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Zertuche-Martínez C, Velázquez-Enríquez JM, González-García K, Santos-Álvarez JC, Romero-Tlalolini MDLÁ, Pina-Canseco S, Pérez-Campos Mayoral L, Muriel P, Villa-Treviño S, Baltiérrez-Hoyos R, Arellanes-Robledo J, Vásquez-Garzón VR. Discovery of candidate biomarkers from plasma-derived extracellular vesicles of patients with cirrhosis and hepatocellular carcinoma: an exploratory proteomic study. Mol Omics 2024; 20:483-495. [PMID: 39011654 DOI: 10.1039/d4mo00043a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/17/2024]
Abstract
Extracellular vesicles (EVs) represent an attractive source of biomarkers due to their biomolecular cargo. The aim of this study was to identify candidate protein biomarkers from plasma-derived EVs of patients with liver cirrhosis (LC) and hepatocellular carcinoma (HCC). Plasma-derived EVs from healthy participants (HP), LC, and HCC patients (eight samples each) were subjected to label-free quantitative proteomic analysis using LC-MS/MS. A total of 248 proteins were identified, and differentially expressed proteins (DEPs) were obtained after pairwise comparison. We found that DEPs mainly involve complement cascade activation, coagulation pathways, cholesterol metabolism, and extracellular matrix components. By choosing a panel of up- and down-regulated proteins involved in cirrhotic and carcinogenesis processes, TGFBI, LGALS3BP, C7, SERPIND1, and APOC3 were found to be relevant for LC patients, while LRG1, TUBA1C, TUBB2B, ACTG1, C9, HP, FGA, FGG, FN1, PLG, APOB and ITIH2 were associated with HCC patients, which could discriminate both diseases. In addition, we identified the top shared proteins in both diseases, which included LCAT, SERPINF2, A2M, CRP, and VWF. Thus, our exploratory proteomic study revealed that these proteins might play an important role in the disease progression and represent a panel of candidate biomarkers for the prognosis and diagnosis of LC and HCC.
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Affiliation(s)
- Cecilia Zertuche-Martínez
- Laboratorio de Fibrosis y cáncer, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca de Juárez 68120, Oaxaca, Mexico
| | - Juan Manuel Velázquez-Enríquez
- Laboratorio de Fibrosis y cáncer, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca de Juárez 68120, Oaxaca, Mexico
| | - Karina González-García
- Laboratorio de Fibrosis y cáncer, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca de Juárez 68120, Oaxaca, Mexico
| | - Jovito Cesar Santos-Álvarez
- Laboratorio de Fibrosis y cáncer, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca de Juárez 68120, Oaxaca, Mexico
| | | | - Socorro Pina-Canseco
- Centro de Investigación Facultad de Medicina UNAM UABJO, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca de Juárez 68120, Oaxaca, Mexico
| | - Laura Pérez-Campos Mayoral
- Centro de Investigación Facultad de Medicina UNAM UABJO, Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca de Juárez 68120, Oaxaca, Mexico
| | - Pablo Muriel
- Laboratorio de Hepatología Experimental, Departamento de Farmacología, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (CINVESTAV-IPN), Ciudad de México 07000, Mexico
| | - Saúl Villa-Treviño
- Departamento de Biología Celular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (CINVESTAV-IPN), Ciudad de México 07360, Mexico
| | - Rafael Baltiérrez-Hoyos
- CONAHCYT-Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca de Juárez 68120, Oaxaca, Mexico.
| | | | - Verónica Rocío Vásquez-Garzón
- CONAHCYT-Facultad de Medicina y Cirugía, Universidad Autónoma Benito Juárez de Oaxaca, Oaxaca de Juárez 68120, Oaxaca, Mexico.
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Wang S, Sun Y, Shao D, Pan Y, Gao X, Zhao P, Liu Q, Shang G, Shang W, Fu Z, Sun Y. High expression of serine protease inhibitor kazal type 1 predicts poor prognosis and promotes the progression and invasion of oral tongue squamous cell carcinoma. Arch Oral Biol 2024; 164:106003. [PMID: 38781741 DOI: 10.1016/j.archoralbio.2024.106003] [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: 02/02/2024] [Revised: 04/08/2024] [Accepted: 05/11/2024] [Indexed: 05/25/2024]
Abstract
OBJECTIVE This study aimed to investigate the expression of serine protease inhibitor kazal type 1 (SPINK1) and its carcinogenic effect in oral tongue squamous cell carcinoma (OTSCC). DESIGN Initially, bioinformatics analysis was conducted using data from The Cancer Genome Atlas and Gene Expression Omnibus to compare SPINK1 mRNA expression between malignant and adjacent tissues. Subsequently, the impact of differential expression on survival and other clinical variables was examined. Additionally, histology microarray analysis was performed to assess SPINK1 protein expression in 35 cases of malignant and adjacent tissues. Finally, alterations in SPINK1 expression were evaluated to determine its biological phenotypes in OTSCC, including proliferation, apoptosis, invasion, and metastasis. RESULTS OTSCC tissues exhibit higher levels of SPINK1 compared to surrounding cancerous tissues. Notably, increased SPINK1 expression correlates with the pathological N stage and independently predicts overall survival among patients with OTSCC. CONCLUSION Suppression of SPINK1 inhibited OTSCC cell proliferation, invasion, and motility while promoting apoptosis. These findings suggest that SPINK1 may serve as a prognostic biomarker as well as a potential therapeutic target for managing OTSCC.
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Affiliation(s)
- Shuang Wang
- Department of Pharmaceutics, School of Pharmacy, Qingdao University, Qingdao 266021, China; Department of Stomatology, Huangdao District Central Hospital, Qingdao 266555, China
| | - Yaping Sun
- Department of Stomatology, Huangdao District Central Hospital, Qingdao 266555, China
| | - Dan Shao
- Department of Stomatology, Huangdao District Central Hospital, Qingdao 266555, China
| | - Yunjie Pan
- Department of Stomatology, Huangdao District Central Hospital, Qingdao 266555, China
| | - Xiaoyan Gao
- Traditional Chinese Medical Hospital of Huangdao District, Qingdao 266499,China
| | - Peng Zhao
- Department of Stomatology, Huangdao District Central Hospital, Qingdao 266555, China
| | - Qiaoling Liu
- Department of Oncology, Huangdao District Central Hospital, Qingdao 266555, China
| | - Gaishuang Shang
- Department of Scientific Research, Qingdao East Sea Pharmaceutical Co., Ltd., Qingdao 266431, China
| | - Wei Shang
- Department of Stomatology, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao 266003, China
| | - Zhiguang Fu
- Department of Tumor Radiotherapy, Air Force Medical Center, PLA, Beijing 100142, China.
| | - Yong Sun
- Department of Pharmaceutics, School of Pharmacy, Qingdao University, Qingdao 266021, China.
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He Y, Qi W, Xie X, Jiang H. Identification and validation of a novel predictive signature based on hepatocyte-specific genes in hepatocellular carcinoma by integrated analysis of single-cell and bulk RNA sequencing. BMC Med Genomics 2024; 17:103. [PMID: 38654290 DOI: 10.1186/s12920-024-01871-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 04/09/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Hepatocellular carcinoma represents a significant global burden in terms of cancer-related mortality, posing a substantial risk to human health. Despite the availability of various treatment modalities, the overall survival rates for patients with hepatocellular carcinoma remain suboptimal. The objective of this study was to explore the potential of novel biomarkers and to establish a novel predictive signature utilizing multiple transcriptome profiles. METHODS The GSE115469 and CNP0000650 cohorts were utilized for single cell analysis and gene identification. The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets were utilized in the development and evaluation of a predictive signature. The expressions of hepatocyte-specific genes were further validated using the GSE135631 cohort. Furthermore, immune infiltration results, immunotherapy response prediction, somatic mutation frequency, tumor mutation burden, and anticancer drug sensitivity were analyzed based on various risk scores. Subsequently, functional enrichment analysis was performed on the differential genes identified in the risk model. Moreover, we investigated the expression of particular genes in chronic liver diseases utilizing datasets GSE135251 and GSE142530. RESULTS Our findings revealed hepatocyte-specific genes (ADH4, LCAT) with notable alterations during cell maturation and differentiation, leading to the development of a novel predictive signature. The analysis demonstrated the efficacy of the model in predicting outcomes, as evidenced by higher risk scores and poorer prognoses in the high-risk group. Additionally, a nomogram was devised to forecast the survival rates of patients at 1, 3, and 5 years. Our study demonstrated that the predictive model may play a role in modulating the immune microenvironment and impacting the anti-tumor immune response in hepatocellular carcinoma. The high-risk group exhibited a higher frequency of mutations and was more likely to benefit from immunotherapy as a treatment option. Additionally, we confirmed that the downregulation of hepatocyte-specific genes may indicate the progression of hepatocellular carcinoma and aid in the early diagnosis of the disease. CONCLUSION Our research findings indicate that ADH4 and LCAT are genes that undergo significant changes during the differentiation of hepatocytes into cancer cells. Additionally, we have created a unique predictive signature based on genes specific to hepatocytes.
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Affiliation(s)
- Yujian He
- Department of Gastroenterology, The Second Hospital of Hebei Medical University, Hebei Key Laboratory of Gastroenterology, Hebei Institute of Gastroenterology, Hebei Clinical Research Center for Digestive Diseases, Shijiazhuang, Hebei, China
| | - Wei Qi
- Department of Gastroenterology, The Second Hospital of Hebei Medical University, Hebei Key Laboratory of Gastroenterology, Hebei Institute of Gastroenterology, Hebei Clinical Research Center for Digestive Diseases, Shijiazhuang, Hebei, China
| | - Xiaoli Xie
- Department of Gastroenterology, The Second Hospital of Hebei Medical University, Hebei Key Laboratory of Gastroenterology, Hebei Institute of Gastroenterology, Hebei Clinical Research Center for Digestive Diseases, Shijiazhuang, Hebei, China
| | - Huiqing Jiang
- Department of Gastroenterology, The Second Hospital of Hebei Medical University, Hebei Key Laboratory of Gastroenterology, Hebei Institute of Gastroenterology, Hebei Clinical Research Center for Digestive Diseases, Shijiazhuang, Hebei, China.
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Deng W, Chen F, Li Y, Xu L. Development of a clinical scoring model to predict the overall and relapse‑free survival of patients with hepatocellular carcinoma following a hepatectomy. Mol Clin Oncol 2023; 19:87. [PMID: 37854326 PMCID: PMC10580259 DOI: 10.3892/mco.2023.2683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 09/08/2023] [Indexed: 10/20/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is a highly lethal disease, and surgical resection is one of the major treatment methods used. However, to date, at least to the best of our knowledge, there is no effective prognostic scoring system for the overall survival (OS) and relapse-free survival (RFS) of patients following hepatectomy. The present study developed a low-cost and easy-to-use model based on the clinicopathological characteristics of patients with HCC for assessment of outcome prediction and risk stratification. A total of 690 patients with HCC undergoing surgery were included and randomly divided into two cohorts (n=345). Cox regression analysis was conducted to investigate the association between the clinicopathological and treatment features, and patient survival. Multivariate analysis revealed that ascites, vascular tumor thrombus, low tumor differentiation and extrahepatic metastasis were independent risk factors for OS. Extrahepatic metastasis and multiple tumors were independent risk factors to predict tumor recurrence. These variables were weighted to construct the ascites, vascular tumor thrombus, low tumor differentiation, extrahepatic metastasis and multiple tumors (AVLEM) score based on the cumulative incidence (CuI) of the aforementioned variables, and the patients were classified into grade 0 (CuI=0), grade 1 (CuI=1 for OS and CuI ≥1 for RFS), and grade 2 (CuI ≥2) subgroups, respectively. Kaplan-Meier analysis revealed that the OS and RFS differed significantly among the subgroups; however, the survival rate between the two cohorts did not exhibit any marked differences. On the whole, the present study demonstrates that with this AVLEM scoring system, patients with HCC with a high score had a poor OS and RFS; thus, it is suggested that such patients undergo imaging examinations following a hepatectomy more frequently.
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Affiliation(s)
- Wanyu Deng
- College of Life Science, Shangrao Normal University, Shangrao, Jiangxi 334001, P.R. China
- Department of Pancreato-Biliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong 510120, P.R. China
| | - Fu Chen
- College of Life Science, Shangrao Normal University, Shangrao, Jiangxi 334001, P.R. China
| | - Yuanxiang Li
- College of Life Science, Shangrao Normal University, Shangrao, Jiangxi 334001, P.R. China
| | - Leibo Xu
- Department of Pancreato-Biliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong 510120, P.R. China
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Chai JW, Hu XW, Zhang MM, Dong YN. Seven chromatin regulators as immune cell infiltration characteristics, potential diagnostic biomarkers and drugs prediction in hepatocellular carcinoma. Sci Rep 2023; 13:18643. [PMID: 37903974 PMCID: PMC10616163 DOI: 10.1038/s41598-023-46107-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 10/27/2023] [Indexed: 11/01/2023] Open
Abstract
Treatment is challenging due to the heterogeneity of hepatocellular carcinoma (HCC). Chromatin regulators (CRs) are important in epigenetics and are closely associated with HCC. We obtained HCC-related expression data and relevant clinical data from The Cancer Genome Atlas (TCGA) databases. Then, we crossed the differentially expressed genes (DEGs), immune-related genes and CRs to obtain immune-related chromatin regulators differentially expressed genes (IRCR DEGs). Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to select the prognostic gene and construct a risk model for predicting prognosis in HCC, followed by a correlation analysis of risk scores with clinical characteristics. Finally, we also carried out immune microenvironment analysis and drug sensitivity analysis, the correlation between risk score and clinical characteristics was analyzed. In addition, we carried out immune microenvironment analysis and drug sensitivity analysis. Functional analysis suggested that IRCR DEGs was mainly enriched in chromatin-related biological processes. We identified and validated PPARGC1A, DUSP1, APOBEC3A, AIRE, HDAC11, HMGB2 and APOBEC3B as prognostic biomarkers for the risk model construction. The model was also related to immune cell infiltration, and the expression of CD48, CTLA4, HHLA2, TNFSF9 and TNFSF15 was higher in high-risk group. HCC patients in the high-risk group were more sensitive to Axitinib, Docetaxel, Erlotinib, and Metformin. In this study, we construct a prognostic model of immune-associated chromatin regulators, which provides new ideas and research directions for the accurate treatment of HCC.
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Affiliation(s)
- Jin-Wen Chai
- Department of Oncology, Laizhou Traditional Chinese Medicine Hospital, Laizhou, Shandong, China
| | - Xi-Wen Hu
- The First Clinical Medical School, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Miao-Miao Zhang
- Department of Oncology, Laizhou Traditional Chinese Medicine Hospital, Laizhou, Shandong, China
| | - Yu-Na Dong
- Department of Gastroenterology, Laizhou People's Hospital, No.1718 Wuli Street, Laizhou, Shandong, China.
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Chen K, Zheng T, Chen C, Liu L, Guo Z, Peng Y, Zhang X, Yang Z. Pregnancy Zone Protein Serves as a Prognostic Marker and Favors Immune Infiltration in Lung Adenocarcinoma. Biomedicines 2023; 11:1978. [PMID: 37509617 PMCID: PMC10377424 DOI: 10.3390/biomedicines11071978] [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: 06/11/2023] [Revised: 07/06/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Lung adenocarcinoma (LUAD) is a public enemy with a very high incidence and mortality rate, for which there is no specific detectable biomarker. Pregnancy zone protein (PZP) is an immune-related protein; however, the functions of PZP in LUAD are unclear. In this study, a series of bioinformatics methods, combined with immunohistochemistry (IHC), four-color multiplex fluorescence immunohistochemistry (mIHC), quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA), were utilized to explore the prognostic value and potential role of PZP in LUAD. Our data revealed that PZP expression was markedly reduced in LUAD tissues, tightly correlated with clinical stage and could be an independent unfavorable prognostic factor. In addition, pathway analysis revealed that high expression of PZP in LUAD was mainly involved in immune-related molecules. Tumor immune infiltration analysis by CIBERSORT showed a significant correlation between PZP expression and several immune cell infiltrations, and IHC further confirmed a positive correlation with CD4+ T-cell infiltration and a negative correlation with CD68+ M0 macrophage infiltration. Furthermore, mIHC demonstrated that PZP expression gave rise to an increase in CD86+ M1 macrophages and a decrease in CD206+ M2 macrophages. Therefore, PZP can be used as a new biomarker for the prediction of prognosis and may be a promising immune-related molecular target for LUAD.
