51
|
Ohandjo AQ, Liu Z, Dammer EB, Dill CD, Griffen TL, Carey KM, Hinton DE, Meller R, Lillard JW. Transcriptome Network Analysis Identifies CXCL13-CXCR5 Signaling Modules in the Prostate Tumor Immune Microenvironment. Sci Rep 2019; 9:14963. [PMID: 31628349 PMCID: PMC6802083 DOI: 10.1038/s41598-019-46491-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 06/26/2019] [Indexed: 12/12/2022] Open
Abstract
The tumor immune microenvironment (TIME) consists of multiple cell types that contribute to the heterogeneity and complexity of prostate cancer (PCa). In this study, we sought to understand the gene-expression signature of patients with primary prostate tumors by investigating the co-expression profiles of patient samples and their corresponding clinical outcomes, in particular “disease-free months” and “disease reoccurrence”. We tested the hypothesis that the CXCL13-CXCR5 axis is co-expressed with factors supporting TIME and PCa progression. Gene expression counts, with clinical attributes from PCa patients, were acquired from TCGA. Profiles of PCa patients were used to identify key drivers that influence or regulate CXCL13-CXCR5 signaling. Weighted gene co-expression network analysis (WGCNA) was applied to identify co-expression patterns among CXCL13-CXCR5, associated genes, and key genetic drivers within the CXCL13-CXCR5 signaling pathway. The processing of downloaded data files began with quality checks using NOISeq, followed by WGCNA. Our results confirmed the quality of the TCGA transcriptome data, identified 12 co-expression networks, and demonstrated that CXCL13, CXCR5 and associated genes are members of signaling networks (modules) associated with G protein coupled receptor (GPCR) responsiveness, invasion/migration, immune checkpoint, and innate immunity. We also identified top canonical pathways and upstream regulators associated with CXCL13-CXCR5 expression and function.
Collapse
Affiliation(s)
- Adaugo Q Ohandjo
- Department of Microbiology, Biochemistry & Immunology, Morehouse School of Medicine, Atlanta, GA, 30310, USA
| | - Zongzhi Liu
- R & D Bioinformatics, Sema4, Stamford, CT, 06902, USA
| | - Eric B Dammer
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Courtney D Dill
- Department of Microbiology, Biochemistry & Immunology, Morehouse School of Medicine, Atlanta, GA, 30310, USA
| | - Tiara L Griffen
- Department of Microbiology, Biochemistry & Immunology, Morehouse School of Medicine, Atlanta, GA, 30310, USA
| | - Kaylin M Carey
- Department of Microbiology, Biochemistry & Immunology, Morehouse School of Medicine, Atlanta, GA, 30310, USA
| | - Denise E Hinton
- Department of Microbiology, Biochemistry & Immunology, Morehouse School of Medicine, Atlanta, GA, 30310, USA
| | - Robert Meller
- Neuroscience Institute, Morehouse School of Medicine, Atlanta, GA, 30310, USA
| | - James W Lillard
- Department of Microbiology, Biochemistry & Immunology, Morehouse School of Medicine, Atlanta, GA, 30310, USA.
| |
Collapse
|
52
|
Zhang YB, Jiang Y, Wang J, Ma J, Han S. Evaluation of core serous epithelial ovarian cancer genes as potential prognostic markers and indicators of the underlying molecular mechanisms using an integrated bioinformatics analysis. Oncol Lett 2019; 18:5508-5522. [PMID: 31612059 PMCID: PMC6781641 DOI: 10.3892/ol.2019.10884] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2019] [Accepted: 08/23/2019] [Indexed: 12/31/2022] Open
Abstract
Ovarian cancer is a major cause of mortality in women. However, the molecular events underlying the pathogenesis of the disease are yet to be fully elucidated. In the present study, an integrated bioinformatics analysis was performed to identify core genes involved in serous epithelial ovarian cancer. A total of three expression datasets were downloaded from the Gene Expression Omnibus database, and included 46 serous epithelial ovarian cancer and 30 ovarian surface epithelium samples. The three datasets were merged, and batch normalization was performed. The normalized merged data were subsequently analyzed for differentially expressed genes (DEGs). In total, 2,212 DEGs were identified, including 1,300 upregulated and 912 downregulated genes. Gene Ontology analysis revealed that these DEGs were primarily involved in ‘regulation of cell cycle’, ‘mitosis’, ‘DNA packaging’ and ‘nucleosome assembly’. The main cellular components included ‘extracellular region part’, ‘chromosome’, ‘extracellular matrix’ and ‘condensed chromosome kinetochore’, whereas the molecular functions included ‘Calcium ion binding’, ‘polysaccharide binding’, ‘enzyme inhibitor activity’, ‘growth factor activity’, ‘cyclin-dependent protein kinase regulator activity’, ‘microtubule motor activity’ and ‘Wnt receptor activity’. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that these DEGs were predominantly involved in ‘Wnt signaling pathway’, ‘pathways in cancer’, ‘PI3K-Akt signaling pathway’, ‘cell cycle’, ‘ECM-receptor interaction’, ‘p53 signaling pathway’ and ‘focal adhesion’. The 20 most significant DEGs were identified from the protein-protein interaction network, and Oncomine analysis of these core genes revealed that 13 were upregulated and two were downregulated in serous epithelial ovarian cancer. Survival analysis revealed that cyclin B1, polo like kinase 1, G protein subunit γ transducin 1 and G protein subunit γ 12 are key molecules that may be involved in the prognosis of serous epithelial ovarian cancer. These core genes may provide novel treatment targets, although their roles in the carcinogenesis and prognosis of serous epithelial ovarian cancer require further study.
