scholarly journals Human Endogenous Retroviruses-K (HML-2) Expression Is Correlated with Prognosis and Progress of Hepatocellular Carcinoma

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Weijie Ma ◽  
Zhenfei Hong ◽  
Hailing Liu ◽  
Xi Chen ◽  
Lu Ding ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Cancer Progression ◽  
Cox Regression ◽  
Roc Curves ◽  
Endogenous Retroviruses ◽  
Human Endogenous Retroviruses ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Kaplan Meier

Background. The association between human endogenous retroviruses-K (HERV-K) (HML-2) and human disease, including a variety of cancers, has been indicated. However, the function of HERV-K (HML-2) in the progression of hepatocellular carcinoma (HCC) still remains largely unclear.Methods. We detected the expression of HERV-K (HML-2) in 84 HCC tissues and adjacent nontumor tissues by quantitative real-time PCR (qRT-PCR) and analyzed its correlation with the clinical parameters.Result. The HEVR-K level was significantly increased in HCC compared with adjacent normal tissues (P<0.01) which was proved to be significantly associated with cirrhosis (P<0.05), tumor differentiation (P<0.05), and TNM stage (P<0.05). Moreover, the high expression of HERV-K (HML-2) had a poorer overall survival than patients with lower expression by a Kaplan-Meier survival analysis (P<0.01). The multivariate Cox regression analysis indicated that the level of HERV-K (HML-2) was an independent prognostic factor for the overall survival rate of HCC patients. Receiver operating characteristic (ROC) curves demonstrated the diagnostic accuracy of HERV-K (HML-2) expression in HCC (AUC = 0.729, 74.7% sensitivity, and 67.8% specificity).Conclusions. Our results suggested that upregulation of HERV-K (HML-2) in HCC patients was significantly related to cancer progression and poor outcome, indicating that HERV-K (HML-2) might be a novel candidate prognostic biomarker for HCC.

scholarly journals NUCKS1 Acts As A Promising Novel Bio-Marker in The Prognosis of Patients with Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Xianfeng Zhang ◽  
Xianjun Zhang ◽  
Xinguo Li ◽  
Hongbing Bao ◽  
Guang Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Mrna Expression ◽  
Prognostic Value ◽  
Cox Regression ◽  
Rank Test ◽  
Cox Regression Analysis ◽  
Kinase Substrate ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Relative Mrna Expression

Abstract Background: Nuclear casein kinase and cyclin-dependent kinase substrate 1 (NUCKS1) was over-expressed in some tumors, including hepatocellular carcinoma (HCC). However, the clinical significance of NUCKS1 in HCC was still unclear. The aim of this study was to explore the expression and prognostic value of NUCKS1 in HCC. Methods: Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the relative mRNA expression of NUCKS1 in HCC tissues and corresponding adjacent normal tissues. The relationship between NUCKS1 expression and clinical characteristics of patients was analyzed by c2 test. Kaplan-Meier method and cox regression analysis were applied to estimate the prognostic value of NUCKS1 in HCC. Results: Compared with normal tissues, the relative mRNA expression level of NUCKS1 was significantly up-regulated in HCC tissues (P < 0.001). And high NUCKS1 expression was closely associated with tumor differentiation, TNM stage, vascular invasion and metastasis (P < 0.05). Kaplan-Meier analysis revealed that the overall survival of HCC patients with low expression of NUCKS1 was obviously longer than those with high NUCKS1 expression (log rank test, P = 0.001). NUCKS1 was an independent prognostic factor of HCC patients via univariate and multivariate cox regression analyses.Conclusions: NUCKS1 may be correlated with the progression of HCC and may serve as a potential factor for the prognosis of this disease.

