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Hasan MAM, Maniruzzaman M, Shin J. Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning. Sci Rep 2023; 13:3771. [PMID: 36882493 PMCID: PMC9992474 DOI: 10.1038/s41598-023-30851-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 03/02/2023] [Indexed: 03/09/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common lethal malignancy of the liver worldwide. Thus, it is important to dig the key genes for uncovering the molecular mechanisms and to improve diagnostic and therapeutic options for HCC. This study aimed to encompass a set of statistical and machine learning computational approaches for identifying the key candidate genes for HCC. Three microarray datasets were used in this work, which were downloaded from the Gene Expression Omnibus Database. At first, normalization and differentially expressed genes (DEGs) identification were performed using limma for each dataset. Then, support vector machine (SVM) was implemented to determine the differentially expressed discriminative genes (DEDGs) from DEGs of each dataset and select overlapping DEDGs genes among identified three sets of DEDGs. Enrichment analysis was performed on common DEDGs using DAVID. A protein-protein interaction (PPI) network was constructed using STRING and the central hub genes were identified depending on the degree, maximum neighborhood component (MNC), maximal clique centrality (MCC), centralities of closeness, and betweenness criteria using CytoHubba. Simultaneously, significant modules were selected using MCODE scores and identified their associated genes from the PPI networks. Moreover, metadata were created by listing all hub genes from previous studies and identified significant meta-hub genes whose occurrence frequency was greater than 3 among previous studies. Finally, six key candidate genes (TOP2A, CDC20, ASPM, PRC1, NUSAP1, and UBE2C) were determined by intersecting shared genes among central hub genes, hub module genes, and significant meta-hub genes. Two independent test datasets (GSE76427 and TCGA-LIHC) were utilized to validate these key candidate genes using the area under the curve. Moreover, the prognostic potential of these six key candidate genes was also evaluated on the TCGA-LIHC cohort using survival analysis.
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Affiliation(s)
- Md Al Mehedi Hasan
- School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Fukushima, 965-8580, Japan.,Department of Computer Science and Engineering, Rajshahi University of Engineering & Technology, Rajshahi, 6204, Bangladesh
| | - Md Maniruzzaman
- School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Fukushima, 965-8580, Japan.,Statistics Discipline, Khulna University, Khulna, 9208, Bangladesh
| | - Jungpil Shin
- School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Fukushima, 965-8580, Japan.
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2
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Loss of WNK1 Suppressed the Malignant Behaviors of Hepatocellular Carcinoma Cells by Promoting Autophagy and Activating AMPK Pathway. DISEASE MARKERS 2022; 2022:6831224. [PMID: 36618969 PMCID: PMC9822739 DOI: 10.1155/2022/6831224] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 12/07/2022] [Accepted: 12/08/2022] [Indexed: 01/01/2023]
Abstract
Background WNK lysine deficient protein kinase 1 (WNK1) has been shown to be highly expressed in hepatocellular carcinoma (HCC) samples and related to poor prognosis of HCC patients based on bioinformatics analysis. However, the specific function of WNK1 in HCC has not been analyzed. This study is aimed at exploring the function of WNK1 in HCC progression as well as its related molecular mechanism. Methods After knockdown of WNK1 by small interference RNA, cell counting kit-8, colony formation, western blot, Transwell, and wound healing assays were employed to evaluate the biological behaviors of HCC cells. Immunofluorescent staining was applied to detect the effect of WNK1 on LC3 II. GSK690693 or si-AMPK was applied to block AMPK pathway. The expression of autophagy and AMPK pathway related molecules was examined by western blot assay. Results WNK1 was highly expressed in HCC cell lines and loss of WNK1 inhibited HCC cell proliferation, cell cycle, migration, and invasion. Additionally, we demonstrated that loss of WNK1 promoted the autophagy and activated AMPK pathway in HCC cells. While, GSK690693 treatment or si-AMPK transfection suppressed the autophagy and promoted HCC cells proliferation. However, WNK1 knockdown counteracted the effect of GSK690693 or si-AMPK in regulating HCC cell proliferation. Finally, we demonstrated that WNK1 regulated the malignant behaviors of HCC cells by modulating autophagy and AMPK pathway. Conclusions The above results indicated that WNK1 may be a worthwhile target to be considered for therapy of HCC.
