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He S, Qiao J, Wang L, Yu L. A novel immune-related gene signature predicts the prognosis of hepatocellular carcinoma. Front Oncol 2022; 12:955192. [PMID: 36185203 PMCID: PMC9520462 DOI: 10.3389/fonc.2022.955192] [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: 07/01/2022] [Accepted: 08/24/2022] [Indexed: 11/21/2022] Open
Abstract
Immune-related genes play a key role in regulating the cancer immune microenvironment, influencing the overall survival of patients with hepatocellular carcinoma (HCC). Along with the rapid development of immunotherapy, identifying immune-related genes with prognostic value in HCC has attracted increasing attention. Here, we aimed to develop a prognostic signature based on immune-related genes. By investigating the transcriptome landscape of 374 HCC and 160 non-HCC samples in silico, a total of 2251 differentially expressed genes were identified. Among which, 183 differentially expressed immune-related genes were subjected to a univariate Cox proportional hazard model to screen for genes with possible prognostic significance. A 10-gene prognostic signature, including HLA-G, S100A9, S100A10, DCK, CCL14, NRAS, EPO, IL1RN, GHR and RHOA, was generated employing a multivariate Cox proportional hazard model. Kaplan–Meier and Receiver Operator Characteristic (ROC) curves were used to evaluate the prognostic utility of the 10-gene signature. Moreover, the underlying mechanisms of these genes were analyzed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. According to the Tumor Immune Estimation Resource (TIMER) database, our prognostic signature was significantly associated with tumor-infiltrating B cells, CD4 T cells, dendritic cells, macrophages and neutrophils. Our study provides a novel prognostic signature based on immune-related genes associated with clinical outco mes of HCC.
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Hallmark guided identification and characterization of a novel immune-relevant signature for prognostication of recurrence in stage I–III lung adenocarcinoma. Genes Dis 2022. [DOI: 10.1016/j.gendis.2022.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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Four-gene signature predicting overall survival and immune infiltration in hepatocellular carcinoma by bioinformatics analysis with RT‒qPCR validation. BMC Cancer 2022; 22:830. [PMID: 35907846 PMCID: PMC9338612 DOI: 10.1186/s12885-022-09934-1] [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: 05/11/2022] [Accepted: 07/26/2022] [Indexed: 12/24/2022] Open
Abstract
Background Hepatocellular carcinoma (HCC) is one of the most lethal cancers, with a poor prognosis. Prognostic biomarkers for HCC patients are urgently needed. We aimed to establish a nomogram prediction system that combines a gene signature to predict HCC prognosis. Methods Differentially expressed genes (DEGs) were identified from publicly available Gene Expression Omnibus (GEO) datasets. The Cancer Genome Atlas (TCGA) cohort and International Cancer Genomics Consortium (ICGC) cohort were regarded as the training cohort and testing cohort, respectively. First, univariate and multivariate Cox analyses and least absolute shrinkage and selection operator (LASSO) regression Cox analysis were performed to construct a predictive risk score signature. Furthermore, a nomogram system containing a risk score and other prognostic factors was developed. In addition, a correlation analysis of risk group and immune infiltration was performed. Finally, we validated the expression levels using real-time PCR. Results Ninety-five overlapping DEGs were identified from four GEO datasets, and we constructed a four-gene-based risk score predictive model (risk score = EZH2 * 0.075 + FLVCR1 * 0.086 + PTTG1 * 0.015 + TRIP13 * 0.020). Moreover, this signature was an independent prognostic factor. Next, the nomogram system containing risk score, sex and TNM stage indicated better predictive performance than independent prognostic factors alone. Moreover, this signature was significantly associated with immune cells, such as regulatory T cells, resting NK cells and M2 macrophages. Finally, RT‒PCR confirmed that the mRNA expressions of four genes were upregulated in most HCC cell lines. Conclusion We developed and validated a nomogram system containing the four-gene risk score, sex, and TNM stage to predict prognosis.
Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-09934-1.