Collapse
Affiliation(s)
- Yu-Bo Zhang
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China
| | - Yuhan Jiang
- Department of Gynecology, The Affiliated Hospital of Jining Medical College, Jining, Shandong 272000, P.R. China
| | - Jiao Wang
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China
| | - Jing Ma
- Department of Gynecology and Obstetrics, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China
| | - Shiyu Han
- Department of Gynecology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China
| |
Collapse
|
53
|
CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 May Be Potential Therapeutic Targets for Hepatocellular Carcinoma Using Integrated Bioinformatic Analysis. BIOMED RESEARCH INTERNATIONAL 2019; 2019:1245072. [PMID: 31737652 PMCID: PMC6815605 DOI: 10.1155/2019/1245072] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 07/07/2019] [Accepted: 08/01/2019] [Indexed: 12/13/2022]
Abstract
Hepatocellular carcinoma (HCC) is a malignant tumor with high mortality. The abnormal expression of genes is significantly related to the occurrence of HCC. The aim of this study was to explore the differentially expressed genes (DEGs) of HCC and to provide bioinformatics basis for the occurrence, prevention and treatment of HCC. The DEGs of HCC and normal tissues in GSE102079, GSE121248, GSE84402 and GSE60502 were obtained using R language. The GO function analysis and KEGG pathway enrichment analysis of DEGs were carried out using the DAVID database. Then, the protein–protein interaction (PPI) network was constructed using the STRING database. Hub genes were screened using Cytoscape software and verified using the GEPIA, UALCAN, and Oncomine database. We used HPA database to exhibit the differences in protein level of hub genes and used LinkedOmics to reveal the relationship between candidate genes and tumor clinical features. Finally, we obtained transcription factor (TF) of hub genes using NetworkAnalyst online tool. A total of 591 overlapping up-regulated genes were identified. These genes were related to cell cycle, DNA replication, pyrimidine metabolism, and p53 signaling pathway. Additionally, the GEPIA database showed that the CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 were associated with the poor survival of HCC patients. UALCAN, Oncomine, and HPA databases and qRT-PCR confirmed that these genes were highly expressed in HCC tissues. LinkedOmics database indicated these genes were correlated with overall survival, pathologic stage, pathology T stage, race, and the age of onset. TF analysis showed that MYBL2, KDM5B, MYC, SOX2, and E2F4 were regulators to these nine hub genes. Overexpression of CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 in tumor tissues predicted poor survival in HCC. They may be potential therapeutic targets for HCC.
Collapse
|
54
|
Zhang L, Gao X, Zhou X, Qin Z, Wang Y, Li R, Tang M, Wang W, Zhang W. Identification of key genes and microRNAs involved in kidney Wilms tumor by integrated bioinformatics analysis. Exp Ther Med 2019; 18:2554-2564. [PMID: 31555364 PMCID: PMC6755433 DOI: 10.3892/etm.2019.7870] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Accepted: 06/27/2019] [Indexed: 12/11/2022] Open
Abstract
Wilms tumor (WT) is one of the most common types of pediatric solid tumors; however, its molecular mechanisms remain unclear. The present study aimed to identify key genes and microRNAs (miRNAs), and to predict the underlying molecular mechanisms of WT using integrated bioinformatics analysis. Original gene expression profiles were downloaded from the Gene Expression Omnibus (GEO; accession, GSE66405) and The Cancer Genome Atlas (TCGA) databases. Similarly, miRNA expression patterns were downloaded from GEO (accession, GSE57370) and TCGA. R version 3.5.0 software was used to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) using the limma and edgeR packages. Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses were performed to examine the biological functions of the DEGs. Additionally, a protein-protein interaction (PPI) network was constructed to screen hub gene modules using Cytoscape software. By predicting target genes of the DEMs and integrating them with DEGs, the present study constructed a miRNA-mRNA regulatory network to predict the possible molecular mechanism of WT. Expression of hub genes was validated using the Oncomine database. A total of 613 genes and 29 miRNAs were identified to be differentially expressed in WT. By constructing a PPI network and screening hub gene modules, 5 upregulated genes, including BUB1 mitotic checkpoint serine/threonine kinase, BUB1B mitotic checkpoint serine/threonine kinase B, cell division cycle protein 45, cyclin B2 and pituitary tumor-transforming 1. These genes were identified to be associated with the cell cycle pathway, which suggested that these genes may serve important roles in WT. In addition, a miRNA-mRNA regulatory network was constructed and comprised 16 DEMs and 19 DEGs. In conclusion, key genes, miRNAs and the mRNA-miRNA regulatory network identified in the present study may improve understanding of the underlying molecular mechanisms in the occurrence and development of WT, and may aid the identification of potential biomarkers and therapeutic targets.
Collapse
Affiliation(s)
- Lei Zhang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China
| | - Xian Gao
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China
| | - Xiang Zhou
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China
| | - Zhiqiang Qin
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China
| | - Yi Wang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China
| | - Ran Li
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China
| | - Min Tang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China
| | - Wei Wang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China
| | - Wei Zhang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China
| |
Collapse
|
55
|
Chen FF, Zhang SR, Peng H, Chen YZ, Cui XB. Integrative genomics analysis of hub genes and their relationship with prognosis and signaling pathways in esophageal squamous cell carcinoma. Mol Med Rep 2019; 20:3649-3660. [PMID: 31485619 PMCID: PMC6755233 DOI: 10.3892/mmr.2019.10608] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Accepted: 07/15/2019] [Indexed: 02/06/2023] Open
Abstract
The main purpose of the present study was to recognize the integrative genomics analysis of hub genes and their relationship with prognosis and signaling pathways in esophageal squamous cell carcinoma (ESCC). The mRNA gene expression profile data of GSE38129 were downloaded from the Gene Expression Omnibus database, which included 30 ESCC and 30 normal tissue samples. The differentially expressed genes (DEGs) between ESCC and normal samples were identified using the GEO2R tool. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to identify the functions and related pathways of the genes. The protein‑protein interaction (PPI) network of these DEGs was constructed with the Search Tool for the Retrieval of Interacting Genes and visualized with a molecular complex detection plug‑in via Cytoscape. The top five important modules were selected from the PPI network. A total of 928 DEGs, including ephrin‑A1 (EFNA1), collagen type IV α1 (COL4A1), C‑X‑C chemokine receptor 2 (CXCR2), adrenoreceptor β2 (ADRB2), P2RY14, BUB1B, cyclin A2 (CCNA2), checkpoint kinase 1 (CHEK1), TTK, pituitary tumor transforming gene 1 (PTTG1) and COL5A1, including 498 upregulated genes, were mainly enriched in the 'cell cycle', 'DNA replication' and 'mitotic nuclear division', whereas 430 downregulated genes were enriched in 'oxidation‑reduction process', 'xenobiotic metabolic process' and 'cell‑cell adhesion'. The KEGG analysis revealed that 'ECM‑receptor interaction', 'cell cycle' and 'p53 signaling pathway' were the most relevant pathways. According to the degree of connectivity and adjusted P‑value, eight core genes were selected, among which those with the highest correlation were CHEK1, BUB1B, PTTG1, COL4A1 and CXCR2. Gene Expression Profiling Interactive Analysis in The Cancer Genome Atlas database for overall survival (OS) was applied among these genes and revealed that EFNA1 and COL4A1 were significantly associated with a short OS in 182 patients. Immunohistochemical results revealed that the expression of PTTG1 in esophageal carcinoma tissues was higher than that in normal tissues. Therefore, these genes may serve as crucial predictors for the prognosis of ESCC.