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3
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Zhang K, Yu M, Liu H, Hui Z, Yang N, Bi X, Sun L, Lin R, Lü G. Upregulated TUBG1 expression is correlated with poor prognosis in hepatocellular carcinoma. PeerJ 2022; 10:e14415. [PMID: 36523478 PMCID: PMC9745943 DOI: 10.7717/peerj.14415] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 10/28/2022] [Indexed: 12/11/2022] Open
Abstract
Background Hepatocellular carcinoma (HCC) development is a complex pathological process. Tubulin gamma 1 (TUBG1) plays an oncogenic role in several human cancers; however, its functional role in HCC tumorigenesis remains unknown. Methods Herein we first evaluated the gene expression levels of TUBG1 in HCC using data from The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis databases. We then elucidated the association between TUBG1 gene expression levels and survival rates of patients with HCC. Cell cycle, proliferation, transwell migration, and matrigel invasion assays were used to study the effects of TUBG1 on the malignant phenotypes of HCC cells. Results Based on the data obtained from the aforementioned databases and our in vitro experiments, TUBG1 was found to be overexpressed in HCC and patients with high TUBG1 expression levels showed a remarkably poor overall survival rate. In addition, the expression of TUBG1 significantly promoted the malignant phenotypes of HCC cells in vitro. Gene ontology term enrichment analysis revealed that co-regulated genes were enriched in biological processes mainly involved in chromosome segregation, chromosomal region, and chromatin binding; moreover, Kyoto Encyclopedia of Genes and Genome pathway analysis showed that they were mainly involved in cell cycle, oocyte meiosis, platinum drug resistance, and the p53 signaling pathway. Conclusions We report that TUBG1 is an important oncogene in HCC. It promotes HCC progression and may serve as a potential prognostic biomarker for HCC. Future studies are warranted to unveil molecular biological mechanisms underlying TUBG1 carcinogenesis.
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Affiliation(s)
- Kainan Zhang
- Xinjiang Medical University, Urumqi, Xinjiang, China,State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Mengsi Yu
- Department of Clinical Laboratory, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Hui Liu
- State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Zhao Hui
- Department of Clinical Laboratory, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Ning Yang
- State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Xiaojuan Bi
- State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Li Sun
- State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - RenYong Lin
- State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Guodong Lü
- State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China,College of Pharmacy, Xinjiang Medical University, Urumqi, Xinjiang, China
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4
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Safrastyan A, Wollny D. Network analysis of hepatocellular carcinoma liquid biopsies augmented by single-cell sequencing data. Front Genet 2022; 13:921195. [PMID: 36092896 PMCID: PMC9452847 DOI: 10.3389/fgene.2022.921195] [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: 04/15/2022] [Accepted: 06/30/2022] [Indexed: 11/17/2022] Open
Abstract
Liquid biopsy, the analysis of body fluids, represents a promising approach for disease diagnosis and prognosis with minimal intervention. Sequencing cell-free RNA derived from liquid biopsies has been very promising for the diagnosis of several diseases. Cancer research, in particular, has emerged as a prominent candidate since early diagnosis has been shown to be a critical determinant of disease prognosis. Although high-throughput analysis of liquid biopsies has uncovered many differentially expressed genes in the context of cancer, the functional connection between these genes is not investigated in depth. An important approach to remedy this issue is the construction of gene networks which describes the correlation patterns between different genes, thereby allowing to infer their functional organization. In this study, we aimed at characterizing extracellular transcriptome gene networks of hepatocellular carcinoma patients compared to healthy controls. Our analysis revealed a number of genes previously associated with hepatocellular carcinoma and uncovered their association network in the blood. Our study thus demonstrates the feasibility of performing gene co-expression network analysis from cell-free RNA data and its utility in studying hepatocellular carcinoma. Furthermore, we augmented cell-free RNA network analysis with single-cell RNA sequencing data which enables the contextualization of the identified network modules with cell-type specific transcriptomes from the liver.
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Affiliation(s)
- Aram Safrastyan
- RNA Bioinformatics and High Throughput Analysis, Friedrich Schiller University Jena, Jena, Germany
- Leibniz Institute on Aging-Fritz Lipmann Institute (FLI), Jena, Germany
| | - Damian Wollny
- RNA Bioinformatics and High Throughput Analysis, Friedrich Schiller University Jena, Jena, Germany
- Leibniz Institute on Aging-Fritz Lipmann Institute (FLI), Jena, Germany
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- *Correspondence: Damian Wollny,
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Dong P, Cai Z, Li B, Zhu Y, Chan AKY, Chiang MWL, Au CH, Sung WK, Cheung TT, Lo CM, Man K, Lee NP. HFE promotes mitotic cell division through recruitment of cytokinetic abscission machinery in hepatocellular carcinoma. Oncogene 2022; 41:4185-4199. [PMID: 35882980 DOI: 10.1038/s41388-022-02419-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/11/2022] [Accepted: 07/13/2022] [Indexed: 11/09/2022]
Abstract
HFE (Hemochromatosis) is a conventional iron level regulator and its loss of function due to gene mutations increases the risk of cancers including hepatocellular carcinoma (HCC). Likewise, studies focusing on HFE overexpression in cancers are all limited to linking up these events as a consequence of iron level deregulation. No study has explored any iron unrelated role of HFE in cancers. Here, we first reported HFE as an oncogene in HCC and its undescribed function on promoting abscission in cytokinesis during mitotic cell division, independent of its iron-regulating ability. Clinical analyses revealed HFE upregulation in tumors linking to large tumor size and poor prognosis. Functionally and mechanistically, HFE promoted cytokinetic abscission via facilitating ESCRT abscission machinery recruitment to the abscission site through signaling a novel HFE/ALK3/Smads/LIF/Hippo/YAP/YY1/KIF13A axis. Pharmacological blockage of HFE signaling axis impeded tumor phenotypes in vitro and in vivo. Our data on HFE-driven HCC unveiled a new mechanism utilized by cancer cells to propel rapid cell division. This study also laid the groundwork for tumor intolerable therapeutics development given the high cytokinetic dependency of cancer cells and their vulnerability to cytokinetic blockage.
