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Liu YG, Jiang ST, Zhang JW, Zheng H, Zhang L, Zhao HT, Sang XT, Xu YY, Lu X. Role of extracellular vesicle-associated proteins in the progression, diagnosis, and treatment of hepatocellular carcinoma. Cell Biosci 2024; 14:113. [PMID: 39227992 DOI: 10.1186/s13578-024-01294-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Accepted: 08/21/2024] [Indexed: 09/05/2024] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, characterized by difficulties in early diagnosis, prone to distant metastasis, and high recurrence rates following surgery. Extracellular vesicles (EVs) are a class of cell-derived particles, including exosomes, characterized by a phospholipid bilayer. They serve as effective carriers for intercellular communication cargo, including proteins and nucleic acids, and are widely involved in tumor progression. They are being explored as potential tumor biomarkers and novel therapeutic avenues. We provide a brief overview of the biogenesis and characteristics of EVs to better understand their classification standards. The focus of this review is on the research progress of EV-associated proteins in the field of HCC. EV-associated proteins are involved in tumor growth and regulation in HCC, participate in intercellular communication within the tumor microenvironment (TME), and are implicated in events including angiogenesis and epithelial-mesenchymal transition (EMT) during tumor metastasis. In addition, EV-associated proteins show promising diagnostic efficacy for HCC. For the treatment of HCC, they also demonstrate significant potential including enhancing the efficacy of tumor vaccines, and as targeting cargo anchors. Facing current challenges, we propose the future directions of research in this field. Above all, research on EV-associated proteins offers the potential to enhance our comprehension of HCC and offer novel insights for developing new treatment strategies.
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Affiliation(s)
- Yao-Ge Liu
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Shi-Tao Jiang
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Jun-Wei Zhang
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Han Zheng
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Lei Zhang
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Hai-Tao Zhao
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Xin-Ting Sang
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Yi-Yao Xu
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China.
| | - Xin Lu
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China.
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Kreis NN, Moon HH, Wordeman L, Louwen F, Solbach C, Yuan J, Ritter A. KIF2C/MCAK a prognostic biomarker and its oncogenic potential in malignant progression, and prognosis of cancer patients: a systematic review and meta-analysis as biomarker. Crit Rev Clin Lab Sci 2024; 61:404-434. [PMID: 38344808 DOI: 10.1080/10408363.2024.2309933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/05/2023] [Accepted: 01/22/2024] [Indexed: 03/24/2024]
Abstract
KIF2C/MCAK (KIF2C) is the most well-characterized member of the kinesin-13 family, which is critical in the regulation of microtubule (MT) dynamics during mitosis, as well as interphase. This systematic review briefly describes the important structural elements of KIF2C, its regulation by multiple molecular mechanisms, and its broad cellular functions. Furthermore, it systematically summarizes its oncogenic potential in malignant progression and performs a meta-analysis of its prognostic value in cancer patients. KIF2C was shown to be involved in multiple crucial cellular processes including cell migration and invasion, DNA repair, senescence induction and immune modulation, which are all known to be critical during the development of malignant tumors. Indeed, an increasing number of publications indicate that KIF2C is aberrantly expressed in multiple cancer entities. Consequently, we have highlighted its involvement in at least five hallmarks of cancer, namely: genome instability, resisting cell death, activating invasion and metastasis, avoiding immune destruction and cellular senescence. This was followed by a systematic search of KIF2C/MCAK's expression in various malignant tumor entities and its correlation with clinicopathologic features. Available data were pooled into multiple weighted meta-analyses for the correlation between KIF2Chigh protein or gene expression and the overall survival in breast cancer, non-small cell lung cancer and hepatocellular carcinoma patients. Furthermore, high expression of KIF2C was correlated to disease-free survival of hepatocellular carcinoma. All meta-analyses showed poor prognosis for cancer patients with KIF2Chigh expression, associated with a decreased overall survival and reduced disease-free survival, indicating KIF2C's oncogenic potential in malignant progression and as a prognostic marker. This work delineated the promising research perspective of KIF2C with modern in vivo and in vitro technologies to further decipher the function of KIF2C in malignant tumor development and progression. This might help to establish KIF2C as a biomarker for the diagnosis or evaluation of at least three cancer entities.