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Affiliation(s)
- Kehong Chen
- Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - Taihao Zheng
- Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - Cai Chen
- Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - Liangzhong Liu
- Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - Zhengjun Guo
- Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - Yuan Peng
- Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - Xiaoyue Zhang
- Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - Zhenzhou Yang
- Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
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Li Z, Li Y, Hou Y, Fan Y, Jiang H, Li B, Zhu H, Liu Y, Zhang L, Zhang J, Wu M, Ma T, Zhao T, Ma L. Association of Plasma Vitamins and Carotenoids, DNA Methylation of LCAT, and Risk of Age-Related Macular Degeneration. Nutrients 2023; 15:2985. [PMID: 37447314 DOI: 10.3390/nu15132985] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/07/2023] [Accepted: 06/08/2023] [Indexed: 07/15/2023] Open
Abstract
Dysregulation of lipid metabolism has been implicated in age-related macular degeneration (AMD), the leading cause of blindness among the elderly. Lecithin cholesterol acyltransferase (LCAT) is an important enzyme responsible for lipid metabolism, which could be regulated by DNA methylation during the development of various age-related diseases. This study aimed to assess the association between LCAT DNA methylation and the risk of AMD, and to examine whether plasma vitamin and carotenoid concentrations modified this association. A total of 126 cases of AMD and 174 controls were included in the present analysis. LCAT DNA methylation was detected by quantitative real-time methylation-1specific PCR (qMSP). Circulating vitamins and carotenoids were measured using reversed-phase high-performance liquid chromatography (RP-HPLC). DNA methylation of LCAT was significantly higher in patients with AMD than those in the control subjects. After multivariable adjustment, participants in the highest tertile of LCAT DNA methylation had a 5.37-fold higher risk (95% CI: 2.56, 11.28) of AMD compared with those in the lowest tertile. Each standard deviation (SD) increment of LCAT DNA methylation was associated with a 2.23-fold (95% CI: 1.58, 3.13) increased risk of AMD. There was a J-shaped association between LCAT DNA methylation and AMD risk (Pnon-linearity = 0.03). Higher concentrations of plasma retinol and β-cryptoxanthin were significantly associated with decreased levels of LCAT DNA methylation, with the multivariate-adjusted β coefficient being -0.05 (95% CI: -0.08, -0.01) and -0.25 (95% CI: -0.42, -0.08), respectively. In joint analyses of LCAT DNA methylation and plasma vitamin and carotenoid concentrations, the inverse association between increased LCAT DNA methylation and AMD risk was more pronounced among participants who had a lower concentration of plasma retinol and β-cryptoxanthin. These findings highlight the importance of comprehensively assessing LCAT DNA methylation and increasing vitamin and carotenoid status for the prevention of AMD.
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Affiliation(s)
- Zhaofang Li
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Yajing Li
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Yijing Hou
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Yahui Fan
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Hong Jiang
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Baoyu Li
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Hailu Zhu
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Yaning Liu
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Lei Zhang
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Jie Zhang
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Min Wu
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Tianyou Ma
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi'an Jiaotong University, Ministry of Education of China, Xi'an 710061, China
| | - Tong Zhao
- College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an 710119, China
| | - Le Ma
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Xi'an Jiaotong University, Ministry of Education of China, Xi'an 710061, China
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Sgro A, Cursons J, Waryah C, Woodward EA, Foroutan M, Lyu R, Yeoh GCT, Leedman PJ, Blancafort P. Epigenetic reactivation of tumor suppressor genes with CRISPRa technologies as precision therapy for hepatocellular carcinoma. Clin Epigenetics 2023; 15:73. [PMID: 37120619 PMCID: PMC10149030 DOI: 10.1186/s13148-023-01482-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 04/09/2023] [Indexed: 05/01/2023] Open
Abstract
BACKGROUND Epigenetic silencing of tumor suppressor genes (TSGs) is a key feature of oncogenesis in hepatocellular carcinoma (HCC). Liver-targeted delivery of CRISPR-activation (CRISPRa) systems makes it possible to exploit chromatin plasticity, by reprogramming transcriptional dysregulation. RESULTS Using The Cancer Genome Atlas HCC data, we identify 12 putative TSGs with negative associations between promoter DNA methylation and transcript abundance, with limited genetic alterations. All HCC samples harbor at least one silenced TSG, suggesting that combining a specific panel of genomic targets could maximize efficacy, and potentially improve outcomes as a personalized treatment strategy for HCC patients. Unlike epigenetic modifying drugs lacking locus selectivity, CRISPRa systems enable potent and precise reactivation of at least 4 TSGs tailored to representative HCC lines. Concerted reactivation of HHIP, MT1M, PZP, and TTC36 in Hep3B cells inhibits multiple facets of HCC pathogenesis, such as cell viability, proliferation, and migration. CONCLUSIONS By combining multiple effector domains, we demonstrate the utility of a CRISPRa toolbox of epigenetic effectors and gRNAs for patient-specific treatment of aggressive HCC.
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Affiliation(s)
- Agustin Sgro
- Cancer Epigenetics Group, The Harry Perkins Institute of Medical Research, Nedlands, Perth, WA, 6009, Australia
- Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia
- School of Human Sciences, The University of Western Australia, Crawley, Perth, WA, 6009, Australia
| | - Joseph Cursons
- Biomedicine Discovery Institute and the Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC, 3800, Australia
| | - Charlene Waryah
- Cancer Epigenetics Group, The Harry Perkins Institute of Medical Research, Nedlands, Perth, WA, 6009, Australia
- Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia
| | - Eleanor A Woodward
- Cancer Epigenetics Group, The Harry Perkins Institute of Medical Research, Nedlands, Perth, WA, 6009, Australia
- Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia
| | - Momeneh Foroutan
- Biomedicine Discovery Institute and the Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC, 3800, Australia
| | - Ruqian Lyu
- Bioinformatics and Cellular Genomics, St Vincent's Institute of Medical Research, Fitzroy, Melbourne, VIC, 3065, Australia
- Melbourne Integrative Genomics/School of Mathematics and Statistics, Faculty of Science, The University of Melbourne, Royal Parade, Parkville, VIC, 3010, Australia
| | - George C T Yeoh
- Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia
- School of Molecular Sciences, University of Western Australia, Crawley, Perth, WA, 6009, Australia
| | - Peter J Leedman
- Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia
- Laboratory for Cancer Medicine, Harry Perkins Institute of Medical Research, QEII Medical Centre, 6 Verdun St, Nedlands, Perth, WA, 6009, Australia
- School of Medicine and Pharmacology, The University of Western Australia, Crawley, Perth, WA, 6009, Australia
| | - Pilar Blancafort
- Cancer Epigenetics Group, The Harry Perkins Institute of Medical Research, Nedlands, Perth, WA, 6009, Australia.
- Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia.
- School of Human Sciences, The University of Western Australia, Crawley, Perth, WA, 6009, Australia.
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9
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Ma K, Wu H, Ji L. Construction of HBV gene-related prognostic and diagnostic models for hepatocellular carcinoma. Front Genet 2023; 13:1065644. [PMID: 36685852 PMCID: PMC9845411 DOI: 10.3389/fgene.2022.1065644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 12/12/2022] [Indexed: 01/06/2023] Open
Abstract
Background: Hepatocellular carcinoma (HCC) is a main cause of malignancy-related death all over the world with a poor prognosis. The current research is focused on developing novel prognostic and diagnostic models of Hepatocellular carcinoma from the perspective of hepatitis B virus (HBV)-related genes, and predicting its prognostic characteristics and potential reliable biomarkers for Hepatocellular carcinoma diagnosis. Methods: As per the information related to Hepatocellular carcinoma expression profile and the clinical data in multiple public databases, we utilized limma for assessing the differentially expressed genes (DEGs) in HBV vs non- hepatitis B virus groups, and the gene set was enriched, analyzed and annotated by WebGestaltR package. Then, STRING was employed to investigate the protein interactions. A risk model for evaluating Hepatocellular carcinoma prognosis was built with Lasso Cox regression analysis. The effect patients receiving immunotherapy was predicted using Tumor Immune Dysfunction and Exclusion (TIDE). Additionally, pRRophetic was used to investigate the drug sensitivity. Lastly, the Support Vector Machine (SVM) approach was utilized for building the diagnostic model. Results: The Hepatocellular Carcinoma Molecular Atlas 18 (HCCDB18) data set was utilized for the identification of 1344 HBV-related differentially expressed genes, mainly associated with cell division activities. Five functional modules were established and then we built a prognostic model in accordance with the protein-protein interaction (PPI) network. Five HBV-related genes affecting prognosis were identified for constructing a prognostic model. Then, the samples were assigned into RS-high and -low groups as per their relevant prognostic risk score (RS). High-risk group showed worse prognosis, higher mutation rate of TP53, lower sensitivity to immunotherapy but higher response to chemotherapeutic drugs than low-risk group. Finally, the hepatitis B virus diagnostic model of Hepatocellular carcinoma was established. Conclusion: In conclusion, the prognostic and diagnostic models of hepatitis B virus gene-related Hepatocellular carcinoma were constructed. ABCB6, IPO7, TIMM9, FZD7, and ACAT1, the five HBV-related genes that affect the prognosis, can work as reliable biomarkers for the diagnosis of Hepatocellular carcinoma, giving a new insight for improving the prognosis, diagnosis, and treatment outcomes of HBV-type Hepatocellular carcinoma.
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Affiliation(s)
- Keqiang Ma
- Department of Hepatobiliary Pancreatic Surgery, Affiliated Huadu Hospital, Southern Medical University (People’s Hospital of Huadu District), Guangzhou, China
| | - Hongsheng Wu
- Department of Hepatobiliary Pancreatic Surgery, Affiliated Huadu Hospital, Southern Medical University (People’s Hospital of Huadu District), Guangzhou, China
| | - Lei Ji
- Department of Hepatobiliary Pancreatic Surgery, Renmin Hospital Hubei University of Medicine, Shiyan, China
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10
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Zhang X, Liu X, Zhu K, Zhang X, Li N, Sun T, Fan S, Dai L, Zhang J. CD5L-associated gene analyses highlight the dysregulations, prognostic effects, immune associations, and drug-sensitivity predicative potentials of LCAT and CDC20 in hepatocellular carcinoma. Cancer Cell Int 2022; 22:393. [PMID: 36494696 PMCID: PMC9733014 DOI: 10.1186/s12935-022-02820-7] [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: 05/30/2022] [Accepted: 12/01/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The dysregulation of CD5L has been reported in hepatocellular carcinoma (HCC). However, its functions in HCC were controversial. In this study, we aimed to identify CD5L-associated pathways and markers and explore their values in HCC diagnosis, prognosis and treatment. METHODS HCC datasets with gene expression profiles and clinical data in TCGA and ICGC were downloaded. The immune/stroma cell infiltrations were estimated with xCell. CD5L-associated pathways and CD5L-associated genes (CD5L-AGs) were identified with gene expression comparisons and gene set enrichment analysis (GSEA). Cox regression, Kaplan-Meier survival analysis, and least absolute shrinkage and selection operator (LASSO) regression analysis were performed. The correlations of the key genes with immune/stroma infiltrations, immunoregulators, and anti-cancer drug sensitivities in HCC were investigated. At protein level, the key genes dysregulations, their correlations and prognostic values were validated in clinical proteomic tumor analysis consortium (CPTAC) database. Serum CD5L and LCAT activity in 50 HCC and 30 normal samples were evaluated and compared. The correlations of serum LCAT activity with alpha-fetoprotein (AFP), albumin (ALB) and high-density lipoprotein (HDL) in HCC were also investigated. RESULTS Through systemic analyses, 14 CD5L-associated biological pathways, 256 CD5L-AGs and 28 CD5L-associated prognostic and diagnostic genes (CD5L-APDGs) were identified. A risk model consisting of LCAT and CDC20 was constructed for HCC overall survival (OS), which could discriminate HCC OS status effectively in both the training and the validation sets. CD5L, LCAT and CDC20 were shown to be significantly correlated with immune/stroma cell infiltrations, immunoregulators and 31 anti-cancer drug sensitivities in HCC. At protein level, the dysregulations of CD5L, LCAT and CDC20 were confirmed. LCAT and CDC20 were shown to be significantly correlated with proliferation marker MKI67. In serum, no significance of CD5L was shown. However, the lower activity of LCAT in HCC serum was obvious, as well as its significant positive correlations ALB and HDL concentrations. CONCLUSIONS CD5L, LCAT and CDC20 were dysregulated in HCC both at mRNA and protein levels. The LCAT-CDC20 signature might be new predicator for HCC OS. The associations of the three genes with HCC microenvironment and anti-cancer drug sensitivities would provide new clues for HCC immunotherapy and chemotherapy.
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Affiliation(s)
- Xiuzhi Zhang
- Department of Pathology, Henan Medical College, Zhengzhou, China
| | - Xiaoli Liu
- grid.414011.10000 0004 1808 090XLaboratory Department, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Keke Zhu
- Department of Pathology, Henan Medical College, Zhengzhou, China
| | - Xue Zhang
- grid.207374.50000 0001 2189 3846Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
| | - Ningning Li
- Department of Pathology, Henan Medical College, Zhengzhou, China
| | - Tao Sun
- Department of Pathology, Henan Medical College, Zhengzhou, China
| | - Shasha Fan
- grid.477407.70000 0004 1806 9292Oncology Department, The First Affiliated Hospital of Hunan Normal University, Hunan Provincial People’s Hospital, Changsha, China ,grid.411427.50000 0001 0089 3695Key Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province, Hunan Normal University, Changsha, China
| | - Liping Dai
- grid.207374.50000 0001 2189 3846Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
| | - Jinzhong Zhang
- Department of Pathology, Henan Medical College, Zhengzhou, China
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11
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Zhou C, Weng J, Gao Y, Liu C, Zhu X, Zhou Q, Li CW, Sun J, Atyah M, Yi Y, Ye Q, Shi Y, Dong Q, Liu Y, Hung MC, Ren N. A Novel mRNA Signature Related to Immunity to Predict Survival and Immunotherapy Response in Hepatocellular Carcinoma. J Clin Transl Hepatol 2022; 10:925-938. [PMID: 36304510 PMCID: PMC9547263 DOI: 10.14218/jcth.2021.00283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/29/2021] [Accepted: 11/22/2021] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND AND AIMS Hepatocellular carcinoma (HCC) is the most common primary liver cancer and the incidence and mortality rates are increasing. Given the limited treatments of HCC and promising application of immunotherapy for cancer, we aimed to identify an immune-related prognostic signature that can predict overall survival (OS) rates and immunotherapy response in HCC. METHODS The initial signature development was conducted using a training dataset from the Cancer Genome Atlas followed by independent internal and external validations from that resource and the Gene Expression Omnibus. A signature based nomogram was generated using multivariate Cox regression analysis. The associations of signature score with tumor immune phenotype and response to immunotherapy were analyzed using single-sample gene set enrichment analysis and tumor immune dysfunction and exclusion algorithm. A cohort from Zhongshan Hospital was employed to verify the predictive robustness of the signature regarding prognostic risk and immunotherapy response. RESULTS The prognostic signature, IGSHCC, consisting of 22 immune-related genes, had independent prognostic ability, with training and validation cohorts. Also, IGSHCC stratified HCC patients with different outcomes in subgroups. The prognostic accuracy of IGSHCC was better than three reported prognostic signatures. The IGSHCC-based nomogram had high accuracy and significant clinical benefits in predicting 3- and 5-year OS. IGSHCC reflected distinct immunosuppressive phenotypes in low- and high-score groups. Patients with low IGSHCC scores were more likely than those with high scores to benefit from immunotherapy. CONCLUSIONS IGSHCC predicted HCC prognosis and response to immunotherapy, and contributed to individualized clinical management.