Collapse
Affiliation(s)
- Fang-Fang Chen
- Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832002, P.R. China
| | - Shi-Rong Zhang
- Department of Science and Education, The First Affiliated Hospital of Nanyang Medical College, Nanyang, Henan 473000, P.R. China
| | - Hao Peng
- Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832002, P.R. China
| | - Yun-Zhao Chen
- The People's Hospital of Suzhou National Hi‑Tech District, Suzhou, Jiangsu 215010, P.R. China
| | - Xiao-Bin Cui
- Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832002, P.R. China
| |
Collapse
|
56
|
Lu S, Qian J, Guo M, Gu C, Yang Y. Insights into a Crucial Role of TRIP13 in Human Cancer. Comput Struct Biotechnol J 2019; 17:854-861. [PMID: 31321001 PMCID: PMC6612527 DOI: 10.1016/j.csbj.2019.06.005] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Revised: 06/05/2019] [Accepted: 06/08/2019] [Indexed: 01/06/2023] Open
Abstract
Thyroid Hormone Receptor Interacting Protein 13 (TRIP13) plays a key role in regulating mitotic processes, including spindle assembly checkpoint and DNA repair pathways, which may account for Chromosome instability (CIN). As CIN is a predominant hallmark of cancer, TRIP13 may act as a tumor susceptibility locus. Amplification of TRIP13 has been observed in various human cancers and implicated in several aspects of malignant transformation, including cancer cell proliferation, drug resistance and tumor progression. Here, we discussed the functional significance of TRIP13 in cell progression, highlighted the recent findings on the aberrant expression in human cancers and emphasized its significance for the therapeutic potential.
Collapse
Affiliation(s)
- S Lu
- The Third Affiliated Hospital, Nanjing University of Chinese Medicine, Nanjing 210023, China.,School of Medicine and Life Sciences, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - J Qian
- School of Medicine and Life Sciences, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - M Guo
- School of Medicine and Life Sciences, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - C Gu
- The Third Affiliated Hospital, Nanjing University of Chinese Medicine, Nanjing 210023, China.,School of Medicine and Life Sciences, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Y Yang
- School of Medicine and Life Sciences, Nanjing University of Chinese Medicine, Nanjing 210023, China.,School of Holistic Integrative Medicine, Nanjing University of Chinese Medicine, 210023 0Nanjing, China
| |
Collapse
|
57
|
Cai Y, Mei J, Xiao Z, Xu B, Jiang X, Zhang Y, Zhu Y. Identification of five hub genes as monitoring biomarkers for breast cancer metastasis in silico. Hereditas 2019; 156:20. [PMID: 31285741 PMCID: PMC6588910 DOI: 10.1186/s41065-019-0096-6] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2019] [Accepted: 06/12/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Breast cancer is one of the most common endocrine cancers among females worldwide. Distant metastasis of breast cancer is causing an increasing number of breast cancer-related deaths. However, the potential mechanisms of metastasis and candidate biomarkers remain to be further explored. RESULTS The gene expression profiles of GSE102484 were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to screen for the most potent gene modules associated with the metastatic risk of breast cancer, and a total of 12 modules were identified based on the analysis. In the most significant module (R2 = 0.68), 21 network hub genes (MM > 0.90) were retained for further analyses. Next, protein-protein interaction (PPI) networks were used to further explore the biomarkers with the most interactions in gene modules. According to the PPI networks, five hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) were identified as key genes associated with breast cancer progression. Furthermore, the prognostic value and differential expression of these genes were validated based on data from The Cancer Genome Atlas (TCGA) and Kaplan-Meier (KM) Plotter. Receiver operating characteristic (ROC) curve analysis revealed that the mRNA expression levels of these five hub genes showed excellent diagnostic value for breast cancer and adjacent tissues. Moreover, these five hub genes were significantly associated with worse distant metastasis-free survival (DMFS) in the patient cohort based on KM Plotter. CONCLUSION Five hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) associated with the risk of distant metastasis were extracted for further research, which might be used as biomarkers to predict distant metastasis of breast cancer.
Collapse
Affiliation(s)
- Yun Cai
- Department of Physiology, Nanjing Medical University, Nanjing, 211166 China
- Department of Bioinformatics, Nanjing Medical University, Nanjing, 211166 China
| | - Jie Mei
- Department of Physiology, Nanjing Medical University, Nanjing, 211166 China
| | - Zhuang Xiao
- Department of Physiology, Nanjing Medical University, Nanjing, 211166 China
| | - Bujie Xu
- Department of Physiology, Nanjing Medical University, Nanjing, 211166 China
| | - Xiaozheng Jiang
- Department of Physiology, Nanjing Medical University, Nanjing, 211166 China
| | - Yongjie Zhang
- Department of Human Anatomy, Nanjing Medical University, Nanjing, 211166 China
- Key Laboratory for Aging & Diseases of Nanjing Medical University, Nanjing Medical University, Nanjing, 211166 China
| | - Yichao Zhu
- Department of Physiology, Nanjing Medical University, Nanjing, 211166 China
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166 China
| |
Collapse
|
58
|
Jin H, Huang X, Shao K, Li G, Wang J, Yang H, Hou Y. Integrated bioinformatics analysis to identify 15 hub genes in breast cancer. Oncol Lett 2019; 18:1023-1034. [PMID: 31423162 PMCID: PMC6607081 DOI: 10.3892/ol.2019.10411] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 03/07/2019] [Indexed: 02/07/2023] Open
Abstract
The aim of the present study was to identify the hub genes and provide insight into the tumorigenesis and development of breast cancer. To examine the hub genes in breast cancer, integrated bioinformatics analysis was performed. Gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database and the differentially expressed genes (DEGs) were identified using the ‘limma’ package in R. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis was used to determine the functional annotations and potential pathways of the DEGs. Subsequently, a protein-protein interaction network analysis and weighted correlation network analysis (WGCNA) were conducted to identify hub genes. To confirm the reliability of the identified hub genes, RNA gene expression profiles were obtained from The Cancer Genome Atlas (TCGA)-breast cancer database, and WGCNA was used to screen for genes that were markedly correlated with breast cancer. By combining the results from the GEO and TCGA datasets, 15 hub genes were identified to be associated with breast cancer pathophysiology. Overall survival analysis was performed to examine the association between the expression of hub genes and the overall survival time of patients with breast cancer. Higher expression of all hub genes was associated with significantly shorter overall survival in patients with breast cancer compared with patients with lower levels of expression of the respective gene.