The association of miR-138 variants with the prognosis of cervical cancer

2020 ◽  
Author(s):  
Shuangqing Cao ◽  
Lei Zheng
Keyword(s):  
Cervical Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Cox Regression ◽  
Critical Role ◽  
Expression Level ◽  
Poor Overall Survival ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Kaplan Meier

Abstract Background MicroRNA-138 (miR-138) is shown to inhibit tumor growth and played a critical role in tumor pathogenesis, the present study aimed to investigate the prognistic value of miR-138 in cervical cancer. Methods Quantitative real-time polymerase chain reaction (qRT-PCR) assay was used to detect the expression of miR-138 in the tissues of cervical cancer and adjacent normal tissues. The association of miR-138 expression with clinical characteristic was analyzed via χ2 test. Then Kaplan-Meier analysis was performed to analyze the association of miR-138 expression with the overall survival of cervical cancer patients. The multivariate cox analysis was used to evaluate the prognostic value of miR-138. Results In the current study, we found the expression level of miR-138 was significantly downregulated in the most cervical cancer patients tissues compared with that in the adjacent normal tissues (P < 0.001). And its expression was closely affected by TNM stage (P = 0.043), lymph node metastasis (P = 0.011) and FIGO stage (P = 0.002). Kaplan-Meier analysis result showed that the decreased expression level of miR-138 expression was associated with poor overall survival of patients. The cox regression analysis result indicated that miR-138 expression was independently associated with the overall survival. Conclusions The expression of miR-138 is down-regulated and involved in the development of cervical cancer. Moreover, it may serve as a prognostic marker for patients with cervical cancer.

scholarly journals A Novel Five-gene Signature Predicts Overall Survival in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Zhigang Wang ◽  
Leyu Pan ◽  
Deliang Guo ◽  
Xiaofeng Luo ◽  
Jie Tang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Regression Analysis ◽  
Cox Regression ◽  
Gene Signature ◽  
Tnm Stage ◽  
Time Dependent ◽  
Quantitative Real Time Pcr ◽  
Cox Regression Analysis ◽  
Normal Tissues

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most common challenges for public health worldwide. Due to its complex molecular and great heterogeneity, the effectiveness of existing HCC risk prediction models is unsatisfactory. Hence, more accurate prognostic models are pressingly needed. Materials and methods: Differentially expressed mRNAs (DEMs) between HCC and normal tissues were identified after downloading GSE1450 from gene omnibus (GEO) database. We randomly divided all patients into training and testing sets. Univariate Cox regression, lasso Cox regression and multivariable Cox regression analysis were used to constructed the prognostic gene signature in training set. Our study utilized Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis with clinical information, nomogram and decision curve analysis (DCA) to evaluate the predictive ability for overall survival of the novel gene signature in training, testing and whole sets. We also validated the prognostic capacity of the five-gene signature in an external validation set. The information of mutation of each gene was explored on cBioPortal online website. We performed gene set enrichment analysis (GSEA) to explore underlying mechanisms in the high and low risk group. Finally, quantitative real-time PCR was conducted to validate the expression tendency between 12 paired HCC and adjacent normal tissues. Results: Our study constructed a novel five-gene signature (CNIH4, SOX4, SPP1, SORBS2 and CCL19) for predicting overall survival of HCC. Time-dependent ROC curve indicated admirable ability in survival prediction in two datasets. Multivariable Cox regression analysis indicated that both this five-gene signature and TNM stage were two independent prognostic factors for overall survival of HCC patients. Combined with TNM stage clinical pathological parameters, the predictive capacity of nomogram had a decent improvement. The mutation of the five genes had no obvious variation. Plenty pathways were enriched by GSEA, including cell cycle and various metabolism. Furthermore, the mRNA levels of these five genes had significantly different expressions between HCC tissues and adjacent normal tissues by quantitative real-time PCR. Conclusions: A five-gene prognostic model and nomogram were constructed and validated for predicting prognostic of HCC patients. And the five-gene risk score with TNM stage models might help various HCC patients to customize individual therapies.

scholarly journals Rab25 Acts as a Promising Novel Bio-Marker in the Prognosis of Patients with Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Zhong Dai ◽  
Ke-Qing Yao ◽  
Xing-Sheng Hu ◽  
Yi-Qun Li ◽  
Yu-Tao Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Value ◽  
Cox Regression ◽  
Rank Test ◽  
Chi Square ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Chi Square Test ◽  
The Relationship

