1
|
Azimi P, Yazdanian T, Ahmadiani A. mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses. BMC Cancer 2024; 24:612. [PMID: 38773447 PMCID: PMC11106946 DOI: 10.1186/s12885-024-12345-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Accepted: 05/06/2024] [Indexed: 05/23/2024] Open
Abstract
BACKGROUND Glioblastoma multiforme (GBM) is a type of fast-growing brain glioma associated with a very poor prognosis. This study aims to identify key genes whose expression is associated with the overall survival (OS) in patients with GBM. METHODS A systematic review was performed using PubMed, Scopus, Cochrane, and Web of Science up to Journey 2024. Two researchers independently extracted the data and assessed the study quality according to the New Castle Ottawa scale (NOS). The genes whose expression was found to be associated with survival were identified and considered in a subsequent bioinformatic study. The products of these genes were also analyzed considering protein-protein interaction (PPI) relationship analysis using STRING. Additionally, the most important genes associated with GBM patients' survival were also identified using the Cytoscape 3.9.0 software. For final validation, GEPIA and CGGA (mRNAseq_325 and mRNAseq_693) databases were used to conduct OS analyses. Gene set enrichment analysis was performed with GO Biological Process 2023. RESULTS From an initial search of 4104 articles, 255 studies were included from 24 countries. Studies described 613 unique genes whose mRNAs were significantly associated with OS in GBM patients, of which 107 were described in 2 or more studies. Based on the NOS, 131 studies were of high quality, while 124 were considered as low-quality studies. According to the PPI network, 31 key target genes were identified. Pathway analysis revealed five hub genes (IL6, NOTCH1, TGFB1, EGFR, and KDR). However, in the validation study, only, the FN1 gene was significant in three cohorts. CONCLUSION We successfully identified the most important 31 genes whose products may be considered as potential prognosis biomarkers as well as candidate target genes for innovative therapy of GBM tumors.
Collapse
Affiliation(s)
- Parisa Azimi
- Neurosurgeon, Neuroscience Research Center, Shahid Beheshti University of Medical Sciences, Arabi Ave, Daneshjoo Blvd, Velenjak, Tehran, 19839- 63113, Iran.
| | | | - Abolhassan Ahmadiani
- Neurosurgeon, Neuroscience Research Center, Shahid Beheshti University of Medical Sciences, Arabi Ave, Daneshjoo Blvd, Velenjak, Tehran, 19839- 63113, Iran.
| |
Collapse
|
2
|
Ling Y, Kang X, Yi Y, Feng S, Ma G, Qu H. CLDN5: From structure and regulation to roles in tumors and other diseases beyond CNS disorders. Pharmacol Res 2024; 200:107075. [PMID: 38228255 DOI: 10.1016/j.phrs.2024.107075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 01/11/2024] [Accepted: 01/11/2024] [Indexed: 01/18/2024]
Abstract
Claudin-5 (CLDN5) is an essential component of tight junctions (TJs) and is critical for the integrity of the blood-brain barrier (BBB), ensuring homeostasis and protection from damage to the central nervous system (CNS). Currently, many researchers have summarized the role and mechanisms of CLDN5 in CNS diseases. However, it is noteworthy that CLDN5 also plays a significant role in tumor growth and metastasis. In addition, abnormal CLDN5 expression is involved in the development of respiratory diseases, intestinal diseases, cardiac diseases, and diabetic ocular complications. This paper aims to review the structure, expression, and regulation of CLDN5, focusing on its role in tumors, including its expression and regulation, effects on malignant phenotypes, and clinical significance. Furthermore, this paper will provide an overview of the role and mechanisms of CLDN5 in respiratory diseases, intestinal diseases, cardiac diseases, and diabetic ocular complications.
Collapse
Affiliation(s)
- Yao Ling
- Department of Histology and Embryology, College of Basic Medical Sciences, Jilin University, Changchun, China; Bethune Second Clinical Medical College of Jilin University, Changchun, China
| | - Xinxin Kang
- Department of Histology and Embryology, College of Basic Medical Sciences, Jilin University, Changchun, China; Bethune Second Clinical Medical College of Jilin University, Changchun, China
| | - Ying Yi
- Department of Histology and Embryology, College of Basic Medical Sciences, Jilin University, Changchun, China; Bethune Second Clinical Medical College of Jilin University, Changchun, China
| | - Shenao Feng
- Department of Histology and Embryology, College of Basic Medical Sciences, Jilin University, Changchun, China; Bethune Second Clinical Medical College of Jilin University, Changchun, China
| | - Guanshen Ma
- Department of Histology and Embryology, College of Basic Medical Sciences, Jilin University, Changchun, China; Bethune Second Clinical Medical College of Jilin University, Changchun, China
| | - Huinan Qu
- Department of Histology and Embryology, College of Basic Medical Sciences, Jilin University, Changchun, China.
| |
Collapse
|
3
|
Wang M, Guo H, Zhang B, Shang Y, Zhang S, Liu X, Cao P, Fan Y, Tan K. Transcription factors-related molecular subtypes and risk prognostic model: exploring the immunogenicity landscape and potential drug targets in hepatocellular carcinoma. Cancer Cell Int 2024; 24:9. [PMID: 38178084 PMCID: PMC10765642 DOI: 10.1186/s12935-023-03185-1] [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: 08/21/2023] [Accepted: 12/19/2023] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is the most prevalent form of liver cancer, with a high mortality rate and poor prognosis. Mutated or dysregulated transcription factors (TFs) are significantly associated with carcinogenesis. The aim of this study was to develop a TF-related prognostic risk model to predict the prognosis and guide the treatment of HCC patients. METHODS RNA sequencing data were obtained from the TCGA database. The ICGC and GEO databases were used as validation datasets. The consensus clustering algorithm was used to classify the molecular subtypes of TFs. Kaplan‒Meier survival analysis and receiver operating characteristic (ROC) analysis were applied to evaluate the prognostic value of the model. The immunogenic landscape differences of molecular subtypes were evaluated by the TIMER and xCell algorithms. Autodock analysis was used to predict possible binding sites of trametinib to TFs. RT‒PCR was used to verify the effect of trametinib on the expression of core TFs. RESULTS According to the differential expression of TFs, HCC samples were divided into two clusters (C1 and C2). The survival time, signaling pathways, abundance of immune cell infiltration and responses to chemotherapy and immunotherapy were significantly different between C1 and C2. Nine TFs with potential prognostic value, including HMGB2, ESR1, HMGA1, MYBL2, TCF19, E2F1, FOXM1, CENPA and ZIC2, were identified by Cox regression analysis. HCC patients in the high-risk group had a poor prognosis compared with those in the low-risk group (p < 0.001). Moreover, the area under the ROC curve (AUC) values of the 1-year, 2-year and 3-year survival rates were 0.792, 0.71 and 0.695, respectively. The risk model was validated in the ICGC database. Notably, trametinib sensitivity was highly correlated with the expression of core TFs, and molecular docking predicted the possible binding sites of trametinib with these TFs. More importantly, the expression of core TFs was downregulated under trametinib treatment. CONCLUSIONS A prognostic signature with 9 TFs performed well in predicting the survival rate and chemotherapy/immunotherapy effect of HCC patients. Trimetinib has potential application value in HCC by targeting TFs.
Collapse
Affiliation(s)
- Meixia Wang
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Research Center of the Basic Discipline of Cell Biology, Hebei Province Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China
| | - Hanyao Guo
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Research Center of the Basic Discipline of Cell Biology, Hebei Province Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China
| | - Bo Zhang
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Research Center of the Basic Discipline of Cell Biology, Hebei Province Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China
| | - Yanan Shang
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Research Center of the Basic Discipline of Cell Biology, Hebei Province Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China
| | - Sidi Zhang
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Research Center of the Basic Discipline of Cell Biology, Hebei Province Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China
| | - Xiaoyu Liu
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Research Center of the Basic Discipline of Cell Biology, Hebei Province Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China
| | - Pengxiu Cao
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Research Center of the Basic Discipline of Cell Biology, Hebei Province Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China.
| | - Yumei Fan
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Research Center of the Basic Discipline of Cell Biology, Hebei Province Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China.
| | - Ke Tan
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Research Center of the Basic Discipline of Cell Biology, Hebei Province Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, Hebei, China.
| |
Collapse
|
4
|
Dai Z, Zhang N, Zhou R, Zhang H, Zhang L, Wang Z, Zeng W, Luo P, Zhang J, Liu Z, Cheng Q. Identification of a single cell-based signature for predicting prognosis risk and immunotherapy response in patients with glioblastoma. Clin Immunol 2023; 251:109345. [PMID: 37100336 DOI: 10.1016/j.clim.2023.109345] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 11/20/2022] [Accepted: 04/14/2023] [Indexed: 04/28/2023]
Abstract
This study constructed a novel gene pair signature based on bulk and single-cell sequencing samples in relative expression order within the samples. The subsequent analysis included glioma samples from Xiangya Hospital. Gene pair signatures possessed a solid ability to predict the prognosis of glioblastoma and pan-cancer. Samples having different malignant biological hallmarks were distinguished by the algorithm, with the high gene pair score group featuring classic copy number variations, oncogenic mutations, and extensive hypomethylation, mediating poor prognosis. The increased gene pair score group with a poorer prognosis demonstrated significant enrichment in tumor and immune-related signaling pathways while presenting immunological diversity. The remarkable infiltration of M2 macrophages in the high gene pair score group was validated by multiplex immunofluorescence, suggesting that combination therapies targeting adaptive and innate immunity may serve as a therapeutic option. Overall, a gene pair signature applicable to predict prognosis hopefully provides a reference to guide clinical practice.
