scholarly journals A novel m6A‐related prognostic signature for predicting the overall survival of hepatocellular carcinoma patients

2021 ◽  
Author(s):  
Shiyang Xie ◽  
Yaxuan Wang ◽  
Jin Huang ◽  
Guang Li
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Prognostic Signature

A six-gene-based prognostic signature for hepatocellular carcinoma overall survival prediction

Life Sciences ◽  
2018 ◽  
Vol 203 ◽  
pp. 83-91 ◽  
Author(s):  
Zhenglu Wang ◽  
Dahong Teng ◽  
Yan Li ◽  
Zhandong Hu ◽  
Lei Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Survival Prediction ◽  
Prognostic Signature ◽  
Overall Survival Prediction

scholarly journals Identification and Validation of a Novel Metabolism‑Related Prognostic Signature in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Zhihao Wang ◽  
Kidane Siele Embaye ◽  
Qing Yang ◽  
Lingzhi Qin ◽  
Chao Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Value ◽  
Cox Regression ◽  
Cancer Genome ◽  
Regression Analyses ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Tcga Dataset

Abstract Background: Given that metabolic reprogramming has been recognized as an essential hallmark of cancer cells, this study sought to investigate the potential prognostic values of metabolism-related genes(MRGs) for hepatocellular carcinoma (HCC) diagnosis and treatment. Methods: The metabolism-related genes sequencing data of HCC samples with clinical information were obtained from the International Cancer Genome Consortium(ICGC) and The Cancer Genome Atlas (TCGA). The differentially expressed MRGs were identified by Wilcoxon rank sum test. Then, univariate Cox regression analysis were performed to identify metabolism-related DEGs that related to overall survival(OS). A novel metabolism-related prognostic signature was developed using the least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analyses . Furthermore, the signature was validated in the TCGA dataset. Finally, cox regression analysis was applied to identify the prognostic value and clinical relationship of the signature in HCC. Results: A total of 178 differentially expressed MRGs were detected between the ICGA dataset and the TCGA dataset. We found that 17 MRGs were most significantly associated with OS by using the univariate Cox proportional hazards regression analysis in HCC. Then, the Lasso and multivariate Cox regression analyses were applied to construct the novel metabolism-relevant prognostic signature, which consisted of six MRGs. The prognostic value of this prognostic model was further successfully validated in the TCGA dataset. Further analysis indicated that this signature could be an independent prognostic indicator after adjusting to other clinical factors. Six MRGs (FLVCR1, MOGAT2, SLC5A11, RRM2, COX7B2, and SCN4A) showed high prognostic performance in predicting HCC outcomes, and were further associated with tumor TNM stage, gender, age, and pathological stage. Finally, the signature was found to be associated with various clinicopathological features. Conclusions: In summary, our data provided evidence that the metabolism-based signature could serve as a reliable prognostic and predictive tool for overall survival in patients with HCC.

scholarly journals Identification and validation of a five-gene prognostic signature for hepatocellular carcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Huibin Yang ◽  
Junyu Huo ◽  
Xin Li
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Cox Regression ◽  
Human Cancer ◽  
External Validation ◽  
Enrichment Analysis ◽  
Risk Classification ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature

Abstract Background ARID1A is a commonly mutated tumor suppressor gene found in all human cancer types, but its clinical significance, oncogenic functions, and relevant mechanisms in hepatocellular carcinoma (HCC) are not well understood. Objective We aimed to improving the prognosis risk classification of HCC from the perspective of ARID1A mutations. Materials and methods We examined the interaction between ARID1A mutations and the overall survival via Kaplan-Meier survival analysis. We used gene set enrichment analysis (GSEA) to elucidate the influence of ARID1A mutations on signaling pathways. A prognostic model was constructed using LASSO and multivariate Cox regression analyses. A receiver operating characteristic (ROC) curve was used to estimate the performance and accuracy of the model. Results HCC patients with ARID1A mutations presented poor prognosis. By GSEA, we showed that genes upregulated by reactive oxygen species (ROS) and regulated by MYC were positively correlated with ARID1A mutations. A prognostic signature consisting of 5 genes (SRXN1, LDHA, TFDP1, PPM1G, and EIF2S1) was constructed in our research. The signature showed good performance in predicting overall survival (OS) for HCC patients by internal and external validation. Conclusion Our research proposed a novel and robust approach for the prognostic risk classification of HCC patients, and this approach may provide new insights to improve the treatment strategy of HCC.

scholarly journals Development and Verification of an Immune-Related Gene Pairs Prognostic Signature in Hepatocellular Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Xiaofei Feng ◽  
Shanshan Mu ◽  
Yao Ma ◽  
Wenji Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Expression Profiles ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Prognostic Signature ◽  
Gene Pairs ◽  
Immune Related Gene ◽  
Risk Patients