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Affiliation(s)
- Pingping Dong
- Department of Surgery, The University of Hong Kong, Hong Kong, Hong Kong.,Department of Radiation Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Ziqing Cai
- Department of Surgery, The University of Hong Kong, Hong Kong, Hong Kong
| | - Bingfeng Li
- Department of Surgery, The University of Hong Kong, Hong Kong, Hong Kong
| | - Yueqin Zhu
- Department of Surgery, The University of Hong Kong, Hong Kong, Hong Kong
| | - Alice K Y Chan
- Department of Chemistry, City University of Hong Kong, Hong Kong, Hong Kong.,Po Leung Kuk Tong Nai Kan Junior Secondary College, Hong Kong, Hong Kong
| | - Michael W L Chiang
- Department of Chemistry, City University of Hong Kong, Hong Kong, Hong Kong
| | - Chun Hang Au
- Hong Kong Genome Institute, Hong Kong, Hong Kong
| | - Wing Kin Sung
- Hong Kong Genome Institute, Hong Kong, Hong Kong.,School of Computing, National University of Singapore, Singapore, Singapore.,Computational and Systems Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Tan To Cheung
- Department of Surgery, The University of Hong Kong, Hong Kong, Hong Kong
| | - Chung Mau Lo
- Department of Surgery, The University of Hong Kong, Hong Kong, Hong Kong
| | - Kwan Man
- Department of Surgery, The University of Hong Kong, Hong Kong, Hong Kong.
| | - Nikki P Lee
- Department of Surgery, The University of Hong Kong, Hong Kong, Hong Kong. .,Advanced Biomedical Instrumentation Centre, Hong Kong Science Park, Hong Kong, Hong Kong.
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6
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Guo J, Li W, Cheng L, Gao X. Identification and Validation of Hub Genes with Poor Prognosis in Hepatocellular Carcinoma by Integrated Bioinformatical Analysis. Int J Gen Med 2022; 15:3933-3941. [PMID: 35431572 PMCID: PMC9012340 DOI: 10.2147/ijgm.s353708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 04/01/2022] [Indexed: 12/24/2022] Open
Abstract
Background Hepatocellular carcinoma (HCC) is the reason for the world’s second largest cancer-related death. It is clinically valuable to study the molecular mechanisms of HCC occurrence and development for formulating more effective diagnosis and treatment strategies. Methods The five microarray data sets GSE45267, GSE101685, GSE84402, GSE62232 and GSE45267 were downloaded from Gene Expression Omnibus (GEO) database, including 165 HCC tissues and 73 normal tissues. Differential expressed genes (DEGs) between HCC tissues and normal tissues were determined by GEO2R. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and the protein–protein interaction network (PPI) network analysis were employed to identify DEGs and to evaluate the clinical significance in prognosis of HCC. Results A total of 152 genes differentially expressed in HCC tissues and normal tissues were identified. GO and KEGG functional enrichment analysis revealed that 39 up-regulated genes were mainly enriched in mitosis, cell cycle and oocyte meiosis, while those down-regulated genes (113) were concentrated in exogenous drug catabolism and the metabolism of cytochrome P450 on exogenous drugs. Totally, 19 hub genes were chosen by PPI network and module analysis and verified by The Cancer Genome Atlas (TCGA) database. Finally, 8 hub genes were selected, including CDK1, CYP2C8, CCNB1, AURKA, CYP2C9, BUB1B, MAD2L1 and TTK, which were associated with the overall survival rate of HCC patients. Conclusion This study presented eight target genes connected to the prognosis of HCC patients. Those mainly exists in cell cycle and drug catabolism, which may be latent targets for clinical treatment.