Collapse
Affiliation(s)
- Ziyu Dai
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha 410078, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China
| | - Nan Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha 410078, China; One-Third Lab, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150088, China
| | - Ran Zhou
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha 410078, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China; Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK
| | - Hao Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha 410078, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China
| | - Liyang Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha 410078, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China; Department of Medicine, The University of Oklahoma Health Sciences Center, OK 73104, USA; Clinical Diagnosis and Therapeutic Center of Glioma, Xiangya Hospital, Central South University, Changsha 410078, China
| | - Zeyu Wang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha 410078, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China
| | - Wenjing Zeng
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha 410078, China
| | - Peng Luo
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Jian Zhang
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Zhixiong Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha 410078, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410078, China.
| | - Quan Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha 410078, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410078, China; Clinical Diagnosis and Therapeutic Center of Glioma, Xiangya Hospital, Central South University, Changsha 410078, China.
| |
Collapse
|
5
|
Vaidya M, Smith J, Field M, Sugaya K. Analysis of regulatory sequences in exosomal DNA of NANOGP8. PLoS One 2023; 18:e0280959. [PMID: 36696426 PMCID: PMC9876286 DOI: 10.1371/journal.pone.0280959] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 12/20/2022] [Indexed: 01/26/2023] Open
Abstract
Exosomes participate in intercellular communication by transporting functionally active molecules. Such cargo from the original cells comprising proteins, micro-RNA, mRNA, single-stranded (ssDNA) and double-stranded DNA (dsDNA) molecules pleiotropically transforms the target cells. Although cancer cells secrete exosomes carrying a significant level of DNA capable of modulating oncogene expression in a recipient cell, the regulatory mechanism is unknown. We have previously reported that cancer cells produce exosomes containing NANOGP8 DNA. NANOGP8 is an oncogenic paralog of embryonic stem cell transcription factor NANOG and does not express in cells since it is a pseudogene. However, in this study, we evaluated NANOGP8 expression in glioblastoma multiforme (GBM) tissue from a surgically removed brain tumor of a patient. Significantly higher NANOGP8 transcription was observed in GBM cancer stem cells (CSCs) than in GBM cancer cells or neural stem cells (NSCs), despite identical sequences of NANOGP8-upstream genomic region in all the cell lines. This finding suggests that upstream genomic sequences of NANOGP8 may have environment-dependent promoter activity. We also found that the regulatory sequences upstream of exosomal NANOGP8 GBM DNA contain multiple core promoter elements, transcription factor binding sites, and segments of human viruses known for their oncogenic role. The exosomal sequence of NANOGP8-upstream GBM DNA is different from corresponding genomic sequences in CSCs, cancer cells, and NSCs as well as from the sequences reported by NCBI. These sequence dissimilarities suggest that exosomal NANOGP8 GBM DNA may not be a part of the genomic DNA. Exosomes possibly acquire this DNA from other sources where it is synthesized by an unknown mechanism. The significance of exosome-bestowed regulatory elements in the transcription of promoter-less retrogene such as NANOGP8 remains to be determined.
Collapse
Affiliation(s)
- Manjusha Vaidya
- Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL, United States of America
| | - Jonhoi Smith
- Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL, United States of America
| | - Melvin Field
- Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL, United States of America
- AdventHealth Cancer Institute, Orlando, FL, United States of America
| | - Kiminobu Sugaya
- Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL, United States of America
- * E-mail:
| |
Collapse
|
6
|
Zhu B, Zhang L, Zhou X, Ning H, Ma T. Transcription factor ZNF22 regulates blood-tumor barrier permeability by interacting with HDAC3 protein. Front Mol Neurosci 2022; 15:1027942. [PMID: 36518188 PMCID: PMC9742255 DOI: 10.3389/fnmol.2022.1027942] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 11/11/2022] [Indexed: 10/09/2023] Open
Abstract
OBJECTIVE The primary goals of this study were to investigate the potential roles of ZNF22 and HDAC3 as a histone deacetylase in regulating an increases in blood-tumor barrier (BTB) permeability and some of the possible molecular mechanisms associated with this effect. METHODS The expression of ZNF22 and HDAC3 in glioma-exposed endothelial cells (GECs) of BTB were detected transcription real-time PCR or western blot. The interaction of ZNF22 and HDAC3 in GECs associated with transcript effect was analyzed by means of Co-Immunoprecipitation and luciferase reporter assay. RESULTS In the present investigation, GECs expressed higher levels of ZNF22 as a zinc finger transcription factor and HDAC3 than endothelial cells. We then affirmed that silencing HDAC3 or ZNF22 led to a reduction in BTB permeability. By bioinformatics analysis, chromatin immunoprecipitation (ChIP) assays and luciferase assay, we found that ZNF22 had a target binding relationship with the promoter regions of ZO-1, Occludin, and Claudin-5 and negatively regulated the expression of ZO-1, Occludin, and Claudin-5. Furthermore, we revealed that HDAC3, as a co-transcript repressor with histone deacetylase activity, could interact with ZNF22 to hinder the expression of TJ-associated proteins, thereby further facilitating the permeability of BTB. CONCLUSION ZNF22 acted as a transcription factor in conjunction with HDAC3 to modulate the expression of TJ-associated proteins, which was correlated with an increase in BTB permeability. These results may provide new strategies and targets for the chemotherapy of gliomas as well as intracranial infections.
Collapse
Affiliation(s)
- Baicheng Zhu
- Department of Neurobiology, School of Life Sciences, China Medical University, Shenyang, China
| | - Lu Zhang
- Department of Neurobiology, School of Life Sciences, China Medical University, Shenyang, China
| | - Xinxin Zhou
- Liaoning TCM Academy, Liaoning University of Traditional Chinese Medicine, Shenyang, China
| | - Hao Ning
- Department of Neurobiology, School of Life Sciences, China Medical University, Shenyang, China
| | - Teng Ma
- Department of Neurobiology, School of Life Sciences, China Medical University, Shenyang, China
| |
Collapse
|
7
|
Wang S, Li L, Zuo S, Kong L, Wei J, Dong J. Metabolic-related gene pairs signature analysis identifies ABCA1 expression levels on tumor-associated macrophages as a prognostic biomarker in primary IDHWT glioblastoma. Front Immunol 2022; 13:869061. [PMID: 36248907 PMCID: PMC9561761 DOI: 10.3389/fimmu.2022.869061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 09/14/2022] [Indexed: 11/26/2022] Open
Abstract
Background Although isocitrate dehydrogenase (IDH) mutation serves as a prognostic signature for routine clinical management of glioma, nearly 90% of glioblastomas (GBM) patients have a wild-type IDH genotype (IDHWT) and lack reliable signatures to identify distinct entities. Methods To develop a robust prognostic signature for IDHWT GBM patients, we retrospectively analyzed 4 public datasets of 377 primary frozen tumor tissue transcriptome profiling and clinical follow-up data. Samples were divided into a training dataset (204 samples) and a validation (173 samples) dataset. A prognostic signature consisting of 21 metabolism-related gene pairs (MRGPs) was developed based on the relative ranking of single-sample gene expression levels. GSEA and immune subtype analyses were performed to reveal differences in biological processes between MRGP risk groups. The single-cell RNA-seq dataset was used to examine the expression distribution of each MRG constituting the signature in tumor tissue subsets. Finally, the association of MRGs with tumor progression was biologically validated in orthotopic GBM models. Results The metabolic signature remained an independent prognostic factor (hazard ratio, 5.71 [3.542-9.218], P < 0.001) for stratifying patients into high- and low-risk levels in terms of overall survival across subgroups with MGMTp methylation statuses, expression subtypes, and chemo/ratio therapies. Immune-related biological processes were significantly different between MRGP risk groups. Compared with the low-risk group, the high-risk group was significantly enriched in humoral immune responses and phagocytosis processes, and had more monocyte infiltration and less activated DC, NK, and γδ T cell infiltration. scRNA-seq dataset analysis identified that the expression levels of 5 MRGs (ABCA1, HMOX1, MTHFD2, PIM1, and PTPRE) in TAMs increased with metabolic risk. With tumor progression, the expression level of ABCA1 in TAMs was positively correlated with the population of TAMs in tumor tissue. Downregulation of ABCA1 levels can promote TAM polarization towards an inflammatory phenotype and control tumor growth. Conclusions The metabolic signature is expected to be used in the individualized management of primary IDHWT GBM patients.
Collapse
Affiliation(s)
- Shiqun Wang
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, Jiangsu, China
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Lu Li
- Department of Nephrology, Affiliated Children’s Hospital of Zhejiang University, Hangzhou, Zhejiang, China
| | - Shuguang Zuo
- Liuzhou Key Laboratory of Molecular Diagnosis, Guangxi Key Laboratory of Molecular Diagnosis and Application, Affiliated Liutie Central Hospital of Guangxi Medical University, Liuzhou, Guangxi, China
| | - Lingkai Kong
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Jiwu Wei
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, Jiangsu, China
- *Correspondence: Jie Dong, ; Jiwu Wei,
| | - Jie Dong
- Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, Jiangsu, China
- *Correspondence: Jie Dong, ; Jiwu Wei,
| |
Collapse
|
8
|
Chen Y, Tang M, Xiong J, Gao Q, Cao W, Huang J. GRB10 is a novel oncogene associated with cell proliferation and prognosis in glioma. Cancer Cell Int 2022; 22:223. [PMID: 35790975 PMCID: PMC9254544 DOI: 10.1186/s12935-022-02636-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 06/14/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Glioma is the most common malignant tumor of the central nervous system and is associated with a poor prognosis. This study aimed to explore the function of growth factor receptor-bound protein 10(GRB 10) in glioma.
Methods
The expression of GRB10 in glioma was determined based on the glioma transcriptome profile downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) databases. RT-qPCR was performed to detect the expression of GRB10 in tissue samples obtained from 68 glioma patients. The patients were followed up via telephone or in-person outpatient visits to determine survival. Kaplan-Meier survival analyses were used to evaluate the effect of GRB10 on the prognosis of glioma patients. Further, we constructed GRB10 knockdown cell lines were constructed to investigate the effect of GRB10 on glioma. The cell growth, colony formation, cell cycle assay, EdU assay, and tumor formation in xenograft were performed.
Results
The expression level of GRB10 was positively correlated to the histological grades of gliomas. In addition, Kaplan-Meier survival curves revealed that glioma patients with lower expression of GRB10 had more prolonged survival. The knockdown of GRB10 was shown to inhibit cell proliferation, colony formation, and tumor formation in the xenograft models. Cell cycle assay revealed that the knockdown of GRB10 can inhibit the cells entering the G2/M phase from the S phase. The analysis of GSEA suggests that the expression of GRB10 was positively correlated with the hypoxia and EMT signaling pathway.
Conclusions
Our data revealed that GRB10 regulated tumorigenesis in glioma and played a vital role in promoting the glioma progression, which indicated that GRB10 could be used as a potential prognostic marker.
Collapse
|
9
|
Liu L, Zhu H, Wang P, Wu S. Construction of a Six-Gene Prognostic Risk Model Related to Hypoxia and Angiogenesis for Cervical Cancer. Front Genet 2022; 13:923263. [PMID: 35769999 PMCID: PMC9234147 DOI: 10.3389/fgene.2022.923263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 05/25/2022] [Indexed: 12/24/2022] Open
Abstract
Background: The prognosis of cervical cancer (CC) is poor and not accurately reflected by the primary tumor node metastasis staging system. Our study aimed to develop a novel survival-prediction model. Methods: Hallmarks of CC were quantified using single-sample gene set enrichment analysis and univariate Cox proportional hazards analysis. We linked gene expression, hypoxia, and angiogenesis using weighted gene co-expression network analysis (WGCNA). Univariate and multivariate Cox regression was combined with the random forest algorithm to construct a prognostic model. We further evaluated the survival predictive power of the gene signature using Kaplan-Meier analysis and receiver operating characteristic (ROC) curves. Results: Hypoxia and angiogenesis were the leading risk factors contributing to poor overall survival (OS) of patients with CC. We identified 109 candidate genes using WGCNA and univariate Cox regression. Our established prognostic model contained six genes (MOCSI, PPP1R14A, ESM1, DES, ITGA5, and SERPINF1). Kaplan-Meier analysis indicated that high-risk patients had worse OS (hazard ratio = 4.63, p < 0.001). Our model had high predictive power according to the ROC curve. The C-index indicated that the risk score was a better predictor of survival than other clinicopathological variables. Additionally, univariate and multivariate Cox regressions indicated that the risk score was the only independent risk factor for poor OS. The risk score was also an independent predictor in the validation set (GSE52903). Bivariate survival prediction suggested that patients exhibited poor prognosis if they had high z-scores for hypoxia or angiogenesis and high risk scores. Conclusions: We established a six-gene survival prediction model associated with hypoxia and angiogenesis. This novel model accurately predicts survival and also provides potential therapeutic targets.