Collapse
Affiliation(s)
- Haoxuan Jin
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong 518083, P.R. China.,BGI-Shenzhen, Shenzhen, Guangdong 518083, P.R. China.,China National GeneBank, BGI-Shenzhen, Shenzhen, Guangdong 518120, P.R. China.,James D. Watson Institute of Genome Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
| | - Xiaoyan Huang
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, Guangdong 518083, P.R. China.,BGI-Shenzhen, Shenzhen, Guangdong 518083, P.R. China.,China National GeneBank, BGI-Shenzhen, Shenzhen, Guangdong 518120, P.R. China.,James D. Watson Institute of Genome Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
| | - Kang Shao
- BGI-Shenzhen, Shenzhen, Guangdong 518083, P.R. China.,China National GeneBank, BGI-Shenzhen, Shenzhen, Guangdong 518120, P.R. China.,James D. Watson Institute of Genome Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
| | - Guibo Li
- BGI-Shenzhen, Shenzhen, Guangdong 518083, P.R. China.,China National GeneBank, BGI-Shenzhen, Shenzhen, Guangdong 518120, P.R. China.,James D. Watson Institute of Genome Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
| | - Jian Wang
- BGI-Shenzhen, Shenzhen, Guangdong 518083, P.R. China.,James D. Watson Institute of Genome Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, Guangdong 518083, P.R. China.,James D. Watson Institute of Genome Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
| | - Yong Hou
- BGI-Shenzhen, Shenzhen, Guangdong 518083, P.R. China.,China National GeneBank, BGI-Shenzhen, Shenzhen, Guangdong 518120, P.R. China.,James D. Watson Institute of Genome Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
| |
Collapse
|
59
|
Duan X, Han L, Peng D, Peng C, Xiao L, Bao Q, Peng H. Bioinformatics analysis of a long non‑coding RNA and mRNA regulation network in rats with middle cerebral artery occlusion based on RNA sequencing. Mol Med Rep 2019; 20:417-432. [PMID: 31180537 PMCID: PMC6580035 DOI: 10.3892/mmr.2019.10300] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Accepted: 03/07/2019] [Indexed: 12/24/2022] Open
Abstract
Long non‑coding RNAs (lncRNAs) have been proven to be critical gene regulators of development and disease. The main aim of the present study was to elucidate the lncRNA‑mRNA regulation network in ischemic stroke induced by middle cerebral artery occlusion (MCAO) using RNA sequencing (RNA‑seq) in rats. lncRNA expression profiles were screened in brain tissues to identify a number of differentially expressed lncRNAs (DELs) and genes (DEGs) by RNA‑seq. Reverse transcription‑quantitative polymerase chain reaction was performed to further confirm the lncRNA expression data. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to mine mRNA functions, and a lncRNA‑mRNA network was constructed. Additionally, cis‑ and trans‑regulatory gene analyses of DELs were predicted. A total of 134 DELs (fold change >2, false discovery rate <0.05) and 1,006 DEGs (fold change >2 and P<0.05) were identified. Eighteen lncRNAs were predicted to regulate heme oxygenase 1, mitotic checkpoint serine/threonine kinase B, chemokine ligand 2 and DNA Topoisomerase IIα, amongst other genes. These genes are all associated with a cellular response to inorganic substances, alkaloids, estradiol, reactive oxygen species, metal ions, oxidative stress, and are associated with metabolic pathways, chemokine signaling pathways, malaria, Parkinson's disease, the cell cycle and other GO and KEGG pathway enrichments. The present study identifies novel DELs and an lncRNA‑mRNA regulatory network that may allow for an improved understanding of the molecular mechanism of ischemic stroke induced by MCAO.
Collapse
Affiliation(s)
- Xianchun Duan
- Department of Pharmacy, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui 230031, P.R. China
| | - Lan Han
- School of Pharmacy, Anhui University of Chinese Medicine, Hefei, Anhui 230012, P.R. China
| | - Daiyin Peng
- School of Pharmacy, Anhui University of Chinese Medicine, Hefei, Anhui 230012, P.R. China
| | - Can Peng
- School of Pharmacy, Anhui University of Chinese Medicine, Hefei, Anhui 230012, P.R. China
| | - Ling Xiao
- School of Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu 211198, P.R. China
| | - Qiuyu Bao
- School of Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu 211198, P.R. China
| | - Huasheng Peng
- School of Pharmacy, Anhui University of Chinese Medicine, Hefei, Anhui 230012, P.R. China
| |
Collapse
|
60
|
Feng H, Gu ZY, Li Q, Liu QH, Yang XY, Zhang JJ. Identification of significant genes with poor prognosis in ovarian cancer via bioinformatical analysis. J Ovarian Res 2019; 12:35. [PMID: 31010415 PMCID: PMC6477749 DOI: 10.1186/s13048-019-0508-2] [Citation(s) in RCA: 96] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Accepted: 04/02/2019] [Indexed: 12/11/2022] Open
Abstract
Ovarian cancer (OC) is the highest frequent malignant gynecologic tumor with very complicated pathogenesis. The purpose of the present academic work was to identify significant genes with poor outcome and their underlying mechanisms. Gene expression profiles of GSE36668, GSE14407 and GSE18520 were available from GEO database. There are 69 OC tissues and 26 normal tissues in the three profile datasets. Differentially expressed genes (DEGs) between OC tissues and normal ovarian (OV) tissues were picked out by GEO2R tool and Venn diagram software. Next, we made use of the Database for Annotation, Visualization and Integrated Discovery (DAVID) to analyze Kyoto Encyclopedia of Gene and Genome (KEGG) pathway and gene ontology (GO). Then protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). There were total of 216 consistently expressed genes in the three datasets, including 110 up-regulated genes enriched in cell division, sister chromatid cohesion, mitotic nuclear division, regulation of cell cycle, protein localization to kinetochore, cell proliferation and Cell cycle, progesterone-mediated oocyte maturation and p53 signaling pathway, while 106 down-regulated genes enriched in palate development, blood coagulation, positive regulation of transcription from RNA polymerase II promoter, axonogenesis, receptor internalization, negative regulation of transcription from RNA polymerase II promoter and no significant signaling pathways. Of PPI network analyzed by Molecular Complex Detection (MCODE) plug-in, all 33 up-regulated genes were selected. Furthermore, for the analysis of overall survival among those genes, Kaplan–Meier analysis was implemented and 20 of 33 genes had a significantly worse prognosis. For validation in Gene Expression Profiling Interactive Analysis (GEPIA), 15 of 20 genes were discovered highly expressed in OC tissues compared to normal OV tissues. Furthermore, four genes (BUB1B, BUB1, TTK and CCNB1) were found to significantly enrich in the cell cycle pathway via re-analysis of DAVID. In conclusion, we have identified four significant up-regulated DEGs with poor prognosis in OC on the basis of integrated bioinformatical methods, which could be potential therapeutic targets for OC patients.
