Transcriptome analysis revealed key prognostic genes and microRNAs in hepatocellular carcinoma

Background Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. However, the molecular mechanisms involved in HCC remain unclear and are in urgent need of elucidation. Therefore, we sought to identify biomarkers in the prognosis of HCC through an integrated bioinformatics analysis. Methods Messenger RNA (mRNA) expression profiles were obtained from the Gene Expression Omnibus database and The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) for the screening of common differentially expressed genes (DEGs). Function and pathway enrichment analysis, protein-protein interaction network construction and key gene identification were performed. The significance of key genes in HCC was validated by overall survival analysis and immunohistochemistry. Meanwhile, based on TCGA data, prognostic microRNAs (miRNAs) were decoded using univariable and multivariable Cox regression analysis, and their target genes were predicted by miRWalk. Results Eleven hub genes (upregulated ASPM, AURKA, CCNB2, CDC20, PRC1 and TOP2A and downregulated AOX1, CAT, CYP2E1, CYP3A4 and HP) with the most interactions were considered as potential biomarkers in HCC and confirmed by overall survival analysis. Moreover, AURKA, PRC1, TOP2A, AOX1, CYP2E1, and CYP3A4 were considered candidate liver-biopsy markers for high risk of developing HCC and poor prognosis in HCC. Upregulation of hsa-mir-1269b, hsa-mir-518d, hsa-mir-548aq, hsa-mir-548f-1, and hsa-mir-6728, and downregulation of hsa-mir-139 and hsa-mir-4800 were determined to be risk factors of poor prognosis, and most of these miRNAs have strong potential to help regulate the expression of key genes. Conclusions This study undertook the first large-scale integrated bioinformatics analysis of the data from Illumina BeadArray platforms and the TCGA database. With a comprehensive analysis of transcriptional alterations, including mRNAs and miRNAs, in HCC, our study presented candidate biomarkers for the surveillance and prognosis of the disease, and also identified novel therapeutic targets at the molecular and pathway levels.

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GCSF As a Potential Molecular Target for Overall Survival of Hepatocellular Carcinoma

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207324666210322124003 ◽

2021 ◽

Vol 24 ◽

Author(s):

Heng Cao ◽

Peng Guo ◽

Xiaohui Wu ◽

Jiankun Li ◽

Chenlong Ge ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Survival Analysis ◽

Molecular Mechanisms ◽

Malignant Tumors ◽

Basic Research ◽

Clinical Samples ◽

Tumor Diameter ◽

Overall Survival Analysis

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of digestive tract in the world. Therefore, it is important to carry out studies on the molecular mechanisms of early diagnosis and treatment of HCC to reduce mortality. Methods: Bioinformatic analysis was performed to explore the significant role of GCSF on the occurrence and development of neoplasm. Differently expressed genes (DEGs) were screened, and the significant hub genes related with GCSF were identified by the multiple algorithms of Cytoscape. Functional annotation for DEGs, pathological stage and overall survival analysis were implemented. In addition, the verification for the role of GCSF on HCC was made via the clinical samples. A total of 70 participates diagnosed as HCC were recruited from November 2014 to November 2019. The immunohistochemistry assay, qRT-PCR, receiver operating characteristic (ROC) curves, and overall survival analysis were carried out. Results: GCSF was related with the tumor size, and the expression of GCSF was up-regulated in hepatocellular carcinoma tissues. The enrichment results of GO and KEGG analysis were mainly enriched in “Inflammatory response”, “Protein binding”, “Metabolic pathways”, and “Proteasome”. The tumor diameter (P < 0.001), and survival time (P < 0.001) were significantly associated with expression of GCSF via the verification of clinical data. The univariate and multivariate Cox proportional regression analysis manifested that high expression of GCSF in patients with HCC was related to poor OS. Conclusion: The expression level of GCSF is significantly associated with the prognostic survival of HCC, and it is expected to become a new prognostic marker of HCC, providing a novel idea for future basic research as well as targeted therapy.