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Affiliation(s)
- Nina-Naomi Kreis
- Obstetrics and Prenatal Medicine, Gynaecology and Obstetrics, University Hospital Frankfurt, J. W. Goethe-University, Frankfurt, Germany
| | - Ha Hyung Moon
- Obstetrics and Prenatal Medicine, Gynaecology and Obstetrics, University Hospital Frankfurt, J. W. Goethe-University, Frankfurt, Germany
| | - Linda Wordeman
- Department of Physiology and Biophysics, University of Washington School of Medicine, Seattle, WA, USA
| | - Frank Louwen
- Obstetrics and Prenatal Medicine, Gynaecology and Obstetrics, University Hospital Frankfurt, J. W. Goethe-University, Frankfurt, Germany
| | - Christine Solbach
- Obstetrics and Prenatal Medicine, Gynaecology and Obstetrics, University Hospital Frankfurt, J. W. Goethe-University, Frankfurt, Germany
| | - Juping Yuan
- Obstetrics and Prenatal Medicine, Gynaecology and Obstetrics, University Hospital Frankfurt, J. W. Goethe-University, Frankfurt, Germany
| | - Andreas Ritter
- Obstetrics and Prenatal Medicine, Gynaecology and Obstetrics, University Hospital Frankfurt, J. W. Goethe-University, Frankfurt, Germany
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Zhao K, Li X, Feng Y, Wang J, Yao W. The role of kinesin family members in hepatobiliary carcinomas: from bench to bedside. Biomark Res 2024; 12:30. [PMID: 38433242 PMCID: PMC10910842 DOI: 10.1186/s40364-024-00559-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 01/03/2024] [Indexed: 03/05/2024] Open
Abstract
As a major component of the digestive system malignancies, tumors originating from the hepatic and biliary ducts seriously endanger public health. The kinesins (KIFs) are molecular motors that enable the microtubule-dependent intracellular trafficking necessary for mitosis and meiosis. Normally, the stability of KIFs is essential to maintain cell proliferation and genetic homeostasis. However, aberrant KIFs activity may destroy this dynamic stability, leading to uncontrolled cell division and tumor initiation. In this work, we have made an integral summarization of the specific roles of KIFs in hepatocellular and biliary duct carcinogenesis, referring to aberrant signal transduction and the potential for prognostic evaluation. Additionally, current clinical applications of KIFs-targeted inhibitors have also been discussed, including their efficacy advantages, relationship with drug sensitivity or resistance, the feasibility of combination chemotherapy or other targeted agents, as well as the corresponding clinical trials. In conclusion, the abnormally activated KIFs participate in the regulation of tumor progression via a diverse range of mechanisms and are closely associated with tumor prognosis. Meanwhile, KIFs-aimed inhibitors also carry out a promising tumor-targeted therapeutic strategy that deserves to be further investigated in hepatobiliary carcinoma (HBC).
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Affiliation(s)
- Kai Zhao
- Department of Biliary and Pancreatic Surgery, Cancer Research Center Affiliated Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430030, Wuhan, Hubei, China
| | - Xiangyu Li
- Department of Thoracic Surgery Affiliated Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430030, Wuhan, Hubei, China
| | - Yunxiang Feng
- Department of Biliary and Pancreatic Surgery, Cancer Research Center Affiliated Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430030, Wuhan, Hubei, China
| | - Jianming Wang
- Department of Biliary and Pancreatic Surgery, Cancer Research Center Affiliated Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430030, Wuhan, Hubei, China.
- Affiliated Tianyou Hospital, Wuhan University of Science & Technology, 430064, Wuhan, China.
| | - Wei Yao
- Department of Oncology Affiliated Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430030, Wuhan, Hubei, China.
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Lei L, Yang J, Peng H, Huang R, Liang L, Liu R, Li J. The Prognostic Significance of the TEAD4 in Hepatocellular Carcinoma. Int J Gen Med 2023; 16:6005-6013. [PMID: 38144438 PMCID: PMC10748864 DOI: 10.2147/ijgm.s440973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 12/04/2023] [Indexed: 12/26/2023] Open
Abstract
Background Abnormal expression of genes causes tumorigenesis, tumor progression, and poor prognosis in hepatocellular carcinoma (HCC). Therefore, the aims of this study were to explore the transcription enhancer domain factor 4 (TEAD4) in patients with liver cancer and its relationship with prognosis. Methods HTSeq-FPKM data and corresponding clinical data of HCC patients were obtained from The Cancer Genome Atlas (TCGA). Difference in TEAD4 expression between normal and tumor and the correlation with clinical characteristics were analyzed by the chi-squared test based on UALCAN. HepG2 cell lines were used to study the effect of TEAD4 on HCC cell lines. The expression and clinical significance of TEAD4 in HCC were detected in clinical cases. Results The transcription and post-transcription levels of TEAD4 were higher in HCC tumors than normal illustrated different expressed transcription of TEAD4 in gender, nodal metastasis status, tumor grades, and individual cancer stages. The high TEAD4 expression was significantly associated with tumor grades. The high expression of TEAD4 was significantly correlated to shorter 2-5 years overall survival. Inhibition of TEAD4 expression in HepG2 cells resulted in significantly decreased cell proliferation and invasion. Conclusion TEAD4 was identified as an independent prognostic factor, and inhibition of TEAD4 expression in HepG2 cells resulted in significantly decreased cell proliferation and invasion.