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Affiliation(s)
- Jiang Guo
- Department of Interventional Oncology, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of China
| | - Wei Li
- Center of Liver Disease, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of China
| | - Long Cheng
- Department of Interventional Oncology, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of China
| | - Xuesong Gao
- Department of General Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of China
- Correspondence: Xuesong Gao, Department of General Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of China, Tel +86 13718689825, Fax +861084322146, Email
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7
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Singh N, Sharma R, Bose S. Meta-analysis of transcriptomics data identifies potential biomarkers and their associated regulatory networks in gallbladder cancer. GASTROENTEROLOGY AND HEPATOLOGY FROM BED TO BENCH 2022; 15:311-325. [PMID: 36762219 PMCID: PMC9876761 DOI: 10.22037/ghfbb.v15i4.2292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 09/21/2022] [Indexed: 02/11/2023]
Abstract
Aim This study aimed to identify key genes, non-coding RNAs, and their possible regulatory interactions during gallbladder cancer (GBC). Background The early detection of GBC, i.e. before metastasis, is restricted by our limited knowledge of molecular markers and mechanism(s) involved during carcinogenesis. Therefore, identifying important disease-associated transcriptome-level alterations can be of clinical importance. Methods In this study, six NCBI-GEO microarray dataseries of GBC and control tissue samples were analyzed to identify differentially expressed genes (DEGs) and non-coding RNAs {microRNAs (DEmiRNAs) and long non-coding RNAs (DElncRNAs)} with a computational meta-analysis approach. A series of bioinformatic methods were applied to enrich functional pathways, create protein-protein interaction networks, identify hub genes, and screen potential targets of DEmiRNAs and DElncRNAs. Expression and interaction data were consolidated to reveal putative DElncRNAs:DEmiRNAs:DEGs interactions. Results In total, 351 DEGs (185 downregulated, 166 upregulated), 787 DEmiRNAs (299 downregulated, 488 upregulated), and 7436 DElncRNAs (3127 downregulated, 4309 upregulated) were identified. Eight genes (FGF, CDK1, RPN2, SEC61A1, SOX2, CALR, NGFR, and NCAM) were identified as hub genes. Genes associated with ubiquitin ligase activity, N-linked glycosylation, and blood coagulation were upregulated, while those for cell-cell adhesion, cell differentiation, and surface receptor-linked signaling were downregulated. DEGs-DEmiRNAs-DElncRNAs interaction network identified 46 DElncRNAs to be associated with 28 DEmiRNAs, consecutively regulating 27 DEGs. DEmiRNAs-hsa-miR-26b-5p and hsa-miR-335-5p; and DElnRNAs-LINC00657 and CTB-89H12.4 regulated the highest number of DEGs and DEmiRNAs, respectively. Conclusion The current study has identified meaningful transcriptome-level changes and gene-miRNA-lncRNA interactions during GBC and laid a platform for future studies on novel prognostic and diagnostic markers in GBC.
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Affiliation(s)
- Nidhi Singh
- Department of Biotechnology, Gauhati University, Guwahati, Assam, India
| | - Rinku Sharma
- Department of Life Sciences, Shiv Nadar University, Noida, Uttar Pradesh, India
| | - Sujoy Bose
- Department of Biotechnology, Gauhati University, Guwahati, Assam, India
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Acharya P, Chouhan K, Weiskirchen S, Weiskirchen R. Cellular Mechanisms of Liver Fibrosis. Front Pharmacol 2021; 12:671640. [PMID: 34025430 PMCID: PMC8134740 DOI: 10.3389/fphar.2021.671640] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 04/21/2021] [Indexed: 12/12/2022] Open
Abstract
The liver is a central organ in the human body, coordinating several key metabolic roles. The structure of the liver which consists of the distinctive arrangement of hepatocytes, hepatic sinusoids, the hepatic artery, portal vein and the central vein, is critical for its function. Due to its unique position in the human body, the liver interacts with components of circulation targeted for the rest of the body and in the process, it is exposed to a vast array of external agents such as dietary metabolites and compounds absorbed through the intestine, including alcohol and drugs, as well as pathogens. Some of these agents may result in injury to the cellular components of liver leading to the activation of the natural wound healing response of the body or fibrogenesis. Long-term injury to liver cells and consistent activation of the fibrogenic response can lead to liver fibrosis such as that seen in chronic alcoholics or clinically obese individuals. Unidentified fibrosis can evolve into more severe consequences over a period of time such as cirrhosis and hepatocellular carcinoma. It is well recognized now that in addition to external agents, genetic predisposition also plays a role in the development of liver fibrosis. An improved understanding of the cellular pathways of fibrosis can illuminate our understanding of this process, and uncover potential therapeutic targets. Here we summarized recent aspects in the understanding of relevant pathways, cellular and molecular drivers of hepatic fibrosis and discuss how this knowledge impact the therapy of respective disease.
