ArticleJournal of cellular and molecular medicine2018
A four-gene-based prognostic model predicts overall survival in patients with hepatocellular carcinoma.
Article in Journal of cellular and molecular medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers.
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Who cites it
95 citing papers in PubMed.
- Article
- Visual analytics framework for survival analysis and biomarker discovery from gene expression data.PloS one · 2026Article
- An exploratory study on the potential of angiogenic genes in early HNSCC detection.Discover oncology · 2025Article
- Upregulation of lncRNA ANRASSF1 is associated with the lymph node metastasis andBiomarkers in medicine · 2025Article
- CENPs in hepatocellular carcinoma: a comprehensive review of expression patterns, clinical correlations, and functional mechanisms.American journal of cancer research · 2025Review
- Machine learning approach identifies inflammatory gene signature for predicting survival outcomes in hepatocellular carcinoma.Scientific reports · 2024Article
- The molecular prognostic score, a classifier for risk stratification of high-grade serous ovarian cancer.Journal of ovarian research · 2024Article
- The Tumor Microbiome as a Predictor of Outcomes in Patients with Metastatic Melanoma Treated with Immune Checkpoint Inhibitors.Cancer research communications · 2024Article
- Article
- Construction of a prognostic prediction model in liver cancer based on genes involved in integrin cell surface interactions pathway by multi-omics screening.Frontiers in cell and developmental biology · 2024Article
- Construction of a Prognostic Model for Hepatocellular Carcinoma Based on Macrophage Polarization-Related Genes.Journal of hepatocellular carcinoma · 2024Article
- Establishment of a risk score model for bladder urothelial carcinoma based on energy metabolism-related genes and their relationships with immune infiltration.FEBS open bio · 2023Article
- Elevated expression of TNFRSF4 impacts immune cell infiltration and gene mutation in hepatocellular carcinoma.Cancer biomarkers : section A of Disease markers · 2023Article
- Prognosis and personalized medicine prediction by integrated whole exome and transcriptome sequencing of hepatocellular carcinoma.Frontiers in genetics · 2023Article
- Beta2-Microglobulin as Predictive Biomarkers in the Prognosis of Hepatocellular Carcinoma and Development of a New Nomogram.Journal of hepatocellular carcinoma · 2023Article
- A novel signature constructed by super-enhancer-related genes for the prediction of prognosis in hepatocellular carcinoma and associated with immune infiltration.Frontiers in oncology · 2023Article
- Screening for aberrantly methylated and differentially expressed genes in nonalcoholic fatty liver disease of hepatocellular carcinoma patients with cirrhosis.World journal of surgical oncology · 2022Article
- Whole-genome sequencing identifies new candidate genes for nonobstructive azoospermia.Andrology · 2022Article
- In Silico Identification and Validation of Cuproptosis-Related LncRNA Signature as a Novel Prognostic Model and Immune Function Analysis in Colon Adenocarcinoma.Current oncology (Toronto, Ont.) · 2022Article
- Identification of multi-omics biomarkers and construction of the novel prognostic model for hepatocellular carcinoma.Scientific reports · 2022Article
35 more citing papers are in PubMed but not listed here.
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the development of new advances in hepatocellular carcinoma (HCC) management and noninvasive radiological techniques, high-risk patient groups such as those with hepatitis virus are closely monitored. HCC is increasingly diagnosed early, and treatment may be successful. In spite of this progress, most patients who undergo a hepatectomy will eventually relapse, and the outcomes of HCC patients remain unsatisfactory. In our study, we aimed to identify potential gene biomarkers based on RNA sequencing data to predict and improve HCC patient survival. The gene expression data and clinical information were acquired from The Cancer Genome Atlas (TCGA) database. A total of 339 differentially expressed genes (DEGs) were obtained between the HCC (n = 374) and normal tissues (n = 50). Four genes (CENPA, SPP1, MAGEB6 and HOXD9) were screened by univariate, Lasso and multivariate Cox regression analyses to develop the prognostic model. Further analysis revealed the independent prognostic capacity of the prognostic model in relation to other clinical characteristics. The receiver operating characteristic (ROC) curve analysis confirmed the good performance of the prognostic model. Then, the prognostic model and the expression levels of the four genes were validated using the Gene Expression Omnibus (GEO) dataset. A nomogram comprising the prognostic model to predict the overall survival was established, and internal validation in the TCGA cohort was performed. The predictive model and the nomogram will enable patients with HCC to be more accurately managed in trials testing new drugs and in clinical practice.
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