Collapse
Affiliation(s)
- Lili Liu
- TCM Gynecology Department, Foshan Fosun Chancheng Hospital, Foshan Clinical Medical School of Guangzhou University of Chinese Medicine, Foshan, China
| | - Hongcang Zhu
- Foshan Retirement Center for Retired Cadres, Guangdong Military Region of the PLA, Foshan, China
| | - Pei Wang
- Foshan Clinical Medical School, Guangzhou University of Chinese Medicine, Foshan, China
| | - Suzhen Wu
- TCM Gynecology Department, Foshan Fosun Chancheng Hospital, Foshan Clinical Medical School of Guangzhou University of Chinese Medicine, Foshan, China
- *Correspondence: Suzhen Wu,
| |
Collapse
|
10
|
Transcription factor SNAI2 exerts pro-tumorigenic effects on glioma stem cells via PHLPP2-mediated Akt pathway. Cell Death Dis 2022; 13:516. [PMID: 35654777 PMCID: PMC9163135 DOI: 10.1038/s41419-021-04481-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 12/01/2021] [Accepted: 12/17/2021] [Indexed: 01/21/2023]
Abstract
The current study aimed to investigate the effects associated with SNAI2 on the proliferation of glioma stem cells (GSCs) to elucidate its underlying molecular mechanism in the development of glioma. The expression of Snail family transcriptional repressor 2 (SNAI2) in glioma tissues was initially predicted via bioinformatics analysis and subsequently confirmed by reverse transcription quantitative polymerase chain reaction (RT-qPCR), which revealed that SNAI2 was highly expressed in glioma tissues as well as GSCs, with an inverse correlation with overall glioma patient survival detected. Loss- and gain- of-function assays were performed to determine the roles of SNAI2 and pleckstrin homology domain and leucine rich repeat protein phosphatase 2 (PHLPP2) on GSC viability, proliferation and apoptosis. Data were obtained indicating that SNAI2 promoted the proliferation of GSCs, while overexpressed PHLPP2 brought about a contrasting trend. As detected by chromatin immunoprecipitation, RT-qPCR and agarose gel electrophoresis, SNAI2 bound to the promoter region of PHLPP2 and repressed the transcription of PHLPP2 while SNAI2 was found to inhibit PHLPP2 resulting in activation of the Akt pathway. Finally, the roles of SNAI2 and PHLPP2 were verified in glioma growth in nude mice xenografted with tumor. Taken together, the key findings of the present study suggest that SNAI2 may promote the proliferation of GSCs through activation of the Akt pathway by downregulating PHLPP2.
Collapse
|
11
|
Akçay S, Güven E, Afzal M, Kazmi I. Non-negative matrix factorization and differential expression analyses identify hub genes linked to progression and prognosis of glioblastoma multiforme. Gene 2022; 824:146395. [PMID: 35283227 DOI: 10.1016/j.gene.2022.146395] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 02/10/2022] [Accepted: 03/04/2022] [Indexed: 12/25/2022]
Abstract
One of the most prevailing primary brain tumors in adult human male is glioblastoma multiforme (GBM), which is categorized by rapid cellular growth. Even though the combination therapy comprises surgery, chemotherapy, and adjuvant therapies, the survival rate, on average, is 14.6 months. Glioma stem cells (GSCs) have key roles in tumorigenesis, progression, and defiance against chemotherapy and radiotherapy. In our study, firstly, the gene expression dataset GSE124145 was retrieved; the non-negative matrix factorization (NMF) method was applied on GBM dataset, and differentially expressed genes analysis (DEGs) was performed. After which, overlapping genes between metagenes and DEGs were detected to examine the Gene Ontology (GO) categories in the biological process (BP) in the stemness of GBM. The common hub genes were used to construct protein-protein interaction (PPI) network and further GO, while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway was utilized to pinpoint the real hub genes. The analysis of hub genes particular for the same GO categories demonstrated that specific hub genes triggered distinct features of the same biological processes. After utilizing GSE124145 and The Cancer Genome Atlas (TCGA) dataset for survival analysis, we screened five real hub genes: GUCA1A, RFC2, GNG11, MMP19, and NRG1, which are strongly associated with the progression and prognosis of GBM. The DEGs analysis revealed that all real hub genes were overexpressed in GBM and TCGA datasets, which further validates our results. The constructed study of PPI, GO, and KEGG pathway on common hub genes was performed. Finally, the KEGG pathways performed on the top 15 candidate hub genes (including six real hub genes) of the PPI network in the GBM gene expression dataset study found mitogen-activated protein kinase (Mapk) signaling pathway to be the most significant pathway. The rest of the hub genes reviewed throughout the analysis might be favorable targets for diagnosing and treating GBM and lower-grade gliomas.
Collapse
Affiliation(s)
- Sevinç Akçay
- Department of Molecular Biology of Genetics, Kırşehir Ahi Evran University, Kırşehir, Turkey
| | - Emine Güven
- Department of Biomedical Engineering, Düzce University, Düzce, Turkey
| | - Muhammad Afzal
- Department of Pharmacology, College of Pharmacy, Jouf University, Sakaka, AlJouf 72341, Saudi Arabia.
| | - Imran Kazmi
- Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
| |
Collapse
|
12
|
MEOX2 Regulates the Growth and Survival of Glioblastoma Stem Cells by Modulating Genes of the Glycolytic Pathway and Response to Hypoxia. Cancers (Basel) 2022; 14:cancers14092304. [PMID: 35565433 PMCID: PMC9099809 DOI: 10.3390/cancers14092304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/03/2022] [Accepted: 05/04/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary Glioblastoma is the most common incurable primary brain tumor in adults, typically leading to death within 15 months of diagnosis. Although there is an ongoing debate in the scientific community about the precise cellular origin of this tumor, glioblastoma stem cells (GSCs), which are able to self-renew, yield a full tumor mass, and determine chemo- and radio-resistance, are recognized to have a pivotal role. Our research aims to understand the role of the mesenchyme homeobox 2 (MEOX2) transcription factor in GSCs where it is strongly and specifically expressed. We have found that MEOX2 is indeed important for the survival of these cells. In fact, when we reduce its expression in two different GSC lines, they undergo a massive death accompanied by the inhibition of key genes of the glycolytic metabolism, the main source of energy for these cells. Our results reveal a novel function for MEOX2 in glioblastoma and suggest a mechanism through which GSCs may survive even in unfavorable conditions. Abstract The most widely accepted hypothesis for the development of glioblastoma suggests that glioblastoma stem-like cells (GSCs) are crucially involved in tumor initiation and recurrence as well as in the occurrence of chemo- and radio-resistance. Mesenchyme homeobox 2 (MEOX2) is a transcription factor overexpressed in glioblastoma, whose expression is negatively correlated with patient survival. Starting from our observation that MEOX2 expression is strongly enhanced in six GSC lines, we performed shRNA-mediated knock-down experiments in two different GSC lines and found that MEOX2 depletion resulted in the inhibition of cell growth and sphere-forming ability and an increase in apoptotic cell death. By a deep transcriptome analysis, we identified a core group of genes modulated in response to MEOX2 knock-down. Among these genes, the repressed ones are largely enriched in genes involved in the hypoxic response and glycolytic pathway, two strictly related pathways that contribute to the resistance of high-grade gliomas to therapies. An in silico study of the regulatory regions of genes differentially expressed by MEOX2 knock-down revealed that they mainly consisted of GC-rich regions enriched for Sp1 and Klf4 binding motifs, two main regulators of metabolism in glioblastoma. Our results show, for the first time, the involvement of MEOX2 in the regulation of genes of GSC metabolism, which is essential for the survival and growth of these cells.
Collapse
|
13
|
Kabir F, Apu MNH. Multi-omics analysis predicts fibronectin 1 as a prognostic biomarker in glioblastoma multiforme. Genomics 2022; 114:110378. [PMID: 35513291 DOI: 10.1016/j.ygeno.2022.110378] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 03/21/2022] [Accepted: 04/27/2022] [Indexed: 01/14/2023]
Abstract
Glioblastoma (GBM) is one of the most malignant and intractable central nervous system tumors with high recurrence, low survival rate, and poor prognosis. Despite the advances of aggressive, multimodal treatment, a successful treatment strategy is still elusive, often leading to therapeutic resistance and fatality. Thus, it is imperative to search for and identify novel markers critically associated with GBM pathogenesis to improve the existing trend of diagnosis, prognosis, and treatment. Seven publicly available GEO microarray datasets containing 409 GBM samples were integrated and further data mining was conducted using several bioinformatics tools. A total of 209 differentially expressed genes (DEGs) were identified in the GBM tissue samples compared to the normal brains. Gene Ontology (GO) enrichment analysis of the DEGs revealed association of the upregulates genes with extracellular matrix (ECM), conceivably contributing to the invasive nature of GBM while downregulated DEGs were found to be predominantly related to neuronal processes and structures. Alongside, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathway analyses described the involvement of the DEGs with various crucial contributing pathways (PI3K-Akt signaling pathway, p53 signaling pathway, insulin secretion, etc.) in GBM progression and pathogenesis. Protein-protein interaction (PPI) network containing 879 nodes and 1237 edges revealed 3 significant modules and consecutive KEGG pathway analysis of these modules showed a significant connection to gliomagenesis. Later, 10 hub genes were screened out based on degree and their expressions were externally validated. Surprisingly, only fibronectin 1 (FN1) high expression appeared to be related to poor prognosis. Subsequently, 109 transcription factors and 211 miRNAs were detected to be involved with the hub genes where FN1 demonstrated the highest number of interactions. Considering its high connectivity and potential prognostic value FN1 could be a novel biomarker providing new insights into the prognosis and treatment for GBM, although experimental validation is required.