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Affiliation(s)
- Pragyan Acharya
- Department of Biochemistry, All India Institute of Medical Sciences, New Delhi, India
| | - Komal Chouhan
- Department of Biochemistry, All India Institute of Medical Sciences, New Delhi, India
| | - Sabine Weiskirchen
- Institute of Molecular Pathobiochemistry, Experimental Gene Therapy and Clinical Chemistry, RWTH University Hospital Aachen, Aachen, Germany
| | - Ralf Weiskirchen
- Institute of Molecular Pathobiochemistry, Experimental Gene Therapy and Clinical Chemistry, RWTH University Hospital Aachen, Aachen, Germany
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9
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Wang J, Peng R, Zhang Z, Zhang Y, Dai Y, Sun Y. Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis. BIOMED RESEARCH INTERNATIONAL 2021; 2021:6662114. [PMID: 33688500 PMCID: PMC7925030 DOI: 10.1155/2021/6662114] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 01/21/2021] [Accepted: 02/17/2021] [Indexed: 12/27/2022]
Abstract
Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer and has poor outcomes. However, the potential molecular biological process underpinning the occurrence and development of HCC is still largely unknown. The purpose of this study was to identify the core genes related to HCC and explore their potential molecular events using bioinformatics methods. HCC-related expression profiles GSE25097 and GSE84005 were selected from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) between 306 HCC tissues and 281 corresponding noncancerous tissues were identified using GEO2R online tools. The protein-protein interaction network (PPIN) was constructed and visualized using the STRING database. Gene Ontology (GO) and KEGG pathway enrichment analyses of the DEGs were carried out using DAVID 6.8 and KOBAS 3.0. Additionally, module analysis and centrality parameter analysis were performed by Cytoscape. The expression differences of key genes in normal hepatocyte cells and HCC cells were verified by quantitative real-time fluorescence polymerase chain reaction (qRT-PCR). Additionally, survival analysis of key genes was performed by GEPIA. Our results showed that a total of 291 DEGs were identified including 99 upregulated genes and 192 downregulated genes. Our results showed that the PPIN of HCC was made up of 287 nodes and 2527 edges. GO analysis showed that these genes were mainly enriched in the molecular function of protein binding. Additionally, KEGG pathway analysis also revealed that DEGs were mainly involved in the metabolic, cell cycle, and chemical carcinogenesis pathways. Interestingly, a significant module with high centrality features including 10 key genes was found. Among these, CDK1, NDC80, HMMR, CDKN3, and PTTG1, which were only upregulated in HCC patients, have attracted much attention. Furthermore, qRT-PCR also confirmed the upregulation of these five key genes in the normal human hepatocyte cell line (HL-7702) and HCC cell lines (SMMC-7721, MHCC-97L, and MHCC-97H); patients with upregulated expression of these five key genes had significantly poorer survival and prognosis. CDK1, NDC80, HMMR, CDKN3, and PTTG1 can be used as molecular markers for HCC. This finding provides potential strategies for clinical diagnosis, accurate treatment, and prognosis analysis of liver cancer.
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Affiliation(s)
- Jia Wang
- Department of Molecular Medicine and Cancer Research Center, Chongqing Medical University, Chongqing, China
| | - Rui Peng
- Department of Bioinformatics, Chongqing Medical University, Chongqing, China
| | - Zheng Zhang
- Department of Molecular Medicine and Cancer Research Center, Chongqing Medical University, Chongqing, China
| | - Yixi Zhang
- Department of Molecular Medicine and Cancer Research Center, Chongqing Medical University, Chongqing, China
| | - Yuke Dai
- Department of Molecular Medicine and Cancer Research Center, Chongqing Medical University, Chongqing, China
| | - Yan Sun
- Department of Molecular Medicine and Cancer Research Center, Chongqing Medical University, Chongqing, China
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10
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Sharma A, Colonna G. System-Wide Pollution of Biomedical Data: Consequence of the Search for Hub Genes of Hepatocellular Carcinoma Without Spatiotemporal Consideration. Mol Diagn Ther 2021; 25:9-27. [PMID: 33475988 PMCID: PMC7847983 DOI: 10.1007/s40291-020-00505-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/01/2020] [Indexed: 12/17/2022]
Abstract
Biomedical institutions rely on data evaluation and are turning into data factories. Big-data storage centers, supercomputing systems, and increased algorithmic efficiency allow us to analyze the ever-increasing amount of data generated every day in biomedical research centers. In network science, the principal intrinsic problem is how to integrate the data and information from different experiments on genes or proteins. Data curation is an essential process in annotating new functional data to known genes or proteins, undertaken by a biobank curator, which is then reflected in the calculated networks. We provide an example of how protein-protein networks today have space-time limits. The next step is the integration of data and information from different biobanks. Omics data and networks are essential parts of this step but also have flawed protocols and errors. Consider data from patients with cancer: from biopsy procedures to experimental tests, to archiving methods and computational algorithms, these are continuously handled so require critical and continuous "updates" to obtain reproducible, reliable, and correct results. We show, as a second example, how all this distorts studies in cellular hepatocellular carcinoma. It is not unlikely that these flawed data have been polluting biobanks for some time before stringent conditions for the veracity of data were implemented in Big data. Therefore, all this could contribute to errors in future medical decisions.
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Affiliation(s)
- Ankush Sharma
- Department of Biosciences, University of Oslo, Oslo, Norway.
- Department of Informatics, University of Oslo, Oslo, Norway.
- Institute of Cancer Research, Institute of Clinical medicine, University of Oslo, Oslo, Norway.
