ArticleAging2020
TCGA and ESTIMATE data mining to identify potential prognostic biomarkers in HCC patients.
Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Research on the molecular mechanism of celastrol targeting CTNNB1/STAT3 to inhibit uveal melanoma based on network pharmacology and multi-omics analysis.Scientific reports · 2026Article
- Role of immune cell homeostasis in research and treatment response in hepatocellular carcinoma.Clinical and experimental medicine · 2025Article
- Review
- Loss of the Novel Mitochondrial Membrane Protein FAM210B Is Associated with Hepatocellular Carcinoma.Biomedicines · 2023Article
- OGG1 contributes to hepatocellular carcinoma by promoting cell cycle-related protein expression and enhancing DNA oxidative damage repair in tumor cells.Journal of clinical laboratory analysis · 2022Article
- Field cancerization profile-based prognosis signatures lead to more robust risk evaluation in hepatocellular carcinoma.iScience · 2022Article
- Natural killer cell-related prognosis signature characterizes immune landscape and predicts prognosis of HNSCC.Frontiers in immunology · 2022Article
- A predictive and prognostic model for hepatocellular carcinoma with microvascular invasion based TCGA database genomics.BMC cancer · 2021Article
- Traditional versus Microsphere Embolization for Hepatocellular Carcinoma: An Effectiveness Evaluation Using Data Mining.Healthcare (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatocellular carcinoma (HCC) is an aggressive form of cancer characterized by a high recurrence rate following resection. Studies have implicated stromal and immune cells, which form part of the tumor microenvironment, as significant contributors to the poor prognoses of HCC patients. In the present study, we first downloaded gene expression datasets for HCC patients from The Cancer Genome Atlas database and categorized the patients into low and high stromal or immune score groups. By comparing those groups, we identified differentially expressed genes significantly associated with HCC prognosis. The Gene Ontology database was then used to perform functional enrichment analysis, and the STRING network database was used to construct protein-protein interaction networks. Our results show that most of the differentially expressed genes were involved in immune processes and responses and the plasma membrane. Those results were then validated using another a dataset from a HCC cohort in the Gene Expression Omnibus database and in 10 pairs of HCC tumor tissue and adjacent nontumor tissue. These findings enabled us to identify several tumor microenvironment-related genes that associate with HCC prognosis, and some those appear to have the potential to serve as HCC biomarkers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.