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Affiliation(s)
- Chenhao Zhou
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
- Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jialei Weng
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Yuan Gao
- Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Biliary-Pancreatic Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chunxiao Liu
- Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xiaoqiang Zhu
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China
| | - Qiang Zhou
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Chia-Wei Li
- Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jialei Sun
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Manar Atyah
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Yong Yi
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Qinghai Ye
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
| | - Yi Shi
- Biomedical Research Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Qiongzhu Dong
- Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Institute of Fudan Minhang Academic Health System, and Key Laboratory of Whole-period Monitoring and Precise Intervention of Digestive Cancer (SMHC), Minhang Hospital & AHS, Fudan University, Shanghai, China
- Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Yingbin Liu
- Department of Biliary-Pancreatic Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Mien-Chie Hung
- Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Graduate Institute of Biomedical Sciences and Center for Molecular Medicine, China Medical University, Taichung
| | - Ning Ren
- Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China
- Institute of Fudan Minhang Academic Health System, and Key Laboratory of Whole-period Monitoring and Precise Intervention of Digestive Cancer (SMHC), Minhang Hospital & AHS, Fudan University, Shanghai, China
- Correspondence to: Ning Ren, Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai 200032, China. ORCID: https://orcid.org/0000-0001-9776-2471. Tel/Fax: +86-21-64041990, E-mail:
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12
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Zhu P, Zhang F, Deng W, Chen W. Integrative analysis of the characteristic of lipid metabolism-related genes for the prognostic prediction of hepatocellular carcinoma. Medicine (Baltimore) 2022; 101:e30695. [PMID: 36181094 PMCID: PMC9524878 DOI: 10.1097/md.0000000000030695] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Dysregulation of lipid metabolism is implicated in the progression of hepatocellular carcinoma (HCC). We therefore investigated the molecular characteristics of lipid-metabolism-related genes in HCC. METHODS Multi-dimensional bioinformatics analysis was conducted to comprehensively identify the lipid metabolism-related genes (LMRGs) from public databases, as well as the clinical information, immune features, and biological characteristics of HCC. The IMGR were then used to classify HCC into molecular phenotypes. Six lipid metabolism-related genes sets with the potential to predict the prognosis of HCC patients were identified. RESULTS A total of 770 HCC patients with complete clinical information and corresponding 776 LMRGs were downloaded from 3 databases. Univariate cox and non-negative matrix factorization analyses were used to classify HCC patients into 2 clusters. This molecular classification was associated with overall survival, clinical characteristics, and immune cells. The biological function of the differentially expressed LMRGs in the 2 clusters showed the genes associated with tumor-related metabolism pathways. A combination of multivariate/univariate cox regression and least absolute shrinkage and selection operator analyses were conducted to build a 6 LMRGs signature (6-IS) to predict the prognosis of HCC. The 6-IS signature was found to be an independent prognostic factor. Performance of the 6-IS prognostic signature was verified in a validation set and compared with an external data set. Results revealed the 6-IS signature could effectively predict the prognosis of patients with HCC. CONCLUSIONS This study provides new insights into the role of LMRG in the pathogenesis of HCC and presents a novel prognostic signature 6-IS monitoring the clinical course of HCC.
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Affiliation(s)
- Peng Zhu
- Central Laboratory, Shenzhen Pingshan District People’s Hospital, Pingshan General Hospital, Southern Medical University, Shenzhen, China
| | - Feng Zhang
- Intensive Care Unit, The First Affiliated Hospital of Jinan University, Guangzhou, 510632, China
| | - Weijie Deng
- Clinical Skills Center, Shenzhen Pingshan District People’s Hospital, Pingshan General Hospital, Southern Medical University, Shenzhen, China
| | - Wenbiao Chen
- Central Molecular Laboratory, People’s Hospital of Longhua, The Affiliated Hospital of Southern Medical University, Shenzhen, China
- Department of Respiratory Medicine, People’s Hospital of Longhua, The Affiliated Hospital of Southern Medical University, Shenzhen, China
- *Correspondence: Wenbiao Chen, Central Molecular Laboratory, People’s Hospital of Longhua, The Affiliated Hospital of Southern Medical University, Shenzhen, 518110, China (e-mail: )
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13
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Ren Y, Qin Z, Wang Z, Wei S, Chen H, Zhu T, Liu L, Zhao Y, Ding B, Song W. Condensed tannins from
Ulmus pumila
L. leaves induce
G2
/M phase arrest and apoptosis via caspase‐cascade activation in
TFK
‐1 cholangiocarcinoma cells. J Food Biochem 2022; 46:e14374. [DOI: 10.1111/jfbc.14374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 06/06/2022] [Accepted: 06/23/2022] [Indexed: 12/01/2022]
Affiliation(s)
- Yuanjing Ren
- College of Life Science Yangtze University Jingzhou China
- College of Life Science and Engineering Henan University of Urban Construction Pingdingshan China
| | - Zeya Qin
- College of Life Science Yangtze University Jingzhou China
| | - Zhanchang Wang
- Forestry and Fruit Tree Research Institute Wuhan Academy of Agricultural Sciences Wuhan China
| | - Shudong Wei
- College of Life Science Yangtze University Jingzhou China
| | - Hui Chen
- College of Life Science Yangtze University Jingzhou China
| | - Tao Zhu
- College of Life Science and Engineering Henan University of Urban Construction Pingdingshan China
| | - Lulu Liu
- College of Life Science Yangtze University Jingzhou China
| | - Yaying Zhao
- College of Life Science Yangtze University Jingzhou China
| | - Baomiao Ding
- College of Life Science Yangtze University Jingzhou China
| | - Wei Song
- College of Life Science and Engineering Henan University of Urban Construction Pingdingshan China
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14
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Jiang X, Lin J, Dong M, Liu X, Huang Y, Zhang H, Ye R, Zhou H, Yan C, Yuan S, Chen L, Jiang R, Zheng K, Jin W. Overexpression of Pregnancy Zone Protein in Fat Antagonizes Diet-Induced Obesity Under an Intermittent Fasting Regime. Front Physiol 2022; 13:950619. [PMID: 36051914 PMCID: PMC9424687 DOI: 10.3389/fphys.2022.950619] [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: 05/23/2022] [Accepted: 06/22/2022] [Indexed: 11/13/2022] Open
Abstract
The intermittent fasting regimen (IFR) has been certified as an effective strategy for improving metabolism. But the underlying mechanism is still obscure. Beige induction in white adipose tissue (WAT) by IFR may account for this. It has been demonstrated that the erupting of pregnancy zone protein (PZP) from the liver coincides with membrane translocation of grp78 in brown adipocytes during IFR to activate brown adipose tissue (BAT), which may partly explain the metabolic benefits of IFR. Liver-derived PZP appears to be responsible for all metabolic regulatory functions; the effect of boosting energy expenditure disappeared in liver-deficient mice. To verify whether any liver-specific modification was essential for functional PZP, we used the PZP adipose tissue-specific overexpression mice model (PZP TG). We found that the metabolic disorders induced by high-fat diet were improved in PZP TG mice under IFR. Additionally, in addition to the activation of BAT, UCP1 protein and angiogenesis were increased in WAT, as well as the expression of genes associated with glucose utilization. These results demonstrate that PZP fat-specific TG increased the energy conversion of WAT, indicating that WAT may be another direct target for PZP during IFR.
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Affiliation(s)
- Xiaoxiao Jiang
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jun Lin
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Meng Dong
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Xiaomeng Liu
- Institute of Neuroscience and Translational Medicine, College of Life Science and Agronomy, Zhoukou Normal University, Zhoukou, China
| | - Yuanyuan Huang
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Hanlin Zhang
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Rongcai Ye
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Huiqiao Zhou
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chunlong Yan
- Agriculture College of Yanbian University, Yanji, China
| | - Shouli Yuan
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Li Chen
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Rui Jiang
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Kexin Zheng
- Institute of Infectious Disease, Ditan Hospital, Capital Medical University, Beijing, China
| | - Wanzhu Jin
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- *Correspondence: Wanzhu Jin,
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15
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Screening of Prognostic Markers for Hepatocellular Carcinoma Patients Based on Multichip Combined Analysis. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:6881600. [PMID: 35872941 PMCID: PMC9303125 DOI: 10.1155/2022/6881600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 06/28/2022] [Indexed: 12/24/2022]
Abstract
Methods GSE (14520, 36376, 57957, 76427) datasets were accessed from GEO database. 55 differential mRNAs (DEGs) were obtained by differential analysis based on the datasets. GO and KEGG analysis results indicated that the DEGs were enriched in xenobiotic metabolic process and other pathways. Expression profiles and clinical data of TCGA-LIHC mRNAs were from TCGA database. We established a prognostic model of HCC through univariate and multivariate Cox risk regression analyses. ROC curve analysis was used to examine the prognostic model performance. GSEA analysis was performed between the high- and low-risk score sample groups. Results A 4-gene HCC prognostic model was constructed, in which the gene expressions correlated to HCC patients' survival. The AUC value presented 0.734 in the ROC analysis for the prognostic model. Conclusion The four-gene model could be introduced as an independent prognostic factors to assess HCC patients' survival status.
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16
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Sharifi H, Safarpour H, Moossavi M, Khorashadizadeh M. Identification of Potential Prognostic Markers and Key Therapeutic Targets in Hepatocellular Carcinoma Using Weighted Gene Co-Expression Network Analysis: A Systems Biology Approach. IRANIAN JOURNAL OF BIOTECHNOLOGY 2022; 20:e2968. [PMID: 36381283 PMCID: PMC9618018 DOI: 10.30498/ijb.2022.269817.2968] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND As the most prevalent form of liver cancer, hepatocellular carcinoma (HCC) ranks the fifth highest cause of cancer-related death worldwide. Despite recent advancements in diagnostic and therapeutic techniques, the prognosis for HCC is still unknown. OBJECTIVES This study aimed to identify potential genes contributing to HCC pathogenicity. MATERIALS AND METHODS To this end, we examined the GSE39791 microarray dataset, which included 72 HCC samples and 72 normal samples. An investigation of co-expression networks using WGCNA found a highly conserved blue module with 665 genes that were strongly linked to HCC. RESULTS APOF, NAT2, LCAT, TTC36, IGFALS, ASPDH, and VIPR1 were the blue module's top 7 hub genes. According to the results of hub gene enrichment, the most related issues in the biological process and KEGG were peroxisome organization and metabolic pathways, respectively. In addition, using the drug-target network, we discovered 19 FDA-approved medication candidates for different reasons that might potentially be employed to treat HCC patients through the modulation of 3 hub genes of the co-expression network (LCAT, NAT2, and VIPR1). Our findings also demonstrated that the 3 scientifically validated miRNAs regulated the co-expression network by the VIPR1 hub gene. CONCLUSION We found co-expressed gene modules and hub genes linked with HCC advancement, offering insights into the mechanisms underlying HCC progression as well as some potential HCC treatments.
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Affiliation(s)
- Hengameh Sharifi
- Department of Molecular Medicine, Faculty of Medicine, Birjand University of Medical Sciences, Birjand, Iran
| | - Hossein Safarpour
- Cellular & Molecular Research Center, Birjand University of Medical Sciences, Birjand, Iran
| | - Maryam Moossavi
- Department of Molecular Medicine, Faculty of Medicine, Birjand University of Medical Sciences, Birjand, Iran
| | - Mohsen Khorashadizadeh
- Department of Molecular Medicine, Faculty of Medicine, Birjand University of Medical Sciences, Birjand, Iran,
Cellular & Molecular Research Center, Birjand University of Medical Sciences, Birjand, Iran,
3Department of Medical Biotechnology, School of Medicine, Birjand University of Medical Sciences, Birjand, Iran
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17
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Ding Y, Liu X, Yuan Y, Sheng Y, Li D, Ojha SC, Sun C, Deng C. THRSP identified as a potential hepatocellular carcinoma marker by integrated bioinformatics analysis and experimental validation. Aging (Albany NY) 2022; 14:1743-1766. [PMID: 35196258 PMCID: PMC8908915 DOI: 10.18632/aging.203900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 01/17/2022] [Indexed: 11/25/2022]
Abstract
Hepatocellular carcinoma (HCC) is the most common malignant liver tumor with high mortality and poor prognosis worldwide. This study aimed to identify hub genes and investigate the underlying molecular mechanisms in HCC progression by integrated bioinformatics analysis and experimental validation. Based on the Gene Expression Omnibus (GEO) databases and The Cancer Genome Atlas (TCGA), 12 critical differential co-expression genes were identified between tumor and normal tissues. Via survival analysis, we found higher expression of LCAT, ACSM3, IGF1, SRD5A2, THRSP and ACADS was associated with better prognoses in HCC patients. Among which, THRSP was selected for the next investigations. We found that THRSP mRNA expression was negatively correlated with its methylation and closely associated with clinical characteristics in HCC patients. Moreover, THRSP expression had a negative correlation with the infiltration levels of several immune cells (e.g., B cells and CD4+ T cells). qRT-PCR verified that THRSP was lower expressed in HCC tissues and cell lines compared with control. Silencing of THRSP promoted the migration, invasion, proliferation, and inhibited cell apoptosis of HCCLM and Huh7 cell lines. Decreased expression of THRSP promoted HCC progression by NF-κB, ERK1/2, and p38 MAPK signaling pathways. In conclusion, THRSP might serve as a novel biomarker and therapeutic target of HCC.
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Affiliation(s)
- Yuxi Ding
- The Department of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,The Department of Tuberculosis, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,Laboratory of Infection and Immunity, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
| | - Xiaoling Liu
- The Department of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,The Department of Tuberculosis, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,Laboratory of Infection and Immunity, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
| | - Yue Yuan
- The Department of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,The Department of Tuberculosis, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,Laboratory of Infection and Immunity, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
| | - Yunjian Sheng
- The Department of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,The Department of Tuberculosis, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,Laboratory of Infection and Immunity, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
| | - Decheng Li
- The Department of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,The Department of Tuberculosis, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,Laboratory of Infection and Immunity, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
| | - Suvash Chandra Ojha
- The Department of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,The Department of Tuberculosis, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,Laboratory of Infection and Immunity, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
| | - Changfeng Sun
- The Department of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,The Department of Tuberculosis, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,Laboratory of Infection and Immunity, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
| | - Cunliang Deng
- The Department of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,The Department of Tuberculosis, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China.,Laboratory of Infection and Immunity, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
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18
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Tevini J, Eder SK, Huber-Schönauer U, Niederseer D, Strebinger G, Gostner JM, Aigner E, Datz C, Felder TK. Changing Metabolic Patterns along the Colorectal Adenoma–Carcinoma Sequence. J Clin Med 2022; 11:jcm11030721. [PMID: 35160173 PMCID: PMC8836789 DOI: 10.3390/jcm11030721] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 01/18/2022] [Accepted: 01/27/2022] [Indexed: 02/06/2023] Open
Abstract
Colorectal cancer (CRC) is a major public health burden and one of the leading causes of cancer-related deaths worldwide. Screening programs facilitate early diagnosis and can help to reduce poor outcomes. Serum metabolomics can extract vital molecular information that may increase the sensitivity and specificity of colonoscopy in combination with histopathological examination. The present study identifies serum metabolite patterns of treatment-naïve patients, diagnosed with either advanced adenoma (AA) or CRC in colonoscopy screenings, in the framework of the SAKKOPI (Salzburg Colon Cancer Prevention Initiative) program. We used a targeted flow injection analysis and liquid chromatography-tandem mass spectrometry metabolomics approach (FIA- and LC-MS/MS) to characterise the serum metabolomes of an initial screening cohort and two validation cohorts (in total 66 CRC, 76 AA and 93 controls). The lipidome was significantly perturbed, with a proportion of lipid species being downregulated in CRC patients, as compared to AA and controls. The predominant alterations observed were in the levels of lyso-lipids, glycerophosphocholines and acylcarnitines, but additionally, variations in the quantity of hydroxylated sphingolipids could be detected. Changed amino acid metabolism was restricted mainly to metabolites of the arginine/dimethylarginine/NO synthase pathway. The identified metabolic divergences observed in CRC set the foundation for mechanistic studies to characterise biochemical pathways that become deregulated during progression through the adenoma to carcinoma sequence and highlight the key importance of lipid metabolites. Biomarkers related to these pathways could improve the sensitivity and specificity of diagnosis, as well as the monitoring of therapies.