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Affiliation(s)
- Liping Lei
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Guilin Medical University, Guilin, 541001, People’s Republic of China
- Department of Geriatric Medicine, The Affiliated Hospital of Guilin Medical University, Guilin, 541001, People’s Republic of China
| | - Jingjing Yang
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Guilin Medical University, Guilin, 541001, People’s Republic of China
| | - Hao Peng
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Guilin Medical University, Guilin, 541001, People’s Republic of China
| | - Ruiyan Huang
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Guilin Medical University, Guilin, 541001, People’s Republic of China
| | - Lichun Liang
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Guilin Medical University, Guilin, 541001, People’s Republic of China
| | - Ruifang Liu
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Guilin Medical University, Guilin, 541001, People’s Republic of China
| | - Jiangfa Li
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Guilin Medical University, Guilin, 541001, People’s Republic of China
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Li S, Hao L, Hu X, Li L. A systematic study on the treatment of hepatitis B-related hepatocellular carcinoma with drugs based on bioinformatics and key target reverse network pharmacology and experimental verification. Infect Agent Cancer 2023; 18:41. [PMID: 37393234 DOI: 10.1186/s13027-023-00520-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 06/20/2023] [Indexed: 07/03/2023] Open
Abstract
BACKGROUND Chronic hepatitis B virus (HBV) infection is the major etiology of hepatocellular carcinoma (HCC). However, the mechanism of hepatitis B-related hepatocellular carcinoma (HBV-related HCC) is still unclear. Therefore, understanding the pathogenesis and searching for drugs to treat HBV-related HCC was an effective strategy to treat this disease. PURPOSE Bioinformatics was used to predict the potential targets of HBV-related HCC. The reverse network pharmacology of key targets was used to analyze the clinical drugs, traditional Chinese medicine (TCM) and small molecules of TCM in the treatment of HBV-related HCC. METHODS In this study, three microarray datasets totally containing 330 tumoral samples and 297 normal samples were selected from the GEO database. These microarray datasets were used to screen DEGs. And the expression profile and survival of 6 key genes were analyzed. In addition, Comparative Toxicogenomics Database and Coremine Medical database were used to enrich clinical drugs and TCM of HBV-related HCC by the 6 key targets. Then the obtained TCM were classified based on the Chinese Pharmacopoeia. Among these top 6 key genes, CDK1 and CCNB1 had the most connection nodes and the highest degree and were the most significantly expressed. In general, CDK1 and CCNB1 tend to form a complex, which is conducive to cell mitosis. Hence, this study mainly studied CDK1 and CCNB1. HERB database was used to predict small molecules TCM. The inhibition effect of quercetin, celastrol and cantharidin on HepG2.2.15 cells and Hep3B cells was verified by CCK8 experiment. The effects of quercetin, celastrol and cantharidin on CDK1 and CCNB1 of HepG2.2.15 cells and Hep3B cells were determined by Western Blot. RESULTS In short, 272 DEGs (53 upregulated and 219 downregulated) were identified. Among these DEGs, 6 key genes with high degree were identified, which were AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS. Kaplan-Meier plotter analysis showed that higher expression levels of AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS were associated with poor OS. According to the first 6 key targets, a variety of drugs and TCM were identified. These results showed that clinical drugs included targeted drugs, such as sorafenib, palbociclib and Dasatinib. and chemotherapy drugs, such as cisplatin and doxorubicin. TCM, such as the TCM flavor was mainly warm and bitter, and the main meridians were liver and lung. Small molecules of TCM included flavonoids, terpenoids, alkaloids and glycosides, such as quercetin, celastrol, cantharidin, hesperidin, silymarin, casticin, berberine and ursolic acid, which have great potential in anti-HBV-related HCC. For molecular docking of chemical components, the molecules with higher scores were flavonoids, alkaloids, etc. Three representative types of TCM small molecules were verified respectively, and it was found that quercetin, celastrol and cantharidin inhibited the proliferation of HepG2.2.15 cells and Hep3B cells along concentration gradient. Quercetin, celastrol and cantharidin decreased CDK1 expression in HepG2.2.15 and Hep3B cells, but for CCNB1, only cantharidin decreased CCNB1 expression in the two strains of cells. CONCLUSION In conclusion, AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS could be potential targets for the diagnosis and prognosis of HBV-related HCC. Clinical drugs include chemotherapeutic and targeted drug, traditional Chinese medicine is mainly bitter and warm TCM. Small molecular of TCM including flavonoids, terpenoids and glycosides and alkaloids, which have great potential in anti-HBV-related HCC. This study provides potential therapeutic targets and novel strategies for the treatment of HBV-related HCC.