Collapse
Affiliation(s)
- Hao Feng
- Department of Gynecology and Obstetrics, Obstetrics and Gynecology Hospital of Fudan University, #128 Shenyang Road, Shanghai, 200090, China
| | - Zhong-Yi Gu
- Department of Gynaecology and Obstetrics, Changhai Hospital, Navy Medical University, #168 Changhai Road, Shanghai, 200433, China
| | - Qin Li
- Department of Gynaecology and Obstetrics, Changhai Hospital, Navy Medical University, #168 Changhai Road, Shanghai, 200433, China
| | - Qiong-Hua Liu
- Department of Gynaecology, Aoyang Hospital Affiliated to Jiangsu University, #279 Jingang Road, Zhangjiagang, 215600, Jiangsu, China
| | - Xiao-Yu Yang
- Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Navy Medical University, #225 Changhai Road, Shanghai, 200438, China.
| | - Jun-Jie Zhang
- Department of Gynaecology and Obstetrics, Changhai Hospital, Navy Medical University, #168 Changhai Road, Shanghai, 200433, China.
| |
Collapse
|
61
|
Overexpression of BUB1B, CCNA2, CDC20, and CDK1 in tumor tissues predicts poor survival in pancreatic ductal adenocarcinoma. Biosci Rep 2019; 39:BSR20182306. [PMID: 30765611 PMCID: PMC6390130 DOI: 10.1042/bsr20182306] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2018] [Revised: 01/29/2019] [Accepted: 02/04/2019] [Indexed: 01/28/2023] Open
Abstract
Overexpressed genes in tumors usually contributed to aggressiveness in pancreatic ductal adenocarcinoma (PDAC). Using Gene Expression Omnibus (GEO) profiles including GSE46234, GSE71989, and GSE107610, we detected overexpressed genes in tumors with R program, which were enriched by Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene ontology (GO), and Reactome pathway databases. Then, we performed a survival analysis of enriched genes based on TCGA profile. Our results revealed that high BUB1B, CCNA2, CDC20, and CDK1 expression in tumors was significantly associated with worse overall survival (OS) (Log rank P=0.00338, P=0.0447, P=0.00965, and P=0.00479, respectively), which was validated using a Kaplan–Meier plotter with a median cutoff (Log rank P=0.028, P=0.0035, P=0.039, and P=0.0033, respectively). Moreover, overexpression of BUB1B, CCNA2, CDC20, and CDK1 in tumor tissues was significantly associated with disease-free survival (DFS) in PDAC patients (Log rank P=0.00565, P=0.0357, P=0.00104, and P=0.00121, respectively). BUB1B, CCNA2, CDC20, and CDK1 were significantly overexpressed in deceased PDAC patients (all P<0.01) and in patients with recurrence/disease progression (all P<0.05). In addition, PDAC patients with neoplasms of histologic grade G3-4 had significantly higher BUB1B, CCNA2 and CDC20 levels (all P<0.05). In conclusion, the up-regulation of BUB1B, CCNA2, CDC20, CDK1, and WEE1 in tumor tissues are associated with worse OS and DFS in PDAC and is correlated with advanced tumor stage and tumor development.
Collapse
|
62
|
Zhu Z, Jin Z, Deng Y, Wei L, Yuan X, Zhang M, Sun D. Co-expression Network Analysis Identifies Four Hub Genes Associated With Prognosis in Soft Tissue Sarcoma. Front Genet 2019; 10:37. [PMID: 30778371 PMCID: PMC6369179 DOI: 10.3389/fgene.2019.00037] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 01/18/2019] [Indexed: 12/13/2022] Open
Abstract
Background: Soft tissue sarcomas (STS) are heterogeneous tumors derived from mesenchymal cells that differentiate into soft tissues. The prognosis of patients who present with an STS is influenced by the regulation of a complex gene network. Methods: Weighted gene co-expression network analysis (WGCNA) was performed to identify gene modules associated with STS (Samples = 156). Results: Among the 11 modules identified, the black and blue modules were highly correlated with STS. However, using preservation analysis, the black module demonstrated low preservation, therefore the blue module was chosen as the module of interest. Furthermore, a total of 20 network hub genes were identified in the blue module, 12 of which were also hub nodes in the protein-protein interaction network of the module genes. Following additional verification, 4 of 12 genes (RRM2, BUB1B, CENPF, and KIF20A) demonstrated poorer overall survival and disease-free survival rate in the test datasets. In addition, gene set enrichment analysis (GSEA) demonstrated that samples with a high level of blue module eigengene (ME) were enriched in cell cycle and metabolism associated signaling pathways. Conclusion: In summary, co-expression network analysis identified four hub genes associated with prognosis for STS, which may diminish the prognosis by influencing cell cycle and metabolism associated signaling pathways.
Collapse
Affiliation(s)
- Zhenhua Zhu
- Department of Orthopaedic Trauma, The First Hospital of Jilin University, Changchun, China
| | - Zheng Jin
- Department of Immunology, College of Basic Medical Sciences, Jilin University, Changchun, China
| | - Yuyou Deng
- Department of Urology, The First Hospital of Jilin University, Changchun, China
| | - Lai Wei
- College of Computer and Control Engineering, Nankai University, Tianjin, China
| | - Xiaowei Yuan
- Department of Orthopaedic Trauma, The First Hospital of Jilin University, Changchun, China
| | - Mei Zhang
- College of Chemistry, Jilin University, Changchun, China
| | - Dahui Sun
- Department of Orthopaedic Trauma, The First Hospital of Jilin University, Changchun, China
| |
Collapse
|
63
|
Song YJ, Tan J, Gao XH, Wang LX. Integrated analysis reveals key genes with prognostic value in lung adenocarcinoma. Cancer Manag Res 2018; 10:6097-6108. [PMID: 30538558 PMCID: PMC6252781 DOI: 10.2147/cmar.s168636] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Background Lung cancer is one of the most common malignant tumors. Despite advances in lung cancer therapies, prognosis of non-small-cell lung cancer is still unfavorable. The aim of this study was to identify the prognostic value of key genes in lung tumorigenesis. Methods Differentially expressed genes (DEGs) were screened out by GEO2R from three Gene Expression Omnibus cohorts. Common DEGs were selected for Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology enrichment analysis. Protein– protein interaction networks were constructed by the STRING database and visualized by Cytoscape software. Hub genes, filtered from the CytoHubba, were validated using the Gene Expression Profiling Interactive Analysis database, and their genomic alterations were identified by performing the cBioportal. Finally, overall survival analysis of hub genes was performed using Kaplan–Meier Plotter. Results From three datasets, 169 DEGs (70 upregulated and 99 downregulated) were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that upregulated DEGs were significantly enriched in cell cycle, p53 pathway, and extracellular matrix–receptor interactions; the downregulated DEGs were significantly enriched in PPAR pathway and tyrosine metabolism. The protein–protein interaction network consisted of 71 nodes and 305 edges, including 49 upregulated and 22 downregulated genes. The hub genes, including AURKB, BUB1B, KIF2C, HMMR, CENPF, and CENPU, were overexpressed compared with the normal group by Gene Expression Profiling Interactive Analysis analysis, and associated with reduced overall survival in lung cancer patients. In the genomic alterations analysis, two hotspot mutations (S2021C/F and E314K/V) were identified in Pfam protein domains. Conclusion DEGs, including AURKB, BUB1B, KIF2C, HMMR, CENPF, and CENPU, might be potential biomarkers for the prognosis and treatment of lung adenocarcinoma.