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Zhao X, Liu W, Liu B, Zeng Q, Cui Z, Wang Y, Cao J, Gao Q, Zhao C, Dou J. Exploring the underlying molecular mechanism of liver cancer cells under hypoxia based on RNA sequencing. BMC Genom Data 2022; 23:38. [PMID: 35590240 PMCID: PMC9121577 DOI: 10.1186/s12863-022-01055-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Accepted: 05/06/2022] [Indexed: 12/18/2022] Open
Abstract
Background The aim of our study was to use the differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNAs (DEmiRNAs) to illustrate the underlying mechanism of hypoxia in liver cancer. Methods In this study, a cell model of hypoxia was established, and autophagy activity was measured with western blotting and transmission electron microscopy. The effect of hypoxia conditions on the invasion of liver cancer cell was evaluated. RNA sequencing was used to identify DEmRNAs and DEmiRNAs to explore the mechanism of hypoxia in liver cancer cells. Results We found that autophagy activation was triggered by hypoxia stress and hypoxia might promote liver cancer cell invasion. In addition, a total of 407 shared DEmRNAs and 57 shared DEmiRNAs were identified in both HCCLM3 hypoxia group and SMMC-7721 hypoxia group compared with control group. Furthermore, 278 DEmRNAs and 24 DEmiRNAs were identified as cancer hypoxia-specific DEmRNAs and DEmiRNAs. Finally, we obtained 19 DEmiRNAs with high degree based on the DEmiRNA-DEmRNA interaction network. Among them, hsa-miR-483-5p, hsa-miR-4739, hsa-miR-214-3p and hsa-miR-296-5p may be potential gene signatures related to liver cancer hypoxia. Conclusions Our study may help to understand the potential molecular mechanism of hypoxia in liver cancer. Supplementary Information The online version contains supplementary material available at 10.1186/s12863-022-01055-9.
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Affiliation(s)
- Xin Zhao
- Department of Hepatobiliary Surgery, The Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang City, 050051, Hebei Province, China
| | - Wenpeng Liu
- Department of Hepatobiliary Surgery, The Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang City, 050051, Hebei Province, China
| | - Baowang Liu
- Department of Hepatobiliary Surgery, The Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang City, 050051, Hebei Province, China
| | - Qiang Zeng
- Department of Hepatobiliary Surgery, The Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang City, 050051, Hebei Province, China
| | - Ziqiang Cui
- Department of Hepatobiliary Surgery, The Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang City, 050051, Hebei Province, China
| | - Yang Wang
- Department of Hepatobiliary Surgery, The Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang City, 050051, Hebei Province, China
| | - Jinglin Cao
- Department of Hepatobiliary Surgery, The Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang City, 050051, Hebei Province, China
| | - Qingjun Gao
- Department of Hepatobiliary Surgery, The Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang City, 050051, Hebei Province, China
| | - Caiyan Zhao
- Department of Infectious Disease, The Third Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jian Dou
- Department of Hepatobiliary Surgery, The Third Hospital of Hebei Medical University, No.139 Ziqiang Road, Shijiazhuang City, 050051, Hebei Province, China.