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Affiliation(s)
- Julia Tevini
- Department of Laboratory Medicine, Paracelsus Medical University, 5020 Salzburg, Austria;
| | - Sebastian K. Eder
- First Department of Medicine, Paracelsus Medical University, 5020 Salzburg, Austria; (S.K.E.); (E.A.)
- Department of Pediatrics and Adolescent Medicine, St. Anna Children’s Hospital, Medical University of Vienna, 1090 Vienna, Austria
| | - Ursula Huber-Schönauer
- Department of Internal Medicine, Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, 5110 Oberndorf, Austria; (U.H.-S.); (G.S.)
| | - David Niederseer
- Department of Cardiology, University Heart Center Zurich, University Hospital Zurich, University of Zurich, 8091 Zurich, Switzerland;
| | - Georg Strebinger
- Department of Internal Medicine, Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, 5110 Oberndorf, Austria; (U.H.-S.); (G.S.)
| | - Johanna M. Gostner
- Institute of Medical Biochemistry, Innsbruck Medical University, 6020 Innsbruck, Austria;
| | - Elmar Aigner
- First Department of Medicine, Paracelsus Medical University, 5020 Salzburg, Austria; (S.K.E.); (E.A.)
| | - Christian Datz
- Department of Internal Medicine, Hospital Oberndorf, Teaching Hospital of the Paracelsus Medical University Salzburg, 5110 Oberndorf, Austria; (U.H.-S.); (G.S.)
- Correspondence: (C.D.); (T.K.F.); Tel.: +43-5-7255-58126 (T.K.F.)
| | - Thomas K. Felder
- Department of Laboratory Medicine, Paracelsus Medical University, 5020 Salzburg, Austria;
- Correspondence: (C.D.); (T.K.F.); Tel.: +43-5-7255-58126 (T.K.F.)
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19
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Li L, Cao Y, Fan Y, Li R. Gene signature to predict prognostic survival of hepatocellular carcinoma. Open Med (Wars) 2022; 17:135-150. [PMID: 35071775 PMCID: PMC8742913 DOI: 10.1515/med-2021-0405] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 10/18/2021] [Accepted: 11/09/2021] [Indexed: 12/11/2022] Open
Abstract
Hepatocellular carcinoma (HCC) has a high incidence and poor prognosis and is the second most fatal cancer, and certain HCC patients also show high heterogeneity. This study developed a prognostic model for predicting clinical outcomes of HCC. RNA and microRNA (miRNA) sequencing data of HCC were obtained from the cancer genome atlas. RNA dysregulation between HCC tumors and adjacent normal liver tissues was examined by DESeq algorithms. Survival analysis was conducted to determine the basic prognostic indicators. We identified competing endogenous RNA (ceRNA) containing 15,364 pairs of mRNA–long noncoding RNA (lncRNA). An imbalanced ceRNA network comprising 8 miRNAs, 434 mRNAs, and 81 lncRNAs was developed using hypergeometric test. Functional analysis showed that these RNAs were closely associated with biosynthesis. Notably, 53 mRNAs showed a significant prognostic correlation. The least absolute shrinkage and selection operator’s feature selection detected four characteristic genes (SAPCD2, DKC1, CHRNA5, and UROD), based on which a four-gene independent prognostic signature for HCC was constructed using Cox regression analysis. The four-gene signature could stratify samples in the training, test, and external validation sets (p <0.01). Five-year survival area under ROC curve (AUC) in the training and validation sets was greater than 0.74. The current prognostic gene model exhibited a high stability and accuracy in predicting the overall survival (OS) of HCC patients.
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Affiliation(s)
- Li Li
- Department of Oncology, The Comprehensive Cancer Centre of Drum Tower Hospital, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University , Nanjing , Jiangsu, 210000 , China
| | - Yundi Cao
- Department of Medical Oncology, Affiliated Taikang Xianlin Drum Tower Hospital, Medical School of Nanjing University , Nanjing , Jiangsu , China
| | - YingRui Fan
- Department of Medical Oncology, Affiliated Taikang Xianlin Drum Tower Hospital, Medical School of Nanjing University , Nanjing , Jiangsu , China
| | - Rong Li
- Department of Medical Oncology, Affiliated Taikang Xianlin Drum Tower Hospital, Medical School of Nanjing University , Nanjing , Jiangsu , China
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20
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Lin H, Xie Y, Kong Y, Yang L, Li M. Identification of molecular subtypes and prognostic signature for hepatocellular carcinoma based on genes associated with homologous recombination deficiency. Sci Rep 2021; 11:24022. [PMID: 34912005 PMCID: PMC8674316 DOI: 10.1038/s41598-021-03432-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 12/03/2021] [Indexed: 01/15/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is a rapidly developing digestive tract carcinoma. The prognosis of patients and side effects caused by clinical treatment should be better improved. Nonnegative matrix factorization (NMF) clustering was performed using 109 homologous recombination deficiency (HRD)-related of HCC genes from The Cancer Genome Atlas (TCGA) database. Limma was applied to analyze subtype differences. Immune scores and clinical characteristics of different subtypes were compared. An HRD signature were built with least absolute shrinkage operator (LASSO) and multivariate Cox analysis. Performance of the signature system was then assessed by Kaplan–Meier curves and receiver operating characteristic (ROC) curves. We identified two molecular subtypes (C1 and C2), with C2 showing a significantly better prognosis than C1. C1 contained 3623 differentially expressed genes. A 4-gene prognostic signature for HCC was established, and showed a high predicting accuracy in validation sets, entire TCGA data set, HCCDB18 and GSE14520 queues. Moreover, the risk score was validated as an independent prognostic marker for HCC. Our research identified two molecular subtypes of HCC, and proposed a novel scoring system for evaluating the prognosis of HCC in clinical practice.
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Affiliation(s)
- Hongsheng Lin
- Guangxi University of Chinese Medicine, Nanning, 530200, China.,Department of Laboratory, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning, 530023, China.,Guangxi Medical University, Nanning, 530021, China.,Department of Microbiology, School of Basic Medical Sciences, Guangxi Medical University, Nanning, 530021, China
| | - Yangyi Xie
- Guangxi University of Chinese Medicine, Nanning, 530200, China.,The First Clinical Faculty of Guangxi University of Chinese Medicine, Nanning, 530200, China
| | - Yinzhi Kong
- Guangxi University of Chinese Medicine, Nanning, 530200, China.,The First Clinical Faculty of Guangxi University of Chinese Medicine, Nanning, 530200, China
| | - Li Yang
- Guangxi University of Chinese Medicine, Nanning, 530200, China.,Department of Laboratory, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning, 530023, China
| | - Mingfen Li
- Guangxi University of Chinese Medicine, Nanning, 530200, China. .,Department of Laboratory, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning, 530023, China.
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21
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Owens AR, McInerney CE, Prise KM, McArt DG, Jurek-Loughrey A. Novel deep learning-based solution for identification of prognostic subgroups in liver cancer (Hepatocellular carcinoma). BMC Bioinformatics 2021; 22:563. [PMID: 34819028 PMCID: PMC8611905 DOI: 10.1186/s12859-021-04454-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 10/20/2021] [Indexed: 02/07/2023] Open
Abstract
Background Liver cancer (Hepatocellular carcinoma; HCC) prevalence is increasing and with poor clinical outcome expected it means greater understanding of HCC aetiology is urgently required. This study explored a deep learning solution to detect biologically important features that distinguish prognostic subgroups. A novel architecture of an Artificial Neural Network (ANN) trained with a customised objective function (LRSC) was developed. The ANN should discover new data representations, to detect patient subgroups that are biologically homogenous (clustering loss) and similar in survival (survival loss) while removing noise from the data (reconstruction loss). The model was applied to TCGA-HCC multi-omics data and benchmarked against baseline models that only use a reconstruction objective function (BCE, MSE) for learning. With the baseline models, the new features are then filtered based on survival information and used for clustering patients. Different variants of the customised objective function, incorporating only reconstruction and clustering losses (LRC); and reconstruction and survival losses (LRS) were also evaluated. Robust features consistently detected were compared between models and validated in TCGA and LIRI-JP HCC cohorts. Results The combined loss (LRSC) discovered highly significant prognostic subgroups (P-value = 1.55E−77) with more accurate sample assignment (Silhouette scores: 0.59–0.7) compared to baseline models (0.18–0.3). All LRSC bottleneck features (N = 100) were significant for survival, compared to only 11–21 for baseline models. Prognostic subgroups were not explained by disease grade or risk factors. Instead LRSC identified robust features including 377 mRNAs, many of which were novel (61.27%) compared to those identified by the other losses. Some 75 mRNAs were prognostic in TCGA, while 29 were prognostic in LIRI-JP also. LRSC also identified 15 robust miRNAs including two novel (hsa-let-7g; hsa-mir-550a-1) and 328 methylation features with 71% being prognostic. Gene-enrichment and Functional Annotation Analysis identified seven pathways differentiating prognostic clusters. Conclusions Combining cluster and survival metrics with the reconstruction objective function facilitated superior prognostic subgroup identification. The hybrid model identified more homogeneous clusters that consequently were more biologically meaningful. The novel and prognostic robust features extracted provide additional information to improve our understanding of a complex disease to help reveal its aetiology. Moreover, the gene features identified may have clinical applications as therapeutic targets. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-021-04454-4.
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Affiliation(s)
- Alice R Owens
- School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, 18 Malone Road, Belfast, BT9 5BN, Northern Ireland, UK
| | - Caitríona E McInerney
- Patrick G. Johnson Centre for Cancer Research, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Kevin M Prise
- Patrick G. Johnson Centre for Cancer Research, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Darragh G McArt
- Patrick G. Johnson Centre for Cancer Research, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Anna Jurek-Loughrey
- School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, 18 Malone Road, Belfast, BT9 5BN, Northern Ireland, UK.
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22
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Xu D, Wang Y, Wu J, Lin S, Chen Y, Zheng J. Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma. Cancer Cell Int 2021; 21:621. [PMID: 34819088 PMCID: PMC8613962 DOI: 10.1186/s12935-021-02326-8] [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: 07/15/2021] [Accepted: 11/10/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND The aim of this study was to construct a model based on the prognostic features associated with epithelial-mesenchymal transition (EMT) to explore the various mechanisms and therapeutic strategies available for the treatment of metastasis and invasion by hepatocellular carcinoma (HCC) cells. METHODS EMT-associated genes were identified, and their molecular subtypes were determined by consistent clustering analysis. The differentially expressed genes (DEGs) among the molecular subtypes were ascertained using the limma package and they were subjected to functional enrichment analysis. The immune cell scores of the molecular subtypes were evaluated using ESTIMATE, MCPcounter, and GSCA packages of R. A multi-gene prognostic model was constructed using lasso regression, and the immunotherapeutic effects of the model were analyzed using the Imvigor210 cohort. In addition, immunohistochemical analysis was performed on a cohort of HCC tissue to validate gene expression. RESULTS Based on the 59 EMT-associated genes identified, the 365-liver hepatocellular carcinoma (LIHC) samples were divided into two subtypes, C1 and C2. The C1 subtype mostly showed poor prognosis, had higher immune scores compared to the C2 subtype, and showed greater correlation with pathways of tumor progression. A four-gene signature construct was fabricated based on the 1130 DEGs among the subtypes. The construct was highly robust and showed stable predictive efficacy when validated using datasets from different platforms (HCCDB18 and GSE14520). Additionally, compared to currently existing models, our model demonstrated better performance. The results of the immunotherapy cohort showed that patients in the low-risk group have a better immune response, leading to a better patient's prognosis. Immunohistochemical analysis revealed that the expression levels of the FTCD, PON1, and TMEM45A were significantly over-expressed in 41 normal samples compared to HCC samples, while that of the G6PD was significantly over-expressed in cancerous tissues. CONCLUSIONS The four-gene signature construct fabricated based on the EMT-associated genes provides valuable information to further study the pathogenesis and clinical management of HCC.
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Affiliation(s)
- Dafeng Xu
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Yu Wang
- Geriatric Medicine Center, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Jincai Wu
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Shixun Lin
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Yonghai Chen
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Jinfang Zheng
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China.
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23
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Lin J, Jiang X, Dong M, Liu X, Shen Q, Huang Y, Zhang H, Ye R, Zhou H, Yan C, Yuan S, Wu X, Chen L, Wang Y, He M, Tao Y, Zhang Z, Jin W. Hepatokine Pregnancy Zone Protein Governs the Diet-Induced Thermogenesis Through Activating Brown Adipose Tissue. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:e2101991. [PMID: 34514733 PMCID: PMC8564441 DOI: 10.1002/advs.202101991] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 07/23/2021] [Indexed: 05/06/2023]
Abstract
Intermittent fasting (IF), as a dietary intervention for weight loss, takes effects primarily through increasing energy expenditure. However, whether inter-organ systems play a key role in IF remains unclear. Here, a novel hepatokine, pregnancy zone protein (PZP) is identified, which has significant induction during the refeeding stage of IF. Further, loss of function studies and protein therapeutic experiment in mice revealed that PZP promotes diet-induced thermogenesis through activating brown adipose tissue (BAT). Mechanistically, circulating PZP can bind to cell surface glucose-regulated protein of 78 kDa (GRP78) to promote uncoupling protein 1 (UCP1) expression via a p38 MAPK-ATF2 signaling pathway in BAT. These studies illuminate a systemic regulation in which the IF promotes BAT thermogenesis through the endocrinal system and provide a novel potential target for treating obesity and related disorders.
