of glioma patients. A pseudogene-miRNA-mRNA regulatory network was established and visualized using Cytoscape 3.5.1. Gene Oncology (GO) and signaling pathway analyses were performed on the targeted genes to investigate functional roles of the risk signature. Results: Five pseudogenes (ANXA2P2, EEF1A1P9, FER1L4, HILS1, and RAET1K) correlating with glioma survival were selected and used to establish a risk signature. Time-dependent receiver operating characteristic (ROC) curves revealed that the risk signature could accurately predict the 1, 3, and 5-year survival of glioma patients. GO and signaling pathway analyses showed that the risk signature was involved in regulation of proliferation, migration, angiogenesis, and apoptosis in glioma. Conclusions: In this study, a risk signature with five pseudogenes was constructed and shown to accurately predict 1-, 3-, and 5-year survival for glioma patient. The risk signature may serve as a potential target against glioma.
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Affiliation(s)
- Yulin Wang
- Department of Neurosurgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Xin Liu
- Department of Stomatology, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Gefei Guan
- Department of Neurosurgery, The First Hospital of China Medical University, Shenyang, China
| | - Zhe Xiao
- Department of Neurosurgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Weijiang Zhao
- Wuxi Medical College, Jiangnan University, Wuxi, China
- Center for Neuroscience, Shantou University Medical College, Shantou, China
- *Correspondence: Weijiang Zhao
| | - Minghua Zhuang
- Department of Neurosurgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- Minghua Zhuang
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21
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Wang Y, Liu X, Guan G, Zhao W, Zhuang M. A Risk Classification System With Five-Gene for Survival Prediction of Glioblastoma Patients. Front Neurol 2019; 10:745. [PMID: 31379707 PMCID: PMC6646669 DOI: 10.3389/fneur.2019.00745] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Accepted: 06/26/2019] [Indexed: 02/05/2023] Open
Abstract
Objective: Glioblastoma (GBM) is the most common and fatal primary brain tumor in adults. It is necessary to identify novel and effective biomarkers or risk signatures for GBM patients. Methods: Differentially expressed genes (DEGs) between GBM and low-grade glioma (LGG) in TCGA samples were screened out and weight correlation network analysis (WGCNA) was performed to confirm WHO grade-related genes. Five genes were selected via multivariate Cox proportional hazards regression analysis and were used to construct a risk signature. A nomogram composed of the risk signature and clinical characters (age, radiotherapy, and chemotherapy experience) was established to predict 1, 3, 5-year survival rate for GBM patients. Results: One hundred ninety-four DEGs in blue gene module were found to be positively related to WHO grade via WGCNA. Five genes (DES, RANBP17, CLEC5A, HOXC11, POSTN) were selected to construct a risk signature for GBM via R language. This risk signature was identified to independently predict the outcome of GBM patients, as well as stratified by IDH1 status, MGMT promoter status, and radio-chemotherapy. The nomogram was established which combined the risk signature with clinical factors. The results of c-index, ROC curve and calibration plot revealed the nomogram showing a good accuracy for predicting 1, 3, or 5-year survival of GBM patients. Conclusion: The risk signature with five genes could serve as an independent factor for predicting the prognosis of patients with GBM. Moreover, the nomogram with the risk signature and clinical traits proved to perform better for predicting 1, 3, 5-year survival rate.
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Affiliation(s)
- Yulin Wang
- Department of Neurosurgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Xin Liu
- Department of Stomatology, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Gefei Guan
- Department of Neurosurgery, The First Hospital of China Medical University, Shenyang, China
| | - Weijiang Zhao
- Center for Neuroscience, Shantou University Medical College, Shantou, China
- *Correspondence: Weijiang Zhao
| | - Minghua Zhuang
- Department of Neurosurgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
- Minghua Zhuang
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22
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Liu YQ, Chai RC, Wang YZ, Wang Z, Liu X, Wu F, Jiang T. Amino acid metabolism-related gene expression-based risk signature can better predict overall survival for glioma. Cancer Sci 2018; 110:321-333. [PMID: 30431206 PMCID: PMC6317920 DOI: 10.1111/cas.13878] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Revised: 10/18/2018] [Accepted: 11/11/2018] [Indexed: 12/20/2022] Open
Abstract
Metabolic reprogramming has been proposed to be a hallmark of cancer. Aside from the glycolytic pathway, the metabolic changes of cancer cells primarily involve amino acid metabolism. However, in glioma, the characteristics of the amino acid metabolism‐related gene set have not been systematically profiled. In the present study, RNA sequencing expression data from 309 patients in the Chinese Glioma Genome Atlas database were included as a training set, while another 550 patients within The Cancer Genome Atlas database were used to validate. Consensus clustering of the 309 samples yielded two robust groups. Compared with Cluster1, Cluster2 correlated with a better clinical outcome. We then developed an amino acid metabolism‐related risk signature for glioma. Our results showed that patients in the high‐risk group had dramatically shorter overall survival than low‐risk counterparts in any subgroup, stratified by isocitrate dehydrogenase and 1p/19q status based on the 2016 World Health Organization classification guidelines. The 30‐gene signature showed better prognostic value than the traditional factors “age” and “grade” by analyzing the receiver operating characteristic curve with areas under curve of 0.966, 0.692, 0.898 and 0.975, 0.677, 0.885 for 3‐ and 5‐year survival, respectively. Moreover, univariate and multivariate analysis showed that the 30‐gene signature was an independent prognostic factor for glioma. Furthermore, Gene Ontology analysis and Gene Set Enrichment Analysis showed that tumors with a high risk score correlated with various aspects of the malignancy of glioma. In summary, we demonstrated a novel amino acid metabolism‐related risk signature for predicting prognosis for glioma.