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Identification of Key Genes and Prognostic Value Analysis in Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

International Journal of Genomics ◽

10.1155/2019/3518378 ◽

2019 ◽

Vol 2019 ◽

pp. 1-21 ◽

Cited By ~ 1

Author(s):

Meng Wang ◽

Licheng Wang ◽

Shusheng Wu ◽

Dongsheng Zhou ◽

Xianming Wang

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Expression Profiles ◽

Cyclin B1 ◽

Ppi Network ◽

Hub Genes ◽

Altered Expression ◽

Value Analysis ◽

Kaplan Meier ◽

Key Genes

Emerging evidence indicates that various functional genes with altered expression are involved in the tumor progression of human cancers. This study is aimed at identifying novel key genes that may be used for hepatocellular carcinoma (HCC) diagnosis, prognosis, and targeted therapy. This study included 3 expression profiles (GSE45267, GSE74656, and GSE84402), which were obtained from the Gene Expression Omnibus (GEO). GEO2R was used to analyze the differentially expressed genes (DEGs) between HCC and normal samples. The functional and pathway enrichment analysis was performed by the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of the identified DEGs was constructed using the Search Tool for the Retrieval of Interacting Gene, and hub genes were identified. ONCOMINE and CCLE databases were used to verify the expression of the hub genes in HCC tissues and cells. Kaplan-Meier plotter was used to assess the effects of the hub genes on the overall survival of HCC patients. A total of 99 DEGs were identified from the 3 expression profiles. These DEGs were enriched with functional processes and pathways related to HCC pathogenesis. From the PPI network, 5 hub genes were identified. The expression of the 5 hub genes was all upregulated in HCC tissues and cells compared with the control tissues and cells. Kaplan-Meier survival curves indicated that high expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), cyclin B2 (CCNB2), MAD2 mitotic arrest deficient-like 1 (MAD2L1), and topoisomerase IIα (TOP2A) predicted poor overall survival in HCC patients (all log-rank P<0.01). These results revealed that the DEGs may serve as candidate key genes during HCC pathogenesis. The 5 hub genes, including CDK1, CCNB1, CCNB2, MAD2L1, and TOP2A, may serve as promising prognostic biomarkers in HCC.

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Prediction of Overall Survival Rate in Patients With Hepatocellular Carcinoma Using an Integrated Model Based on Autophagy Gene Marker

Frontiers in Genetics ◽

10.3389/fgene.2021.647309 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shuaiqun Wang ◽

Dalu Yang ◽

Wei Kong

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Survival Rate ◽

Clinical Data ◽

Cox Regression ◽

Cox Model ◽

Pathway Enrichment Analysis ◽

Gene Marker ◽

Overall Survival Rate ◽

Cox Regression Analysis

The autophagy cell, which can inhibit the formation of tumor in the early stage and can promote the development of tumor in the late stage, plays an important role in the development of tumor. Therefore, it has potential significance to explore the influence of autophagy-related genes (AAGs) on the prognosis of hepatocellular carcinoma (HCC). The differentially expressed AAGs are selected from HCC gene expression profile data and clinical data downloaded from the TCGA database, and human autophagy database (HADB). The role of AAGs in HCC is elucidated by GO functional annotation and KEGG pathway enrichment analysis. Combining with clinical data, we selected age, gender, grade, stage, T state, M state, and N state as Cox model indexes to construct the multivariate Cox model and survival curve of Kaplan Meier (KM) was drawn to estimate patients’ survival between high- and low-risk groups. Through an ROC curve drawn by univariate and multivariate Cox regression analysis, we found that seven genes with high expression levels, including HSP90AB1, SQSTM1, RHEB, HDAC1, ATIC, HSPB8, and BIRC5 were associated with poor prognosis of HCC patients. Then the ICGC database is used to verify the reliability and robustness of the model. Therefore, the prognosis model of HCC constructed by autophagy genes might effectively predict the overall survival rate and help to find the best personalized targeted therapy of patients with HCC, which can provide better prognosis for patients.

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RAD50 predicts the prognosis of hepatitis B virus-related hepatocellular carcinoma

10.21203/rs.2.11886/v2 ◽

2020 ◽

Author(s):

Wangrui Liu ◽

Wenhao Xu ◽

Yuyan Chen ◽

Liugen Gu ◽

Xiaolei Sun ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Hepatitis B Virus ◽