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Affiliation(s)
- Jun Lin
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
| | - Xiaoxiao Jiang
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
- University of Chinese Academy of SciencesBeijing100049China
| | - Meng Dong
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
| | - Xiaomeng Liu
- Institute of Neuroscience and Translational MedicineCollege of Life Science and AgronomyZhoukou Normal UniversityZhoukou466000China
| | - Qiwei Shen
- Department of General SurgeryHuashan HospitalFudan UniversityShanghaiChina
| | - Yuanyuan Huang
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
- University of Chinese Academy of SciencesBeijing100049China
| | - Hanlin Zhang
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
- University of Chinese Academy of SciencesBeijing100049China
| | - Rongcai Ye
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
- University of Chinese Academy of SciencesBeijing100049China
| | - Huiqiao Zhou
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
- University of Chinese Academy of SciencesBeijing100049China
| | - Chunlong Yan
- College of AgricultureYanbian UniversityYanji133000China
| | - Shouli Yuan
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
- University of Chinese Academy of SciencesBeijing100049China
| | - Xiangnan Wu
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
- University of Chinese Academy of SciencesBeijing100049China
| | - Li Chen
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
- University of Chinese Academy of SciencesBeijing100049China
| | - Yanfang Wang
- State Key Laboratory of Animal NutritionInstitute of Animal ScienceChinese Academy of Agricultural SciencesBeijing100193China
| | - Min He
- Division of Endocrinology and MetabolismHuashan HospitalFudan UniversityShanghaiChina
| | - Yi Tao
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
| | - Zhaoyun Zhang
- Division of Endocrinology and MetabolismHuashan HospitalFudan UniversityShanghaiChina
| | - Wanzhu Jin
- Key Laboratory of Animal Ecology and Conservation BiologyInstitute of ZoologyChinese Academy of SciencesBeijing100101China
- University of Chinese Academy of SciencesBeijing100049China
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24
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Xu D, Wang Y, Wu J, Zhang Y, Liu Z, Chen Y, Zheng J. Systematic Characterization of Novel Immune Gene Signatures Predicts Prognostic Factors in Hepatocellular Carcinoma. Front Cell Dev Biol 2021; 9:686664. [PMID: 34631695 PMCID: PMC8494981 DOI: 10.3389/fcell.2021.686664] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 08/20/2021] [Indexed: 01/08/2023] Open
Abstract
Background: The prognosis of patients with hepatocellular carcinoma (HCC) is negatively affected by the lack of effective prognostic indicators. The change of tumor immune microenvironment promotes the development of HCC. This study explored new markers and predicted the prognosis of HCC patients by systematically analyzing immune characteristic genes. Methods: Immune-related genes were obtained, and the differentially expressed immune genes (DEIGs) between tumor and para-cancer samples were identified and analyzed using gene expression profiles from TCGA, HCCDB, and GEO databases. An immune prognosis model was also constructed to evaluate the predictive performance in different cohorts. The high and low groups were divided based on the risk score of the model, and different algorithms were used to evaluate the tumor immune infiltration cell (TIIC). The expression and prognosis of core genes in pan-cancer cohorts were analyzed, and gene enrichment analysis was performed using clusterProfiler. Finally, the expression of the hub genes of the model was validated by clinical samples. Results: Based on the analysis of 730 immune-related genes, we identified 64 common DEIGs. These genes were enriched in the tumor immunologic related signaling pathways. The first 15 genes were selected using RankAggreg analysis, and all the genes showed a consistent expression trend across multi-cohorts. Based on lasso cox regression analysis, a 5-gene signature risk model (ATG10, IL18RAP, PRKCD, SLC11A1, and SPP1) was constructed. The signature has strong robustness and can stabilize different cohorts (TCGA-LIHC, HCCDB18, and GSE14520). Compared with other existing models, our model has better performance. CIBERSORT was used to assess the landscape maps of 22 types of immune cells in TCGA, GSE14520, and HCCDB18 cohorts, and found a consistent trend in the distribution of TIIC. In the high-risk score group, scores of Macrophages M1, Mast cell resting, and T cells CD8 were significantly lower than those of the low-risk score group. Different immune expression characteristics, lead to the different prognosis. Western blot demonstrated that ATG10, PRKCD, and SPP1 were highly expressed in cancer tissues, while IL18RAP and SLC11A1 expression in cancer tissues was lower. In addition, IL18RAP has a highly positive correlation with B cell, macrophage, Neutrophil, Dendritic cell, CD8 cell, and CD4 cell. The SPP1, PRKCD, and SLC11A1 genes have the strongest correlation with macrophages. The expression of ATG10, IL18RAP, PRKCD, SLC11A1, and SPP1 genes varies among different immune subtypes and between different T stages. Conclusion: The 5-immu-gene signature constructed in this study could be utilized as a new prognostic marker for patients with HCC.
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Affiliation(s)
- Dafeng Xu
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Yu Wang
- Geriatric Medicine Center, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Jincai Wu
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Yuliang Zhang
- Department of Otolaryngology-Head and Neck Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Zhehao Liu
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Yonghai Chen
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Jinfang Zheng
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
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25
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Lin Z, Xie YZ, Zhao MC, Hou PP, Tang J, Chen GL. Xanthine dehydrogenase as a prognostic biomarker related to tumor immunology in hepatocellular carcinoma. Cancer Cell Int 2021; 21:475. [PMID: 34496841 PMCID: PMC8425161 DOI: 10.1186/s12935-021-02173-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 08/23/2021] [Indexed: 01/10/2023] Open
Abstract
Background Xanthine dehydrogenase (XDH) is a critical enzyme involved in the oxidative metabolism of purines, pterin and aldehydes and a central component of the innate immune system. However, the prognostic value of XDH in predicting tumor-infiltrating lymphocyte abundance, the immune response, and survival in different cancers, including hepatocellular carcinoma (HCC), is still unclear. Methods XDH expression was analyzed in multiple databases, including Oncomine, the Tumor Immune Estimation Resource (TIMER), the Kaplan–Meier plotter database, the Gene Expression Profiling Interactive Analysis (GEPIA) database, and The Cancer Genome Atlas (TCGA). XDH-associated transcriptional profiles were detected with an mRNA array, and the levels of infiltrating immune cells were validated by immunohistochemistry (IHC) of HCC tissues. A predictive signature containing multiple XDH-associated immune genes was established using the Cox regression model. Results Decreased XDH mRNA expression was detected in human cancers originating from the liver, bladder, breast, colon, bile duct, kidney, and hematolymphoid system. The prognostic potential of XDH mRNA expression was also significant in certain other cancers, including HCC, breast cancer, kidney or bladder carcinoma, gastric cancer, mesothelioma, lung cancer, and ovarian cancer. In HCC, a low XDH mRNA level predicted poorer overall survival, disease-specific survival, disease-free survival, and progression-free survival. The prognostic value of XDH was independent of the clinical features of HCC patients. Indeed, XDH expression in HCC activated several immune-related pathways, including the T cell receptor, PI3K-AKT, and MAPK signaling pathways, which induced a cytotoxic immune response. Importantly, the microenvironment of XDHhigh HCC tumors contained abundant infiltrating CD8 + T cells but not exhausted T cells. A risk prediction signature based on multiple XDH-associated immune genes was revealed as an independent predictor in the TCGA liver cancer cohort. Conclusion These findings suggest that XDH is a valuable prognostic biomarker in HCC and other cancers and indicate that it may function in tumor immunology. Loss of XDH expression may be an immune evasion mechanism for HCC. Supplementary Information The online version contains supplementary material available at 10.1186/s12935-021-02173-7.
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Affiliation(s)
- Zhen Lin
- Department of Oncology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, China.,Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, 91054, Erlangen, Germany
| | - Yi-Zhao Xie
- Department of Medical Oncology, Fudan University, Shanghai Cancer Center, Shanghai, 200032, China.,Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Ming-Chun Zhao
- Department of Pathology, Guilin Hospital of Chinese Traditional and Western Medicine, Guilin, 541004, China
| | - Pin-Pin Hou
- Central Laboratory, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201114, China
| | - Juan Tang
- Department of Pathology, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, China.
| | - Guang-Liang Chen
- Department of Medical Oncology, Fudan University, Shanghai Cancer Center, Shanghai, 200032, China. .,Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, 200032, China.
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26
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Garcia-Ruiz C, Conde de la Rosa L, Ribas V, Fernandez-Checa JC. MITOCHONDRIAL CHOLESTEROL AND CANCER. Semin Cancer Biol 2021; 73:76-85. [PMID: 32805396 PMCID: PMC7882000 DOI: 10.1016/j.semcancer.2020.07.014] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 07/22/2020] [Accepted: 07/29/2020] [Indexed: 12/11/2022]
Abstract
Cholesterol is a crucial component of membrane bilayers that determines their physical and functional properties. Cells largely satisfy their need for cholesterol through the novo synthesis from acetyl-CoA and this demand is particularly critical for cancer cells to sustain dysregulated cell proliferation. However, the association between serum or tissue cholesterol levels and cancer development is not well established as epidemiologic data do not consistently support this link. While most preclinical studies focused on the role of total celular cholesterol, the specific contribution of the mitochondrial cholesterol pool to alterations in cancer cell biology has been less explored. Although low compared to other bilayers, the mitochondrial cholesterol content plays an important physiological function in the synthesis of steroid hormones in steroidogenic tissues or bile acids in the liver and controls mitochondrial function. In addition, mitochondrial cholesterol metabolism generates oxysterols, which in turn, regulate multiple pathways, including cholesterol and lipid metabolism as well as cell proliferation. In the present review, we summarize the regulation of mitochondrial cholesterol, including its role in mitochondrial routine performance, cell death and chemotherapy resistance, highlighting its potential contribution to cancer. Of particular relevance is hepatocellular carcinoma, whose incidence in Western countries had tripled in the past decades due to the obesity and type II diabetes epidemic. A better understanding of the role of mitochondrial cholesterol in cancer development may open up novel opportunities for cancer therapy.
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Affiliation(s)
- Carmen Garcia-Ruiz
- Department of Cell Death and Proliferation, Institute of Biomedical Research of Barcelona (IIBB), CSIC, Barcelona, Spain; Liver Unit, Hospital Clinic I Provincial de Barcelona, Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Center for the Study of Liver and Gastrointestinal Diseases (CIBERehd), Carlos III National Institute of Health, Madrid, Spain; Center for ALPD, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Laura Conde de la Rosa
- Department of Cell Death and Proliferation, Institute of Biomedical Research of Barcelona (IIBB), CSIC, Barcelona, Spain; Liver Unit, Hospital Clinic I Provincial de Barcelona, Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Center for the Study of Liver and Gastrointestinal Diseases (CIBERehd), Carlos III National Institute of Health, Madrid, Spain
| | - Vicent Ribas
- Department of Cell Death and Proliferation, Institute of Biomedical Research of Barcelona (IIBB), CSIC, Barcelona, Spain; Liver Unit, Hospital Clinic I Provincial de Barcelona, Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Center for the Study of Liver and Gastrointestinal Diseases (CIBERehd), Carlos III National Institute of Health, Madrid, Spain
| | - Jose C Fernandez-Checa
- Department of Cell Death and Proliferation, Institute of Biomedical Research of Barcelona (IIBB), CSIC, Barcelona, Spain; Liver Unit, Hospital Clinic I Provincial de Barcelona, Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Center for the Study of Liver and Gastrointestinal Diseases (CIBERehd), Carlos III National Institute of Health, Madrid, Spain; Center for ALPD, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
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Kosvyra A, Ntzioni E, Chouvarda I. Network analysis with biological data of cancer patients: A scoping review. J Biomed Inform 2021; 120:103873. [PMID: 34298154 DOI: 10.1016/j.jbi.2021.103873] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 06/30/2021] [Accepted: 07/18/2021] [Indexed: 12/25/2022]
Abstract
BACKGROUND & OBJECTIVE Network Analysis (NA) is a mathematical method that allows exploring relations between units and representing them as a graph. Although NA was initially related to social sciences, the past two decades was introduced in Bioinformatics. The recent growth of the networks' use in biological data analysis reveals the need to further investigate this area. In this work, we attempt to identify the use of NA with biological data, and specifically: (a) what types of data are used and whether they are integrated or not, (b) what is the purpose of this analysis, predictive or descriptive, and (c) the outcome of such analyses, specifically in cancer diseases. METHODS & MATERIALS The literature review was conducted on two databases, PubMed & IEEE, and was restricted to journal articles of the last decade (January 2010 - December 2019). At a first level, all articles were screened by title and abstract, and at a second level the screening was conducted by reading the full text article, following the predefined inclusion & exclusion criteria leading to 131 articles of interest. A table was created with the information of interest and was used for the classification of the articles. The articles were initially classified to analysis studies and studies that propose a new algorithm or methodology. Each one of these categories was further screened by the following clustering criteria: (a) data used, (b) study purpose, (c) study outcome. Specifically for the studies proposing a new algorithm, the novelty presented in each one was detected. RESULTS & Conclusions: In the past five years researchers are focusing on creating new algorithms and methodologies to enhance this field. The articles' classification revealed that only 25% of the analyses are integrating multi-omics data, although 50% of the new algorithms developed follow this integrative direction. Moreover, only 20% of the analyses and 10% of the newly developed methodologies have a predictive purpose. Regarding the result of the works reviewed, 75% of the studies focus on identifying, prognostic or not, gene signatures. Concluding, this review revealed the need for deploying predictive and multi-omics integrative algorithms and methodologies that can be used to enhance cancer diagnosis, prognosis and treatment.
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Affiliation(s)
- A Kosvyra
- Laboratory of Computing, Medical Informatics and Biomedical Imaging Technologies, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.
| | - E Ntzioni
- Laboratory of Computing, Medical Informatics and Biomedical Imaging Technologies, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - I Chouvarda
- Laboratory of Computing, Medical Informatics and Biomedical Imaging Technologies, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
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Wang Z, Pan L, Guo D, Luo X, Tang J, Yang W, Zhang Y, Luo A, Gu Y, Pan Y. A novel five-gene signature predicts overall survival of patients with hepatocellular carcinoma. Cancer Med 2021; 10:3808-3821. [PMID: 33934539 PMCID: PMC8178492 DOI: 10.1002/cam4.3900] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 02/17/2021] [Accepted: 03/23/2021] [Indexed: 12/24/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is one of the most common public health challenges, worldwide. Because of molecular complexity and tumor heterogeneity, there are no effective predictive models for prognosis of HCC. This underlines the unmet need for accurate prognostic models for HCC. Analysis of GSE14520 data from gene omnibus (GEO) database identified multiple differentially expressed mRNAs (DEMs) between HCC and normal tissues. After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set. We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis of clinical information, nomogram, and decision curve analysis (DCA) to evaluate the predictive and overall survival value of a novel five-gene signature (CNIH4, SOX4, SPP1, SORBS2, and CCL19) within and across sets, separately and combined. We also validated the prognostic value of the five-gene signature using The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC), GSE54236 and International Cancer Genome Consortium (ICGC) sets. Multivariable Cox regression analysis revealed that the five-gene signature and tumor node metastasis (TNM) stage were independent prognostic factors for overall survival of HCC patients in GSE14520 and TCGA-LIHC. Combining TNM stage clinical pathological parameters and nomogram greatly improved the prognosis prediction of HCC. Further gene set enrichment analysis (GSEA) revealed enrichment of KEGG pathways related to cell cycle in the high-risk group and histidine metabolism in the low-risk group. Finally, all these five mRNAs are overexpressed between 12 pairs of HCC and adjacent normal tissues by quantitative real-time PCR validation. In brief, a five-gene prognostic signature and a nomogram were identified and constructed, respectively, and further validated for their HCC prognostic value. The five-gene risk score together with TNM stage models could aid in rationalizing customized therapies in HCC patients.
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Affiliation(s)
- Zhigang Wang
- Department of Hepatobiliary and PancreasThe First People's Hospital of JingmenJingmenChina
| | - Leyu Pan
- Department of Hepatobiliary and PancreasThe First People's Hospital of JingmenJingmenChina
| | - Deliang Guo
- Department of Hepatobiliary and PancreasZhongnan Hospital of Wuhan UniversityWuhanChina
| | - Xiaofeng Luo
- Department of Hepatobiliary and PancreasThe First People's Hospital of JingmenJingmenChina
| | - Jie Tang
- Department of Hepatobiliary and PancreasThe First People's Hospital of JingmenJingmenChina
| | - Weihua Yang
- Department of Hepatobiliary and PancreasThe First People's Hospital of JingmenJingmenChina
| | - Yuxian Zhang
- Department of Hepatobiliary and PancreasThe First People's Hospital of JingmenJingmenChina
| | - Anni Luo
- Department of AnesthesiologyThe First People's Hospital of JingmenJingmenChina
| | - Yang Gu
- Department of Hepatobiliary and PancreasThe First People's Hospital of JingmenJingmenChina
| | - Yuxuan Pan
- Department of Blood TransfusionThe First People's Hospital of JingmenJingmenChina
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Development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma. Aging (Albany NY) 2021; 13:13822-13845. [PMID: 33929972 PMCID: PMC8202896 DOI: 10.18632/aging.202976] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Accepted: 03/27/2021] [Indexed: 12/24/2022]
Abstract
Epithelial cell transformation (EMT) plays an important role in the pathogenesis and metastasis of hepatocellular carcinoma (HCC). We aimed to establish a genetic risk model to evaluate HCC prognosis based on the expression levels of EMT-related genes. The data of HCC patients were collected from TCGA and ICGC databases. Gene expression differential analysis, univariate analysis, and lasso combined with stepwise Cox regression were used to construct the prognostic model. Kaplan–Meier curve, receiver operating characteristic (ROC) curve, calibration analysis, Harrell’s concordance index (C-index), and decision curve analysis (DCA) were used to evaluate the predictive ability of the risk model or nomogram. GO and KEGG were used to analyze differently expressed EMT genes, or genes that directly or indirectly interact with the risk-associated genes. A 10-gene signature, including TSC2, ACTA2, SLC2A1, PGF, MYCN, PIK3R1, EOMES, BDNF, ZNF746, and TFDP3, was identified. Kaplan–Meier survival analysis showed a significant prognostic difference between high- and low-risk groups of patients. ROC curve analysis showed that the risk score model could effectively predict the 1-, 3-, and 5-year overall survival rates of patients with HCC. The nomogram showed a stronger predictive effect than clinical indicators. C-index, DCA, and calibration analysis demonstrated that the risk score and nomogram had high accuracy. The single sample gene set enrichment analysis results confirmed significant differences in the types of infiltrating immune cells between patients in the high- and low-risk groups. This study established a new prediction model of risk gene signature for predicting prognosis in patients with HCC, and provides a new molecular tool for the clinical evaluation of HCC prognosis.