Collapse
Affiliation(s)
- Farzana Kabir
- Department of Clinical Pharmacy and Pharmacology, Faculty of Pharmacy, University of Dhaka, Dhaka 1000, Bangladesh
| | - Mohd Nazmul Hasan Apu
- Department of Clinical Pharmacy and Pharmacology, Faculty of Pharmacy, University of Dhaka, Dhaka 1000, Bangladesh.
| |
Collapse
|
14
|
Li X, Dai Z, Wu X, Zhang N, Zhang H, Wang Z, Zhang X, Liang X, Luo P, Zhang J, Liu Z, Zhou Y, Cheng Q, Chang R. The Comprehensive Analysis Identified an Autophagy Signature for the Prognosis and the Immunotherapy Efficiency Prediction in Lung Adenocarcinoma. Front Immunol 2022; 13:749241. [PMID: 35529878 PMCID: PMC9072793 DOI: 10.3389/fimmu.2022.749241] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 03/09/2022] [Indexed: 12/30/2022] Open
Abstract
Background Lung adenocarcinoma (LUAD) is a fatal malignancy in the world. Growing evidence demonstrated that autophagy-related genes regulated the immune cell infiltration and correlated with the prognosis of LUAD. However, the autophagy-based signature that can predict the prognosis and the efficiency of checkpoint immunotherapy in LUAD patients is yet to be discovered. Methods We used conventional autophagy-related genes to screen candidates for signature construction in TCGA cohort and 9 GEO datasets (tumor samples, n=2181; normal samples, n=419). An autophagy-based signature was constructed, its correlation with the prognosis and the immune infiltration of LUAD patients was explored. The prognostic value of the autophagy-based signature was validated in an independent cohort with 70 LUAD patients. Single-cell sequencing data was used to further characterize the various immunological patterns in tumors with different signature levels. Moreover, the predictive value of autophagy-based signature in PD-1 immunotherapy was explored in the IMvigor210 dataset. At last, the protective role of DRAM1 in LUAD was validated by in vitro experiments. Results After screening autophagy-related gene candidates, a signature composed by CCR2, ITGB1, and DRAM1 was established with the ATscore in each sample. Further analyses showed that the ATscore was significantly associated with immune cell infiltration and low ATscore indicated poor prognosis. Meanwhile, the prognostic value of ATscore was validated in our independent LUAD cohort. GSEA analyses and single-cell sequencing analyses revealed that ATscore was associated with the immunological status of LUAD tumors, and ATscore could predict the efficacy of PD-1 immunotherapy. Moreover, in vitro experiments demonstrated that the inhibition of DRAM1 suppressed the proliferation and migration capacity of LUAD cells. Conclusion Our study identified a new autophagy-based signature that can predict the prognosis of LUAD patients, and this ATscore has potential applicative value in the checkpoint therapy efficiency prediction.
Collapse
Affiliation(s)
- Xizhe Li
- Department of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, China
- Hunan Engineering Research Center for Pulmonary Nodules Precise Diagnosis & Treatment, Changsha, China
| | - Ziyu Dai
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Changsha, China
| | - Xianning Wu
- Department of Thoracic Surgery, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Nan Zhang
- One-third Lab, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Hao Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Changsha, China
| | - Zeyu Wang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Changsha, China
| | - Xun Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Changsha, China
| | - Xisong Liang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Changsha, China
| | - Peng Luo
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Jian Zhang
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Zaoqu Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yanwu Zhou
- Department of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, China
- Hunan Engineering Research Center for Pulmonary Nodules Precise Diagnosis & Treatment, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Changsha, China
| | - Quan Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Changsha, China
| | - Ruimin Chang
- Department of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, China
- Hunan Engineering Research Center for Pulmonary Nodules Precise Diagnosis & Treatment, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Changsha, China
| |
Collapse
|
15
|
Wang J, Chen Y, Wang Q, Xu H, Wu C, Jiang Q, Wu G, Zhou H, Xiao Z, Chen Y, Zhang T, Lan Q. MEOX2-mediated regulation of Cathepsin S promotes cell proliferation and motility in glioma. Cell Death Dis 2022; 13:360. [PMID: 35436995 PMCID: PMC9016080 DOI: 10.1038/s41419-022-04845-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 04/01/2022] [Accepted: 04/06/2022] [Indexed: 11/30/2022]
Abstract
Nuclear transcription factor Mesenchyme Homeobox 2 (MEOX2) is a homeobox gene that is originally discovered to suppress the growth of vascular smooth muscle and endothelial cells. However, whether or not it is connected to cancer is yet unknown. Here, we report that MEOX2 functions as a tumor-initiating element in glioma. Bioinformatic analyses of public databases and investigation of MEOX2 expression in patients with glioma demonstrated that MEOX2 was abundant at both mRNA and protein levels in glioma. MEOX2 expression was shown to be inversely linked with the prognosis of glioma patients. MEOX2 inhibition changed the morphology of glioma cells, inhibited cell proliferation and motility, whereas had no effect on cell apoptosis. Besides, silencing MEOX2 also hampered the epithelial-mesenchymal transition (EMT), focal adhesion formation, and F-actin assembly. Overexpression of MEOX2 exhibited opposite effects. Importantly, RNA-sequencing, ChIP-qPCR assay, and luciferase reporter assay revealed Cathepsin S (CTSS) as a novel transcriptional target of MEOX2 in glioma cells. Consistently, MEOX2 causes glioma tumor development in mice and greatly lowers the survival period of tumor-bearing mice. Our findings indicate that MEOX2 promotes tumorigenesis and progression of glioma partially through the regulation of CTSS. Targeting MEOX2-CTSS axis might be a promising alternative for the treatment of glioma.
Collapse
|
16
|
Peng J, Liang Q, Xu Z, Cai Y, Peng B, Li J, Zhang W, Kang F, Hong Q, Yan Y, Zhang M. Current Understanding of Exosomal MicroRNAs in Glioma Immune Regulation and Therapeutic Responses. Front Immunol 2022; 12:813747. [PMID: 35095909 PMCID: PMC8796999 DOI: 10.3389/fimmu.2021.813747] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 12/27/2021] [Indexed: 02/05/2023] Open
Abstract
Exosomes, the small extracellular vesicles, are released by multiple cell types, including tumor cells, and represent a novel avenue for intercellular communication via transferring diverse biomolecules. Recently, microRNAs (miRNAs) were demonstrated to be enclosed in exosomes and therefore was protected from degradation. Such exosomal miRNAs can be transmitted to recipient cells where they could regulate multiple cancer-associated biological processes. Accumulative evidence suggests that exosomal miRNAs serve essential roles in modifying the glioma immune microenvironment and potentially affecting the malignant behaviors and therapeutic responses. As exosomal miRNAs are detectable in almost all kinds of biofluids and correlated with clinicopathological characteristics of glioma, they might be served as promising biomarkers for gliomas. We reviewed the novel findings regarding the biological functions of exosomal miRNAs during glioma pathogenesis and immune regulation. Furthermore, we elaborated on their potential clinical applications as biomarkers in glioma diagnosis, prognosis and treatment response prediction. Finally, we summarized the accessible databases that can be employed for exosome-associated miRNAs identification and functional exploration of cancers, including glioma.
Collapse
Affiliation(s)
- Jinwu Peng
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, China.,Department of Pathology, Xiangya Changde Hospital, Changde, China
| | - Qiuju Liang
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, China
| | - Zhijie Xu
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, China.,Department of Pathology, Xiangya Changde Hospital, Changde, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Yuan Cai
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, China
| | - Bi Peng
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, China
| | - Jianbo Li
- Department of Pathology, Xiangya Changde Hospital, Changde, China
| | - Wenqin Zhang
- Department of Pathology, Xiangya Changde Hospital, Changde, China
| | - Fanhua Kang
- Department of Pathology, Xiangya Changde Hospital, Changde, China
| | - Qianhui Hong
- Department of Pathology, Xiangya Changde Hospital, Changde, China
| | - Yuanliang Yan
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Mingyu Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| |
Collapse
|
17
|
Yu Z, Du M, Lu L. A Novel 16-Genes Signature Scoring System as Prognostic Model to Evaluate Survival Risk in Patients with Glioblastoma. Biomedicines 2022; 10:biomedicines10020317. [PMID: 35203526 PMCID: PMC8869708 DOI: 10.3390/biomedicines10020317] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 01/20/2022] [Accepted: 01/21/2022] [Indexed: 12/15/2022] Open
Abstract
Previous studies have found that gene expression levels are associated with prognosis and some genes can be used to predict the survival risk of glioblastoma (GBM) patients. However, most of them just built the survival-related gene signature, and personal survival risk can be evaluated only in group. This study aimed to find the prognostic survival related genes of GBM, and construct survival risk prediction model, which can be used to evaluate survival risk by individual. We collected gene expression data and clinical information from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Cox regression analysis and LASSO-cox regression analysis were performed to get survival-related genes and establish the overall survival prediction model. The ROC curve and Kaplan Meier analysis were used to evaluate the prediction ability of the model in training set and two independent cohorts. We also analyzed the biological functions of survival-related genes by GO and KEGG enrichment analysis. We identified 99 genes associated with overall survival and selected 16 genes (IGFBP2, GPRASP1, C1R, CHRM3, CLSTN2, NELL1, SEZ6L2, NMB, ICAM5, HPCAL4, SNAP91, PCSK1N, PGBD5, INA, UCHL1 and LHX6) to establish the survival risk prediction model. Multivariate Cox regression analysis indicted that the risk score could predict overall survival independent of age and gender. ROC analyses showed that our model was more robust than four existing signatures. The sixteen genes can also be potential transcriptional biomarkers and the model can assist doctors on clinical decision-making and personalized treatment of GBM patients.
Collapse
|
18
|
Papavassiliou KA, Papavassiliou AG. Transcription factors in glioblastoma - Molecular pathogenesis and clinical implications. Biochim Biophys Acta Rev Cancer 2021; 1877:188667. [PMID: 34894431 DOI: 10.1016/j.bbcan.2021.188667] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 11/25/2021] [Accepted: 12/01/2021] [Indexed: 12/15/2022]
Abstract
Glioblastoma, also known as glioblastoma multiforme (GBM), is one of the most lethal human cancers, however, the molecular mechanisms driving GBM remain largely elusive. Recent studies have revealed that transcription factors are significantly involved in GBM biology. Transcription factors (TFs), which are proteins that bind DNA to regulate gene expression, have critical roles at focal points in signaling pathways, orchestrating many cellular processes, such as cell growth and proliferation, differentiation, apoptosis, immune responses, and metabolism. Dysregulated or mutated TFs are common in GBM, resulting in aberrant gene expression that promotes tumor initiation, progression, and resistance to conventional therapies. In the present Review, we focus on TFs that are implicated in GBM pathogenesis, highlighting their oncogenic or tumor suppressive functions and describing the molecular mechanisms underlying their effect on GBM cells. We also discuss their use as biomarkers for GBM prognosis and therapeutic response, as well as their targeting with drugs for GBM treatment. Deciphering the role of TFs in the biology of GBM will provide new insights into the pathological mechanisms and reveal novel biomarkers and therapeutic targets.