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Zhang G, Su L, Lv X, Yang Q. A novel tumor doubling time-related immune gene signature for prognosis prediction in hepatocellular carcinoma. Cancer Cell Int 2021; 21:522. [PMID: 34627241 PMCID: PMC8502295 DOI: 10.1186/s12935-021-02227-w] [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: 05/17/2021] [Accepted: 09/24/2021] [Indexed: 12/30/2022] Open
Abstract
Background Hepatocellular carcinoma (HCC) has become a global health issue of wide concern due to its high prevalence and poor therapeutic efficacy. Both tumor doubling time (TDT) and immune status are closely related to the prognosis of HCC patients. However, the association between TDT-related genes (TDTRGs) and immune-related genes (IRGs) and the value of their combination in predicting the prognosis of HCC patients remains unclear. The current study aimed to discover reliable biomarkers for anticipating the future prognosis of HCC patients based on the relationship between TDTRGs and IRGs. Methods Tumor doubling time-related genes (TDTRGs) were acquired from GSE54236 by using Pearson correlation test and immune-related genes (IRGs) were available from ImmPort. Prognostic TDTRGs and IRGs in TCGA-LIHC dataset were determined to create a prognostic model by the LASSO-Cox regression and stepwise Cox regression analysis. International Cancer Genome Consortium (ICGC) and another cohort of individual clinical samples acted as external validations. Additionally, significant impacts of the signature on HCC immune microenvironment and reaction to immune checkpoint inhibitors were observed. Results Among the 68 overlapping genes identified as TDTRG and IRG, a total of 29 genes had significant prognostic relevance and were further selected by performing a LASSO-Cox regression model based on the minimum value of λ. Subsequently, a prognostic three-gene signature including HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1 (HACE1), C-type lectin domain family 1 member B (CLEC1B), and Collectin sub-family member 12 (COLEC12) was finally identified by stepwise Cox proportional modeling. The signature exhibited superior accuracy in forecasting the survival outcomes of HCC patients in TCGA, ICGC and the independent clinical cohorts. Patients in high-risk subgroup had significantly increased levels of immune checkpoint molecules including PD-L1, CD276, CTLA4, CXCR4, IL1A, PD-L2, TGFB1, OX40 and CD137, and are therefore more sensitive to immune checkpoint inhibitors (ICIs) treatment. Finally, we first found that overexpression of CLEC1B inhibited the proliferation and migration ability of HuH7 cells. Conclusions In summary, the prognostic signature based on TDTRGs and IRGs could effectively help clinicians classify HCC patients for prognosis prediction and individualized immunotherapies. Supplementary Information The online version contains supplementary material available at 10.1186/s12935-021-02227-w.
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Affiliation(s)
- Genhao Zhang
- Department of Blood Transfusion, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Lisa Su
- Department of Genetic and Prenatal Diagnosis Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xianping Lv
- Department of Blood Transfusion, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qiankun Yang
- Department of Blood Transfusion, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Guo H, Li C, Su X, Huang X. A Five-mRNA Expression Signature to Predict Survival in Oral Squamous Cell Carcinoma by Integrated Bioinformatic Analyses. Genet Test Mol Biomarkers 2021; 25:517-527. [PMID: 34406843 PMCID: PMC8403201 DOI: 10.1089/gtmb.2021.0066] [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] [Indexed: 12/13/2022] Open
Abstract
Objectives: This study was designed to identify a messenger RNA (mRNA) expression signature to predict survival in patients with oral squamous cell carcinoma (OSCC). Methods: mRNA expression profiles were integrated with clinical data from 280 samples, including 19 normal tissues and 261 OSCC tissues in The Cancer Genome Atlas. We identified differentially expressed mRNAs (DEmRNAs) between the OSCC and normal tissue samples and developed a novel mRNA-focused expression signature using a Cox regression analysis and other bioinformatic methods. The prognostic value of this signature was evaluated by Kaplan–Meier analysis, multivariable COX regression, and receiver operating characteristic (ROC) curve analysis. Protein–protein interaction (PPI) network, gene ontology, and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed to predict the function of the DEmRNAs. Signature-related mRNAs were analyzed by gene set enrichment analyses (GSEA) and validated by quantitative real-time polymerase chain reaction (qRT-PCR) in 20 paired OSCC and adjacent healthy tissues. Results: We identified a novel 5-mRNA expression signature (HOXA1, CELSR3, HIST1H3J, ZFP42, and ASCL4) that could predict patient outcomes in OSCC. The risk score based on the signature was able to separate OSCC patients into high- and low-risk groups that showed significantly different overall survival (p < 0.001, log-rank test). The signature was further validated as an effective independent prognostic predictor of OSCC by multivariate Cox regression analysis (hazard ratio = 3.747, confidence interval: 2.279–5.677, p < 0.001) and ROC curve of the third year (area under the curve = 0.733). Functional analysis demonstrated that the key hub genes in the PPI network were mainly enriched in cell division, cell proliferation, and the p53 signaling pathway. GSEA results showed that the 5 mRNAs were significantly enriched in mismatch repair, DNA replication, and the NOTCH signaling pathway. Finally, qRT-PCR results showed that the 5 mRNAs were upregulated in OSCC tissue in agreement with the predictions from our bioinformatics analysis. Conclusions: We identified a novel 5-mRNA signature that could predict the survival of patients with OSCC and may be a promising biomarker for personalized cancer treatments.
