ArticleBioMed research international2019
Mining TCGA Database for Tumor Microenvironment-Related Genes of Prognostic Value in Hepatocellular Carcinoma.
Article in BioMed research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Constructing a tumor immune microenvironment-driven prognostic model in acute myeloid leukemia using bioinformatics and validation data.Scientific reports · 2025Article
- Oleanolic Acid Restores Drug Sensitivity in Sorafenib-resistant Hepatocellular Carcinoma: Evidence fromJournal of clinical and translational hepatology · 2025Article
- Constructing and validating a novel prognostic risk score model for rectal cancer based on four immune-related genes.Translational cancer research · 2025Article
- The role of MYEOV gene: a review and future directions.Frontiers in oncology · 2025Review
- A prognostic binary classifier comprised of five critical mRNAs stratified pancreatic cancer patients following resection.Heliyon · 2024Article
- Evolutionarily conserved enhancer-associated features within theFrontiers in cell and developmental biology · 2024Article
- Evaluation of vital genes correlated with CD8 + T cell infiltration as prognostic biomarkers in stomach adenocarcinoma.BMC gastroenterology · 2023Article
- Mechanisms of portal vein tumour thrombus formation and development in patients with hepatocellular carcinoma.Journal of cellular and molecular medicine · 2023Review
- Role of NCF2 as a potential prognostic factor and immune infiltration indicator in hepatocellular carcinoma.Cancer medicine · 2023Article
- Identifying TME signatures for cervical cancer prognosis based on GEO and TCGA databases.Heliyon · 2023Article
- GALNT5 functions as a suppressor of ferroptosis and a predictor of poor prognosis in pancreatic adenocarcinoma.American journal of cancer research · 2023Article
- Identification of immune cell infiltration landscape for predicting prognosis of colorectal cancer.Gastroenterology report · 2023Article
- A universal co-expression gene network and prognostic model for hepatic-biliary-pancreatic cancers identified by integrative analyses.FEBS open bio · 2022Article
- Article
- Evaluation of gene expression of PLEKHS1, AADAC, and CDKN3 as novel genomic markers in gastric carcinoma.PloS one · 2022Article
- Identification of Candidate Therapeutic Target Genes and Profiling of Tumor-Infiltrating Immune Cells in Pancreatic Cancer via Integrated Transcriptomic Analysis.Disease markers · 2022Article
- Identification of FABP7 as a Potential Biomarker for Predicting Prognosis and Antiangiogenic Drug Efficacy of Glioma.Disease markers · 2022Article
- Weighted Gene Coexpression Network Analysis Identifies TBC1D10C as a New Prognostic Biomarker for Breast Cancer.Analytical cellular pathology (Amsterdam) · 2022Article
- A predictive and prognostic model for hepatocellular carcinoma with microvascular invasion based TCGA database genomics.BMC cancer · 2021Article
- Identification and immunoprofiling of key prognostic genes in the tumor microenvironment of hepatocellular carcinoma.Bioengineered · 2021Article
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9 authors.
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Abstract
Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies. Recent studies reveal that tumor microenvironment (TME) components significantly affect HCC growth and progression, particularly the infiltrating stromal and immune cells. Thus, mining of TME-related biomarkers is crucial to improve the survival of patients with HCC. Public access of The Cancer Genome Atlas (TCGA) database allows convenient performance of gene expression-based analysis of big data, which contributes to the exploration of potential association between genes and prognosis of a variety of malignancies, including HCC. The "Estimation of STromal and Immune cells in MAlignant Tumors using Expression data" algorithm renders the quantification of the stromal and immune components in TME possible by calculating the stromal and immune scores. Differentially expressed genes (DEGs) were screened by dividing the HCC cohort of TCGA database into high- and low-score groups according to stromal and immune scores. Further analyses of functional enrichment and protein-protein interaction networks show that the DEGs are mainly involved in immune response, cell adhesion, and extracellular matrix. Finally, seven DEGs have significant association with HCC poor outcomes. These genes contain
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