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Affiliation(s)
- Shenghao Li
- Chengdu University of Traditional Chinese Medicine, No. 37 Shi-er-qiao Road, Chengdu, 610075, Sichuan, People's Republic of China
- Hospital of Chengdu University of Traditional Chinese Medicine, No. 39 Shi-er-qiao Road, Chengdu, 610072, Sichuan, People's Republic of China
| | - Liyuan Hao
- Chengdu University of Traditional Chinese Medicine, No. 37 Shi-er-qiao Road, Chengdu, 610075, Sichuan, People's Republic of China
- Hospital of Chengdu University of Traditional Chinese Medicine, No. 39 Shi-er-qiao Road, Chengdu, 610072, Sichuan, People's Republic of China
| | - Xiaoyu Hu
- Hospital of Chengdu University of Traditional Chinese Medicine, No. 39 Shi-er-qiao Road, Chengdu, 610072, Sichuan, People's Republic of China.
| | - Luya Li
- Department of Pharmacy Department, The Fourth Hospital of Hebei Medical University, NO.12, Jian Kang Road, Shijiazhuang, 050010, Hebei, People's Republic of China
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Li J, Ren J, Liao H, Guo W, Feng K, Huang T, Cai YD. Identification of dynamic gene expression profiles during sequential vaccination with ChAdOx1/BNT162b2 using machine learning methods. Front Microbiol 2023; 14:1138674. [PMID: 37007526 PMCID: PMC10063797 DOI: 10.3389/fmicb.2023.1138674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 03/01/2023] [Indexed: 03/19/2023] Open
Abstract
To date, COVID-19 remains a serious global public health problem. Vaccination against SARS-CoV-2 has been adopted by many countries as an effective coping strategy. The strength of the body’s immune response in the face of viral infection correlates with the number of vaccinations and the duration of vaccination. In this study, we aimed to identify specific genes that may trigger and control the immune response to COVID-19 under different vaccination scenarios. A machine learning-based approach was designed to analyze the blood transcriptomes of 161 individuals who were classified into six groups according to the dose and timing of inoculations, including I-D0, I-D2-4, I-D7 (day 0, days 2–4, and day 7 after the first dose of ChAdOx1, respectively) and II-D0, II-D1-4, II-D7-10 (day 0, days 1–4, and days 7–10 after the second dose of BNT162b2, respectively). Each sample was represented by the expression levels of 26,364 genes. The first dose was ChAdOx1, whereas the second dose was mainly BNT162b2 (Only four individuals received a second dose of ChAdOx1). The groups were deemed as labels and genes were considered as features. Several machine learning algorithms were employed to analyze such classification problem. In detail, five feature ranking algorithms (Lasso, LightGBM, MCFS, mRMR, and PFI) were first applied to evaluate the importance of each gene feature, resulting in five feature lists. Then, the lists were put into incremental feature selection method with four classification algorithms to extract essential genes, classification rules and build optimal classifiers. The essential genes, namely, NRF2, RPRD1B, NEU3, SMC5, and TPX2, have been previously associated with immune response. This study also summarized expression rules that describe different vaccination scenarios to help determine the molecular mechanism of vaccine-induced antiviral immunity.
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Affiliation(s)
- Jing Li
- School of Computer Science, Baicheng Normal University, Baicheng, Jilin, China
| | - JingXin Ren
- School of Life Sciences, Shanghai University, Shanghai, China
| | | | - Wei Guo
- Key Laboratory of Stem Cell Biology, Shanghai Jiao Tong University School of Medicine (SJTUSM) and Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, China
| | - KaiYan Feng
- Department of Computer Science, Guangdong AIB Polytechnic College, Guangzhou, China
| | - Tao Huang
- CAS Key Laboratory of Computational Biology, Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Science, Shanghai, China
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- *Correspondence: Tao Huang, ; Yu-Dong Cai,
| | - Yu-Dong Cai
- School of Life Sciences, Shanghai University, Shanghai, China
- *Correspondence: Tao Huang, ; Yu-Dong Cai,
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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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Gongye X, Tian M, Xia P, Qu C, Chen Z, Wang J, Zhu Q, Li Z, Yuan Y. Multi-omics analysis revealed the role of extracellular vesicles in hepatobiliary & pancreatic tumor. J Control Release 2022; 350:11-25. [PMID: 35963466 DOI: 10.1016/j.jconrel.2022.08.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 08/04/2022] [Accepted: 08/05/2022] [Indexed: 12/24/2022]
Abstract
Liquid biopsy is rapidly growing into a hot research field due to its unique advantages of minimal invasiveness, and extracellular vesicle (EVs) are also expected to become an important pillar in the diagnostic technology system as a newly discovered active substance carrier. More and more research has highlighted the important contribution of EVs in the progress of tumor. Molecular changes during disease progression could be detected in EVs. However, the diagnostic applications of EVs are not generally understood. Combined with the characteristics of hepatobiliary and pancreatic tumor, we summarized the recent developments in various omics analysis of EVs. Furtherly, we explored the role of EVs in the early diagnosis of hepatobiliary and pancreatic tumors by multi-omics analysis.