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Affiliation(s)
- Hejia Guo
- Guangxi Medical University College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Guangxi Key Laboratory of the Rehabilitation and Reconstruction of Oral and Maxillofacial Research, College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Guangxi Colleges and Universities Key Laboratory of Treatment and Research for Oral and Maxillofacial Surgery Disease, College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Medical Scientific Research Center, College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Department of Oral and Maxillofacial Surgery, the Affiliated Stomatology Hospital of Guangxi Medical University, Nanning, P.R. China
| | - Cuiping Li
- Guangxi Medical University College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Guangxi Key Laboratory of the Rehabilitation and Reconstruction of Oral and Maxillofacial Research, College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Guangxi Colleges and Universities Key Laboratory of Treatment and Research for Oral and Maxillofacial Surgery Disease, College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Medical Scientific Research Center, College of Stomatology, Guangxi Medical University, Nanning, P.R. China
| | - Xiaoping Su
- Guangxi Medical University College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Guangxi Key Laboratory of the Rehabilitation and Reconstruction of Oral and Maxillofacial Research, College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Guangxi Colleges and Universities Key Laboratory of Treatment and Research for Oral and Maxillofacial Surgery Disease, College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Medical Scientific Research Center, College of Stomatology, Guangxi Medical University, Nanning, P.R. China
| | - Xuanping Huang
- Guangxi Medical University College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Guangxi Key Laboratory of the Rehabilitation and Reconstruction of Oral and Maxillofacial Research, College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Guangxi Colleges and Universities Key Laboratory of Treatment and Research for Oral and Maxillofacial Surgery Disease, College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Medical Scientific Research Center, College of Stomatology, Guangxi Medical University, Nanning, P.R. China.,Department of Oral and Maxillofacial Surgery, the Affiliated Stomatology Hospital of Guangxi Medical University, Nanning, P.R. China
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Su L, Zhang G, Kong X. A Novel Five-Gene Signature for Prognosis Prediction in Hepatocellular Carcinoma. Front Oncol 2021; 11:642563. [PMID: 34336648 PMCID: PMC8322700 DOI: 10.3389/fonc.2021.642563] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 04/06/2021] [Indexed: 01/12/2023] Open
Abstract
Hepatocellular carcinoma (HCC) has been a global health issue and attracted wide attention due to its high incidence and poor outcomes. In this study, our purpose was to explore an effective prognostic marker for HCC. Five cohort profile datasets from GEO (GSE25097, GSE36376, GSE62232, GSE76427 and GSE101685) were integrated with TCGA-LIHC and GTEx dataset to identify differentially expressed genes (DEGs) between normal and cancer tissues in HCC patients, then 5 upregulated differentially expressed genes and 32 downregulated DEGs were identified as common DEGs in total. Next, we systematically explored the relationship between the expression of 37 common DEGs in tumor tissues and overall survival (OS) rate of HCC patients in TCGA and constructed a novel prognostic model composed of five genes (AURKA, PZP, RACGAP1, ACOT12 and LCAT). Furthermore, the predicted performance of the five-gene signature was verified in ICGC and another independent clinical samples cohort, and the results demonstrated that the signature performed well in predicting the OS rate of patients with HCC. What is more, the signature was an independent hazard factor for HCC patients when considering other clinical factors in the three cohorts. Finally, we found the signature was significantly associated with HCC immune microenvironment. In conclusion, the prognostic five-gene signature identified in our present study could efficiently classify patients with HCC into subgroups with low and high risk of longer overall survival time and help clinicians make decisions for individualized treatment.