Abstract Background: Rab25 was indicated to be involved in several human tumors. However, the clinical significance of Rab25 in hepatocellular carcinoma (HCC) was still unclear. The purpose of this study was to investigate the expression and prognostic value of Rab25 in HCC.Methods: The relative mRNA expression levels of Rab25 in HCC tissues and adjacent normal tissues were detected by quantitative real-time polymerase chain reaction (qRT-PCR). Chi-square test was used to analyze the relationship between Rab25 expression and clinical characteristics of patients. The prognostic value of Rab25 in HCC was estimated through Kaplan-Meier method and cox regression analysis.Results: Rab25 gene expression level was significantly higher in HCC tissues than that in normal tissues (P<0.001). Importantly, the increased Rab25 expression was closely associated with TNM stage (P=0.024), metastasis (P=0.022) and invasion classification (P=0.039). Moreover, patients with high Rab25 expression tended to have obviously shorter overall survival than those with low expression of Rab25 (log rank test, P<0.001) via Kaplan-Meier analysis. Univariate and multivariate cox regression analyses revealed that Rab25 was an independent prognostic factor of HCC.Conclusions: Rab25 is up-regulated in HCC and contributes to the progression of this tumor. What’s more, Rab25 may be a potential bio-marker for the prognosis of HCC.

The Relationship Between microRNA-195 and the Prognosis of Cervical Cancer

2020 ◽  
Author(s):  
Shuangqing Cao ◽  
Lei Zheng
Keyword(s):  
Cervical Cancer ◽  
Overall Survival ◽  
Prognostic Value ◽  
Cox Regression ◽  
Rank Test ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Cancer Tissues ◽  
The Relationship

Abstract Background: MicroRNA-195 (miR-195), a tumor suppressor, had reported to be involved in carcinogenesis and the progression of some cancers. However, the prognostic value of miR-195 in cervical cancer remained unclear. The purpose of this study was to detect the expression of miR-195 in cervical cancer tissues and to investigate its correlation with tumor progression and prognosis.Methods: Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the relative mRNA expression of miR-195 in cervical cancer tissues and corresponding adjacent normal tissues. The relationship between miR-195 expression and clinical characteristics of patients was analyzed by chi-square test. Kaplan-Meier method was applied to compare the overall survival, and the prognostic value of miR-195 was estimated via cox regression analysis.Results: Compared with normal tissues, miR-195 expression was significantly down-regulated in cervical cancer tissues (P < 0.001). Importantly, decreased expression of miR-195 was closely associated with FIGO stage, lymph node metastasis and vascular invasion (P < 0.05). Additionally, Kaplan-Meier analysis indicated that patients with high miR-195 expression had obviously longer overall survival than those with low miR-195 expression (log rank test, P = 0.001). And miR-195 was an independent prognostic factor of cervical cancer patients via univariate and multivariate cox regression analyses.Conclusions: Decreased expression of miR-195 is associated with the progression of cervical cancer. And miR-195 may have potency to predict the prognosis of cervical cancer.

scholarly journals Identification of lncRNA prognostic signature and analysis of their functions for HCV-related hepatocellular carcinoma

2020 ◽  
Author(s):  
Kun Wang ◽  
Wenxin Li ◽  
Yefu Liu ◽  
Zhiqiang Hao ◽  
Xiangdong Hua ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Risk Score ◽  
Cox Regression ◽  
Roc Curves ◽  
The Cancer Genome Atlas ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Clinical Variables ◽  
Kaplan Meier ◽  
Underlying Mechanisms