Collapse
Affiliation(s)
- Kostas A Papavassiliou
- Department of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, Athens 11527, Athens, Greece
| | - Athanasios G Papavassiliou
- Department of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, Athens 11527, Athens, Greece.
| |
Collapse
|
19
|
Zhang Y, Wang X, Cheng XK, Zong YY, He RQ, Chen G, Qin YJ. Clinical significance and effect of lncRNA BBOX1-AS1 on the proliferation and migration of lung squamous cell carcinoma. Oncol Lett 2021; 23:17. [PMID: 34820016 PMCID: PMC8607367 DOI: 10.3892/ol.2021.13135] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 10/19/2021] [Indexed: 12/25/2022] Open
Abstract
Long non-coding RNAs (lncRNAs) have a role in the occurrence and development of lung squamous cell carcinoma (LUSC). lncRNA γ-butyrobetaine hydroxylase 1 (BBOX1)-antisense 1 (AS1) may contribute to disease development. However, there are no studies on the role of BBOX1-AS1 in LUSC to date. In the present study, an in-house gene microarray analysis was performed to detect the differentially expressed lncRNAs and mRNAs between three pairs of LUSC and normal lung tissues. Only one lncRNA, BBOX1-AS1, was differentially expressed in the in-house microarray and The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and ArrayExpress databases. Reverse transcription-quantitative PCR (RT-qPCR) was then performed and the original RNA-sequencing data from the TCGA, GEO and ArrayExpress datasets were used to determine the expression and clinical value of BBOX1-AS1 in LUSC. In addition, a Cell Counting Kit-8 assay, cell cycle analysis and scratch assay were performed to explore whether BBOX1-AS1 expression affected the proliferation and migration of LUSC cells in vitro. The results of the RT-qPCR analysis and data obtained from the TCGA database, GEO datasets, in-house gene microarray and standard mean deviation analysis all supported the upregulated expression level of BBOX1-AS1 in LUSC. Furthermore, silencing of BBOX1-AS1 inhibited the proliferation and migration of LUSC cells according to in vitro assays. In addition, the cells were arrested in S-phase after knockdown of BBOX1-AS1. In conclusion, the expression level of BBOX1-AS1 was upregulated in LUSC tissues. BBOX1-AS1 may exert an oncogenic effect on LUSC by regulating various biological functions. However, additional functional experiments should be performed to verify the exact mechanism.
Collapse
Affiliation(s)
- Yu Zhang
- Department of Pathology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250000, P.R. China
| | - Xiao Wang
- Department of Orthopedics, Shandong Second Provincial General Hospital, Shandong Provincial ENT Hospital, Jinan, Shandong 250000, P.R. China
| | - Xian-Kui Cheng
- Department of Pathology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250000, P.R. China
| | - Yuan-Yuan Zong
- Department of Pathology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250000, P.R. China
| | - Rong-Quan He
- Department of Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China
| | - Gang Chen
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, P.R. China
| | - Ye-Jun Qin
- Department of Pathology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250000, P.R. China
| |
Collapse
|
20
|
Tachon G, Masliantsev K, Rivet P, Desette A, Milin S, Gueret E, Wager M, Karayan-Tapon L, Guichet PO. MEOX2 Transcription Factor Is Involved in Survival and Adhesion of Glioma Stem-like Cells. Cancers (Basel) 2021; 13:cancers13235943. [PMID: 34885053 PMCID: PMC8672280 DOI: 10.3390/cancers13235943] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 11/19/2021] [Accepted: 11/22/2021] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Glioblastoma is the most common and lethal primary brain tumor for which no curative treatment currently exists. In our previous work, we showed that MEOX2 was associated with a poor patient prognosis but its biological involvement in tumor development remains ill defined. To this purpose, the aim of our study was to investigate the role of MEOX2 in patient-derived glioblastoma cell cultures. We unraveled the MEOX2 contribution to cell viability and growth and its potential involvement in phenotype and adhesion properties of glioblastoma cells. This work paves the way toward a better understanding of the role of MEOX2 in the pathophysiology of primary brain tumors. Abstract The high expression of MEOX2 transcription factor is closely associated with poor overall survival in glioma. MEOX2 has recently been described as an interesting prognostic biomarker, especially for lower grade glioma. MEOX2 has never been studied in glioma stem-like cells (GSC), responsible for glioma recurrence. The aim of our study was to investigate the role of MEOX2 in GSC. Loss of function approach using siRNA was used to assess the impact of MEOX2 on GSC viability and stemness phenotype. MEOX2 was localized in the nucleus and its expression was heterogeneous between GSCs. MEOX2 expression depends on the methylation state of its promoter and is strongly associated with IDH mutations. MEOX2 is involved in cell proliferation and viability regulation through ERK/MAPK and PI3K/AKT pathways. MEOX2 loss of function correlated with GSC differentiation and acquisition of neuronal lineage characteristics. Besides, inhibition of MEOX2 is correlated with increased expression of CDH10 and decreased pFAK. In this study, we unraveled, for the first time, MEOX2 contribution to cell viability and proliferation through AKT/ERK pathway and its potential involvement in phenotype and adhesion properties of GSC.
Collapse
Affiliation(s)
- Gaëlle Tachon
- Université de Poitiers, CHU Poitiers, ProDiCeT, 86000 Poitiers, France; (G.T.); (K.M.); (A.D.); (M.W.)
- Laboratoire de Cancérologie Biologique, CHU Poitiers, 86000 Poitiers, France;
| | - Konstantin Masliantsev
- Université de Poitiers, CHU Poitiers, ProDiCeT, 86000 Poitiers, France; (G.T.); (K.M.); (A.D.); (M.W.)
- Laboratoire de Cancérologie Biologique, CHU Poitiers, 86000 Poitiers, France;
| | - Pierre Rivet
- Laboratoire de Cancérologie Biologique, CHU Poitiers, 86000 Poitiers, France;
| | - Amandine Desette
- Université de Poitiers, CHU Poitiers, ProDiCeT, 86000 Poitiers, France; (G.T.); (K.M.); (A.D.); (M.W.)
- Laboratoire de Cancérologie Biologique, CHU Poitiers, 86000 Poitiers, France;
| | - Serge Milin
- Service d’Anatomo-Cytopathologie, CHU Poitiers, 86000 Poitiers, France;
| | - Elise Gueret
- Université Montpellier, CNRS, INSERM, 34094 Montpellier, France;
- Montpellier GenomiX, France Génomique, 34095 Montpellier, France
| | - Michel Wager
- Université de Poitiers, CHU Poitiers, ProDiCeT, 86000 Poitiers, France; (G.T.); (K.M.); (A.D.); (M.W.)
- Service de Neurochirurgie, CHU Poitiers, 86000 Poitiers, France
| | - Lucie Karayan-Tapon
- Université de Poitiers, CHU Poitiers, ProDiCeT, 86000 Poitiers, France; (G.T.); (K.M.); (A.D.); (M.W.)
- Laboratoire de Cancérologie Biologique, CHU Poitiers, 86000 Poitiers, France;
- Correspondence: (L.K.-T.); (P.-O.G.)
| | - Pierre-Olivier Guichet
- Université de Poitiers, CHU Poitiers, ProDiCeT, 86000 Poitiers, France; (G.T.); (K.M.); (A.D.); (M.W.)
- Laboratoire de Cancérologie Biologique, CHU Poitiers, 86000 Poitiers, France;
- Correspondence: (L.K.-T.); (P.-O.G.)
| |
Collapse
|
21
|
m5C-Related Signatures for Predicting Prognosis in Cutaneous Melanoma with Machine Learning. JOURNAL OF ONCOLOGY 2021; 2021:6173206. [PMID: 34394351 PMCID: PMC8360728 DOI: 10.1155/2021/6173206] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 07/28/2021] [Indexed: 12/21/2022]
Abstract
Background Cutaneous melanoma (CM) is one of the most life-threatening primary skin cancers and is prone to distant metastases. A widespread presence of posttranscriptional modification of RNA, 5-methylcytosine (m5C), has been observed in human cancers. However, the potential mechanism of the tumorigenesis and prognosis in CM by dysregulated m5C-related regulators is obscure. Methods We use comprehensive bioinformatics analyses to explore the expression of m5C regulators in CM, the prognostic implications of the m5C regulators, the frequency of the copy number variant (CNV), and somatic mutations in m5C regulators. Additionally, the CM patients were divided into three clusters for better predicting clinical features and outcomes via consensus clustering of m5C regulators. Then, the risk score was established via Lasso Cox regression analysis. Next, the prognosis value and clinical characteristics of m5C-related signatures were further explored. Then, machine learning was used to recognize the outstanding m5C regulators to risk score. Finally, the expression level and clinical value of USUN6 were analyzed via the tissue microarray (TMA) cohort. Results We found that m5C regulators were dysregulated in CM, with a high frequency of somatic mutations and CNV alterations of the m5C regulatory gene in CM. Furthermore, 16 m5C-related proteins interacted with each other frequently, and we divided CM patients into three clusters to better predicting clinical features and outcomes. Then, five m5C regulators were selected as a risk score based on the LASSO model. The XGBoost algorithm recognized that NOP2 and NSUN6 were the most significant risk score contributors. Immunohistochemistry has verified that low expression of USUN6 was closely correlated with CM progression. Conclusion The m5C-related signatures can be used as new prognostic biomarkers and therapeutic targets for CM, and NSUN6 might play a vital role in tumorigenesis and malignant progression.
Collapse
|
22
|
Promoting Prognostic Model Application: A Review Based on Gliomas. JOURNAL OF ONCOLOGY 2021; 2021:7840007. [PMID: 34394352 PMCID: PMC8356003 DOI: 10.1155/2021/7840007] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 07/03/2021] [Indexed: 12/13/2022]
Abstract
Malignant neoplasms are characterized by poor therapeutic efficacy, high recurrence rate, and extensive metastasis, leading to short survival. Previous methods for grouping prognostic risks are based on anatomic, clinical, and pathological features that exhibit lower distinguishing capability compared with genetic signatures. The update of sequencing techniques and machine learning promotes the genetic panels-based prognostic model development, especially the RNA-panel models. Gliomas harbor the most malignant features and the poorest survival among all tumors. Currently, numerous glioma prognostic models have been reported. We systematically reviewed all 138 machine-learning-based genetic models and proposed novel criteria in assessing their quality. Besides, the biological and clinical significance of some highly overlapped glioma markers in these models were discussed. This study screened out markers with strong prognostic potential and 27 models presenting high quality. Conclusively, we comprehensively reviewed 138 prognostic models combined with glioma genetic panels and presented novel criteria for the development and assessment of clinically important prognostic models. This will guide the genetic models in cancers from laboratory-based research studies to clinical applications and improve glioma patient prognostic management.
Collapse
|
23
|
Abstract
Malignant neoplasms are characterized by poor therapeutic efficacy, high recurrence rate, and extensive metastasis, leading to short survival. Previous methods for grouping prognostic risks are based on anatomic, clinical, and pathological features that exhibit lower distinguishing capability compared with genetic signatures. The update of sequencing techniques and machine learning promotes the genetic panels-based prognostic model development, especially the RNA-panel models. Gliomas harbor the most malignant features and the poorest survival among all tumors. Currently, numerous glioma prognostic models have been reported. We systematically reviewed all 138 machine-learning-based genetic models and proposed novel criteria in assessing their quality. Besides, the biological and clinical significance of some highly overlapped glioma markers in these models were discussed. This study screened out markers with strong prognostic potential and 27 models presenting high quality. Conclusively, we comprehensively reviewed 138 prognostic models combined with glioma genetic panels and presented novel criteria for the development and assessment of clinically important prognostic models. This will guide the genetic models in cancers from laboratory-based research studies to clinical applications and improve glioma patient prognostic management.