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Affiliation(s)
- Lisa Su
- Department of Genetic and Prenatal Diagnosis Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Genhao Zhang
- Department of Blood Transfusion, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiangdong Kong
- Department of Genetic and Prenatal Diagnosis Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Zhang Y, Tang Y, Guo C, Li G. Integrative analysis identifies key mRNA biomarkers for diagnosis, prognosis, and therapeutic targets of HCV-associated hepatocellular carcinoma. Aging (Albany NY) 2021; 13:12865-12895. [PMID: 33946043 PMCID: PMC8148482 DOI: 10.18632/aging.202957] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 03/23/2021] [Indexed: 02/05/2023]
Abstract
Hepatitis C virus-associated HCC (HCV-HCC) is a prevalent malignancy worldwide and the molecular mechanisms are still elusive. Here, we screened 240 differentially expressed genes (DEGs) of HCV-HCC from Gene expression omnibus (GEO) and the Cancer Genome Atlas (TCGA), followed by weighted gene coexpression network analysis (WGCNA) to identify the most significant module correlated with the overall survival. 10 hub genes (CCNB1, AURKA, TOP2A, NEK2, CENPF, NUF2, CDKN3, PRC1, ASPM, RACGAP1) were identified by four approaches (Protein-protein interaction networks of the DEGs and of the significant module by WGCNA, and diagnostic and prognostic values), and their abnormal expressions, diagnostic values, and prognostic values were successfully verified. A four hub gene-based prognostic signature was built using the least absolute shrinkage and selection operator (LASSO) algorithm and a multivariate Cox regression model with the ICGC-LIRI-JP cohort (N =112). Kaplan-Meier survival plots (P = 0.0003) and Receiver Operating Characteristic curves (ROC = 0.778) demonstrated the excellent predictive potential for the prognosis of HCV-HCC. Additionally, upstream regulators including transcription factors and miRNAs of hub genes were predicted, and candidate drugs or herbs were identified. These findings provide a firm basis for the exploration of the molecular mechanism and further clinical biomarkers development of HCV-HCC.
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Affiliation(s)
- Yongqiang Zhang
- Molecular Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, P.R. China.,West China School of Medicine, West China Hospital, Sichuan University, Chengdu 610041, P.R. China
| | - Yuqin Tang
- School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, P.R. China
| | - Chengbin Guo
- Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, P.R. China
| | - Gen Li
- Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, P.R. China
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Yu B, Liang H, Ye Q, Wang Y. Establishment of a Genomic-Clinicopathologic Nomogram for Predicting Early Recurrence of Hepatocellular Carcinoma After R0 Resection. J Gastrointest Surg 2021; 25:112-124. [PMID: 32128678 DOI: 10.1007/s11605-020-04554-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Accepted: 02/18/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND A high rate of postoperative recurrence, especially early recurrence (ER) occurring within 1 year, seriously impedes patients with hepatocellular carcinoma (HCC) from achieving long-term survival. This study aimed to establish a genomic-clinicopathologic nomogram for precisely predicting ER in HCC patients after R0 resection. METHODS Two reliable datasets from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were selected as the training and validation cohorts, respectively. The prognostic genes related to ER were screened out by univariate Cox regression analysis and differential expression analysis. The gene-based prognostic index was constructed using LASSO and Cox regression analyses, and its independent prognostic value was assessed by Kaplan-Meier and multivariate Cox analyses. Gene set enrichment analysis (GSEA) was performed to explore the biological pathways related to the prognostic index. Finally, the nomogram integrating all the independent prognostic factors was established and comprehensively evaluated by calibration plots, the C-index, receiver operating characteristic curves, and decision curve analysis. RESULTS Nine dysregulated and prognostic genes related to ER (ZNF131, TATDN2, TXN, DDX55, KPNA2, ZNF30, TIMELESS, SFRP1, and COLEC11) were identified (all P < 0.05). The prognostic index model based on the 9 genes was successfully constructed using the TCGA cohort and showed a certain capability to discriminate the ER group from the non-ER group (P < 0.05) and good independent prognostic value in terms of predicting poor early recurrence-free survival (P < 0.05). Eight biological pathways significantly related to ER were identified by GSEA, such as "cell cycle", "homologous recombination" and "p53 signaling pathway." The genomic-clinicopathologic nomogram integrating the 9-gene-based prognostic index and TNM stage displayed significantly higher predictive accuracy and clinical application value than that of TNM stage model both in the training and validation cohorts (all P < 0.05). CONCLUSIONS The novel genomic-clinicopathologic nomogram may be a convenient and powerful tool for accurately predicting ER in HCC patients after R0 resection.