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Affiliation(s)
- Xiangdong Gongye
- Department of Hepatobiliary & Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, PR China; Clinical Medicine Research Center for Minimally Invasive Procedure of Hepatobiliary & Pancreatic Diseases of Hubei Province, Hubei, PR China.
| | - Ming Tian
- Department of Hepatobiliary & Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, PR China; Clinical Medicine Research Center for Minimally Invasive Procedure of Hepatobiliary & Pancreatic Diseases of Hubei Province, Hubei, PR China.
| | - Peng Xia
- Department of Hepatobiliary & Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, PR China; Clinical Medicine Research Center for Minimally Invasive Procedure of Hepatobiliary & Pancreatic Diseases of Hubei Province, Hubei, PR China.
| | - Chengmin Qu
- Department of Hepatobiliary & Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, PR China; Clinical Medicine Research Center for Minimally Invasive Procedure of Hepatobiliary & Pancreatic Diseases of Hubei Province, Hubei, PR China.
| | - Zhang Chen
- Department of Hepatobiliary & Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, PR China; Clinical Medicine Research Center for Minimally Invasive Procedure of Hepatobiliary & Pancreatic Diseases of Hubei Province, Hubei, PR China.
| | - Jigang Wang
- Department of Geriatrics, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong 518020, PR China.
| | - Qian Zhu
- Department of Hepatobiliary & Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, PR China; Clinical Medicine Research Center for Minimally Invasive Procedure of Hepatobiliary & Pancreatic Diseases of Hubei Province, Hubei, PR China.
| | - Zhijie Li
- Department of Geriatrics, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong 518020, PR China.
| | - Yufeng Yuan
- Department of Hepatobiliary & Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, PR China; Clinical Medicine Research Center for Minimally Invasive Procedure of Hepatobiliary & Pancreatic Diseases of Hubei Province, Hubei, PR China.
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Systems Biology and Bioinformatics approach to Identify blood based signatures molecules and drug targets of patient with COVID-19. INFORMATICS IN MEDICINE UNLOCKED 2022; 28:100840. [PMID: 34981034 PMCID: PMC8716147 DOI: 10.1016/j.imu.2021.100840] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 12/27/2021] [Indexed: 01/08/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection results in the development of a highly contagious respiratory ailment known as new coronavirus disease (COVID-19). Despite the fact that the prevalence of COVID-19 continues to rise, it is still unclear how people become infected with SARS-CoV-2 and how patients with COVID-19 become so unwell. Detecting biomarkers for COVID-19 using peripheral blood mononuclear cells (PBMCs) may aid in drug development and treatment. This research aimed to find blood cell transcripts that represent levels of gene expression associated with COVID-19 progression. Through the development of a bioinformatics pipeline, two RNA-Seq transcriptomic datasets and one microarray dataset were studied and discovered 102 significant differentially expressed genes (DEGs) that were shared by three datasets derived from PBMCs. To identify the roles of these DEGs, we discovered disease-gene association networks and signaling pathways, as well as we performed gene ontology (GO) studies and identified hub protein. Identified significant gene ontology and molecular pathways improved our understanding of the pathophysiology of COVID-19, and our identified blood-based hub proteins TPX2, DLGAP5, NCAPG, CCNB1, KIF11, HJURP, AURKB, BUB1B, TTK, and TOP2A could be used for the development of therapeutic intervention. In COVID-19 subjects, we discovered effective putative connections between pathological processes in the transcripts blood cells, suggesting that blood cells could be used to diagnose and monitor the disease’s initiation and progression as well as developing drug therapeutics.