Collapse
|
24
|
Pérez RF, Tejedor JR, Santamarina-Ojeda P, Martínez VL, Urdinguio RG, Villamañán L, Candiota AP, Sarró NMV, Barradas M, Fernandez-Marcos PJ, Serrano M, Fernández AF, Fraga MF. Conservation of Aging and Cancer Epigenetic Signatures across Human and Mouse. Mol Biol Evol 2021; 38:3415-3435. [PMID: 33871658 PMCID: PMC8321527 DOI: 10.1093/molbev/msab112] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Aging and cancer are two interrelated processes, with aging being a major risk factor for the development of cancer. Parallel epigenetic alterations have been described for both, although differences, especially within the DNA hypomethylation scenario, have also been recently reported. Although many of these observations arise from the use of mouse models, there is a lack of systematic comparisons of human and mouse epigenetic patterns in the context of disease. However, such comparisons are significant as they allow to establish the extent to which some of the observed similarities or differences arise from pre-existing species-specific epigenetic traits. Here, we have used reduced representation bisulfite sequencing to profile the brain methylomes of young and old, tumoral and nontumoral brain samples from human and mouse. We first characterized the baseline epigenomic patterns of the species and subsequently focused on the DNA methylation alterations associated with cancer and aging. Next, we described the functional genomic and epigenomic context associated with the alterations, and finally, we integrated our data to study interspecies DNA methylation levels at orthologous CpG sites. Globally, we found considerable differences between the characteristics of DNA methylation alterations in cancer and aging in both species. Moreover, we describe robust evidence for the conservation of the specific cancer and aging epigenomic signatures in human and mouse. Our observations point toward the preservation of the functional consequences of these alterations at multiple levels of genomic regulation. Finally, our analyses reveal a role for the genomic context in explaining disease- and species-specific epigenetic traits.
Collapse
Affiliation(s)
- Raúl F Pérez
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain.,Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain.,Health Research Institute of Asturias (ISPA), University of Oviedo, Oviedo, Spain.,Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain.,Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII), Madrid, Spain
| | - Juan Ramón Tejedor
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain.,Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain.,Health Research Institute of Asturias (ISPA), University of Oviedo, Oviedo, Spain.,Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain.,Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII), Madrid, Spain
| | - Pablo Santamarina-Ojeda
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain.,Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain.,Health Research Institute of Asturias (ISPA), University of Oviedo, Oviedo, Spain.,Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain.,Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII), Madrid, Spain
| | - Virginia López Martínez
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain.,Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain.,Health Research Institute of Asturias (ISPA), University of Oviedo, Oviedo, Spain.,Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain.,Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII), Madrid, Spain
| | - Rocío G Urdinguio
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain.,Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain.,Health Research Institute of Asturias (ISPA), University of Oviedo, Oviedo, Spain.,Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain.,Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII), Madrid, Spain
| | - Lucía Villamañán
- Unitat de Bioquímica de Biociències, Departament de Bioquímica i Biologia Molecular, Edifici Cs, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
| | - Ana Paula Candiota
- Unitat de Bioquímica de Biociències, Departament de Bioquímica i Biologia Molecular, Edifici Cs, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - N Mí Vidal Sarró
- Servicio Anatomía Patológica, Hospital Universitari de Bellvitge-IDIBELL, Hospitalet de Llobregat, Spain
| | - Marta Barradas
- Metabolic Syndrome Group-BIOPROMET, Madrid Institute for Advanced Studies-IMDEA Food, CEI UAM+CSIC, Madrid, Spain
| | - Pablo Jose Fernandez-Marcos
- Metabolic Syndrome Group-BIOPROMET, Madrid Institute for Advanced Studies-IMDEA Food, CEI UAM+CSIC, Madrid, Spain
| | - Manuel Serrano
- Tumour Suppression Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.,Cellular Plasticity and Disease Group, Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.,Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Agusín F Fernández
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain.,Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain.,Health Research Institute of Asturias (ISPA), University of Oviedo, Oviedo, Spain.,Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain.,Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII), Madrid, Spain
| | - Mario F Fraga
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain.,Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain.,Health Research Institute of Asturias (ISPA), University of Oviedo, Oviedo, Spain.,Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain.,Rare Diseases CIBER (CIBERER) of the Carlos III Health Institute (ISCIII), Madrid, Spain
| |
Collapse
|
25
|
Identification and Analysis of Three Hub Prognostic Genes Related to Osteosarcoma Metastasis. JOURNAL OF ONCOLOGY 2021; 2021:6646459. [PMID: 33564309 PMCID: PMC7867449 DOI: 10.1155/2021/6646459] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 12/24/2020] [Accepted: 01/09/2021] [Indexed: 12/15/2022]
Abstract
Osteosarcoma (OS) often occurs in children and often undergoes metastasis, resulting in lower survival rates. Information on the complexity and pathogenic mechanism of OS is limited, and thus, the development of treatments involving alternative molecular and genetic targets is hampered. We categorized transcriptome data into metastasis and nonmetastasis groups, and 400 differential RNAs (230 messenger RNAs (mRNAs) and 170 long noncoding RNAs (lncRNAs)) were obtained by the edgeR package. Prognostic genes were identified by performing univariate Cox regression analysis and the Kaplan-Meier (KM) survival analysis. We then examined the correlation between the expression level of prognostic lncRNAs and mRNAs. Furthermore, microRNAs (miRNAs) corresponding to the coexpression of lncRNA-mRNA was predicted, which was used to construct a competitive endogenous RNA (ceRNA) regulatory network. Finally, multivariate Cox proportional risk regression analysis was used to identify hub prognostic genes. Three hub prognostic genes (ABCG8, LOXL4, and PDE1B) were identified as potential prognostic biomarkers and therapeutic targets for OS. Furthermore, transcriptions factors (TFs) (DBP, ESX1, FOS, FOXI1, MEF2C, NFE2, and OTX2) and lncRNAs (RP11-357H14.16, RP11-284N8.3, and RP11-629G13.1) that were able to affect the expression levels of genes before and after transcription were found to regulate the prognostic hub genes. In addition, we identified drugs related to the prognostic hub genes, which may have potential clinical applications. Immunohistochemistry (IHC) and quantitative real-time polymerase chain reaction (qRT-PCR) confirmed that the expression levels of ABCG8, LOXL4, and PDE1B coincided with the results of bioinformatics analysis. Moreover, the relationship between the hub prognostic gene expression and patient prognosis was also validated. Our study elucidated the roles of three novel prognostic biomarkers in the pathogenesis of OS as well as presenting a potential clinical treatment for OS.
Collapse
|
26
|
Liu J, Zhang SQ, Chen J, Li ZB, Chen JX, Lu QQ, Han YS, Dai W, Xie C, Li JC. Identifying Prognostic Significance of RCL1 and Four-Gene Signature as Novel Potential Biomarkers in HCC Patients. JOURNAL OF ONCOLOGY 2021; 2021:5574150. [PMID: 34257652 PMCID: PMC8260302 DOI: 10.1155/2021/5574150] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 06/05/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is a highly malignant disease, and it is characterized by rapid progression and low five-year survival rate. At present, there are no effective methods for monitoring the treatment and prognosis of HCC. METHODS The transcriptome and gene expression profiles of HCC were obtained from the Cancer Genome Atlas (TCGA) program, International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. The random forest method was applied to construct a four-gene prognostic model based on RNA terminal phosphate cyclase like 1 (RCL1) expression. The Kaplan-Meier method was performed to evaluate the prognostic value of RCL1, long noncoding RNAs (AC079061, AL354872, and LINC01093), and four-gene signature (SPP1, MYBL2, TRNP1, and FTCD). We examined the relationship between RCL1 expression and immune cells infiltration, tumor mutation burden (TMB), and microsatellite instability (MSI). RESULTS The results of multiple databases indicated that the aberrant expression of RCL1 was associated with clinical outcome, immune cells infiltration, TMB, and MSI in HCC patients. Meanwhile, we found that long noncoding RNAs (AC079061, AL354872, and LINC01093) and RCL1 were significantly coexpressed in HCC patients. We also confirmed that the four-gene signature was an independent prognostic factor for HCC patients. Ferroptosis potential index, immune checkpoint molecules, and clinical feature were found to have obvious correlations with risk score. The area under the receiver operating characteristic curve values for the model were 0.7-0.8 in the training set and the validation set, suggesting high robustness of the four-gene signature. We then built a nomogram for facilitating the use in clinical practice. CONCLUSION Our study demonstrated that RCL1 and a novel four-gene signature can be used as prognostic biomarkers for predicting clinical outcome in HCC patients; and this model may assist in individualized treatment monitoring of HCC patients in clinical practice.
Collapse
Affiliation(s)
- Jun Liu
- Medical Research Center, The Affiliated Yue Bei People's Hospital, Shantou University Medical College, Shaoguan 512025, China
| | - Shan-Qiang Zhang
- Medical Research Center, The Affiliated Yue Bei People's Hospital, Shantou University Medical College, Shaoguan 512025, China
| | - Jing Chen
- Institute of Cell Biology, Zhejiang University, Hangzhou 310058, China
| | - Zhi-Bin Li
- Institute of Cell Biology, Zhejiang University, Hangzhou 310058, China
| | - Jia-Xi Chen
- Institute of Cell Biology, Zhejiang University, Hangzhou 310058, China
| | - Qi-Qi Lu
- Medical Research Center, The Affiliated Yue Bei People's Hospital, Shantou University Medical College, Shaoguan 512025, China
| | - Yu-Shuai Han
- Institute of Cell Biology, Zhejiang University, Hangzhou 310058, China
| | - Wenjie Dai
- Medical Research Center, The Affiliated Yue Bei People's Hospital, Shantou University Medical College, Shaoguan 512025, China
| | - Chongwei Xie
- Medical Research Center, The Affiliated Yue Bei People's Hospital, Shantou University Medical College, Shaoguan 512025, China
| | - Ji-Cheng Li
- Medical Research Center, The Affiliated Yue Bei People's Hospital, Shantou University Medical College, Shaoguan 512025, China
- Institute of Cell Biology, Zhejiang University, Hangzhou 310058, China
| |
Collapse
|
27
|
Wang X, Gao M, Ye J, Jiang Q, Yang Q, Zhang C, Wang S, Zhang J, Wang L, Wu J, Zhan H, Hou X, Han D, Zhao S. An Immune Gene-Related Five-lncRNA Signature for to Predict Glioma Prognosis. Front Genet 2020; 11:612037. [PMID: 33391355 PMCID: PMC7772413 DOI: 10.3389/fgene.2020.612037] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 11/09/2020] [Indexed: 12/19/2022] Open
Abstract
Background The tumor immune microenvironment is closely related to the malignant progression and treatment resistance of glioma. Long non-coding RNA (lncRNA) plays a regulatory role in this process. We investigated the pathological mechanisms within the glioma microenvironment and potential immunotherapy resistance related to lncRNAs. Method We downloaded datasets derived from glioma patients and analyzed them by hierarchical clustering. Next, we analyzed the immune microenvironment of glioma, related gene expression, and patient survival. Coexpressed lncRNAs were analyzed to generate a model of lncRNAs and immune-related genes. We analyzed the model using survival and Cox regression. Then, univariate, multivariate, receiver operating characteristic (ROC), and principle component analysis (PCA) methods were used to verify the accuracy of the model. Finally, GSEA was used to evaluate which functions and pathways were associated with the differential genes. Results Normal brain tissue maintains a low-medium immune state, and gliomas are clearly divided into three groups (low to high immunity). The stromal, immune, and estimate scores increased along with immunity, while tumor purity decreased. Further, human leukocyte antigen (HLA), programmed cell death-1 (PDL1), T cell immunoglobulin and mucin domain 3 (TIM-3), B7-H3, and cytotoxic T lymphocyte-associated antigen-4 (CTLA4) expression increases concomitantly with immune state, and the patient prognosis worsens. Five immune gene-related lncRNAs (AP001007.1, LBX-AS1, MIR155HG, MAPT-AS1, and LINC00515) were screened to construct risk models. We found that risk scores are related to patient prognosis and clinical characteristics, and are positively correlated with PDL1, TIM-3, and B7-H3 expression. These lncRNAs may regulate the tumor immune microenvironment through cytokine-cytokine receptor interactions, complement, and coagulation cascades, and may promote CD8 + T cell, regulatory T cell, M1 macrophage, and infiltrating neutrophils activity in the high-immunity group. In vitro, the abnormal expression of immune-related lncRNAs and the relationship between risk scores and immune-related indicators (PDL1, CTLA4, CD3, CD8, iNOS) were verified by q-PCR and immunohistochemistry (IHC). Conclusion For the first time, we constructed immune gene-related lncRNA risk models. The risk score may be a new biomarker for tumor immune subtypes and provide molecular targets for glioma immunotherapy.