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Affiliation(s)
- Bin Yu
- Zhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, Hubei Key Laboratory of Medical Technology on Transplantation, Wuhan, 430071, Hubei, People's Republic of China
| | - Han Liang
- Zhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, Hubei Key Laboratory of Medical Technology on Transplantation, Wuhan, 430071, Hubei, People's Republic of China
| | - Qifa Ye
- Zhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, Hubei Key Laboratory of Medical Technology on Transplantation, Wuhan, 430071, Hubei, People's Republic of China.,TThe 3rd Xiangya Hospital of Central South University, Research Center of National Health Ministry on Transplantation Medicine Engineering and Technology, Changsha, 410013, Hunan, People's Republic of China
| | - Yanfeng Wang
- Zhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, Hubei Key Laboratory of Medical Technology on Transplantation, Wuhan, 430071, Hubei, People's Republic of China.
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Zhong LK, Gan XX, Deng XY, Shen F, Feng JH, Cai WS, Liu QY, Miao JH, Zheng BX, Xu B. Potential five-mRNA signature model for the prediction of prognosis in patients with papillary thyroid carcinoma. Oncol Lett 2020; 20:2302-2310. [PMID: 32782547 PMCID: PMC7400165 DOI: 10.3892/ol.2020.11781] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 05/21/2020] [Indexed: 12/12/2022] Open
Abstract
Although the mortality rate of papillary thyroid carcinoma (PTC) is relatively low, the recurrence rates of PTC remain high. The high recurrence rates are related to the difficulties in treatment. Gene expression profiles has provided novel insights into potential therapeutic targets and molecular biomarkers of PTC. The aim of the present study was to identify mRNA signatures which may categorize PTCs into high-and low-risk subgroups and aid with the predictions for prognoses. The mRNA expression profiles of PTC and normal thyroid tissue samples were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs were identified using the ‘EdgeR’ software package. Gene signatures associated with the overall survival of PTC were selected, and enrichment analysis was performed to explore the biological pathways and functions of the prognostic mRNAs using the Database for Visualization, Annotation and Integration Discovery. A signature model was established to investigate a specific and robust risk stratification for PTC. A total of 1,085 differentially expressed mRNAs were identified between the PTC and normal thyroid tissue samples. Among them, 361 mRNAs were associated with overall survival (P<0.05). A 5-mRNA prognostic signature for PTC (ADRA1B, RIPPLY3, PCOLCE, TEKT1 and SALL3) was identified to classify the patients into high-and low-risk subgroups. These prognostic mRNAs were enriched in Gene Ontology terms such as ‘calcium ion binding’, ‘enzyme inhibitor activity’, ‘carbohydrate binding’, ‘transcriptional activator activity’, ‘RNA polymerase II core promoter proximal region sequence-specific binding’ and ‘glutathione transferase activity’, and Kyoto Encyclopedia of Genes and Genomes signaling pathways such as ‘pertussis’, ‘ascorbate and aldarate metabolism’, ‘systemic lupus erythematosus’, ‘drug metabolism-cytochrome P450 and ‘complement and coagulation cascades’. The 5-mRNA signature model may be useful during consultations with patients with PTC to improve the prediction of their prognosis. In addition, the prognostic signature identified in the present study may reveal novel therapeutic targets for patients with PTC.