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10
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Qiu X, Hua X, Li Q, Zhou Q, Chen J. m 6A Regulator-Mediated Methylation Modification Patterns and Characteristics of Immunity in Blood Leukocytes of COVID-19 Patients. Front Immunol 2021; 12:774776. [PMID: 34917088 PMCID: PMC8669770 DOI: 10.3389/fimmu.2021.774776] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 11/08/2021] [Indexed: 12/28/2022] Open
Abstract
Both RNA N6-methyladenosine (m6A) modification of SARS-CoV-2 and immune characteristics of the human body have been reported to play an important role in COVID-19, but how the m6A methylation modification of leukocytes responds to the virus infection remains unknown. Based on the RNA-seq of 126 samples from the GEO database, we disclosed that there is a remarkably higher m6A modification level of blood leukocytes in patients with COVID-19 compared to patients without COVID-19, and this difference was related to CD4+ T cells. Two clusters were identified by unsupervised clustering, m6A cluster A characterized by T cell activation had a higher prognosis than m6A cluster B. Elevated metabolism level, blockage of the immune checkpoint, and lower level of m6A score were observed in m6A cluster B. A protective model was constructed based on nine selected genes and it exhibited an excellent predictive value in COVID-19. Further analysis revealed that the protective score was positively correlated to HFD45 and ventilator-free days, while negatively correlated to SOFA score, APACHE-II score, and crp. Our works systematically depicted a complicated correlation between m6A methylation modification and host lymphocytes in patients infected with SARS-CoV-2 and provided a well-performing model to predict the patients' outcomes.
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Affiliation(s)
- Xiangmin Qiu
- The Ministry of Education Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
| | - Xiaoliang Hua
- Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei, China
| | - Qianyin Li
- The Ministry of Education Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
| | - Qin Zhou
- The Ministry of Education Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
| | - Juan Chen
- The Ministry of Education Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
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11
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Huang G, Wang C, Fu X. Bidirectional deep neural networks to integrate RNA and DNA data for predicting outcome for patients with hepatocellular carcinoma. Future Oncol 2021; 17:4481-4495. [PMID: 34374301 DOI: 10.2217/fon-2021-0659] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Aims: Individualized patient profiling is instrumental for personalized management in hepatocellular carcinoma (HCC). This study built a model based on bidirectional deep neural networks (BiDNNs), an unsupervised machine-learning approach, to integrate multi-omics data and predict survival in HCC. Methods: DNA methylation and mRNA expression data for HCC samples from the TCGA database were integrated using BiDNNs. With optimal clusters as labels, a support vector machine model was developed to predict survival. Results: Using the BiDNN-based model, samples were clustered into two survival subgroups. The survival subgroup classification was an independent prognostic factor. BiDNNs were superior to multimodal autoencoders. Conclusion: This study constructed and validated a BiDNN-based model for predicting prognosis in HCC, with implications for individualized therapies in HCC.
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Affiliation(s)
- Guojun Huang
- Department of Oncology, Pidu District People's Hospital, Chengdu, Sichuan, China
| | - Cheng Wang
- Department of General Surgery, Pidu District People's Hospital, Chengdu, Sichuan, China
| | - Xi Fu
- Department of Oncology, Pidu District People's Hospital, Chengdu, Sichuan, China
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12
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Wang J, Wang Y, Xu J, Song Q, Shangguan J, Xue M, Wang H, Gan J, Gao W. Global analysis of gene expression signature and diagnostic/prognostic biomarker identification of hepatocellular carcinoma. Sci Prog 2021; 104:368504211029429. [PMID: 34315286 PMCID: PMC10450782 DOI: 10.1177/00368504211029429] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Hepatocellular carcinoma (HCC) is one of the most common cancers in the world. The landscape of HCC's molecular alteration signature has been explored over the last few decades. Even so, more comprehensive research is still needed to improve understanding of tumorigenesis and progression of HCC, as well as to identify potential biomarkers for the malignancy. In this research, a comprehensive bioinformatics analysis was conducted based on the publicly available databases from both the Cancer Genome Atlas (TCGA) program and the gene expression omnibus (GEO) database. R/Bioconductor was used to analyze differentially expressed genes (DEGs) between HCC tumor and normal control (NC) samples, and then a protein-protein interaction (PPI) network of DEGs was established through the STRING platform. Finally, the application of specific candidate genes as diagnostic or prognostic biomarkers of HCC was explored and evaluated by ROC and survival analysis. A total of 310 DEGs were detected in the HCC tumor samples. Thirty-six hub DEGs in the PPI network and 10 candidates of the 36 genes showed significant alterations in tumor expression, including CDKN3, TOP2A, UBE2C, CDC20, PBK, ASPM, KIF20A, NCAPG, CCNB2, CYP3A4. The 10-gene signature had relatively significant effects when distinguishing tumors from normal samples (sensitivity >70%, specificity >70%, AUC >0.8, p < 0.001). Eight candidate genes were negatively correlated with the overall survival rate of the patients (p < 0.05) and were all up-regulated in HCC tumor samples. The age and gender factors had no significant impact on the overall survival rate of HCC patients (p > 0.05), and the TNM stage status factor had a significant negative prognosis correlation (p < 0.05). This research provides evidence for a better understanding of tumorigenesis and progression of HCC and helps to explore candidate targets for disease diagnosis and treatment.