Hepatitis B ◽

Differential Expression ◽

Poor Prognosis ◽

Disease Free Survival ◽

Partial Likelihood ◽

Cox Regression Analysis ◽

B Virus

Abstract Background Increasing evidence indicates that RAD50, which is involved in the DNA double-strand break (DSB) repair process, is also involved in cancer outcomes. However, its role in hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC) remains unclear.Aim This study was designed to investigate the expression of RAD50 and its prognostic value in HCC patients.Method A total of 207 patientswith HBV-associated HCCfrom two cohorts (107 and 100 patientsfrom the Affiliated Hospital of Youjiang Medical University of Nationalities and the Affiliated Hospital of Nantong University, respectively) were enrolled in the current study.The distribution of the categorical clinical-pathological data and the levels of RAD50 expression were compared with a χ 2 test. IHC staining of RAD50 was performed.A partial likelihood test based onunivariate and multivariate Cox regression analysis was developed to address the influence of independent factors on disease-free survival (DFS) and overall survival (OS). The Oncomine online database was used to analyse and validate the differential expression of RAD50. The Kaplan-Meier method and a log-rank test were performed to assess the influence of RAD50 on survival at different levels.Results RAD50 was highly expressed in HCC tissues compared to normal tissues and was significantly correlated with OS in the TCGA cohort. The validation analysis indicated that significantly increased levels of RAD50 were expressed in HCC tissues in the two independent cohorts, AHYMUN and AHNTU. In addition, HCC patients with elevated RAD50 expression levels showed poor OS and DFSin the AHYMUN cohort and decreased OS and DF Sin the AHNTU cohort. Furthermore, four datasets obtained from the Oncomine database validated the analysis of the differential expression of RAD50 in HCC tumours and normal tissues.Discussion In our study, we demonstrated that RAD50 was positively correlated with poor prognosis in HCC patients in the TCGA cohort. Our study also suggested that increased RAD50 expression in HBV-related HCC is a marker of poor prognosis. In this study, the analysis of the data form the two cohorts supported our hypothesis and clearly demonstrated thehigh expression of RAD50 in tumour tissues from HCC patients, which results inincreases in the HCC recurrence rate and poor overall survival.

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Comprehensive Analysis of the Prognostic Values of the TRIM Family in Hepatocellular Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.767644 ◽

2021 ◽

Vol 11 ◽

Author(s):

Weiyu Dai ◽

Jing Wang ◽

Zhi Wang ◽

Yizhi Xiao ◽

Jiaying Li ◽

...

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Survival Analysis ◽

Risk Score ◽

Roc Curves ◽

Genetic Alterations ◽

Pathway Enrichment Analysis ◽

Family Risk ◽

Cox Regression Analysis ◽

Family Gene

BackgroundAccumulating studies have demonstrated the abnormal expressions and prognostic values of certain members of the tripartite motif (TRIM) family in diverse cancers. However, comprehensive prognostic values of the TRIM family in hepatocellular carcinoma (HCC) are yet to be clearly defined.MethodsThe prognostic values of the TRIM family were evaluated by survival analysis and univariate Cox regression analysis based on gene expression data and clinical data of HCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The expression profiles, protein–protein interaction among the TRIM family, prediction of transcription factors (TFs) or miRNAs, genetic alterations, correlations with the hallmarks of cancer and immune infiltrates, and pathway enrichment analysis were explored by multiple public databases. Further, a TRIM family gene-based signature for predicting overall survival (OS) in HCC was built by using the least absolute shrinkage and selection operator (LASSO) regression. TCGA–Liver Hepatocellular Carcinoma (LIHC) cohort was used as the training set, and GSE76427 was used for external validation. Time-dependent receiver operating characteristic (ROC) and survival analysis were used to estimate the signature. Finally, a nomogram combining the TRIM family risk score and clinical parameters was established.ResultsHigh expressions of TRIM family members including TRIM3, TRIM5, MID1, TRIM21, TRIM27, TRIM32, TRIM44, TRIM47, and TRIM72 were significantly associated with HCC patients’ poor OS. A novel TRIM family gene-based signature (including TRIM5, MID1, TRIM21, TRIM32, TRIM44, and TRIM47) was built for OS prediction in HCC. ROC curves suggested the signature’s good performance in OS prediction. HCC patients in the high-risk group had poorer OS than the low-risk patients based on the signature. A nomogram integrating the TRIM family risk score, age, and TNM stage was established. The ROC curves suggested that the signature presented better discrimination than the similar model without the TRIM family risk score.ConclusionOur study identified the potential application values of the TRIM family for outcome prediction in HCC.

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Identification of Biomarkers of Hepatocellular Carcinoma Gene Prognosis Based on Immune-Related lncRNA Signature of Transcriptome Data

10.21203/rs.3.rs-57303/v1 ◽

2020 ◽

Author(s):

Andi Ma ◽

Yukai Sun ◽

Racheal O. Ogbodu ◽

Ling Xiao ◽

Haibing Deng ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Cox Regression ◽

Risk Group ◽

Enrichment Analysis ◽

Low Risk ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Pathway Enrichment Analysis ◽

