ArticleTranslational cancer research2024
A novel anoikis-related gene signature can predict the prognosis of hepatocarcinoma patients.
Article in Translational cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Article
- Newly Established Anoikis-Associated Genes Predict the Prognosis of Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2025Article
- Massive gastrointestinal hemorrhage and iodine-125 seed migration due to hepatogastric fistula: a case report and literature review.Translational cancer research · 2024Article
- Exploring SSR1 as a novel diagnostic and prognostic biomarker in hepatocellular carcinoma, and its relationship with immune infiltration.Translational cancer research · 2024Article
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Authors and funding
4 authors.
Funding
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Abstract
Background: Hepatocellular carcinoma (HCC) is a major health problem with more than 850,000 cases per year worldwide. This cancer is now the third leading cause of cancer-related deaths worldwide, and the number is rising. Cancer cells develop anoikis resistance which is a vital step during cancer progression and metastatic colonization. However, there is not much research that specifically addresses the role of anoikis in HCC, especially in terms of prognosis. Methods: This study obtained gene expression data and clinical information from 371 HCC patients through The Cancer Genome Atlas (TCGA) Program and The Gene Expression Omnibus (GEO) databases. A total of 516 anoikis-related genes (ANRGs) were retrieved from GeneCard database and Harmonizome portal. Differential expression analysis identified 219 differentially expressed genes (DEGs), and univariate Cox regression analysis was utilized to select 99 ANRGs associated with the prognosis of HCC patients. A risk scoring model with seven genes was established using the least absolute shrinkage and selection operator (LASSO) regression model, and internal validation of the model was performed. Results: The identified 99 ANRGs are closely associated with the prognosis of HCC patients. The risk scoring model based on seven characteristic genes demonstrates excellent predictive performance, further validated by receiver operating characteristic (ROC) curves and Kaplan-Meier survival curves. The study reveals significant differences in immune cell infiltration, gene expression, and survival status among different risk groups. Conclusions: The prognosis of HCC patients can be predicted using a unique prognostic model built on ANRGs in HCC.
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