Collapse
Affiliation(s)
- Ying-Jian Song
- Department of Respiratory Medicine, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, People's Republic of China,
| | - Juan Tan
- Department of Gerontology, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, People's Republic of China
| | - Xin-Huai Gao
- Department of Respiratory Medicine, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, People's Republic of China,
| | - Li-Xin Wang
- Department of Respiratory Medicine, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, People's Republic of China,
| |
Collapse
|
64
|
Simonetti G, Bruno S, Padella A, Tenti E, Martinelli G. Aneuploidy: Cancer strength or vulnerability? Int J Cancer 2018; 144:8-25. [PMID: 29981145 PMCID: PMC6587540 DOI: 10.1002/ijc.31718] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Revised: 06/05/2018] [Accepted: 06/14/2018] [Indexed: 12/12/2022]
Abstract
Aneuploidy is a very rare and tissue‐specific event in normal conditions, occurring in a low number of brain and liver cells. Its frequency increases in age‐related disorders and is one of the hallmarks of cancer. Aneuploidy has been associated with defects in the spindle assembly checkpoint (SAC). However, the relationship between chromosome number alterations, SAC genes and tumor susceptibility remains unclear. Here, we provide a comprehensive review of SAC gene alterations at genomic and transcriptional level across human cancers and discuss the oncogenic and tumor suppressor functions of aneuploidy. SAC genes are rarely mutated but frequently overexpressed, with a negative prognostic impact on different tumor types. Both increased and decreased SAC gene expression show oncogenic potential in mice. SAC gene upregulation may drive aneuploidization and tumorigenesis through mitotic delay, coupled with additional oncogenic functions outside mitosis. The genomic background and environmental conditions influence the fate of aneuploid cells. Aneuploidy reduces cellular fitness. It induces growth and contact inhibition, mitotic and proteotoxic stress, cell senescence and production of reactive oxygen species. However, aneuploidy confers an evolutionary flexibility by favoring genome and chromosome instability (CIN), cellular adaptation, stem cell‐like properties and immune escape. These properties represent the driving force of aneuploid cancers, especially under conditions of stress and pharmacological pressure, and are currently under investigation as potential therapeutic targets. Indeed, promising results have been obtained from synthetic lethal combinations exploiting CIN, mitotic defects, and aneuploidy‐tolerating mechanisms as cancer vulnerability.
Collapse
Affiliation(s)
- Giorgia Simonetti
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna and Institute of Hematology "L. e A. Seràgnoli", Bologna, Italy
| | - Samantha Bruno
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna and Institute of Hematology "L. e A. Seràgnoli", Bologna, Italy
| | - Antonella Padella
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna and Institute of Hematology "L. e A. Seràgnoli", Bologna, Italy
| | - Elena Tenti
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna and Institute of Hematology "L. e A. Seràgnoli", Bologna, Italy
| | - Giovanni Martinelli
- Scientific Directorate, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, Italy
| |
Collapse
|
65
|
Yin X, Sun J, Zhang H, Wang S. Comprehensive analysis of multi Ewing sarcoma microarray datasets identifies several prognosis biomarkers. Mol Med Rep 2018; 18:4229-4238. [PMID: 30221671 PMCID: PMC6172382 DOI: 10.3892/mmr.2018.9432] [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: 01/16/2018] [Accepted: 07/25/2018] [Indexed: 11/27/2022] Open
Abstract
Ewing sarcoma (ES) is a common primary malignancy in children and adolescents. Progression of treatment methods hasn't contributed a lot to the imrovement of prognosis. To identify potential prognostic biomarkers, a meta-analysis pipeline of multi-gene expression datasets for ES from the Gene Expression Omnibus (GEO) was performed. Three datasets were screened and differential expression genes (DEGs) in ES samples compared with normal tissues were identified through limma package and subjected to network analysis. As a result, 1,470 DEGs were obtained which were mainly involved in biological processes associated with immune response and transcription regulation. Network analysis obtained 22 core genes with high network degree and fold change. Kaplan-Meier analysis based on ES datasets from The Cancer Genome Atlas identified five genes, including glycogen phosphorylase, muscle-associated, myocyte-specific enhancer factor 2C, tripartite motif containing 63, budding uninhibited by benzimidazoses1 and Ras GTPase-activating protein 1, whose altered expression profiles are significantly associated with survival. Changes of their expression values were further confirmed through RT-qPCR in ES cell and normal cell lines. Those genes may be considered as potential prognostic biomarkers of ES and should be helpful for its early diagnosis and treatment.
Collapse
Affiliation(s)
- Xuqing Yin
- Department of Traumatic Orthopaedics, Central Hospital of Zibo, Zibo, Shandong 255036, P.R. China
| | - Jiubo Sun
- Department of Radiation Oncology, Central Hospital of Zibo, Zibo, Shandong 255036, P.R. China
| | - Haiyang Zhang
- Department of Microinvasive Othopaedics, Central Hospital of Zibo, Zibo, Shandong 255036, P.R. China
| | - Shuai Wang
- Department of Spine Surgery, Jining No. 1 People's Hospital, Jining, Shandong 272000, P.R. China
| |
Collapse
|
66
|
Sun B, Lin G, Ji D, Li S, Chi G, Jin X. Dysfunction of Sister Chromatids Separation Promotes Progression of Hepatocellular Carcinoma According to Analysis of Gene Expression Profiling. Front Physiol 2018; 9:1019. [PMID: 30100882 PMCID: PMC6072861 DOI: 10.3389/fphys.2018.01019] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2018] [Accepted: 07/10/2018] [Indexed: 12/12/2022] Open
Abstract
Despite studying the various molecular mechanisms of hepatocellular carcinoma (HCC), effective drugs and biomarkers in HCC therapy are still scarce. The present study was designed to investigate dysregulated pathways, novel biomarkers and therapeutic targets for HCC. The gene expression dataset of GSE14520, which included 362 tumor and their paired non-tumor tissues of HCC, was extracted for processing by the Robust multi-array average (RMA) algorithm in the R environment. SAM methods were leveraged to identify differentially expressed genes (DEGs). Functional analysis of DEGs was performed using DAVID. The GeneMania and Cytohubba were used to construct the PPI network. To avoid individual bias, GSEA and survival analysis were employed to verify the results. The results of these analyses indicated that separation of sister chromatids was the most aberrant phase in the progression of HCC, and the most frequently involved genes, EZH2, GINS1, TPX2, CENPF, and BUB1B, require further study to be used as drug targets or biomarkers in diagnosis and treatment of HCC.