Collapse
Affiliation(s)
- Xinzhuang Wang
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China
| | - Ming Gao
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China
| | - Junyi Ye
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China
| | - Qiuyi Jiang
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China
| | - Quan Yang
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China
| | - Cheng Zhang
- North Broward Preparatory School, Coconut Creek, FL, United States
| | - Shengtao Wang
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China
| | - Jian Zhang
- Department of General Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Ligang Wang
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China
| | - Jianing Wu
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China
| | - Hua Zhan
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China
| | - Xu Hou
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China
| | - Dayong Han
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China
| | - Shiguang Zhao
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,Key Colleges and Universities Laboratory of Neurosurgery in Heilongjiang Province, Harbin, China.,Institute of Neuroscience, Sino-Russian Medical Research Center, Harbin Medical University, Harbin, China.,Department of Neurosurgery, The Pinghu Hospital of Shenzhen University, Shenzhen, China
| |
Collapse
|
28
|
Hou X, Chen J, Zhang Q, Fan Y, Xiang C, Zhou G, Cao F, Yao S. Interaction network of immune-associated genes affecting the prognosis of patients with glioblastoma. Exp Ther Med 2020; 21:61. [PMID: 33365061 PMCID: PMC7716634 DOI: 10.3892/etm.2020.9493] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 10/06/2020] [Indexed: 12/18/2022] Open
Abstract
Glioblastoma multiforme (GBM) is a common malignant tumor type of the nervous system. The purpose of the present study was to establish a regulatory network of immune-associated genes affecting the prognosis of patients with GBM. The GSE4290, GSE50161 and GSE2223 datasets from the Gene Expression Omnibus database were screened to identify common differentially expressed genes (co-DEGs). A functional enrichment analysis indicated that the co-DEGs were mainly enriched in cell communication, regulation of enzyme activity, immune response, nervous system, cytokine signaling in immune system and the AKT signaling pathway. The co-DEGs accumulated in immune response were then further investigated. For this, the intersection of those co-DEGs and currently known immune-regulatory genes was obtained and a differential expression analysis of these overlapping immune-associated genes was performed. A risk model was established using immune-regulatory genes that affect the prognosis of patients with GBM. The risk score was significantly associated with the prognosis of patients with GBM and had a significant independent predictive value. The risk model had high accuracy in predicting the prognosis of patients with GBM [area under the receiver operating characteristic curve (AUC)=0.764], which was higher than that of a previously reported model of prognosis-associated biomarkers (AUC=0.667). Furthermore, an interaction network was constructed by using immune-regulatory genes and transcription factors affecting the prognosis of patients with GBM and the University of California Santa Cruz database was used to perform a preliminary analysis of the transcription factors and immune genes of interest. The interaction network of immune-regulatory genes constructed in the present study enhances the current understanding of mechanisms associated with poor prognosis of patients with GBM. The risk score model established in the present study may be used to evaluate the prognosis of patients with GBM.
Collapse
Affiliation(s)
- Xiaohong Hou
- Department of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Jialin Chen
- Department of Neonatology, The First People's Hospital of Zunyi Affiliated to Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Qiang Zhang
- Department of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Yinchun Fan
- Department of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Chengming Xiang
- Department of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Guiyin Zhou
- Department of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Fang Cao
- Department of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| | - Shengtao Yao
- Department of Cerebrovascular Disease, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China
| |
Collapse
|
29
|
Xiao K, Tan J, Yuan J, Peng G, Long W, Su J, Xiao Y, Xiao Q, Wu C, Qin C, Hu L, Liu K, Liu S, Zhou H, Ning Y, Ding X, Liu Q. Prognostic value and immune cell infiltration of hypoxic phenotype-related gene signatures in glioblastoma microenvironment. J Cell Mol Med 2020; 24:13235-13247. [PMID: 33009892 PMCID: PMC7701576 DOI: 10.1111/jcmm.15939] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 07/14/2020] [Accepted: 09/14/2020] [Indexed: 02/06/2023] Open
Abstract
Glioblastoma (GBM) is a malignant intracranial tumour with the highest proportion and lethality. It is characterized by invasiveness and heterogeneity. However, the currently available therapies are not curative. As an essential environmental cue that maintains glioma stem cells, hypoxia is considered the cause of tumour resistance to chemotherapy and radiation. Growing evidence shows that immunotherapy focusing on the tumour microenvironment is an effective treatment for GBM; however, the current clinicopathological features cannot predict the response to immunotherapy and provide accurate guidance for immunotherapy. Based on the ESTIMATE algorithm, GBM cases of The Cancer Genome Atlas (TCGA) data set were classified into high- and low-immune/stromal score groups, and a four-gene tumour environment-related model was constructed. This model exhibited good efficiency at forecasting short- and long-term prognosis and could also act as an independent prognostic biomarker. Additionally, this model and four of its genes (CLECL5A, SERPING1, CHI3L1 and C1R) were found to be associated with immune cell infiltration, and further study demonstrated that these four genes might drive the hypoxic phenotype of perinecrotic GBM, which affects hypoxia-induced glioma stemness. Therefore, these might be important candidates for immunotherapy of GBM and deserve further exploration.
Collapse
Affiliation(s)
- Kai Xiao
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, China
| | - Jun Tan
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, China.,Institute of Skull Base Surgery and Neuro-oncology at Hunan, Changsha, China
| | - Jian Yuan
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, China.,Institute of Skull Base Surgery and Neuro-oncology at Hunan, Changsha, China
| | - Gang Peng
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, China.,Institute of Skull Base Surgery and Neuro-oncology at Hunan, Changsha, China
| | - Wenyong Long
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, China.,Institute of Skull Base Surgery and Neuro-oncology at Hunan, Changsha, China
| | - Jun Su
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, China
| | - Yao Xiao
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, China
| | - Qun Xiao
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, China
| | - Changwu Wu
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, China.,Institute of Anatomy, University of Leipzig, Leipzig, Germany
| | - Chaoying Qin
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, China.,Institute of Skull Base Surgery and Neuro-oncology at Hunan, Changsha, China
| | - Lili Hu
- Medical College of Hunan Normal University, Changsha, China
| | - Kaili Liu
- State Key Laboratory of Developmental Biology of Freshwater Fish, College of Life Science, Hunan Normal University, Changsha, China
| | - Shunlian Liu
- State Key Laboratory of Developmental Biology of Freshwater Fish, College of Life Science, Hunan Normal University, Changsha, China
| | - Hao Zhou
- State Key Laboratory of Developmental Biology of Freshwater Fish, College of Life Science, Hunan Normal University, Changsha, China
| | - Yichong Ning
- State Key Laboratory of Developmental Biology of Freshwater Fish, College of Life Science, Hunan Normal University, Changsha, China
| | - Xiaofeng Ding
- State Key Laboratory of Developmental Biology of Freshwater Fish, College of Life Science, Hunan Normal University, Changsha, China
| | - Qing Liu
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha, China.,Institute of Skull Base Surgery and Neuro-oncology at Hunan, Changsha, China
| |
Collapse
|
30
|
A two-gene-based prognostic signature for pancreatic cancer. Aging (Albany NY) 2020; 12:18322-18342. [PMID: 32966237 PMCID: PMC7585105 DOI: 10.18632/aging.103698] [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: 12/10/2019] [Accepted: 06/29/2020] [Indexed: 02/06/2023]
Abstract
The purpose of this study was to identify a vital gene signature that has prognostic value for pancreatic cancer based on gene expression datasets from the Cancer Genome Atlas and Gene Expression Omnibus. A total of 34 genes were obtained by the univariate analysis, which were significantly associated with the overall survival of PC patients. After further analysis, Anillin (ANLN) and Histone H1c (HIST1H1C) were identified and considered to be the most significant prognostic genes among the 34 genes. A prognostic model based on these two genes was constructed, and successfully distinguished pancreatic cancer survival into high-risk and low-risk groups in the training set and testing set. Subsequently, independent predictive factors, including the age, margin condition and risk score, were then employed to construct the nomogram model. The area under curve for the nomogram model was 0.826 at 0.5 years and 0.726 at 1 year, and the C-index of the nomogram model was 0.664 higher than the others variables alone. These findings have indicated that high expression of ANLN and HIST1H1C predicted poor outcomes for patients with pancreatic cancer. The nomogram model based on the expression of two genes could be valuable for the guidance of clinical treatment.
Collapse
|
31
|
Prasad B, Tian Y, Li X. Large-Scale Analysis Reveals Gene Signature for Survival Prediction in Primary Glioblastoma. Mol Neurobiol 2020; 57:5235-5246. [PMID: 32875483 PMCID: PMC7541357 DOI: 10.1007/s12035-020-02088-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 08/24/2020] [Indexed: 12/22/2022]
Abstract
Glioblastoma multiforme (GBM) is the most aggressive and common primary central nervous system tumour. Despite extensive therapy, GBM patients usually have poor prognosis with a median survival of 12–15 months. Novel molecular biomarkers that can improve survival prediction and help with treatment strategies are still urgently required. Here we aimed to robustly identify a gene signature panel for improved survival prediction in primary GBM patients. We identified 2166 differentially expressed genes (DEGs) using meta-analysis of microarray datasets comprising of 955 samples (biggest primary GBM cohort for such studies as per our knowledge) and 3368 DEGs from RNA-seq dataset with 165 samples. Based on the 1443 common DEGs, using univariate Cox and least absolute shrinkage and selection operator (LASSO) with multivariate Cox regression, we identified a survival associated 4-gene signature panel including IGFBP2, PTPRN, STEAP2 and SLC39A10 and thereafter established a risk score model that performed well in survival prediction. High-risk group patients had significantly poorer survival as compared with those in the low-risk group (AUC = 0.766 for 1-year prediction). Multivariate analysis demonstrated that predictive value of the 4-gene signature panel was independent of other clinical and pathological features and hence is a potential prognostic biomarker. More importantly, we validated this signature in three independent GBM cohorts to test its generality. In conclusion, our integrated analysis using meta-analysis approach maximizes the use of the available gene expression data and robustly identified a 4-gene panel for predicting survival in primary GBM.