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Affiliation(s)
- Jihan Wang
- Department of Basic Medicine, School of Medicine, Xi’an International University, Xi’an, China
| | - Yangyang Wang
- School of Electronics and Information, Northwestern Polytechnical University, Xi’an, China
| | - Jing Xu
- Department of Basic Medicine, School of Medicine, Xi’an International University, Xi’an, China
| | - Qiying Song
- Department of Basic Medicine, School of Medicine, Xi’an International University, Xi’an, China
| | - Jingbo Shangguan
- Department of Basic Medicine, School of Medicine, Xi’an International University, Xi’an, China
| | - Mengju Xue
- Department of Basic Medicine, School of Medicine, Xi’an International University, Xi’an, China
| | - Hanghui Wang
- Department of Nursing, School of Medicine, Xi’an International University, Xi’an, China
| | - Jingyi Gan
- Department of Basic Medicine, School of Medicine, Xi’an International University, Xi’an, China
| | - Wenjie Gao
- Department of Spine Surgery, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China
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13
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Zhang Y, Tang Y, Guo C, Li G. Integrative analysis identifies key mRNA biomarkers for diagnosis, prognosis, and therapeutic targets of HCV-associated hepatocellular carcinoma. Aging (Albany NY) 2021; 13:12865-12895. [PMID: 33946043 PMCID: PMC8148482 DOI: 10.18632/aging.202957] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 03/23/2021] [Indexed: 02/05/2023]
Abstract
Hepatitis C virus-associated HCC (HCV-HCC) is a prevalent malignancy worldwide and the molecular mechanisms are still elusive. Here, we screened 240 differentially expressed genes (DEGs) of HCV-HCC from Gene expression omnibus (GEO) and the Cancer Genome Atlas (TCGA), followed by weighted gene coexpression network analysis (WGCNA) to identify the most significant module correlated with the overall survival. 10 hub genes (CCNB1, AURKA, TOP2A, NEK2, CENPF, NUF2, CDKN3, PRC1, ASPM, RACGAP1) were identified by four approaches (Protein-protein interaction networks of the DEGs and of the significant module by WGCNA, and diagnostic and prognostic values), and their abnormal expressions, diagnostic values, and prognostic values were successfully verified. A four hub gene-based prognostic signature was built using the least absolute shrinkage and selection operator (LASSO) algorithm and a multivariate Cox regression model with the ICGC-LIRI-JP cohort (N =112). Kaplan-Meier survival plots (P = 0.0003) and Receiver Operating Characteristic curves (ROC = 0.778) demonstrated the excellent predictive potential for the prognosis of HCV-HCC. Additionally, upstream regulators including transcription factors and miRNAs of hub genes were predicted, and candidate drugs or herbs were identified. These findings provide a firm basis for the exploration of the molecular mechanism and further clinical biomarkers development of HCV-HCC.
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Affiliation(s)
- Yongqiang Zhang
- Molecular Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, P.R. China.,West China School of Medicine, West China Hospital, Sichuan University, Chengdu 610041, P.R. China
| | - Yuqin Tang
- School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, P.R. China
| | - Chengbin Guo
- Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, P.R. China
| | - Gen Li
- Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, P.R. China
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14
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Zhang P, Feng J, Wu X, Chu W, Zhang Y, Li P. Bioinformatics Analysis of Candidate Genes and Pathways Related to Hepatocellular Carcinoma in China: A Study Based on Public Databases. Pathol Oncol Res 2021; 27:588532. [PMID: 34257537 PMCID: PMC8262246 DOI: 10.3389/pore.2021.588532] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 02/01/2021] [Indexed: 12/30/2022]
Abstract
Background and Objective: Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor of the digestive system worldwide. Chronic hepatitis B virus (HBV) infection and aflatoxin exposure are predominant causes of HCC in China, whereas hepatitis C virus (HCV) infection and alcohol intake are likely the main risk factors in other countries. It is an unmet need to recognize the underlying molecular mechanisms of HCC in China. Methods: In this study, microarray datasets (GSE84005, GSE84402, GSE101685, and GSE115018) derived from Gene Expression Omnibus (GEO) database were analyzed to obtain the common differentially expressed genes (DEGs) by R software. Moreover, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the protein-protein interaction (PPI) network was constructed, and hub genes were identified by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape, respectively. The hub genes were verified using Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Kaplan-Meier Plotter online databases were performed on the TCGA HCC dataset. Moreover, the Human Protein Atlas (HPA) database was used to verify candidate genes’ protein expression levels. Results: A total of 293 common DEGs were screened, including 103 up-regulated genes and 190 down-regulated genes. Moreover, GO analysis implied that common DEGs were mainly involved in the oxidation-reduction process, cytosol, and protein binding. KEGG pathway enrichment analysis presented that common DEGs were mainly enriched in metabolic pathways, complement and coagulation cascades, cell cycle, p53 signaling pathway, and tryptophan metabolism. In the PPI network, three subnetworks with high scores were detected using the Molecular Complex Detection (MCODE) plugin. The top 10 hub genes identified were CDK1, CCNB1, AURKA, CCNA2, KIF11, BUB1B, TOP2A, TPX2, HMMR and CDC45. The other public databases confirmed that high expression of the aforementioned genes related to poor overall survival among patients with HCC. Conclusion: This study primarily identified candidate genes and pathways involved in the underlying mechanisms of Chinese HCC, which is supposed to provide new targets for the diagnosis and treatment of HCC in China.