Collapse
Affiliation(s)
- Baozhen Sun
- Department of Hepatopancreatobiliary, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Guibo Lin
- First Department of Neurosurgery, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Degang Ji
- Department of Hepatopancreatobiliary, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Shuo Li
- Department of Hepatopancreatobiliary, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Guonan Chi
- First Department of Neurosurgery, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Xingyi Jin
- First Department of Neurosurgery, China-Japan Union Hospital of Jilin University, Changchun, China
| |
Collapse
|
67
|
Zou J, Huang RY, Jiang FN, Chen DX, Wang C, Han ZD, Liang YX, Zhong WD. Overexpression of TPX2 is associated with progression and prognosis of prostate cancer. Oncol Lett 2018; 16:2823-2832. [PMID: 30127868 PMCID: PMC6096215 DOI: 10.3892/ol.2018.9016] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Accepted: 04/06/2018] [Indexed: 12/17/2022] Open
Abstract
Targeting protein for Xenopus kinesin-like protein 2 (TPX2) activates Aurora kinase A during mitosis and targets its activity to the mitotic spindle, serving an important role in mitosis. It has been associated with different types of cancer and is considered to promote tumor growth. The aim of the present study was to explore the role of TPX2 in diagnosing prostate cancer (PCa). It was identified that TPX2 expression in PCa tissues was increased compared with benign prostate tissues. Microarray analysis demonstrated that TPX2 was positively associated with the Gleason score, tumor-node-metastasis (TNM) stage, clinicopathological stage, metastasis, overall survival and biochemical relapse-free survival. In vitro studies revealed that the high expression of TPX2 in PCa cells improved proliferative, invasive and migratory abilities, and repressed apoptosis of the PCa cells, without affecting tolerance to docetaxel. The results suggested that TPX2 serves as a tumorigenesis-promoting gene in PCa, and a potential therapeutic target for patients with PCa.
Collapse
Affiliation(s)
- Jun Zou
- Department of Emergency Surgery, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong 510150, P.R. China
| | - Rui-Yan Huang
- Department of Ultrasonography and Electrocardiograms, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong 510060, P.R. China
| | - Fu-Neng Jiang
- Department of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, The Second Affiliated Hospital of South China University of Technology, Guangzhou, Guangdong 510180, P.R. China
| | - De-Xiong Chen
- Department of Emergency Surgery, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong 510150, P.R. China
| | - Cong Wang
- Department of Clinical Pharmacy, School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang 325035, P.R. China
| | - Zhao-Dong Han
- Department of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, The Second Affiliated Hospital of South China University of Technology, Guangzhou, Guangdong 510180, P.R. China
| | - Yu-Xiang Liang
- Department of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, The Second Affiliated Hospital of South China University of Technology, Guangzhou, Guangdong 510180, P.R. China
| | - Wei-De Zhong
- Department of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, The Second Affiliated Hospital of South China University of Technology, Guangzhou, Guangdong 510180, P.R. China.,Department of Urology, Huadu District People's Hospital, Southern Medical University, Guangzhou, Guangdong 510800, P.R. China
| |
Collapse
|
68
|
Zhuang L, Yang Z, Meng Z. Upregulation of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in Tumor Tissues Predicted Worse Overall Survival and Disease-Free Survival in Hepatocellular Carcinoma Patients. BIOMED RESEARCH INTERNATIONAL 2018; 2018:7897346. [PMID: 30363964 PMCID: PMC6186344 DOI: 10.1155/2018/7897346] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2018] [Revised: 09/04/2018] [Accepted: 09/13/2018] [Indexed: 02/08/2023]
Abstract
OBJECTIVE To evaluate the association between upregulated differentially expressed genes (DEGs) and the outcomes of patients with hepatocellular carcinoma (HCC). METHODS Using Gene Expression Omnibus (GEO) datasets including GSE45436, GSE55092, GSE60502, GSE84402, and GSE17548, we detected upregulated DEGs in tumors. KEGG, GO, and Reactome enrichment analysis of the DEGs was conducted to clarify their function. The impact of the upregulated DEGs on patients' survival was analyzed based on TCGA profile. RESULTS 161 shared upregulated DEGs were identified among GSE45436, GSE55092, GSE60502, and GSE84402 profiles. Cell cycle was the shared pathway/biological process in the gene sets investigation among databases of KEGG, GO, and Reactome. After being validated in GSE17548, 13 genes including BUB1B, CCNA2, CCNB1, CCNE2, CDC20, CDC6, CDC7, CDK1, CDK4, CDKN2A, CHEK1, MAD2L1, and MCM3 in cell cycle pathway were shared in the three databases for enrichment. The expression of BUB1B, CCNB1, CDC7, CDC20, and MCM3 was upregulated in HCC tissues when compared with adjacent normal tissues in 6.67%, 7.5%, 8.06%, 5.56%, and 9.72% of HCC patients, respectively. Overexpression of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in HCC tissues accounted for poorer overall survival (OS) and disease-free survival (DFS) in HCC patients (all log rank P < 0.05). BUB1B, CCNB1, CDC7, CDC20, and MCM3 were all overexpressed in HCC patients with neoplasm histologic grade G3-4 compared to those with G1-2 (all P < 0.05). BUB1B, CCNB1, and CDC20 were significantly upregulated in HCC patients with vascular invasion (all P < 0.05). Additionally, levels of BUB1B, CCNB1, CDC7, and CDC20 were significantly higher in HCC patients deceased, recurred, or progressed (all P < 0.05). CONCLUSION Correlated with advanced histologic grade and/or vascular invasion, upregulation of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in HCC tissues predicted worse OS and DFS in HCC patients. These genes could be novel therapeutic targets for HCC treatment.