Collapse
Affiliation(s)
- Birbal Prasad
- National Horizons Centre, School of Health and Life Sciences, Teesside University, Darlington, DL1 1HG UK
| | - Yongji Tian
- Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070 People’s Republic of China
| | - Xinzhong Li
- National Horizons Centre, School of Health and Life Sciences, Teesside University, Darlington, DL1 1HG UK
| |
Collapse
|
32
|
Identification of Key Differentially Expressed Transcription Factors in Glioblastoma. JOURNAL OF ONCOLOGY 2020; 2020:9235101. [PMID: 32612655 PMCID: PMC7313158 DOI: 10.1155/2020/9235101] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 05/13/2020] [Accepted: 05/25/2020] [Indexed: 01/08/2023]
Abstract
Glioblastoma (GBM) is the most frequent malignant brain tumor in adults. Our study focused on uncovering differentially expressed genes (DEGs) and their methylation in order to identify novel diagnostic biomarkers and potential treatment targets. Using GBM RNA-sequencing data from The Cancer Genome Atlas (TCGA) database, DEGs between GBM samples and paracancer tissue samples were analyzed. Enrichment analysis for DEGs and transcription factors (TFs) was performed. A total of 1029 upregulated genes and 1542 downregulated genes were identified, which were associated mainly with multiple tumor-related and immune-related pathways such as cell cycle, mitogen-activated protein kinase signaling pathway, leukocyte transendothelial migration, and autoimmune thyroid disease. These DEGs were enriched for 174 TFs, and six TFs were differentially expressed and identified as key TFs in GBM: HOXA3, EN1, ZIC1, and FOXD3 were upregulated, while HLF and EGR3 were downregulated. A total of 1978 DEGs were involved in the regulatory networks of the six key differentially expressed TFs. High expression of EN1 was associated with shorter overall survival, while high expression of EGR3 was associated with shorter recurrence-free survival. The six TFs were differentially methylated in GBM samples compared with paracancer tissues. Our study identifies numerous DEGs and their associated pathways as potential contributors to GBM, particularly the TFs EN1, EGR3, HOXA3, ZIC1, FOXD3, and HLF. The differential expression of these TFs may be unlikely driven by aberrant methylation. These TFs may be useful as diagnostic markers and treatment targets in GBM, and EN1 and EGR3 may have predictive prognostic value.
Collapse
|
33
|
Mao H, Nian J, Wang Z, Li X, Huang C. KDELR2 is an unfavorable prognostic biomarker and regulates CCND1 to promote tumor progression in glioma. Pathol Res Pract 2020; 216:152996. [PMID: 32534703 DOI: 10.1016/j.prp.2020.152996] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 04/07/2020] [Accepted: 04/22/2020] [Indexed: 01/09/2023]
Abstract
BACKGROUND The KDEL receptor is a seven-transmembrane-domain protein, which plays a key role in ER quality control and in the ER stress response, KDELR2 involved in regulation of cellular functions, including cell proliferation, survival, promotes glioblastoma tumorigenesis. The aim of this study was to investigate the clinicpathological value and biological role of KDELR2 in glioma. METHODS We studied the expression of KEDLR2 and its association with the prognosis through the TCGA, CGGA, and GSE16011 database. To explore the role of KDELR2 in glioma, KDELR2 siRNA was constructed and transfected into U87 glioma cells. CCK-8, colony formation and Transwell assays were used to investigate the roles of KDELR2 on GBM cell proliferation. We further studied the effect of KDELR2 on tumorigenesis in animal model. Additionally, flow cytometry was used to monitor the changes in the cell cycle and apoptosis following transfection with KDELR2 siRNA. We applied GeneChip primeview expression array to analysis the differential gene expression profiling. Ingenuity Pathway Analysis to show that KDELR2 has a significant impact in canonical pathway in cell cycle regulation and participate in multiple pathways. And we detected the cell cycle proteins CCND1 expression by Western blot analysis. RESULTS Our results showed that KDELR2 was up-regulated in glioma tissue and cell lines. Knockdown KDELR2 was able to reduce cell viability, promote cell cycle arrest at the G1 phase, and induce apoptotic cell death. Moreover, our results suggested that KDELR2 regulated the cellular functions of U87 cells by targeting CCND1. Therefore, we demonstrated that KDELR2 is a novel biomarker in glioma. CONCLUSIONS KDELR2 is highly expressed in human glioma tissues and cell lines, a higher expression of KDELR2 is associated with a poor prognosis of glioma patients. Moreover, KDELR2 regulated the cellular functions of U87 cells by targeting CCND1. The KDELR2/CCND1 axis may provide a new therapeutic target for the treatment of glioma and deepen our understanding of glioma mechanisms.
Collapse
Affiliation(s)
- Hui Mao
- Department of Neurosurgery, First Affiliated Hospital of Jishou University, Jishou 416000, Hunan, China
| | - Jiang Nian
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Zhao Wang
- Department of Neurosurgery, First Affiliated Hospital of Jishou University, Jishou 416000, Hunan, China
| | - XueJun Li
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - ChunHai Huang
- Department of Neurosurgery, First Affiliated Hospital of Jishou University, Jishou 416000, Hunan, China.
| |
Collapse
|
34
|
Luo C, Xu S, Dai G, Xiao Z, Chen L, Liu Z. Tumor treating fields for high-grade gliomas. Biomed Pharmacother 2020; 127:110193. [PMID: 32407989 DOI: 10.1016/j.biopha.2020.110193] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 04/13/2020] [Accepted: 04/21/2020] [Indexed: 12/12/2022] Open
Abstract
High-grade gliomas (HGG) are the most common malignant intracranial tumors with poor prognosis. Current treatments have not yielded optimal remission rates; there are no standard treatments for recurrent and drug-resistant gliomas. Tumor treating fields, which was recently approved by the Food and Drug Administration (FDA), could significantly improve progression free survival and the overall survival of glioma patients. In this review, we elaborate on the mechanism of tumor treating fields in tumor cells and detail various preclinical and clinical studies on gliomas. Tumor treating fields could be a promising option for patients with malignant tumors for which there are no standard treatment plans. Moreover, we identify several potential problems for the practical application of tumor treating fields and predict future directions for further studies. Tumor treating fields may be a potential therapy with high efficacy, fewer adverse effects, and high cost-effectiveness.
Collapse
Affiliation(s)
- Chengke Luo
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China
| | - Shengchao Xu
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China
| | - Gan Dai
- Department of Microbiology, Xiangya School of Medicine, Central South University, Changsha 410008, Hunan, China
| | - Zhiqiang Xiao
- Research Center of Carcinogenesis and Targeted Therapy, Xiangya Hospital of Central South University, Changsha, Hunan, China.
| | - Ling Chen
- Department of Neurosurgery, Chinese People's Liberation Army of China (PLA) General Hospital, Medical School of Chinese PLA, Institute of Neurosurgery of Chinese PLA, Beijing, 100853, China.
| | - Zhixiong Liu
- Department of Neurosurgery, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China.
| |
Collapse
|
35
|
Pan Y, Zhang JH, Zhao L, Guo JC, Wang S, Zhao Y, Tao S, Wang H, Zhu YB. A robust two-gene signature for glioblastoma survival prediction. J Cell Biochem 2020; 121:3593-3605. [PMID: 31960992 DOI: 10.1002/jcb.29653] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 12/11/2019] [Indexed: 12/21/2022]
Abstract
Glioblastoma multiforme (GBM) is a highly malignant brain tumor. We explored the prognostic gene signature in 443 GBM samples by systematic bioinformatics analysis, using GSE16011 with microarray expression and corresponding clinical data from Gene Expression Omnibus as the training set. Meanwhile, patients from The Chinese Glioma Genome Atlas database (CGGA) were used as the test set and The Cancer Genome Atlas database (TCGA) as the validation set. Through Cox regression analysis, Kaplan-Meier analysis, t-distributed Stochastic Neighbor Embedding algorithm, clustering, and receiver operating characteristic analysis, a two-gene signature (GRIA2 and RYR3) associated with survival was selected in the GSE16011 dataset. The GRIA2-RYR3 signature divided patients into two risk groups with significantly different survival in the GSE16011 dataset (median: 0.72, 95% confidence interval [CI]: 0.64-0.98, vs median: 0.98, 95% CI: 0.65-1.61 years, logrank test P < .001), the CGGA dataset (median: 0.84, 95% CI: 0.70-1.18, vs median: 1.21, 95% CI: 0.95-2.94 years, logrank test P = .0017), and the TCGA dataset (median: 1.03, 95% CI: 0.86-1.24, vs median: 1.23, 95% CI: 1.04-1.85 years, logrank test P = .0064), validating the predictive value of the signature. And the survival predictive potency of the signature was independent from clinicopathological prognostic features in multivariable Cox analysis. We found that after transfection of U87 cells with small interfering RNA, GRIA2 and RYR3 influenced the biological behaviors of proliferation, migration, and invasion of glioblastoma cells. In conclusion, the two-gene signature was a robust prognostic model to predict GBM survival.
Collapse
Affiliation(s)
- Yuhualei Pan
- Experimental and Translational Research Center, Beijing Friendship Hospital, Affiliated to the Capital University of Medical Sciences, Beijing, China
| | - Jian-Hua Zhang
- Department of Blood Transfusion, Peking University People's Hospital, Peking university, Beijing, China
| | - Lianhe Zhao
- Key Laboratory of Intelligent Information Processing, Advanced Computer Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Jin-Cheng Guo
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Song Wang
- Experimental and Translational Research Center, Beijing Friendship Hospital, Affiliated to the Capital University of Medical Sciences, Beijing, China
| | - Yushang Zhao
- Experimental and Translational Research Center, Beijing Friendship Hospital, Affiliated to the Capital University of Medical Sciences, Beijing, China
| | - Shaoxin Tao
- Experimental and Translational Research Center, Beijing Friendship Hospital, Affiliated to the Capital University of Medical Sciences, Beijing, China
| | - Huan Wang
- Experimental and Translational Research Center, Beijing Friendship Hospital, Affiliated to the Capital University of Medical Sciences, Beijing, China
| | - Yan-Bing Zhu
- Experimental and Translational Research Center, Beijing Friendship Hospital, Affiliated to the Capital University of Medical Sciences, Beijing, China
| |
Collapse
|