With the increasing prevalence of Hepatocellular carcinoma (HCC) and the poor prognosis of immunotherapy, reliable immune-related gene pairs (IRGPs) prognostic signature is required for personalized management and treatment of patients. Gene expression profiles and clinical information of HCC patients were obtained from the TCGA and ICGC databases. The IRGPs are constructed using immune-related genes (IRGs) with large variations. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct IRGPs signature. The IRGPs signature was verified through the ICGC cohort. 1,309 IRGPs were constructed from 90 IRGs with high variability. We obtained 50 IRGPs that were significantly connected to the prognosis and constructed a signature that included 17 IRGPs. In the TCGA and ICGC cohorts, patients were divided into high and low-risk patients by the IRGPs signature. The overall survival time of low-risk patients is longer than that of high-risk patients. After adjustment for clinical and pathological factors, multivariate analysis showed that the IRGPs signature is an independent prognostic factor. The Receiver operating characteristic (ROC) curve confirmed the accuracy of the signature. Besides, gene set enrichment analysis (GSEA) revealed that the signature is related to immune biological processes, and the immune microenvironment status is distinct in different risk patients. The proposed IRGPs signature can effectively assess the overall survival of HCC, and provide the relationship between the signature and the reactivity of immune checkpoint therapy and the sensitivity of targeted drugs, thereby providing new ideas for the diagnosis and treatment of the disease.

scholarly journals Identification of a novel metabolism‑related prognostic signature in hepatocellular carcinoma through bioinformatics analysis and validation through experimental studies

2020 ◽  
Author(s):  
Zhihao Wang ◽  
Kidane Siele Embaye ◽  
Qing Yang ◽  
Lingzhi Qin Qin ◽  
Chao Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Regression Analysis ◽  
Cell Lines ◽  
Cox Regression ◽  
Cancer Genome ◽  
Regression Analyses ◽  
Prognostic Signature ◽  
Hub Genes ◽  
Tcga Dataset

Abstract BackgroundGiven that metabolic reprogramming has been recognized as an essential hallmark of cancer cells, this study sought to investigate the potential prognostic values of metabolism-related genes(MRGs) for hepatocellular carcinoma (HCC) diagnosis and treatment.MethodsThe metabolism-related genes sequencing data of HCC samples with clinical information were obtained from the International Cancer Genome Consortium(ICGC) and The Cancer Genome Atlas (TCGA). The differentially expressed MRGs were identified by Wilcoxon rank sum test. Then, univariate Cox regression analysis were performed to identify metabolism-related DEGs that related to overall survival(OS) . A novel metabolism-related prognostic signature was developed using the least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analyses . Furthermore, the signature was validated in the TCGA dataset. Finally, the expression levels of hub genes were validated in cell lines by Western blotting (WB) and quantitative real-timePCR (qRT-PCR).ResultsA total of 178 differentially expressed MRGs were detected between the ICGA dataset and the TCGA dataset. We found that 17 MRGs were most significantly associated with OS by using the univariate Cox proportional hazards regression analysis in HCC. Then, the Lasso and multivariate Cox regression analyses were applied to construct the novel metabolism-relevant prognostic signature, which consisted of six MRGs. The prognostic value of this prognostic model was further successfully validated in the TCGA dataset. Further analysis indicated that this signature could be an independent prognostic indicator after adjusting to other clinical factors. Six MRGs (FLVCR1, MOGAT2, SLC5A11, RRM2, COX7B2, and SCN4A) showed high prognostic performance in predicting HCC outcomes. Finally, hub genes were chosen for validation and the expression of FLVCR1, SLC5A11, and RRM2 were significantly increased in human hepatocellular carcinoma cell lines when compared to normal human hepatic cell line, which were in agreement with the results of differential expression analysis.ConclusionsIn summary, our data provided evidence that the metabolism-based signature could serve as a reliable prognostic and predictive tool for overall survival in patients with HCC.

scholarly journals Clinical value evaluation of microRNA-324-3p and other available biomarkers in patients with HBV-infection-related hepatocellular carcinoma

2021 ◽  
Author(s):  
Li Zhao ◽  
Qian Yang ◽  
Jianbo Liu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Hepatitis B ◽  
Diagnostic Performance ◽  
Cox Regression ◽  
Hbv Infection ◽  
Healthy Controls ◽  
Survival Prognosis ◽  
Diagnosis And Prognosis ◽  
Hcc Cells

Abstract Background Patients with hepatitis B virus (HBV) infection are at high risk of hepatocellular carcinoma (HCC). This study aimed to evaluate the expression of microRNA-324-3p (miR-324-3p) in HBV-related HCC, and explore the clinical significance of serum miR-324-3p and other available biomarkers in the diagnosis and prognosis of HBV-related HCC. Methods Expression of miR-324-3p in HBV-infection-related cells and patients was estimated using quantitative real-time PCR. The receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance of serum miR-324-3p, AFP and PIVKA-II in the differentiation of HBV-related HCC from healthy controls and chronic hepatitis B (CHB). The relationship between serum miR-324-3p and patients’ clinical features was assessed using Chi-square test, and the value of miR-324-3p to predict overall survival prognosis was evaluated using Kaplan-Meier methods and Cox regression assay in patients with HBV-related HCC. Results HBV-related HCC cells had significantly increased miR-324-3p compared with normal and HBV-unrelated HCC cells, and serum miR-324-3p in HCC patients with HBV infection was also higher than that in healthy controls and CHB. Serum miR-324-3p had relatively high diagnostic accuracy for the screening of HCC case with HBV infection, and the combination of miR-324-3p, AFP and PIVKA-II showed the improved diagnostic performance. Additionally, high serum miR-324-2p in HBV-related HCC patients was associated with cirrhosis, tumor size, clinical stage and poor overall survival prognosis. Conclusion Serum increased miR-324-3p may be involved in the progression of HBV-related hepatitis to HCC, and may serve as a candidate biomarker for the diagnosis and prognosis of HBV-related HCC.

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