ArticleCancer cell international2025
Predicting hepatocellular carcinoma outcomes and immune therapy response with ATP-dependent chromatin remodeling-related genes, highlighting MORF4L1 as a promising target.
Article in Cancer cell international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Key hub genes and pathways associated with HCV-related hepatocellular carcinoma as potential diagnostic biomarkers.Journal, genetic engineering & biotechnology · 2026Article
- Acquired Genetic Variants, Not Tumor Mutation Burden, Drive Resistance to Immunotherapy in Hepatocellular Carcinoma.Liver cancer · 2026Article
- Site-Specific and Quantitative O-GlcNAc Proteomics for Hepatocellular Carcinoma.Journal of proteome research · 2026Article
- Potential oncogene VPS72 in hepatocellular carcinoma: prognostic and immune infiltration implications.European journal of medical research · 2026Article
- Integrated machine learning and single-cell analysis identify chromatin-remodeling gene signature for diagnosis and prognosis in nasopharyngeal carcinoma.Clinical and experimental medicine · 2025Article
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Authors and funding
13 authors.
Funding
Abstract
backgroundHepatocellular carcinoma (HCC) continues to be a major cause of cancer-related death worldwide, primarily due to delays in diagnosis and resistance to existing treatments. Recent research has identified ATP-dependent chromatin remodeling-related genes (ACRRGs) as promising targets for therapeutic intervention across various types of cancer. This development offers potential new avenues for addressing the challenges in HCC management.
methodsThis study integrated bioinformatics analyses and experimental approaches to explore the role of ACRRGs in HCC. We utilized data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), applying machine learning algorithms to develop a prognostic model based on ACRRGs' expression. Experimental validation was conducted using quantitative real-time Polymerase Chain Reaction (qRT-PCR), Western blotting, and functional assays in HCC cell lines and xenograft models.
resultsOur bioinformatics analysis identified four key ACRRGs-MORF4L1, HDAC1, VPS72, and RUVBL2-that serve as prognostic markers for HCC. The developed risk prediction model effectively distinguished between high-risk and low-risk patients, showing significant differences in survival outcomes and predicting responses to immunotherapy in HCC patients. Experimentally, MORF4L1 was demonstrated to enhance cancer stemness by activating the Hedgehog signaling pathway, as supported by both in vitro and in vivo assays.
conclusionACRRGs, particularly MORF4L1, play crucial roles in modulating HCC progression, offering new insights into the molecular mechanisms driving HCC and potential therapeutic targets. Our findings advocate for the inclusion of chromatin remodeling dynamics in the strategic development of precision therapies for HCC.
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