Predicting hepatocellular carcinoma outcomes and immune therapy response with ATP-dependent chromatin remodeling-related genes, highlighting MORF4L1 as a promising target

Abstract Background Hepatocellular 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. Methods This 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. Results Our 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. Conclusion ACRRGs, 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.