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Affiliation(s)
- Lin-Kun Zhong
- Department of General Surgery, The First Affiliated Hospital, Jinan University, Guangzhou, Guangdong 510630, P.R. China.,Department of General Surgery, Zhongshan City People's Hospital Affiliated to Sun Yat-sen University, Zhongshan, Guangdong 528403, P.R. China
| | - Xiao-Xiong Gan
- Department of General Surgery, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong 510180, P.R. China
| | - Xing-Yan Deng
- Department of General Surgery, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong 510180, P.R. China
| | - Fei Shen
- Department of General Surgery, The First Affiliated Hospital, Jinan University, Guangzhou, Guangdong 510630, P.R. China.,Department of General Surgery, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong 510180, P.R. China
| | - Jian-Hua Feng
- Department of General Surgery, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong 510180, P.R. China
| | - Wen-Song Cai
- Department of General Surgery, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong 510180, P.R. China
| | - Qiong-Yao Liu
- Department of Oncology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong 510180, P.R. China
| | - Jian-Hang Miao
- Department of General Surgery, Zhongshan City People's Hospital Affiliated to Sun Yat-sen University, Zhongshan, Guangdong 528403, P.R. China
| | - Bing-Xing Zheng
- Department of General Surgery, Zhongshan City People's Hospital Affiliated to Sun Yat-sen University, Zhongshan, Guangdong 528403, P.R. China
| | - Bo Xu
- Department of General Surgery, The First Affiliated Hospital, Jinan University, Guangzhou, Guangdong 510630, P.R. China.,Department of General Surgery, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong 510180, P.R. China
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Wang XH, Liao B, Hu WJ, Tu CX, Xiang CL, Hao SH, Mao XH, Qiu XM, Yang XJ, Yue X, Kuang M, Peng BG, Li SQ. Novel Models Predict Postsurgical Recurrence and Overall Survival for Patients with Hepatitis B Virus-Related Solitary Hepatocellular Carcinoma ≤10 cm and Without Portal Venous Tumor Thrombus. Oncologist 2020; 25:e1552-e1561. [PMID: 32663354 DOI: 10.1634/theoncologist.2019-0766] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Accepted: 06/22/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The predictive model of postsurgical recurrence for solitary early hepatocellular carcinoma (SE-HCC) is not well established. The aim of this study was to develop a novel model for prediction of postsurgical recurrence and survival for patients with hepatitis B virus (HBV)-related SE-HCC ≤10 cm. PATIENTS AND METHODS Data from 1,081 patients with HBV-related SE-HCC ≤10 cm who underwent curative liver resection from 2003 to 2016 in our center were collected retrospectively and randomly divided into the derivation cohort (n = 811) and the internal validation cohort (n = 270). Eight hundred twenty-three patients selected from another four tertiary hospitals served as the external validation cohort. Postsurgical recurrence-free survival (RFS) and overall survival (OS) predictive nomograms were generated. The discriminatory accuracies of the nomograms were compared with six conventional hepatocellular carcinoma (HCC) staging systems. RESULTS Tumor size, differentiation, microscopic vascular invasion, preoperative α-fetoprotein, neutrophil-to-lymphocyte ratio, albumin-to-bilirubin ratio, and blood transfusion were identified as the risk factors associated with RFS and OS. RFS and OS predictive nomograms based on these seven variables were generated. The C-index was 0.83 (95% confidence interval [CI], 0.79-0.87) for the RFS-nomogram and 0.87 (95% CI, 0.83-0.91) for the OS-nomogram. Calibration curves showed good agreement between actual observation and nomogram prediction. Both C-indices of the two nomograms were substantially higher than those of the six conventional HCC staging systems (0.54-0.74 for RFS; 0.58-0.76 for OS) and those of HCC nomograms reported in literature. CONCLUSION The novel nomograms were shown to be accurate at predicting postoperative recurrence and OS for patients with HBV-related SE-HCC ≤10 cm after curative liver resection. IMPLICATIONS FOR PRACTICE This multicenter study proposed recurrence or mortality predictive nomograms for patients with hepatitis B virus-related solitary early hepatocellular carcinoma ≤10 cm after curative liver resection. A close postsurgical surveillance protocol and adjuvant therapy should be considered for patients at high risk of recurrence.
