Dataset Information

Identification of biomarkers for Barcelona Clinic Liver Cancer staging and overall survival of patients with hepatocellular carcinoma.

ABSTRACT: The aim of the current study was to identify biomarkers that correlate with the Barcelona Clinic Liver Cancer (BCLC) staging system and prognosis of patients with hepatocellular carcinoma (HCC). We downloaded 4 gene expression datasets from the Gene Expression Omnibus database (http://www.ncbi.nlm.nih.gov/geo), and screened for genes that were differentially expressed between HCC and normal liver tissues, using significance analysis of the microarray algorithm. We used a weighted gene co-expression network analysis (WGCNA) to identify hub genes that correlate with BCLC staging, functional enrichment analysis to associate hub genes with their functions, protein-protein interaction network analysis to identify interactions among hub genes, UALCAN analysis to assess gene expression levels based on tumour stage, and survival analyses to clarify the effects of hub genes on patients' overall survival (OS). We identified 50 relevant hub genes using WGCNA; among them, 13 genes (including TIGD5, C8ORF33, NUDCD1, INSB8, and STIP1) correlated with OS and BCLC staging. Significantly enriched gene ontology biological process terms included RNA processing, non-coding RNA processing and phosphodiester bond hydrolysis, and 6 genes were found to interact with 10 or more hub genes. We identified several candidate biomarkers that correlate with BCLC staging and OS of HCC. These genes might be used for prognostic assessment and selection of HCC patients for surgery, especially those with intermediate or advanced disease.

SUBMITTER: Xu W

PROVIDER: S-EPMC6107203 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Identification of biomarkers for Barcelona Clinic Liver Cancer staging and overall survival of patients with hepatocellular carcinoma.

Xu Wei W Rao Quan Q An Yongbo Y Li Mengyi M Zhang Zhongtao Z

PloS one 20180823 8

The aim of the current study was to identify biomarkers that correlate with the Barcelona Clinic Liver Cancer (BCLC) staging system and prognosis of patients with hepatocellular carcinoma (HCC). We downloaded 4 gene expression datasets from the Gene Expression Omnibus database (http://www.ncbi.nlm.nih.gov/geo), and screened for genes that were differentially expressed between HCC and normal liver tissues, using significance analysis of the microarray algorithm. We used a weighted gene co-express ...[more]

PMID: 30138346

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Project description:This study compared the prognostic significance of staging between the American Joint Committee on Cancer 8th edition Tumor, Node, Metastasis (TNM) staging system and the Barcelona Clinic Liver Cancer (BCLC) classification in patients with hepatocellular carcinoma (HCC). The study population comprised patients with liver cancer registered in the Taiwan Cancer Database from 2007 to 2013 and was followed up until December 31, 2016. The study included patients with HCC, with known staging in both TNM and BCLC systems, and with follow-up >1 month. Primary endpoint was overall survival. Univariate and multivariate Cox proportional hazards model were constructed to investigate the significance of staging by two systems. Goodness-of-fit of model was evaluated via Akaike's information criterion (AIC), the lower the better. Among 73,136 patients with newly diagnosed liver cancer, a total of 37,062 patients with HCC (25.6% underwent surgery) were eligible. The mean age and overall survival of this cohort were 63.9 years and 27.2%, respectively. Overall survivals for stages I, II, III, and IV (the TNM system) were 54.5%, 34.9%, 10.3%, and 6.4%, respectively. Overall survivals for stages A, B, C, and D (the BCLC classification) were 54.5%, 29.2%, 9.8%, and 4.0%, respectively. The median follow-up time was 59.4 months. Multivariate Cox proportional hazards model revealed that both systems predicted overall survival, cancer-specific survival, disease-free survival, and local recurrence-free rate well. Values of ΔAIC of the BCLC classification and the TNM system were lower for the surgery group and nonsurgery group, respectively. The TNM system (8th edition) predicted long-term outcome better than the BCLC classification in patients with HCC. But in patients treated initially with surgery, the BCLC classification outperformed the 8th edition of the TNM system. IMPLICATIONS FOR PRACTICE: This work demonstrates that the Tumor, Node, Metastasis (TNM) system (8th edition) and the Barcelona Clinic Liver Cancer (BCLC) classification both predict long-term outcome significantly in patients with hepatocellular carcinoma but that the TNM system (8th edition) predicts long-term outcome better than the BCLC classification. For patients treated initially with surgery, BCLC classification outperforms in 8th edition TNM system in predicting long-term outcome.

Project description: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.

Dataset Information

Identification of biomarkers for Barcelona Clinic Liver Cancer staging and overall survival of patients with hepatocellular carcinoma.

Publications

Identification of biomarkers for Barcelona Clinic Liver Cancer staging and overall survival of patients with hepatocellular carcinoma.

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