ArticleOncology letters2025
Construction and validation of transcription‑factor‑based prognostic signature for TACE non‑response and characterization of tumor microenvironment infiltration in hepatocellular carcinoma.
Article in Oncology letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Advancing engineering design strategies for targeted cancer nanomedicine.Nature reviews. Cancer · 2025Review
- Magnetic resonance imaging bias field correction improves tumor prognostic evaluation after transcatheter arterial chemoembolization for liver cancer.World journal of gastrointestinal surgery · 2025Article
- Integrating single cell analysis and machine learning methods reveals stem cell-related gene S100A10 as an important target for prediction of liver cancer diagnosis and immunotherapy.Frontiers in immunology · 2024Article
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Authors and funding
6 authors.
Funding
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Abstract
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Despite continuous development of treatment methods, overall survival rate of liver cancer is low. Transcatheter arterial chemoembolization (TACE) is a first-choice treatment for advanced liver cancer. Although it is generally effective, a number of patients do not benefit from it. Therefore, the present study was conducted to assess the response of patients following TACE. RNA-sequencing data and corresponding clinical information were extracted from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. Models were constructed using weighted gene co-expression network analysis and least absolute shrinkage and selection operator-Cox regression analysis based on TCGA-LIHC and GSE104580 cohorts. The receiver operating characteristic curve was used for evaluation. Immunoassay, half-maximal inhibitory concentration analysis of risk groups, genomic enrichment analysis and nomogram construction were also performed. The predictive models were validated at the single-cell level using single-cell databases. Finally, the present study examined the expression of TACE refractoriness-related TFs (TRTs) in TACE-resistant and non-resistant cell lines
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