| | - Giovanni Colonna
- Medical Informatics, AOU-Vanvitelli, Università della Campania, Naples, Italy
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Zeng L, Fan X, Wang X, Deng H, Zhang K, Zhang X, He S, Li N, Han Q, Liu Z. Bioinformatics Analysis based on Multiple Databases Identifies Hub Genes Associated with Hepatocellular Carcinoma. Curr Genomics 2019; 20:349-361. [PMID: 32476992 PMCID: PMC7235396 DOI: 10.2174/1389202920666191011092410] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 08/27/2019] [Accepted: 08/30/2019] [Indexed: 02/07/2023] Open
Abstract
Background Hepatocellular carcinoma (HCC) is the most common liver cancer and the mechanisms of hepatocarcinogenesis remain elusive. Objective This study aims to mine hub genes associated with HCC using multiple databases. Methods Data sets GSE45267, GSE60502, GSE74656 were downloaded from GEO database. Differentially expressed genes (DEGs) between HCC and control in each set were identified by limma software. The GO term and KEGG pathway enrichment of the DEGs aggregated in the datasets (aggregated DEGs) were analyzed using DAVID and KOBAS 3.0 databases. Protein-protein interaction (PPI) network of the aggregated DEGs was constructed using STRING database. GSEA software was used to verify the biological process. Association between hub genes and HCC prognosis was analyzed using patients' information from TCGA database by survminer R package. Results From GSE45267, GSE60502 and GSE74656, 7583, 2349, and 553 DEGs were identified respectively. A total of 221 aggregated DEGs, which were mainly enriched in 109 GO terms and 29 KEGG pathways, were identified. Cell cycle phase, mitotic cell cycle, cell division, nuclear division and mitosis were the most significant GO terms. Metabolic pathways, cell cycle, chemical carcinogenesis, retinol metabolism and fatty acid degradation were the main KEGG pathways. Nine hub genes (TOP2A, NDC80, CDK1, CCNB1, KIF11, BUB1, CCNB2, CCNA2 and TTK) were selected by PPI network and all of them were associated with prognosis of HCC patients. Conclusion TOP2A, NDC80, CDK1, CCNB1, KIF11, BUB1, CCNB2, CCNA2 and TTK were hub genes in HCC, which may be potential biomarkers of HCC and targets of HCC therapy.
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Affiliation(s)
- Lu Zeng
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, P.R. China.,Xi'an Medical University, Xi'an 710021, Shaanxi Province, P.R. China
| | - Xiude Fan
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, P.R. China
| | - Xiaoyun Wang
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, P.R. China
| | - Huan Deng
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, P.R. China
| | - Kun Zhang
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, P.R. China
| | - Xiaoge Zhang
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, P.R. China
| | - Shan He
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, P.R. China.,Xi'an Medical University, Xi'an 710021, Shaanxi Province, P.R. China
| | - Na Li
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, P.R. China
| | - Qunying Han
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, P.R. China
| | - Zhengwen Liu
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, P.R. China
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12
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Identification of Key Genes and Prognostic Value Analysis in Hepatocellular Carcinoma by Integrated Bioinformatics Analysis. Int J Genomics 2019; 2019:3518378. [PMID: 31886163 PMCID: PMC6893264 DOI: 10.1155/2019/3518378] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 08/07/2019] [Accepted: 08/20/2019] [Indexed: 01/17/2023] Open
Abstract
Emerging evidence indicates that various functional genes with altered expression are involved in the tumor progression of human cancers. This study is aimed at identifying novel key genes that may be used for hepatocellular carcinoma (HCC) diagnosis, prognosis, and targeted therapy. This study included 3 expression profiles (GSE45267, GSE74656, and GSE84402), which were obtained from the Gene Expression Omnibus (GEO). GEO2R was used to analyze the differentially expressed genes (DEGs) between HCC and normal samples. The functional and pathway enrichment analysis was performed by the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of the identified DEGs was constructed using the Search Tool for the Retrieval of Interacting Gene, and hub genes were identified. ONCOMINE and CCLE databases were used to verify the expression of the hub genes in HCC tissues and cells. Kaplan-Meier plotter was used to assess the effects of the hub genes on the overall survival of HCC patients. A total of 99 DEGs were identified from the 3 expression profiles. These DEGs were enriched with functional processes and pathways related to HCC pathogenesis. From the PPI network, 5 hub genes were identified. The expression of the 5 hub genes was all upregulated in HCC tissues and cells compared with the control tissues and cells. Kaplan-Meier survival curves indicated that high expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), cyclin B2 (CCNB2), MAD2 mitotic arrest deficient-like 1 (MAD2L1), and topoisomerase IIα (TOP2A) predicted poor overall survival in HCC patients (all log-rank P < 0.01). These results revealed that the DEGs may serve as candidate key genes during HCC pathogenesis. The 5 hub genes, including CDK1, CCNB1, CCNB2, MAD2L1, and TOP2A, may serve as promising prognostic biomarkers in HCC.