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Affiliation(s)
- Yu-Qing Liu
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network (CGGA), Beijing, China
| | - Rui-Chao Chai
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network (CGGA), Beijing, China
| | - Yong-Zhi Wang
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network (CGGA), Beijing, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zheng Wang
- Chinese Glioma Genome Atlas Network (CGGA), Beijing, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xing Liu
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network (CGGA), Beijing, China
| | - Fan Wu
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network (CGGA), Beijing, China
| | - Tao Jiang
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.,Chinese Glioma Genome Atlas Network (CGGA), Beijing, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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23
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Romanidou O, Kotoula V, Fountzilas G. Bridging Cancer Biology with the Clinic: Comprehending and Exploiting IDH Gene Mutations in Gliomas. Cancer Genomics Proteomics 2018; 15:421-436. [PMID: 30194083 DOI: 10.21873/cgp.20101] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Revised: 07/23/2018] [Accepted: 07/24/2018] [Indexed: 12/22/2022] Open
Abstract
Isocitrate dehydrogenases 1 and 2 (IDH1/2) are enzymes that play a major role in the Krebs cycle. Mutations in these enzymes are found in the majority of lower gliomas and secondary glioblastomas, but also in myeloid malignancies and other cancers. IDH1 and IDH2 mutations are restricted to specific arginine residues in the active site of the enzymes and are gain-of-function, i.e. they confer a neomorphic enzyme activity resulting in the accumulation of D-2-hydroxyglutarate (2-HG). 2-HG is an oncometabolite causing profound metabolic dysregulation which, among others, results in methylator phenotypes and in defects in homologous recombination repair. In this review, we summarize current knowledge regarding the function of normal and mutated IDH, explain the possible mechanisms through which these mutations might drive malignant transformation of progenitor cells in the central nervous system, and provide a comprehensive review of potential treatment strategies for IDH-mutated malignancies, focusing on gliomas.
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Affiliation(s)
- Ourania Romanidou
- Department of Medical Oncology, Papageorgiou Hospital, Aristotle University of Thessaloniki, School of Health Sciences, Faculty of Medicine, Thessaloniki, Greece
| | - Vassiliki Kotoula
- Department of Pathology, Aristotle University of Thessaloniki, School of Health Sciences, Faculty of Medicine, Thessaloniki, Greece.,Laboratory of Molecular Oncology, Hellenic Foundation for Cancer Research/Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - George Fountzilas
- Laboratory of Molecular Oncology, Hellenic Foundation for Cancer Research/Aristotle University of Thessaloniki, Thessaloniki, Greece
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24
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25
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Wang PF, Meng Z, Song HW, Yao K, Duan ZJ, Yu CJ, Li SW, Yan CX. Preoperative Changes in Hematological Markers and Predictors of Glioma Grade and Survival. Front Pharmacol 2018; 9:886. [PMID: 30154718 PMCID: PMC6103192 DOI: 10.3389/fphar.2018.00886] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 07/20/2018] [Indexed: 12/18/2022] Open
Abstract
Background: Preoperative hematological markers that indicate nutritional, coagulation, and inflammation statuses have prognostic value for gliomas. This study aimed to investigate hematological markers with regard to tumor grades, isocitrate dehydrogenase mutations (IDH), age, and sex in patients with gliomas. Methods: From 2008 to 2017, patients with a pathological diagnosis of glioma who underwent surgery were retrospectively enrolled in this study. Information from clinical records, including age, sex, preoperative experiment tests (routine blood tests, biochemistry, and coagulation examinations), pathological results, and IDH status, was collected. A univariable survival analysis was performed. Hematological factors such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte-ratio (PLR), and albumin-to-globulin (AGR) were calculated. The prognostic nutrition index (PNI) was calculated as 10 × serum albumin value (g/dl) + 0.005 × peripheral lymphocyte count (per mm3). Results: Our study included 706 patients. The univariate analysis showed that age, IDH-1, and hematological factors were all significantly associated with overall survival (OS) in patients with gliomas. Our results showed that inflammation markers (NLR, PLR, and fibrinogen) were positively associated with age, whereas AGR was negatively associated with age. The PLR was significantly increased, whereas the AGR and PNI were decreased in women with gliomas, as compared with men. We found that inflammation markers increased and nutrition markers decreased with gliomas grade. However, these hematological markers did not significantly differ with IDH status. NLR was the best single hematological marker for distinguishing glioblastoma (GBM) [0.684 (0.645-0.723)], IDH-wt GBM [0.672 (0.631-0.71)] from other gliomas subtypes. Combinations of age with PNI and age with AGR were the best predictors of GBM [0.750 (0.713-0.786)] and IDH-wt GBM [0.759 (0.719-0.798)], respectively. Conclusion: Preoperative hematological marker levels vary among glioma grades and have high predictive values for GBM.
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Affiliation(s)
- Peng-Fei Wang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Zhe Meng
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Hong-Wang Song
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Kun Yao
- Department of Pathology, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Ze-Jun Duan
- Department of Pathology, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Chun-Jiang Yu
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Shou-Wei Li
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Chang-Xiang Yan
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
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