Abstract Background Hepatitis C virus (HCV) infection is a main contribution to the increase in hepatocellular carcinoma (HCC) incidence and patients’ death recently, but prognostic biomarkers for HCV-related HCC remain rarely reported. This study was to identify an lncRNA prognostic signature for HCV-HCC patients and explore their underlying function mechanisms. Methods In total, 102 HCV-HCC samples and 50 normal control samples were obtained from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analysis were conducted to screen an lncRNA signature that could predict overall survival (OS) and then, the risk score was calculated using this signature. The prognostic potential of this risk score was evaluated by drawing Kaplan-Meier, receiver operating characteristic (ROC) curves and performing multivariate Cox regression analyses with clinical variables. Furthermore, a co-expression and competing endogenous RNA (ceRNA) networks were constructed to explore the functional mechanisms of lncRNAs. Results Multivariate Cox regression showed six lncRNAs (SLC16A1-AS1, ZFPM2-AS1, JARID2-AS1, LINC01426, USP3-AS1 and LYPLAL1-AS1) were significantly associated with OS of HCV-HCC patients. These six lncRNAs were used to establish a risk score model, which displayed a higher prognosis prediction accuracy [area under the ROC curve (AUC) = 0.95 for training set; AUC = 0.885 for testing; AUC = 0.907 for entire set]. Also, this was independent of various clinical variables. The crucial co-expression (LINC01426/SLC16A1-AS1-AURKA/SFN/CCNB1, ZFPM2-AS1/LYPLAL1-AS1/JARID2-AS1-TSSK6) or ceRNA (USP3-AS1-hsa-miR-383-SFN) interaction axes were identified. Conclusion Our study identified a novel six-lncRNA prognosis signature for HCV-HCC patients and indicated their underlying mechanisms for HCC progression.

scholarly journals Identification of a five-gene signature in association with overall survival for hepatocellular carcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11273
Author(s):  
Lei Yang ◽  
Weilong Yin ◽  
Xuechen Liu ◽  
Fangcun Li ◽  
Li Ma ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Overall Survival ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Enrichment Score ◽  
Hub Genes ◽  
Cox Regression Analysis

Background Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC. Methods The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort. Results We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.

scholarly journals Surgical Resection Significantly Promotes the Overall Survival of Patients with Hepatocellular Carcinoma: A Propensity Score Matching Analysis

2021 ◽  
Author(s):  
Pei-Min Hsieh ◽  
Hung-Yu Lin ◽  
Chao-Ming Hung ◽  
Gin-Ho Lo ◽  
I-Cheng Lu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Surgical Resection ◽  
Cox Regression ◽  
Survival Rates ◽  
Hbv Infection ◽  
Cox Regression Analysis

Abstract Background: The benefits of surgical resection (SR) for various Barcelona Clinic Liver Cancer (BCLC) stages of hepatocellular carcinoma (HCC) remain unclear. We investigated the risk factors of overall survival (OS) and survival benefits of SR over nonsurgical treatments in patients with HCC of various BCLC stages.Methods: Overall, 2316 HCC patients were included, and their clinicopathological data and OS were recorded. OS was analyzed by the Kaplan-Meier method and Cox regression analysis. Propensity score matching (PSM) analysis was performed.Results: In total, 66 (2.8%), 865 (37.4%), 575 (24.8%) and 870 (35.0%) patients had BCLC stage 0, A, B, and C disease, respectively. Furthermore, 1302 (56.2%) of all patients, and 37 (56.9%), 472 (54.6%), 313 (54.4%) and 480 (59.3%) of patients with BCLC stage 0, A, B, and C disease, respectively, died. The median follow-up duration time was 20 (range 0-96) months for the total cohort and was subdivided into 52 (8-96), 32 (1-96), 19 (0-84), and 12 (0-79) months for BCLC stages 0, A, B, and C cohorts, respectively. The risk factors for OS were 1) SR and cirrhosis; 2) SR, cirrhosis, and Child-Pugh (C-P) class; 3) SR, hepatitis B virus (HBV) infection, and C-P class; and 4) SR, HBV infection, and C-P class for the BCLC stage 0, A, B, and C cohorts, respectively. Compared to non-SR treatment, SR resulted in significantly higher survival rates in all cohorts. The 5-year OS rates for SR vs non-SR were 44.0% vs 28.7%, 72.2% vs 42.6%, 42.6% vs 36.2, 44.6% vs 23.5%, and 41.4% vs 15.3% (all p-values<0.05) in the total and BCLC stage 0, A, B, and C cohorts, respectively. After PSM, SR resulted in significantly higher survival rates compared to non-SR treatment in various BCLC stages.Conclusion: SR conferred significant survival benefits to patients with HCC of various BCLC stages and should be considered a recommended treatment for select HCC patients, especially patients with BCLC stage B and C disease.