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Identification of a thirteen-gene signature predicting overall survival for hepatocellular carcinoma. Biosci Rep 2021; 41:228241. [PMID: 33835133 PMCID: PMC8065179 DOI: 10.1042/bsr20202870] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 02/23/2021] [Accepted: 03/19/2021] [Indexed: 01/21/2023] Open
Abstract
Background: Hepatocellular carcinoma (HCC) is a malignant tumor of the digestive system characterized by mortality rate and poor prognosis. To indicate the prognosis of HCC patients, lots of genes have been screened as prognostic indicators. However, the predictive efficiency of single gene is not enough. Therefore, it is essential to identify a risk-score model based on gene signature to elevate predictive efficiency. Methods: Lasso regression analysis followed by univariate Cox regression was employed to establish a risk-score model for HCC prognosis prediction based on The Cancer Genome Atlas (TCGA) dataset and Gene Expression Omnibus (GEO) dataset GSE14520. R package ‘clusterProfiler’ was used to conduct function and pathway enrichment analysis. The infiltration level of various immune and stromal cells in the tumor microenvironment (TME) were evaluated by single-sample GSEA (ssGSEA) of R package ‘GSVA’. Results: This prognostic model is an independent prognostic factor for predicting the prognosis of HCC patients and can be more effective by combining with clinical data through the construction of nomogram model. Further analysis showed patients in high-risk group possess more complex TME and immune cell composition. Conclusions: Taken together, our research suggests the thirteen-gene signature to possess potential prognostic value for HCC patients and provide new information for immunological research and treatment in HCC.
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Construction of liver hepatocellular carcinoma-specific lncRNA-miRNA-mRNA network based on bioinformatics analysis. PLoS One 2021; 16:e0249881. [PMID: 33861762 PMCID: PMC8051809 DOI: 10.1371/journal.pone.0249881] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Accepted: 02/09/2021] [Indexed: 12/24/2022] Open
Abstract
Liver hepatocellular carcinoma (LIHC) is one of the major causes of cancer-related death worldwide with increasing incidences, however there are very few studies about the underlying mechanisms and pathways in the development of LIHC. We obtained LIHC samples from The Cancer Genome Atlas (TCGA) to screen differentially expressed mRNAs, lncRNAs, miRNAs and driver mutations. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses and protein–protein interaction (PPI) network were performed. Moreover, we constructed a competing endogenous lncRNAs-miRNAs-mRNAs network. Finally, cox proportional hazards regression analysis was used to identify important prognostic differentially expressed genes. Total of 1284 mRNAs, 123 lncRNAs, 47 miRNAs were identified within different tissues of LIHC patients. GO analysis indicated that upregulated and downregulated differentially expressed mRNAs (DEmRNAs) were mainly associated with cell division, DNA replication, mitotic sister chromatid segregation and complement activation respectively. Meanwhile, KEGG terms revealed that upregulated and downregulated DEmRNAs were primarily involved in DNA replication, Metabolic pathways, cell cycle and Metabolic pathways, chemical carcinogenesis, retinol metabolism pathway respectively. Among the DERNAs, 542 lncRNAs-miRNAs-mRNAs pairs were predicted to construct a ceRNA regulatory network including 35 DElncRNAs, 26 DEmiRNAs and 112 DEmRNAs. In the Kaplan‐Meier analysis, total of 43 mRNAs, 14 lncRNAs and 3 miRNAs were screened out to be significantly correlated with overall survival of LIHC. The mutation signatures were analyzed and its correlation with immune infiltrates were evaluated using the TIMER in LIHC. Among the mutation genes, TTN mutation is often associated with poor immune infiltration and a worse prognosis in LIHC. This work conducted a novel lncRNAs-miRNAs-mRNAs network and mutation signatures for finding potential molecular mechanisms underlying the development of LIHC. The biomarkers also can be used for predicting prognosis of LIHC.
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Identification of hepatocellular carcinoma prognostic markers based on 10-immune gene signature. Biosci Rep 2021; 40:226069. [PMID: 32789471 PMCID: PMC7457228 DOI: 10.1042/bsr20200894] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 07/14/2020] [Accepted: 08/05/2020] [Indexed: 12/13/2022] Open
Abstract
Background: Due to the heterogeneity of hepatocellular carcinoma (HCC), hepatocelluarin-associated differentially expressed genes were analyzed by bioinformatics methods to screen the molecular markers for HCC prognosis and potential molecular targets for immunotherapy. Methods: RNA-seq data and clinical follow-up data of HCC were downloaded from The Cancer Genome Atlas (TCGA) database. Multivariate Cox analysis and Lasso regression were used to identify robust immunity-related genes. Finally, a risk prognosis model of immune gene pairs was established and verified by clinical features, test set and Gene Expression Omnibus (GEO) external validation set. Results: A total of 536 immune-related gene (IRGs) were significantly associated with the prognosis of patients with HCC. Ten robust IRGs were finally obtained and a prognostic risk prediction model was constructed by feature selection of Lasso. The risk score of each sample is calculated based on the risk model and is divided into high risk group (Risk-H) and low risk group (Risk-L). Risk models enable risk stratification of samples in training sets, test sets, external validation sets, staging and subtypes. The area under the curve (AUC) in the training set and the test set were all >0.67, and there were significant overall suvival (OS) differences between the Risk-H and Risk-L samples. Compared with the published four models, the traditional clinical features of Grade, Stage and Gender, the model performed better on the risk prediction of HCC prognosis. Conclusion: The present study constructed 10-gene signature as a novel prognostic marker for predicting survival in patients with HCC.
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Revealing the Role of High-Density Lipoprotein in Colorectal Cancer. Int J Mol Sci 2021; 22:ijms22073352. [PMID: 33805921 PMCID: PMC8037642 DOI: 10.3390/ijms22073352] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 03/11/2021] [Accepted: 03/15/2021] [Indexed: 12/12/2022] Open
Abstract
Colorectal cancer (CRC) is a highly prevalent malignancy with multifactorial etiology, which includes metabolic alterations as contributors to disease development. Studies have shown that lipid status disorders are involved in colorectal carcinogenesis. In line with this, previous studies have also suggested that the serum high-density lipoprotein cholesterol (HDL-C) level decreases in patients with CRC, but more recently, the focus of investigations has shifted toward the exploration of qualitative properties of HDL in this malignancy. Herein, a comprehensive overview of available evidences regarding the putative role of HDL in CRC will be presented. We will analyze existing findings regarding alterations of HDL-C levels but also HDL particle structure and distribution in CRC. In addition, changes in HDL functionality in this malignancy will be discussed. Moreover, we will focus on the genetic regulation of HDL metabolism, as well as the involvement of HDL in disturbances of cholesterol trafficking in CRC. Finally, possible therapeutic implications related to HDL will be presented. Given the available evidence, future studies are needed to resolve all raised issues concerning the suggested protective role of HDL in CRC, its presumed function as a biomarker, and eventual therapeutic approaches based on HDL.
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Zheng Y, Wen Y, Cao H, Gu Y, Yan L, Wang Y, Wang L, Zhang L, Shao F. Global Characterization of Immune Infiltration in Clear Cell Renal Cell Carcinoma. Onco Targets Ther 2021; 14:2085-2100. [PMID: 33790572 PMCID: PMC7997590 DOI: 10.2147/ott.s282763] [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: 09/21/2020] [Accepted: 02/03/2021] [Indexed: 12/26/2022] Open
Abstract
Background Immunotherapy has revolutionized the treatment of clear cell renal cell carcinoma (ccRCC). However, the therapy is constrained by drug resistance. Therefore, further characterization of immune infiltration in ccRCC is needed to improve its efficacy. Methods Here, we adopted the CIBERSORT method to analyze the level of 22 immune cells, and analyzed the correlation of immune cells and clinical parameters in ccRCC in The Cancer Genome Atlas. We used consensus clustering to cluster ccRCC and identified differently expressed genes (DEGs) between hot and cold tumors using the "Limma" package, and then performed enrichment analysis of DEGs. Finally, we constructed and validated a Cox regression model using the "survival", "glmnet", and "survivalROC" packages, implemented in R. Results Regulatory T cells upregulated in tumor tissue increased during tumor progression, and correlated with poor overall survival in ccRCC. Consensus clustering identified four clusters of ccRCC. To elucidate the underlying mechanisms of immune cell infiltration, we subdivided these four clusters into two major types, immune hot and cold, and identified DEGs between them. The results revealed different transcription profiles in the two tumor types, with hot tumors being enriched in immune-related signaling, whereas cold tumors were enriched in extracellular matrix remodeling and the phosphatidylinositol 3-kinase-AKT (PI3K/AKT) pathway. We further identified hub genes and prognostic-related genes from the DEGs, and constructed a Cox regression model for predicting the overall survival of patients with ccRCC. The areas under the receiver operating characteristics curve for the risk model for the training, testing, and external Zhengzhou validation cohorts were 0.834, 0.733, and 0.812, respectively. Notably, gene sets in the prediction model could also predict the overall survival of patients receiving immunotherapy. Conclusion These findings provide a comprehensive characterization of immune infiltration in ccRCC, while the constructed model can be used effectively to predict the overall survival of ccRCC patients.
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Affiliation(s)
- Yan Zheng
- Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China
| | - Yibo Wen
- Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, People's Republic of China
| | - Huixia Cao
- Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China
| | - Yue Gu
- Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China
| | - Lei Yan
- Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China
| | - Yanliang Wang
- Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China
| | - Limeng Wang
- Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China
| | - Lina Zhang
- Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China
| | - Fengmin Shao
- Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People's Hospital, Zhengzhou, 450052, Henan, People's Republic of China
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Xiao S, Hu J, Hu N, Sheng L, Rao H, Zheng G. Identification of a Novel Epithelial-to-Mesenchymal-related Gene Signature in Predicting Survival of Patients with Hepatocellular Carcinoma. Comb Chem High Throughput Screen 2021; 25:1254-1270. [PMID: 33655854 DOI: 10.2174/1386207324666210303093629] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 12/11/2020] [Accepted: 02/09/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Epithelial-mesenchymal transformation (EMT) promotes cancer metastasis including hepatocellular carcinoma. Therefore, EMT-related gene signature was explored. OBJECTIVE The present study was designed to develop an EMT-related gene signature for predicting the prognosis of patients with hepatocellular carcinoma. METHODS We conducted an integrated gene expression analysis based on tumor data of the patients with hepatocellular carcinoma from The Cancer Genome Atlas (TCGA), HCCDB18 and GSE14520 dataset. An EMT-related gene signature was constructed by least absolute shrinkage and selection operator (LASSO) and COX regression analysis of univariate and multivariate survival. RESULTS A 3-EMT gene signature was developed and validated based on gene expression profiles of hepatocellular carcinoma from three microarray platforms. Patients with a high risk score had a significantly worse overall survival (OS) than those with low risk scores. The EMT-related gene signature showed a high performance in accurately predicting prognosis and in examining the clinical characteristics and immune score analysis. Univariate and multivariate Cox regression analyses confirmed that the EMT-related gene signature was an independent prognostic factor for predicting survival in hepatocellular carcinoma patients. Compared with the existing models, our EMT-related gene signature reached higher area under curve (AUC). CONCLUSION Our findings provide novel insight into understanding EMT and help identify hepatocellular carcinoma patients with poor prognosis.
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Affiliation(s)
- Simeng Xiao
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, 430065. China
| | - Junjie Hu
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, 430065. China
| | - Na Hu
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, 430065. China
| | - Lei Sheng
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, 430065. China
| | - Hui Rao
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, 430065. China
| | - Guohua Zheng
- Key Laboratory for Chinese Medicine Resource and Compound Prescription of Ministry of Education, Hubei University of Chinese Medicine, Wuhan, Hubei, 430065. China
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Wu D, Pan Y, Zheng X. Identification of hub genes-based predictive model in hepatocellular carcinoma by robust rank aggregation and regression analysis. J Cancer 2021; 12:1884-1893. [PMID: 33753986 PMCID: PMC7974519 DOI: 10.7150/jca.52089] [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: 08/17/2020] [Accepted: 12/27/2020] [Indexed: 12/24/2022] Open
Abstract
Background: Though various hub genes for HCC have been identified in decades, the limited sample size, inconsistent bioinformatic analysis methods and lacking evaluation in validation cohorts would make the results less reliable, novel biomarkers and risk model for HCC prognosis are still urgently desired. Methods: The Robust Rank Aggression method was applied to integrate 12 HCC microarray datasets to screen for robustly and stably differentially expressed candidates. The Least Absolute Shrinkage and Selection Operator regression and multivariate Cox regression analysis were performed to construct a six hub genes-based prognostic model, which was further verified in matched tumor and non-tumor hepatic samples and two independent validation cohorts. Results: Six hub genes for HCC were identified including CD163, EHHADH, KIAA0101, SLC16A2, SPP1 and THBS4. The risk score according to hub genes-based prognostic model could be an independent predictive factor for HCC. Quantitative real-time polymerase chain reaction results showed significant difference in expression level between tumor and non-tumor hepatic tissues. Prognostic value of risk model has been verified in TCGA-HCC and GSE76240 datasets. Biological function analysis revealed these hub genes were closely associated with tumorigenesis processes. Conclusion: A novel six hub genes predictive risk model for HCC has been established based on multiple datasets analyses, providing novel features for the prediction of HCC patients' outcome.
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Affiliation(s)
- Di Wu
- Department of General Surgery, Sir Run-Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China
| | - Yun Pan
- Department of Emergency, Sir Run-Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China
| | - Xueyong Zheng
- Department of General Surgery, Sir Run-Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China
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Gu X, Guan J, Xu J, Zheng Q, Chen C, Yang Q, Huang C, Wang G, Zhou H, Chen Z, Zhu H. Model based on five tumour immune microenvironment-related genes for predicting hepatocellular carcinoma immunotherapy outcomes. J Transl Med 2021; 19:26. [PMID: 33407546 PMCID: PMC7788940 DOI: 10.1186/s12967-020-02691-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 12/22/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Although the tumour immune microenvironment is known to significantly influence immunotherapy outcomes, its association with changes in gene expression patterns in hepatocellular carcinoma (HCC) during immunotherapy and its effect on prognosis have not been clarified. METHODS A total of 365 HCC samples from The Cancer Genome Atlas liver hepatocellular carcinoma (TCGA-LIHC) dataset were stratified into training datasets and verification datasets. In the training datasets, immune-related genes were analysed through univariate Cox regression analyses and least absolute shrinkage and selection operator (LASSO)-Cox analyses to build a prognostic model. The TCGA-LIHC, GSE14520, and Imvigor210 cohorts were subjected to time-dependent receiver operating characteristic (ROC) and Kaplan-Meier survival curve analyses to verify the reliability of the developed model. Finally, single-sample gene set enrichment analysis (ssGSEA) was used to study the underlying molecular mechanisms. RESULTS Five immune-related genes (LDHA, PPAT, BFSP1, NR0B1, and PFKFB4) were identified and used to establish the prognostic model for patient response to HCC treatment. ROC curve analysis of the TCGA (training and validation sets) and GSE14520 cohorts confirmed the predictive ability of the five-gene-based model (AUC > 0.6). In addition, ROC and Kaplan-Meier analyses indicated that the model could stratify patients into a low-risk and a high-risk group, wherein the high-risk group exhibited worse prognosis and was less sensitive to immunotherapy than the low-risk group. Functional enrichment analysis predicted potential associations of the five genes with several metabolic processes and oncological signatures. CONCLUSIONS We established a novel five-gene-based prognostic model based on the tumour immune microenvironment that can predict immunotherapy efficacy in HCC patients.