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13
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Liao X, Yu T, Yang C, Huang K, Wang X, Han C, Huang R, Liu X, Yu L, Zhu G, Su H, Qin W, Deng J, Zeng X, Han B, Han Q, Liu Z, Zhou X, Liu J, Gong Y, Liu Z, Huang J, Lu L, Ye X, Peng T. Comprehensive investigation of key biomarkers and pathways in hepatitis B virus-related hepatocellular carcinoma. J Cancer 2019; 10:5689-5704. [PMID: 31737106 PMCID: PMC6843875 DOI: 10.7150/jca.31287] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 06/30/2019] [Indexed: 02/06/2023] Open
Abstract
Objective: Our study is aim to explore potential key biomarkers and pathways in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) using genome-wide expression profile dataset and methods. Methods: Dataset from the GSE14520 is used as the training cohort and The Cancer Genome Atlas dataset as the validation cohort. Differentially expressed genes (DEGs) screening were performed by the limma package. Gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), gene ontology, the Kyoto Encyclopedia of Genes and Genomes, and risk score model were used for pathway and genes identification. Results: GSEA revealed that several pathways and biological processes are associated with hepatocarcinogenesis, such as the cell cycle, DNA repair, and p53 pathway. A total of 160 DEGs were identified. The enriched functions and pathways of the DEGs included toxic substance decomposition and metabolism processes, and the P450 and p53 pathways. Eleven of the DEGs were identified as hub DEGs in the WGCNA. In survival analysis of hub DEGs, high expression of PRC1 and TOP2A were significantly associated with poor clinical outcome of HBV-related HCC, and shown a good performance in HBV-related HCC diagnosis. The prognostic signature consisting of PRC1 and TOP2A also doing well in the prediction of HBV-related HCC prognosis. The diagnostic and prognostic values of PRC1 and TOP2A was confirmed in TCGA HCC patients. Conclusions: Key biomarkers and pathways identified in the present study may enhance the comprehend of the molecular mechanisms underlying hepatocarcinogenesis. Additionally, mRNA expression of PRC1 and TOP2A may serve as potential diagnostic and prognostic biomarkers for HBV-related HCC.
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Affiliation(s)
- Xiwen Liao
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Tingdong Yu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Chengkun Yang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Ketuan Huang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Xiangkun Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Chuangye Han
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Rui Huang
- Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Xiaoguang Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.,Department of Hepatobiliary Surgery, Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524001, Guangdong Province, China
| | - Long Yu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.,Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, Henan Province, China
| | - Guangzhi Zhu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Hao Su
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Wei Qin
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Jianlong Deng
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.,Department of Hepatobiliary Surgery, The Sixth Affiliated Hospital of Guangxi Medical University, Yulin, 537000, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Xianmin Zeng
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Bowen Han
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Quanfa Han
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Zhengqian Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Xin Zhou
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Junqi Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Yizhen Gong
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.,Department of Evidence-based Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Zhengtao Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.,Key Laboratory of Combined Multi-Organ Transplantation, Ministry of Public Health and Key Laboratory of Organ Transplantation of Zhejiang Province, Hangzhou, 310003, Zhejiang Province, People's Republic of China.,Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, SE-171 21, Sweden
| | - Jianlv Huang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.,Department of Hepatobiliary Surgery, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Lei Lu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.,Department of General Surgery, Beijing Haidian Hospital, Beijing Haidian Section of Peking University Third Hospital, Beijing, 100080, People's Republic of China
| | - Xinping Ye
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Tao Peng
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
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14
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Liu ZK, Zhang RY, Yong YL, Zhang ZY, Li C, Chen ZN, Bian H. Identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis. PeerJ 2019; 7:e7436. [PMID: 31410310 PMCID: PMC6689388 DOI: 10.7717/peerj.7436] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 07/08/2019] [Indexed: 12/24/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is one of the most heterogeneous malignant cancers with no effective targets and treatments. However, the molecular pathogenesis of HCC remains largely uncertain. The aims of our study were to find crucial genes involved in HCC through multidimensional methods and revealed potential molecular mechanisms. Here, we reported the gene expression profile GSE121248 findings from 70 HCC and 37 adjacent normal tissues, all of which had chronic hepatitis B virus (HBV) infection, we were seeking to identify the dysregulated pathways, crucial genes and therapeutic targets implicated in HBV-associated HCC. We found 164 differentially expressed genes (DEGs) (92 downregulated genes and 72 upregulated genes). Gene ontology (GO) analysis of DEGs revealed significant functional enrichment of mitotic nuclear division, cell division, and the epoxygenase P450 pathway. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the DEGs were mainly enriched in metabolism, cell cycle regulation and the p53 signaling pathway. The Mcode plugin was calculated to construct a module complex of DEGs, and the module was mainly enriched in cell cycle checkpoints, RHO GTPase effectors and cytochrome P450. Considering a weak contribution of each gene, gene set enrichment analysis (GSEA) was performed, revealing results consistent with those described above. Six crucial proteins were selected based on the degree of centrality, including NDC80, ESR1, ZWINT, NCAPG, ENO3 and CENPF. Real-time quantitative PCR analysis validated the six crucial genes had the same expression trend as predicted. Furthermore, the methylation data of The Cancer Genome Atlas (TCGA) with HCC showed that mRNA expression of crucial genes was negatively correlated with methylation levels of their promoter region. The overall survival reflected that high expression of NDC80, CENPF, ZWINT, and NCAPG significantly predicted poor prognosis, whereas ESR1 high expression exhibited a favorable prognosis. The identification of the crucial genes and pathways would contribute to the development of novel molecular targets and biomarker-driven treatments for HCC.