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Affiliation(s)
- Xiao-Hui Wang
- Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China
- Department of Hepatobiliary Surgery, The Tumor Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Bing Liao
- Department of Pathology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Wen-Jie Hu
- Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Cai-Xue Tu
- Department of Hepatobiliary Surgery, The Xiehe Hospital of Huazhong University of Science and Technology, Wuhan, People's Republic of China
| | - Cai-Ling Xiang
- Department of Hepatobiliary Surgery, The Hunan Provincial People's Hospital, Changsha, People's Republic of China
| | - Sheng-Hua Hao
- Department of Hepatobiliary Surgery, The Xiehe Hospital of Huazhong University of Science and Technology, Wuhan, People's Republic of China
| | - Xian-Hai Mao
- Department of Hepatobiliary Surgery, The Hunan Provincial People's Hospital, Changsha, People's Republic of China
| | - Xiao-Ming Qiu
- Department of Surgery, The Gansu People's Hospital, Lanzhou, People's Republic of China
| | - Xiao-Jun Yang
- Department of Surgery, The Gansu People's Hospital, Lanzhou, People's Republic of China
| | - Xiao Yue
- Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Ming Kuang
- Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Bao-Gang Peng
- Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Shao-Qiang Li
- Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China
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Yang L, He Y, Zhang Z, Wang W. Systematic analysis and prediction model construction of alternative splicing events in hepatocellular carcinoma: a study on the basis of large-scale spliceseq data from The Cancer Genome Atlas. PeerJ 2019; 7:e8245. [PMID: 31844595 PMCID: PMC6907093 DOI: 10.7717/peerj.8245] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 11/19/2019] [Indexed: 02/05/2023] Open
Abstract
Growing evidence showed that alternative splicing (AS) event is significantly related to tumor occurrence and progress. This study was performed to make a systematic analysis of AS events and constructed a robust prediction model of hepatocellular carcinoma (HCC). The clinical information and the genes expression profile data of 335 HCC patients were collected from The Cancer Genome Atlas (TCGA). Information of seven types AS events were collected from the TCGA SpliceSeq database. Overall survival (OS) related AS events and splicing factors (SFs) were identified using univariate Cox regression analysis. The corresponding genes of OS-related AS events were sent for gene network analysis and functional enrichment analysis. Optimal OS-related AS events were selected by LASSO regression to construct prediction model using multivariate Cox regression analysis. Prognostic value of the prediction models were assessed by receiver operating characteristic (ROC) curve and KaplanMeir survival analysis. The relationship between the Percent Spliced In (PSI) value of OS-related AS events and SFs expression were analyzed using Spearman correlation analysis. And the regulation network was generated by Cytoscape. A total of 34,163 AS events were identified, which consist of 3,482 OS-related AS events. UBB, UBE2D3, SF3A1 were the hub genes in the gene network of the top 800 OS-related AS events. The area under the curve (AUC) of the final prediction model based on seven types OS-related AS events was 0.878, 0.843, 0.821 in 1, 3, 5 years, respectively. Upon multivariate analysis, risk score (All) served as the risk factor to independently predict OS for HCC patients. SFs HNRNPH3 and HNRNPL were overexpressed in tumor samples and were signifcantly associated with the OS of HCC patients. The regulation network showed prominent correlation between the expression of SFs and OS-related AS events in HCC patients. The final prediction model performs well in predicting the prognosis of HCC patients. And the findings in this study improve our understanding of the association between AS events and HCC.
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Affiliation(s)
- Lingpeng Yang
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yang He
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Zifei Zhang
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wentao Wang
- Department of Liver Surgery & Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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