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Affiliation(s)
- Xinyu Gu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, NO. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Jun Guan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, NO. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Jia Xu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, NO. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Qiuxian Zheng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, NO. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Chao Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, NO. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Qin Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, NO. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Chunhong Huang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, NO. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Gang Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, NO. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Haibo Zhou
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, NO. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Zhi Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, NO. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Haihong Zhu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, NO. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China.
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Yang Z, Zi Q, Xu K, Wang C, Chi Q. Development of a macrophages-related 4-gene signature and nomogram for the overall survival prediction of hepatocellular carcinoma based on WGCNA and LASSO algorithm. Int Immunopharmacol 2020; 90:107238. [PMID: 33316739 DOI: 10.1016/j.intimp.2020.107238] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 11/11/2020] [Accepted: 11/23/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND Immune system instability and poor prognosis are the two major clinical performance of hepatocellular carcinoma (HCC). Abnormal expression of MiR-424-5p has been reported to accelerate the progression of liver cancer, but it mediated immune cell infiltration imbalance is still unknown. We aim to mine the immune-related genes (IRGs) targeted by miR-424-5p and construct a multi-gene signature to improve the prognostic prediction of HCC. METHODS The HCC-related data of the cancer genome atlas (TCGA) database and the GSE14520 dataset of the gene expression omnibus (GEO) database were downloaded as the discovery dataset and the validation dataset, respectively. Weighted gene co-expression network analysis (WGCNA), the deconvolution algorithm of CIBERSORT and LASSO algorithm participated in the identification of IRGs and the development of prognostic signature and nomogram. RESULTS Our study found that the abundance of macrophages M0, M1 and M2 are all drastically changed during the cancerous process. A total of 920 macrophages infiltration-related LRGs were identified and a novel 4-gene signature (CDCA8, CBX2, UCK2 and SOCS2) with superior prognostic independence was established. The prognostic signature based risk score has superior capability to identify high-risk patients and predict overall survival (p < 0.001; AUC = 0.798 for 1 year; AUC = 0.748 for 3 years; AUC = 0.721 for 5 years). And it (C-index = 0.726) has a better prognostic potential than the TNM stage (C-index = 0.619), which is widely adopted in clinical practice. Additionally, the nomogram formed by combining the risk score and TNM stage further improved the accuracy of survival prediction (C-index = 0.733). CONCLUSION In summary, the immune landscape with abnormal infiltration of macrophages may be one of the prelude to the cancerous process. The novel macrophages-related 4-gene signature is expected to become a potential prognostic marker in liver cancer.
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Affiliation(s)
- Zichang Yang
- Department of Mechanics and Engineering Structure, Wuhan University of Technology, China
| | - Quan Zi
- Department of Mechanics and Engineering Structure, Wuhan University of Technology, China
| | - Kang Xu
- Hubei Engineering Technology Research Center of TCM Processing, College of Pharmacy, Hubei University of Chinese Medicine, Wuhan 430065, China
| | - Chunli Wang
- "111" Project Laboratory of Biomechanics and Tissue Repair, Bioengineering College, Chongqing University, Chongqing 400044, China
| | - Qingjia Chi
- Department of Mechanics and Engineering Structure, Wuhan University of Technology, China.
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Kumar R, Kuligina E, Sokolenko A, Siddiqui Q, Gardi N, Gupta S, Varma AK, Hasan SK. Genetic ablation of pregnancy zone protein promotes breast cancer progression by activating TGF-β/SMAD signaling. Breast Cancer Res Treat 2020; 185:317-330. [PMID: 33057846 DOI: 10.1007/s10549-020-05958-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 09/28/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE Pregnancy zone protein (PZP) is best known as protease inhibitor and its concentration in human blood plasma increases dramatically during pregnancy. Recent investigation revealed a role of PZP inactivating germ-line mutation in breast cancer predisposition, and therefore we designed a study to evaluate functional involvement of this protein in tumor pathogenesis. METHODS PZP knockout cells were generated utilizing the CRISPR-Cas9 approach in MCF7 and T47D (breast cancer) cell lines, and colony formation, cell proliferation, and migration assays carried out. TGF-β and SMAD expression studies were performed using qRT-PCR and Western blot. PZP expression in tumor vs normal tissue was compared using meta-analyses of data records of breast cancer patients (n = 1211) included in the TCGA consortium registry as well as in independent cohorts of hormone receptor-positive (n = 118) and triple-negative breast cancer (TNBC) patients (n = 116). RESULTS We demonstrated that genetic ablation of PZP efficiently inhibits tamoxifen-induced apoptosis and enhances cell proliferation, migration, and colony-forming capacity. We found a significant increase in survival fraction of CRISPR/Cas9-mediated PZP knockout clones compared to wild-type counterpart after tamoxifen treatment (p < 0.05). The PZP knockout significantly promoted breast cancer cell migration (p < 0.01) in vitro. We observed high expression of TGF-β2 ligand, TGF-β- receptor 2, and upregulation of phosphorylated regulatory-SMADs (pSMAD2 and pSMAD3) activating the pro-survival function of TGF-β/SMAD signaling in PZP knockout clones. Meta-analyses of data records of breast cancer patients indicated that low PZP expression is associated with poor overall survival at 6 years (51.7% vs 62.9% in low vs high expressers, respectively; p = 0.026). We also observed a significantly lower PZP mRNA expression in TNBC as compared with hormone receptor-positive tumors (p = 0.019). CONCLUSION Taken together, our results suggest that genetic ablation of PZP results in tumor progression and low expression of PZP is associated with poor survival of breast cancer patients.
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Affiliation(s)
- Rohit Kumar
- Cell and Tumor Biology Group, Advanced Centre for Treatment, Research and Education in Cancer, Sector 22, Kharghar, Navi Mumbai, 410210, Maharashtra, India
| | - Ekaterina Kuligina
- Laboratory of Molecular Oncology, N.N. Petrov Institute of Oncology, Pesochny-2, 197758, St.-Petersburg, Russia
| | - Anna Sokolenko
- Laboratory of Molecular Oncology, N.N. Petrov Institute of Oncology, Pesochny-2, 197758, St.-Petersburg, Russia
| | - Quadir Siddiqui
- Cell and Tumor Biology Group, Advanced Centre for Treatment, Research and Education in Cancer, Sector 22, Kharghar, Navi Mumbai, 410210, Maharashtra, India
| | - Nilesh Gardi
- Department of Medical Oncology, Tata Memorial Centre, Mumbai, 400012, Maharashtra, India
- Homi Bhabha National Institute (HBNI), Anushaktinagar, Mumbai, 400094, India
| | - Sudeep Gupta
- Department of Medical Oncology, Tata Memorial Centre, Mumbai, 400012, Maharashtra, India
- Homi Bhabha National Institute (HBNI), Anushaktinagar, Mumbai, 400094, India
| | - Ashok K Varma
- Varma Laboratory, Advanced Centre for Treatment, Research and Education in Cancer, Navi Mumbai, 410210, India.
- Homi Bhabha National Institute (HBNI), Anushaktinagar, Mumbai, 400094, India.
| | - Syed K Hasan
- Cell and Tumor Biology Group, Advanced Centre for Treatment, Research and Education in Cancer, Sector 22, Kharghar, Navi Mumbai, 410210, Maharashtra, India.
- Homi Bhabha National Institute (HBNI), Anushaktinagar, Mumbai, 400094, India.
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Jia Y, Dai J, Zeng Z. Potential relationship between the selenoproteome and cancer. Mol Clin Oncol 2020; 13:83. [PMID: 33133596 PMCID: PMC7590431 DOI: 10.3892/mco.2020.2153] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Accepted: 09/10/2020] [Indexed: 02/07/2023] Open
Abstract
The role of the selenoproteome, which is the collection of all proteins containing selenium in an organism, in cancer development, growth and progression requires further investigation, due to the importance of selenium in both cancer and immune system function. Data about the selenoproteome, including its differential expression, single nucleotide variations, copy number variations, methylation, pathways and overall survival (OS) in five leading types of cancer are available from the GSCALite website. Subsequent to the analysis of these datasets, it was revealed that there was increased expression of GPX3 in stomach adenocarcinoma and lung squamous cell carcinoma, SELENOV in oesophageal carcinoma, GPX8 and GPX4 in colon adenocarcinoma, TXNRD1 and SEPHS1 in hepatocellular carcinoma and GPX8 in lung adenocarcinoma were associated with poor survival. Decreased gene expression of SELENOP was indicated in liver hepatocellular carcinoma and GPX3, and SELENOW, SELENOK, SELENBP1 and SECISBP2 in lung adenocarcinoma were associated with a poor prognosis. OS data suggested that hypermethylation of GPX4 in colon adenocarcinoma, GPX8 in lung squamous cell carcinoma, GPX1 in stomach adenocarcinoma and GPX3 in lung adenocarcinoma was associated with low survival, as is hypomethylation of GPX5 in lung adenocarcinoma. The selenoproteome is heterogeneous, especially in its effect on the OS of patients with cancer. The present study demonstrated that the roles of GPX4 in colon adenocarcinoma, SCLY and SELENOV in oesophageal carcinoma, SEPHS1 in liver hepatocellular carcinoma, SELENOK in lung cancer, as well as SELENOM and SELENOW in stomach adenocarcinoma requires further research. The present study may lead to the identification of novel biomarkers or potential therapeutic targets for use in the treatment of cancers, such as colon adenocarcinoma, oesophageal carcinoma, liver hepatocellular carcinoma, lung cancer and stomach adenocarcinoma.
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Affiliation(s)
- Yi Jia
- Immune Cells and Antibody Engineering Research Center of Guizhou Province/Key Laboratory of Biology and Medical Engineering, Guizhou Medical University, Guiyang, Guizhou 550025, P.R. China.,School of Biology and Engineering, Guizhou Medical University, Guiyang, Guizhou 550025, P.R. China
| | - Jie Dai
- Immune Cells and Antibody Engineering Research Center of Guizhou Province/Key Laboratory of Biology and Medical Engineering, Guizhou Medical University, Guiyang, Guizhou 550025, P.R. China.,School of Biology and Engineering, Guizhou Medical University, Guiyang, Guizhou 550025, P.R. China
| | - Zhu Zeng
- School of Biology and Engineering, Guizhou Medical University, Guiyang, Guizhou 550025, P.R. China.,School of Basic Medical Science, Guizhou Medical University, Guiyang, Guizhou 550025, P.R. China
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Xu D, Wang Y, Zhou K, Wu J, Zhang Z, Zhang J, Yu Z, Liu L, Liu X, Li B, Zheng J. Development and Validation of a Novel 8 Immune Gene Prognostic Signature Based on the Immune Expression Profile for Hepatocellular Carcinoma. Onco Targets Ther 2020; 13:8125-8140. [PMID: 32884295 PMCID: PMC7439501 DOI: 10.2147/ott.s263047] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Accepted: 07/29/2020] [Indexed: 12/17/2022] Open
Abstract
Background The immune microenvironment plays a vital role in the development of hepatocellular carcinoma (HCC). This study explored novel immune-related biomarkers to predict the prognosis of patients with HCC. Methods RNA-Seq data were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to identify prognosis-related genes; the Lasso method was used to construct the prognosis risk model. Validation was performed on the International Cancer Genome Consortium (ICGC) cohort, and the C-index was calculated to evaluate its overall predictive performance. Western blots were conducted to evaluate the expression of genes. Results There were 320 immune-related genes, 40 of which were significantly related to prognosis. Eight immune gene signatures (CKLF, IL12A, CCL20, PRELID1, GLMN, ACVR2A, CD7, and FYN) were established by Lasso Cox regression analysis. This immune signature performed well in different cohorts and can be an independent risk factor for prognosis. In addition, the overall predictive performance of this model was higher than the other models reported previously. Conclusion The predictive immune model will enable patients with HCC to be more accurately managed in immunotherapy.
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Affiliation(s)
- Dafeng Xu
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, People's Republic of China
| | - Yu Wang
- Geriatrics Center, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, People's Republic of China
| | - Kailun Zhou
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, People's Republic of China
| | - Jincai Wu
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, People's Republic of China
| | - Zhensheng Zhang
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, People's Republic of China
| | - Jiachao Zhang
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, People's Republic of China
| | - Zhiwei Yu
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, People's Republic of China
| | - Luzheng Liu
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, People's Republic of China
| | - Xiangmei Liu
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, People's Republic of China
| | - Bidan Li
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, People's Republic of China
| | - Jinfang Zheng
- Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan 570311, People's Republic of China
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Zhou T, Cai Z, Ma N, Xie W, Gao C, Huang M, Bai Y, Ni Y, Tang Y. A Novel Ten-Gene Signature Predicting Prognosis in Hepatocellular Carcinoma. Front Cell Dev Biol 2020; 8:629. [PMID: 32760725 PMCID: PMC7372135 DOI: 10.3389/fcell.2020.00629] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 06/23/2020] [Indexed: 01/27/2023] Open
Abstract
Hepatocellular carcinoma (HCC) has a dismal long-term outcome. We aimed to construct a multi-gene model for prognosis prediction to inform HCC management. The cancer-specific differentially expressed genes (DEGs) were identified using RNA-seq data of paired tumor and normal tissue. A prognostic signature was built by LASSO regression analysis. Gene set enrichment analysis (GSEA) was performed to further understand the underlying molecular mechanisms. A 10-gene signature was constructed to stratify the TCGA and ICGC cohorts into high- and low-risk groups where prognosis was significantly worse in the high-risk group across cohorts (P < 0.001 for all). The 10-gene signature outperformed all previously reported models for both C-index and the AUCs for 1-, 3-, 5-year survival prediction (C-index, 0.84 vs 0.67 to 0.73; AUCs for 1-, 3- and 5-year OS, 0.84 vs 0.68 to 0.79, 0.81 to 0.68 to 0.80, and 0.85 vs 0.67 to 0.78, respectively). Multivariate Cox regression analysis revealed risk group and tumor stage to be independent predictors of survival in HCC. A nomogram incorporating tumor stage and signature-based risk group showed better performance for 1- and 3-year survival than for 5-year survival. GSEA revealed enrichment of pathways related to cell cycle regulation among high-risk samples and metabolic processes in the low-risk group. Our 10-gene model is robust for prognosis prediction and may help inform clinical management of HCC.
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Affiliation(s)
- Taicheng Zhou
- Department of Gastroenterological Surgery and Hernia Center, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Supported by National Key Clinical Discipline, Guangzhou, China
| | - Zhihua Cai
- Department of Oncology, The Affiliated Cancer Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ning Ma
- Department of Gastroenterological Surgery and Hernia Center, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Supported by National Key Clinical Discipline, Guangzhou, China
| | - Wenzhuan Xie
- The Medical Department, 3D Medicines Inc., Shanghai, China
| | - Chan Gao
- The Medical Department, 3D Medicines Inc., Shanghai, China
| | - Mengli Huang
- The Medical Department, 3D Medicines Inc., Shanghai, China
| | - Yuezong Bai
- The Medical Department, 3D Medicines Inc., Shanghai, China
| | - Yangpeng Ni
- Department of Oncology, Jieyang People's Hospital, Sun Yat-sen University, Jieyang, China
| | - Yunqiang Tang
- Department of Hepatic-Biliary Surgery, The Affiliated Cancer Hospital of Guangzhou Medical University, Guangzhou, China
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Transcriptomic profiling of peroxisome-related genes reveals a novel prognostic signature in hepatocellular carcinoma. Genes Dis 2020; 9:116-127. [PMID: 35005112 PMCID: PMC8720664 DOI: 10.1016/j.gendis.2020.04.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 03/25/2020] [Accepted: 04/13/2020] [Indexed: 02/07/2023] Open
Abstract
Emerging evidence suggests that peroxisomes play a role in the regulation of tumorigenesis and cancer progression. However, the prognostic value of peroxisome-related genes has been rarely investigated. This study aimed to establish a peroxisome-related gene signature for overall survival (OS) prediction in patients with hepatocellular carcinoma (HCC). First, univariate Cox regression analysis was employed to identify prognostic peroxisome-related genes in The Cancer Genome Atlas liver cancer cohort, and least absolute shrinkage and selection operator Cox regression analysis was used to construct a 10-gene signature. The risk score based on the signature was positively correlated with poor prognosis (HR = 4.501, 95% CI = 3.021–6.705, P = 1.39e−13). Second, multivariate Cox regression incorporating additional characteristics revealed that the signature was an independent predictor. Time-dependent ROC curves demonstrated good performance of the signature in predicting the OS of HCC patients. The prognostic performance was validated using International Cancer Genome Consortium HCC cohort data. Gene set enrichment analysis revealed that the signature-related alterations in biological processes mainly involved peroxisomal functions. Finally, we developed a nomogram model based on the gene signature and TNM stage, which showed a superior prognostic power (C-index = 0.702). Thus, our study revealed a novel peroxisome-related gene signature that may help improve personalized OS prediction in HCC patients.