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Affiliation(s)
- Peng Zhang
- School of Graduates, Tianjin Medical University, Tianjin, China.,Department of Hepatology, Tianjin Second People's Hospital, Tianjin, China
| | - Jing Feng
- School of Graduates, Tianjin Medical University, Tianjin, China.,Department of Hepatology, Tianjin Second People's Hospital, Tianjin, China
| | - Xue Wu
- School of Graduates, Tianjin Medical University, Tianjin, China.,Department of Hepatology, Tianjin Second People's Hospital, Tianjin, China
| | - Weike Chu
- School of Graduates, Tianjin Medical University, Tianjin, China.,Department of Hepatology, Tianjin Second People's Hospital, Tianjin, China
| | - Yilian Zhang
- School of Graduates, Tianjin Medical University, Tianjin, China.,Department of Hepatology, Tianjin Second People's Hospital, Tianjin, China
| | - Ping Li
- Department of Hepatology, Tianjin Second People's Hospital, Tianjin, China.,Tianjin Research Institute of Liver Diseases, Tianjin, China
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15
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Zhu W, Ru L, Ma Z. Identification of a Novel Four-Gene Signature Correlated With the Prognosis of Patients With Hepatocellular Carcinoma: A Comprehensive Analysis. Front Oncol 2021; 11:626654. [PMID: 33777771 PMCID: PMC7994902 DOI: 10.3389/fonc.2021.626654] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 01/21/2021] [Indexed: 12/13/2022] Open
Abstract
Purpose Hepatocellular carcinoma (HCC) is a common solid-tumor malignancy with high heterogeneity, and accurate prognostic prediction in HCC remains difficult. This analysis was performed to find a novel prognostic multigene signature. Methods The TCGA-LIHC dataset was analyzed for differentially coexpressed genes through weighted gene coexpression network analysis (WGCNA) and differential gene expression analysis. A protein-protein interaction (PPI) network and univariate Cox regression analysis of overall survival (OS) were utilized to identify their prognostic value. Next, we used least absolute shrinkage and selection operator (LASSO) Cox regression to establish a prognostic module. Subsequently, the ICGC-LIRI-JP dataset was applied for further validation. Based on this module, HCC cases were stratified into high-risk and low-risk groups, and differentially expressed genes (DEGs) were identified. Functional enrichment analyses of these DEGs were conducted. Finally, single-sample gene set enrichment analysis (ssGSEA) was performed to explore the correlation between the prognostic signature and immune status. Results A total of 393 differentially coexpressed genes were obtained. Forty differentially coexpressed hub genes were identified using the CytoHubba plugin, and 38 of them were closely correlated with OS. Afterward, we established the four-gene prognostic signature with an acceptable accuracy (area under the curve [AUC] of 1-year survival: 0.739). The ICGC-LIRI-JP dataset also supported the acceptable accuracy (AUC of 1-year survival:0.752). Compared with low-risk cohort, HCC cases in the high-risk cohort had shorter OS, higher tumor grades, and higher T stages. The risk scores of this signature still act as independent predictors of OS (P<0.001). Functional enrichment analyses suggest that it was mainly organelle fission and nuclear division that were enriched. Finally, ssGSEA revealed that this signature is strongly associated with the immune status of HCC patients. Conclusions The proposed prognostic signature of four differentially coexpressed hub genes has satisfactory prognostic ability, providing important insight into the prediction of HCC prognosis.
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Affiliation(s)
- Weihua Zhu
- Department of Gastroenterology, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, China
| | - Lixin Ru
- Department of Radiation Oncology, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, China
| | - Zhenchao Ma
- Department of Radiation Oncology, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, China.,Department of Radiation Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China
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