Collapse
Affiliation(s)
- Liping Zhuang
- 1Department of Integrative Oncology, Fudan University Shanghai Cancer Center and Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Zongguo Yang
- 2Department of Integrative Medicine, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China
| | - Zhiqiang Meng
- 1Department of Integrative Oncology, Fudan University Shanghai Cancer Center and Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| |
Collapse
|
69
|
Zhang Z, Zhang G, Gao Z, Li S, Li Z, Bi J, Liu X, Li Z, Kong C. Comprehensive analysis of differentially expressed genes associated with PLK1 in bladder cancer. BMC Cancer 2017; 17:861. [PMID: 29246203 PMCID: PMC5732388 DOI: 10.1186/s12885-017-3884-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Accepted: 12/07/2017] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND The significance of PLK1 (polo-like kinase 1) has become increasingly essential as both a biomarker and a target for cancer treatment. Here, we aimed to determine the downstream genes of PLK1 and their effects on the carcinogenesis and progression of bladder cancer. METHODS Specific siRNA was utilized to silence the target gene expression. The cell proliferation, invasion and migration of bladder cancer cells by MTT assay, BrdU assay and transwell assay. The differential expression genes were identified using Affymetrix HTA2.0 Array. The KEGG, GO and STRING analysis were used to analyze the signaling pathway and protein-protein interaction. Spearman analysis was used to analyze the correlation between protein and protein, between protein and clincopathologic characteristics. RESULTS PLK1 siRNA hindered the proliferation, invasion and migration of bladder cancer cells, as determined by the MTT, BrdU and transwell assays. A total of 561 differentially expressed genes were identified using an Affymetrix HTA2.0 Array in PLK1 knockdown T24 cells. According to KEGG, GO and STRING analysis, five key genes (BUB1B, CCNB1, CDC25A, FBXO5, NDC80) were determined to be involved in cell proliferation, invasion and migration. PLK1 knockdown decreased BUB1B, CCNB1, CDC25A and NDC80 expressions but increased FBXO5 expression. BUB1B, CCNB1, CDC25A and NDC80 were positively correlated with cell proliferation, invasion, migration and PLK1 expression in tissues, but FBXO5 was negatively correlated with each of those factors. The results showed that the five genes expressions were significantly correlation with the PLK1 expression in normal bladder tissues and bladder cancer tissues. Four of them (BUB1B, CCNB1, CDC25A, NDC80) were obviously positive correlations with pT stage and metastasis. But FBXO5 was negative correlated with pT stage and metastasis. Furthermore, significant correlations were found between CCNB1 or CDC25A or NDC80 and histological grade; between BUB1B or NDC80 and recurrence. CONCLUSION Five downstream genes of PLK1 were associated with the regulation of cell proliferation, invasion and migration in bladder cancer. Furthermore, these genes may play important roles in bladder cancer and become important biomarkers and targets for cancer treatment.
Collapse
Affiliation(s)
- Zhe Zhang
- Department of Urology, First Hospital of China Medical University, 155 North Nanjing Street, Heping, Shenyang, Liaoning 110001 China
- Institute of Urology, China Medical University, Shenyang, 110001 China
| | - Guojun Zhang
- Department of Hematology, Shengjing Hospital of China Medical University, 39 Huaxiang Road, Tiexi, Shenyang, Liaoning 110022 China
| | - Zhipeng Gao
- Department of Urology, First Hospital of China Medical University, 155 North Nanjing Street, Heping, Shenyang, Liaoning 110001 China
- Institute of Urology, China Medical University, Shenyang, 110001 China
| | - Shiguang Li
- Department of Urology, First Hospital of China Medical University, 155 North Nanjing Street, Heping, Shenyang, Liaoning 110001 China
- Institute of Urology, China Medical University, Shenyang, 110001 China
| | - Zeliang Li
- Department of Urology, First Hospital of China Medical University, 155 North Nanjing Street, Heping, Shenyang, Liaoning 110001 China
- Institute of Urology, China Medical University, Shenyang, 110001 China
| | - Jianbin Bi
- Department of Urology, First Hospital of China Medical University, 155 North Nanjing Street, Heping, Shenyang, Liaoning 110001 China
- Institute of Urology, China Medical University, Shenyang, 110001 China
| | - Xiankui Liu
- Department of Urology, First Hospital of China Medical University, 155 North Nanjing Street, Heping, Shenyang, Liaoning 110001 China
- Institute of Urology, China Medical University, Shenyang, 110001 China
| | - Zhenhua Li
- Department of Urology, First Hospital of China Medical University, 155 North Nanjing Street, Heping, Shenyang, Liaoning 110001 China
- Institute of Urology, China Medical University, Shenyang, 110001 China
| | - Chuize Kong
- Department of Urology, First Hospital of China Medical University, 155 North Nanjing Street, Heping, Shenyang, Liaoning 110001 China
- Institute of Urology, China Medical University, Shenyang, 110001 China
| |
Collapse
|
70
|
Ma Q, Liu Y, Shang L, Yu J, Qu Q. The FOXM1/BUB1B signaling pathway is essential for the tumorigenicity and radioresistance of glioblastoma. Oncol Rep 2017; 38:3367-3375. [PMID: 29039578 PMCID: PMC5783581 DOI: 10.3892/or.2017.6032] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2017] [Accepted: 07/18/2017] [Indexed: 12/20/2022] Open
Abstract
Accumulating evidence indicates that mitotic checkpoint serine/threonine kinase B (BUB1B) plays a critical role in multiple types of cancer. However, the biological function and molecular regulatory mechanism of BUB1B in glioblastoma (GBM) remain unclear. In the present study, we identified that BUB1B expression was enriched in GBM tumors and was functionally required for tumor proliferation both in vitro and in vivo. Clinically, BUB1B expression was associated with poor prognosis in GBM patients and BUB1B-dependent radioresistance in GBM was decreased by targeting BUB1B via shRNAs. Mechanistically, forkhead box protein M1 (FOXM1) transcriptionally regulated BUB1B expression by binding to and then activating the BUB1B promoter. Therapeutically, we found that FOXM1 inhibitor attenuated tumorigenesis and radioresistance of GBM both in vitro and in vivo. Altogether, BUB1B promotes tumor proliferation and induces radioresistance in GBM, indicating that BUB1B could be a potential therapeutic target for GBM.
Collapse
Affiliation(s)
- Qing Ma
- The Third Affiliated Hospital, Medical School of Xi'an Jiaotong University, Xi'an, Shaanxi 710068, P.R. China
| | - Yanmei Liu
- The Department of West Yard Ward 2 (Geriatrics), Shaanxi Provincial People's Hospital, Xi'an, Shaanxi 710068, P.R. China
| | - Liang Shang
- The Department of West Yard Ward 2 (Geriatrics), Shaanxi Provincial People's Hospital, Xi'an, Shaanxi 710068, P.R. China
| | - Jiao Yu
- Department of Radiotherapy, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi 710068, P.R. China
| | - Qiumin Qu
- Department of Internal Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
| |
Collapse
|