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Xie Z, Dang Y, Wu H, He R, Ma J, Peng Z, Rong M, Li Z, Yang J, Jiang Y, Chen G, Yang L. Effect of CELSR3 on the Cell Cycle and Apoptosis of Hepatocellular Carcinoma Cells. J Cancer 2020; 11:2830-2844. [PMID: 32226501 PMCID: PMC7086248 DOI: 10.7150/jca.39328] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 02/06/2020] [Indexed: 02/07/2023] Open
Abstract
Cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3) has been reported in cancers but its role and potential molecular mechanism in hepatocellular carcinoma (HCC) is unclear. Therefore, we aimed to investigate the clinical value and molecular mechanism of CELSR3 in HCC using an in vitro experiment, a meta-analysis and bioinformatics. The in vitro experiment determined the promoting effect of CELSR3 in the proliferation, invasion, and migration of HCC cells. CELSR3 knockout causes S-phage arrest in HCC cells. CELSR3 can also inhibit the apoptosis of HCC cells. The expression of the CELSR3 gene and protein was significantly elevated in HCC. Elevated CELSR3 was correlated to the bigger tumor size, higher pathological stage, and the worse overall survival of HCC. Methylation analysis revealed that the hypomethylation of CELSR3 regulated by DNMT1, DNMT3A, and DNMT3B may be the underlying mechanism of upregulated CELSR3. Biological enrichment analysis uncovered that the cell cycle, DNA replication, and PI3K-Akt signaling pathways were important pathways regulated by CELSR3 and its co-expressed genes in HCC. Taken together, upregulated CELSR3 is an important regulator in the progression and prognosis of HCC. The hypomethylation of CELSR3 and its regulation in the cell cycle may be the potential molecular mechanism in HCC.
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Affiliation(s)
- Zucheng Xie
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, P. R. China
| | - Yiwu Dang
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, P. R. China
| | - Huayu Wu
- Department of Cell Biology and Genetics, School of Pre-clinical Medicine, Guangxi Medical University, 22 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, P. R. China
| | - Rongquan He
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, P. R. China
| | - Jie Ma
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, P. R. China
| | - Zhigang Peng
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, P. R. China
| | - Minhua Rong
- Research Department, Affiliated Cancer Hospital, Guangxi Medical University, 71 Hedi Road, Nanning, Guangxi Zhuang Autonomous Region 530021, P. R. China
| | - Zhekun Li
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, P. R. China
| | - Jiapeng Yang
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, P. R. China
| | - Yizhao Jiang
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, P. R. China
| | - Gang Chen
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, P. R. China
| | - Lihua Yang
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning 530021, Guangxi Zhuang Autonomous Region, P. R. China
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Kaur H, Dhall A, Kumar R, Raghava GPS. Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data. Front Genet 2020; 10:1306. [PMID: 31998366 PMCID: PMC6967266 DOI: 10.3389/fgene.2019.01306] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 11/26/2019] [Indexed: 12/20/2022] Open
Abstract
The high mortality rate of hepatocellular carcinoma (HCC) is primarily due to its late diagnosis. In the past, numerous attempts have been made to design genetic biomarkers for the identification of HCC; unfortunately, most of the studies are based on small datasets obtained from a specific platform or lack reasonable validation performance on the external datasets. In order to identify a universal expression-based diagnostic biomarker panel for HCC that can be applicable across multiple platforms, we have employed large-scale transcriptomic profiling datasets containing a total of 2,316 HCC and 1,665 non-tumorous tissue samples. These samples were obtained from 30 studies generated by mainly four types of profiling techniques (Affymetrix, Illumina, Agilent, and High-throughput sequencing), which are implemented in a wide range of platforms. Firstly, we scrutinized overlapping 26 genes that are differentially expressed in numerous datasets. Subsequently, we identified a panel of three genes (FCN3, CLEC1B, and PRC1) as HCC biomarker using different feature selection techniques. Three-genes-based HCC biomarker identified HCC samples in training/validation datasets with an accuracy between 93 and 98%, Area Under Receiver Operating Characteristic curve (AUROC) in a range of 0.97 to 1.0. A reasonable performance, i.e., AUROC 0.91–0.96 achieved on validation dataset containing peripheral blood mononuclear cells, concurred their non-invasive utility. Furthermore, the prognostic potential of these genes was evaluated on TCGA-LIHC and GSE14520 cohorts using univariate survival analysis. This analysis revealed that these genes are prognostic indicators for various types of the survivals of HCC patients (e.g., Overall Survival, Progression-Free Survival, Disease-Free Survival). These genes significantly stratified high-risk and low-risk HCC patients (p-value <0.05). In conclusion, we identified a universal platform-independent three-genes-based biomarker that can predict HCC patients with high precision and also possess significant prognostic potential. Eventually, we developed a web server HCCpred based on the above study to facilitate scientific community (http://webs.iiitd.edu.in/raghava/hccpred/).
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Affiliation(s)
- Harpreet Kaur
- Bioinformatics Center, CSIR-Institute of Microbial Technology, Chandigarh, India.,Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India
| | - Anjali Dhall
- Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India
| | - Rajesh Kumar
- Bioinformatics Center, CSIR-Institute of Microbial Technology, Chandigarh, India.,Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India
| | - Gajendra P S Raghava
- Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India
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Liu J, Lu J, Ma Z, Li W. A Nomogram Based on a Three-Gene Signature Derived from AATF Coexpressed Genes Predicts Overall Survival of Hepatocellular Carcinoma Patients. BIOMED RESEARCH INTERNATIONAL 2020; 2020:7310768. [PMID: 32382568 PMCID: PMC7195644 DOI: 10.1155/2020/7310768] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Revised: 03/14/2020] [Accepted: 03/16/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is a common cancer with an extremely high mortality rate. Therefore, there is an urgent need in screening key biomarkers of HCC to predict the prognosis and develop more individual treatments. Recently, AATF is reported to be an important factor contributing to HCC. METHODS We aimed to establish a gene signature to predict overall survival of HCC patients. Firstly, we examined the expression level of AATF in the Gene Expression Omnibus (GEO), the Cancer Genome Atlas (TCGA), and the International Union of Cancer Genome (ICGC) databases. Genes coexpressed with AATF were identified in the TCGA dataset by the Poisson correlation coefficient and used to establish a gene signature for survival prediction. The prognostic significance of this gene signature was then validated in the ICGC dataset and used to build a combined prognostic model for clinical practice. RESULTS Gene expression data and clinical information of 2521 HCC patients were downloaded from three public databases. AATF expression in HCC tissue was higher than that in matched normal liver tissues. 644 genes coexpressed with AATF were identified by the Poisson correlation coefficient and used to establish a three-gene signature (KIF20A, UCK2, and SLC41A3) by the univariate and multivariate least absolute shrinkage and selection operator Cox regression analyses. This three-gene signature was then used to build a combined nomogram for clinical practice. CONCLUSION This integrated nomogram based on the three-gene signature can predict overall survival for HCC patients well. The three-gene signature may be a potential therapeutic target in HCC.
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Affiliation(s)
- Jun Liu
- Departments of Clinical Laboratory, Yue Bei People's Hospital, Shantou University Medical College, Shaoguan, Guangdong, China
| | - Jianjun Lu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, China
- Department of Medical Services, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhanzhong Ma
- Departments of Clinical Laboratory, Yue Bei People's Hospital, Shantou University Medical College, Shaoguan, Guangdong, China
| | - Wenli Li
- Departments of Clinical Laboratory, Yue Bei People's Hospital, Shantou University Medical College, Shaoguan, Guangdong, China
- Departments of Reproductive Medicine Center, Yue Bei People's Hospital, Shantou University Medical College, Shaoguan, Guangdong, China
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47
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Kuligina ES, Sokolenko AP, Bizin IV, Romanko AA, Zagorodnev KA, Anisimova MO, Krylova DD, Anisimova EI, Mantseva MA, Varma AK, Hasan SK, Ni VI, Koloskov AV, Suspitsin EN, Venina AR, Aleksakhina SN, Sokolova TN, Milanović AM, Schürmann P, Prokofyeva DS, Bermisheva MA, Khusnutdinova EK, Bogdanova N, Dörk T, Imyanitov EN. Exome sequencing study of Russian breast cancer patients suggests a predisposing role for USP39. Breast Cancer Res Treat 2019; 179:731-742. [DOI: 10.1007/s10549-019-05492-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 11/07/2019] [Indexed: 12/11/2022]
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48
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Kong J, Wang T, Shen S, Zhang Z, Yang X, Wang W. A genomic-clinical nomogram predicting recurrence-free survival for patients diagnosed with hepatocellular carcinoma. PeerJ 2019; 7:e7942. [PMID: 31687273 PMCID: PMC6825747 DOI: 10.7717/peerj.7942] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 09/23/2019] [Indexed: 02/05/2023] Open
Abstract
Liver resection surgery is the most commonly used treatment strategy for patients diagnosed with hepatocellular carcinoma (HCC). However, there is still a chance for recurrence in these patients despite the survival benefits of this procedure. This study aimed to explore recurrence-related genes (RRGs) and establish a genomic-clinical nomogram for predicting postoperative recurrence in HCC patients. A total of 123 differently expressed genes and three RRGs (PZP, SPP2, and PRC1) were identified from online databases via Cox regression and LASSO logistic regression analyses and a gene-based risk model containing RRGs was then established. The Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves showed that the model performed well. Finally, a genomic-clinical nomogram incorporating the gene-based risk model, AJCC staging system, and Eastern Cooperative Oncology Group performance status was constructed to predict the 1-, 2-, and 3-year recurrence-free survival rates (RFS) for HCC patients. The C-index, ROC analysis, and decision curve analysis were good indicators of the nomogram’s performance. In conclusion, we identified three reliable RRGs associated with the recurrence of cancer and constructed a nomogram that performed well in predicting RFS for HCC patients. These findings could enrich our understanding of the mechanisms for HCC recurrence, help surgeons predict patients’ prognosis, and promote HCC treatment.
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Affiliation(s)
- Junjie Kong
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Tao Wang
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Shu Shen
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Zifei Zhang
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Xianwei Yang
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Wentao Wang
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
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49
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Liu F, Liao Z, Song J, Yuan C, Liu Y, Zhang H, Pan Y, Zhang Z, Zhang B. Genome-wide screening diagnostic biomarkers and the construction of prognostic model of hepatocellular carcinoma. J Cell Biochem 2019; 121:2582-2594. [PMID: 31692036 DOI: 10.1002/jcb.29480] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Accepted: 10/08/2019] [Indexed: 12/24/2022]
Abstract
Although methods in diagnosis and therapy of hepatocellular carcinoma (HCC) have made significant progress in decades, the overall survival (OS) of HCC remains dissatisfactory, so it is particularly important to find better diagnostic and prognostic biomarkers. In this study, we found a more reliable potential diagnostic biomarkers and constructed a more accurate prognostic evaluation model based on integrated transcriptome sequencing analysis of multiple independent data sets. First, we performed quality evaluation and differential analysis on seven Gene Expression Omnibus (GEO) data sets, and then comprehensively analyzed the differentially expressed genes with a robust rank aggregation algorithm. Next, Least absolute shrinkage and selection operator (LASSO) regression was used to establish an 8-gene prognostic risk score (RS) model. Finally, the prognostic model was further validated in the GEO data set. Also, RS has independence on other clinicopathological characteristics but has similarities in prognostic assessment compared with the T stage. Moreover, the combination of T stage and prognostic RS model based on the 8-gene had a better prognostic evaluation effect. In brief, our research suggest that the prognostic risk model of 8 genes has important clinical significance in HCC patients, and can further enrich the prognostic guidance value of the traditional T stage.
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Affiliation(s)
- Furong Liu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province for the Clinical Medicine Research Center of Hepatic Surgery, Wuhan, Hubei, China.,The Second Clinical Medicine College, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, Hubei, China
| | - Zhibin Liao
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province for the Clinical Medicine Research Center of Hepatic Surgery, Wuhan, Hubei, China
| | - Jia Song
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province for the Clinical Medicine Research Center of Hepatic Surgery, Wuhan, Hubei, China
| | - Chaoyi Yuan
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province for the Clinical Medicine Research Center of Hepatic Surgery, Wuhan, Hubei, China
| | - Yachong Liu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province for the Clinical Medicine Research Center of Hepatic Surgery, Wuhan, Hubei, China
| | - Hongwei Zhang
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province for the Clinical Medicine Research Center of Hepatic Surgery, Wuhan, Hubei, China
| | - Yonglong Pan
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province for the Clinical Medicine Research Center of Hepatic Surgery, Wuhan, Hubei, China
| | - Zhanguo Zhang
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province for the Clinical Medicine Research Center of Hepatic Surgery, Wuhan, Hubei, China
| | - Bixiang Zhang
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Hubei Province for the Clinical Medicine Research Center of Hepatic Surgery, Wuhan, Hubei, China
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50
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Kong J, Wang T, Zhang Z, Yang X, Shen S, Wang W. Five Core Genes Related to the Progression and Prognosis of Hepatocellular Carcinoma Identified by Analysis of a Coexpression Network. DNA Cell Biol 2019; 38:1564-1576. [PMID: 31633379 DOI: 10.1089/dna.2019.4932] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
The molecular mechanism of tumorigenesis of the prevalent cancer hepatocellular carcinoma (HCC) is unclear. In this study, through weighted gene coexpression network analysis, a coexpression network was constructed by selecting the top 25% most variant genes in the dataset GSE62232. The average linkage hierarchical clustering identified 24 modules, and among them, the pink module associated with prognosis of HCC was screened. Five gene candidates (PCNA, RFC4, PTTG1, H2AFZ, and RRM1) with a common network in the module were screened after the protein-protein interaction network complex was combined with the coexpression network. After progression and survival analysis, all candidates were identified as real core genes. According to the Human Protein Atlas and the Oncomine database, these genes were dysregulated in HCC samples. The receiver operating characteristic curve proved that the expression levels of the core genes had high diagnostic efficacy. The results of gene set enrichment analysis and functional enrichment analysis demonstrated the importance of the cell cycle-related pathways in HCC progression and prognosis. In conclusion, the five real core genes and cell cycle-related pathways identified in this study could greatly improve the knowledge about HCC progression and contribute to HCC treatment.
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Affiliation(s)
- Junjie Kong
- Department of Liver Surgery, Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, P.R. China
| | - Tao Wang
- Department of Liver Surgery, Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, P.R. China
| | - Zifei Zhang
- Department of Liver Surgery, Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, P.R. China
| | - Xianwei Yang
- Department of Liver Surgery, Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, P.R. China
| | - Shu Shen
- Department of Liver Surgery, Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, P.R. China
| | - Wentao Wang
- Department of Liver Surgery, Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, P.R. China
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