scholarly journals Identification of a Liver Progenitor Cell-Related Genes Signature Predicting Overall Survival for Hepatocellular Carcinoma

2021 ◽  
Vol 20 ◽  
pp. 153303382110414
Author(s):  
Xiaoyong Li ◽  
Jiaqong Lin ◽  
Yuguo pan ◽  
Peng Cui ◽  
Jintang Xia
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Group ◽  
Gene Signature ◽  
Regression Analyses ◽  
Related Gene ◽  
Cox Regression Analysis

Background: Liver progenitor cells (LPCs) play significant roles in the development and progression of hepatocellular carcinoma (HCC). However, no studies on the value of LPC-related genes for evaluating HCC prognosis exist. We developed a gene signature of LPC-related genes for prognostication in HCC. Methods: To identify LPC-related genes, we analyzed mRNA expression arrays from a dataset (GSE57812 & GSE 37071) containing LPCs, mature hepatocytes, and embryonic stem cell samples. HCC RNA-Seq data from The Cancer Genome Atlas (TCGA) were used to explore the differentially expressed genes (DEGs) related to prognosis through DEG analysis and univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed to construct the LPC-related gene prognostic model in the TCGA training dataset. This model was validated in the TCGA testing set and an external dataset (International Cancer Genome Consortium [ICGC] dataset). Finally, we investigated the relationship between this prognostic model with tumor-node-metastasis stage, tumor grade, and vascular invasion of HCC. Results: Overall, 1770 genes were identified as LPC-related genes, of which 92 genes were identified as DEGs in HCC tissues compared with normal tissues. Furthermore, we randomly assigned patients from the TCGA dataset to the training and testing cohorts. Twenty-six DEGs correlated with overall survival (OS) in the univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed in the TCGA training set, and a 3-gene signature was constructed to stratify patients into 2 risk groups: high-risk and low-risk. Patients in the high-risk group had significantly lower OS than those in the low-risk group. Receiver operating characteristic curve analysis confirmed the signature's predictive capacity. Moreover, the risk score was confirmed to be an independent predictor for patients with HCC. Conclusion: We demonstrated that the LPC-related gene signature can be used for prognostication in HCC. Thus, targeting LPCs may serve as a therapeutic alternative for HCC.

scholarly journals Establishment and Validation of an MTORC1 Signaling-Related Gene Signature to Predict Overall Survival in Patients with Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Zheng Yao ◽  
Song Wen ◽  
Jun Luo ◽  
Weiyuan Hao ◽  
Weiren Liang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Decision Tree ◽  
Survival Data ◽  
Cox Regression ◽  
Gene Signature ◽  
Related Gene ◽  
Cox Regression Analysis ◽  
Cancer Hallmarks ◽  
Mtorc1 Signaling

Background. Accurate and effective biomarkers for the prognosis of patients with hepatocellular carcinoma (HCC) are poorly identified. A network-based gene signature may serve as a valuable biomarker to improve the accuracy of risk discrimination in patients. Methods. The expression levels of cancer hallmarks were determined by Cox regression analysis. Various bioinformatic methods, such as GSEA, WGCNA, and LASSO, and statistical approaches were applied to generate an MTORC1 signaling-related gene signature (MSRS). Moreover, a decision tree and nomogram were constructed to aid in the quantification of risk levels for each HCC patient. Results. Active MTORC1 signaling was found to be the most vital predictor of overall survival in HCC patients in the training cohort. MSRS was established and proved to hold the capacity to stratify HCC patients with poor outcomes in two validated datasets. Analysis of the patient MSRS levels and patient survival data suggested that the MSRS can be a valuable risk factor in two validated datasets and the integrated cohort. Finally, we constructed a decision tree which allowed to distinguish subclasses of patients at high risk and a nomogram which could accurately predict the survival of individuals. Conclusions. The present study may contribute to the improvement of current prognostic systems for patients with HCC.

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