Cox Regression Analysis

Abstract Background: It is well known that long non-coding RNAs (lncRNAs) play a vital role in cancer. We aimed to explore the prognostic value of potential immune-related lncRNAs in hepatocellular carcinoma (HCC). Methods: Validated the established lncRNA signature of 343 patients with HCC from The Cancer Genome Atlas (TCGA) and 81 samples from Gene Expression Omnibus (GEO). Immune-related lncRNAs for HCC prognosis were evaluated using Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) analyses. LASSO analysis was performed to calculate a risk score formula to explore the difference in overall survival between high- and low-risk groups in TCGA, which was verified using GEO, Gene Ontology (GO), and pathway-enrichment analysis. These analyses were used to identify the function of screened genes and construct a co-expression network of these genes. Results: Using computational difference algorithms and lasso Cox regression analysis, the differentially expressed and survival-related immune-related genes (IRGs) among patients with HCC were established as five novel immune-related lncRNA signatures (AC099850.3, AL031985.3, PRRT3-AS1, AC023157.3, MSC-AS1). Patients in the low‐risk group showed significantly better survival than patients in the high‐risk group ( P = 3.033e−05). The signature identified can be an effective prognostic factor to predict patient survival. The nomogram showed some clinical net benefits predicted by overall survival. In order to explore its underlying mechanism, several methods of enrichment were elucidated using Gene Set Enrichment Analysis. Conclusion: Identifying five immune-related lncRNA signatures has important clinical implications for predicting patient outcome and guiding tailored therapy for patients with HCC with further prospective validation.

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Identification of Key Genes and Evaluation of Their Prognosis Potential in Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

10.21203/rs.3.rs-40788/v1 ◽

2020 ◽

Author(s):

Jankun Liu ◽

zy liu ◽

Wei Li ◽

Xinghua Pan ◽

Zongjiang Fan ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Target Genes ◽

Bioinformatics Analysis ◽

Expression Profiles ◽

Survival Curve ◽

Treatment Strategies ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Key Genes

Abstract Background Hepatocellular carcinoma (HCC) is a malignancy causing highly death rate in the world. Despite the development of treatment strategies for HCC, prognosis of this malignancy remains unsatisfactory. In this study, we aimed to identify the target genes associated with the prognosis of HCC patients. Methods Three expression profiles of HCC tissues were extracted from the Gene Expression Omnibus database to explore the differentially expressed genes (DEGs) using GEO2R method. Functional enrichment analysis was performed to reveal the biological characteristics of DEGs. Protein-protein interaction (PPI) network was constructed using Cytoscape software. The survival curve of identified DEGs were tested by Kaplan-Meier analysis. Results We identified 15 DEGs (CYP39A1, CYR61, FOS, FOXO1, GADD45B, ID1, IL1RAP, MT1M, PHLDA1, RND3, SDS, SOCS2, TAT, S100P, and SPINK1) in HCC tissues. Prognosis analysis showed that 4 DEGs (FOXO1,SPINK1༌SOCS2, and TAT) correlated with overall survival time of HCC patients, which might serve as therapeutic targets for HCC patients. Conclusions By integrated bioinformatics analysis, we proposed a novel way to reveal key genes that closely relate to HCC development.

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miR-224 is an early-stage biomarker of hepatocellular carcinoma with miR-224 and miR-125b as prognostic biomarkers

Biomarkers in Medicine ◽

10.2217/bmm-2020-0099 ◽

2020 ◽

Vol 14 (15) ◽

pp. 1485-1500

Author(s):

Lichao Yang ◽

Chunmeng Wei ◽

Yasi Li ◽

Xiao He ◽

Min He

Keyword(s):

Hepatocellular Carcinoma ◽

Systematic Review ◽

Survival Analysis ◽

Sensitivity And Specificity ◽

Poor Prognosis ◽

Early Stage ◽

Meta Analysis ◽

Benign Lesion ◽

Diagnostic Efficiency ◽

Low Expression

Aim: The aim was to systematically investigate the miRNA biomarkers for early diagnosis of hepatocellular carcinoma (HCC). Materials & methods: A systematic review and meta-analysis of miRNA expression in HCC were performed. Results: A total of 4903 cases from 30 original studies were comprehensively analyzed. The sensitivity and specificity of miR-224 in discriminating early-stage HCC patients from benign lesion patients were 0.868 and 0.792, which were superior to α-fetoprotein. Combined miR-224 with α-fetoprotein, the sensitivity and specificity were increased to 0.882 and 0.808. Prognostic survival analysis showed low expression of miR-125b and high expression of miR-224 were associated with poor prognosis. Conclusion: miR-224 had a prominent diagnostic efficiency in early-stage HCC, with miR-224 and miR-125b being valuable in the prognostic diagnosis.

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