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Affiliation(s)
- Ze-Kun Liu
- Fourth Military Medical University, Department of Cell Biology, National Translational Science Center for Molecular Medicine, Xi'an, Shaanxi, China
| | - Ren-Yu Zhang
- Fourth Military Medical University, Department of Cell Biology, National Translational Science Center for Molecular Medicine, Xi'an, Shaanxi, China
| | - Yu-Le Yong
- Fourth Military Medical University, Department of Cell Biology, National Translational Science Center for Molecular Medicine, Xi'an, Shaanxi, China
| | - Zhi-Yun Zhang
- Fourth Military Medical University, Department of Cell Biology, National Translational Science Center for Molecular Medicine, Xi'an, Shaanxi, China
| | - Can Li
- Fourth Military Medical University, Department of Cell Biology, National Translational Science Center for Molecular Medicine, Xi'an, Shaanxi, China
| | - Zhi-Nan Chen
- Fourth Military Medical University, Department of Cell Biology, National Translational Science Center for Molecular Medicine, Xi'an, Shaanxi, China
| | - Huijie Bian
- Fourth Military Medical University, Department of Cell Biology, National Translational Science Center for Molecular Medicine, Xi'an, Shaanxi, China
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15
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Liu ZZ, Yan LN, Dong CN, Ma N, Yuan MN, Zhou J, Gao P. Cytochrome P450 family members are associated with fast-growing hepatocellular carcinoma and patient survival: An integrated analysis of gene expression profiles. Saudi J Gastroenterol 2019; 25:167-175. [PMID: 30971588 PMCID: PMC6526731 DOI: 10.4103/sjg.sjg_290_18] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND/AIMS The biological heterogeneity of hepatocellular carcinoma (HCC) makes prognosis difficult. Although many molecular tools have been developed to assist in stratification and prediction of patients by using microarray analysis, the classification and prediction are still improvable because the high-through microarray contains a large amount of information. Meanwhile, gene expression patterns and their prognostic value for HCC have not been systematically investigated. In order to explore new molecular diagnostic and prognostic biomarkers, the gene expression profiles between HCCs and adjacent nontumor tissues were systematically analyzed in the present study. MATERIALS AND METHODS In this study, gene expression profiles were obtained by repurposing five Gene Expression Omnibus databases. Differentially expressed genes were identified by using robust rank aggregation method. Three datasets (GSE14520, GSE36376, and GSE54236) were used to validate the associations between cytochrome P450 (CYP) family genes and HCC. GSE14520 was used as the training set. GSE36376 and GSE54236 were considered as the testing sets. RESULTS From the training set, a four-CYP gene signature was constructed to discriminate between HCC and nontumor tissues with an area under curve (AUC) of 0.991. Accuracy of this four-gene signature was validated in two testing sets (AUCs for them were 0.973 and 0.852, respectively). Moreover, this gene signature had a good performance to make a distinction between fast-growing HCC and slow-growing HCC (AUC = 0.898), especially for its high sensitivity of 95%. At last, CYP2C8 was identified as an independent risk factor of recurrence-free survival (hazard ratio [HR] =0.865, 95% confidence interval [CI], 0.754-0.992, P = 0.038) and overall survival (HR = 0.849; 95% CI, 0.716-0.995, P = 0.033). CONCLUSIONS In summary, our results confirmed for the first time that a four-CYP gene (CYP1A2, CYP2E1, CYP2A7, and PTGIS) signature is associated with fast-growing HCC, and CYP2C8 is associated with patient survival. Our findings could help to identify HCC patients at high risk of rapid growth and recurrence.
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Affiliation(s)
- Zhao-Zhen Liu
- Department of Social Medicine and Health Care Management, School of Public Health, Hebei Medical University, Hebei, China,Hebei Province Key Laboratory of Environment and Human Health, Hebei, China
| | - Li-Na Yan
- Hebei Province Key Laboratory of Environment and Human Health, Hebei, China,Department of Epidemiology and Biostatistics, School of Public Health, Hebei Medical University, Hebei, China
| | - Chun-Nan Dong
- Department of Pathogenic Biology, Hebei Medical University, Hebei, China
| | - Ning Ma
- Department of Social Medicine and Health Care Management, School of Public Health, Hebei Medical University, Hebei, China,Hebei Province Key Laboratory of Environment and Human Health, Hebei, China
| | - Mei-Na Yuan
- Department of Social Medicine and Health Care Management, School of Public Health, Hebei Medical University, Hebei, China,Hebei Province Key Laboratory of Environment and Human Health, Hebei, China
| | - Jin Zhou
- Department of Social Medicine and Health Care Management, School of Public Health, Hebei Medical University, Hebei, China,Hebei Province Key Laboratory of Environment and Human Health, Hebei, China
| | - Ping Gao
- Department of Social Medicine and Health Care Management, School of Public Health, Hebei Medical University, Hebei, China,Hebei Province Key Laboratory of Environment and Human Health, Hebei, China,Address for correspondence: Dr. Ping Gao, Department of Social Medicine and Health Care Management, School of Public Health, Hebei Medical University, No. 361 Zhongshan East Road, Shijiazhuang, 050017, Hebei Province, China. E-mail:
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