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Integrated Single-Cell and Spatial Transcriptomics Coupled with Machine Learning Uncovers as a Critical Epigenetic Mediator of Radiotherapy Resistance in Colorectal Cancer Liver Metastasis.

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Biomedicines 📖 저널 OA 100% 2021: 1/1 OA 2022: 22/22 OA 2023: 20/20 OA 2024: 55/55 OA 2025: 152/152 OA 2026: 94/94 OA 2021~2026 2026 Vol.14(2)
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Zhang Y, Wang X, Liu H, Xiang Y, Yu L

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Colorectal cancer (CRC) liver metastasis (CRLM) represents a major clinical challenge, and acquired resistance to radiotherapy (RT) significantly limits therapeutic efficacy.

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APA Zhang Y, Wang X, et al. (2026). Integrated Single-Cell and Spatial Transcriptomics Coupled with Machine Learning Uncovers as a Critical Epigenetic Mediator of Radiotherapy Resistance in Colorectal Cancer Liver Metastasis.. Biomedicines, 14(2). https://doi.org/10.3390/biomedicines14020273
MLA Zhang Y, et al.. "Integrated Single-Cell and Spatial Transcriptomics Coupled with Machine Learning Uncovers as a Critical Epigenetic Mediator of Radiotherapy Resistance in Colorectal Cancer Liver Metastasis.." Biomedicines, vol. 14, no. 2, 2026.
PMID 41751172 ↗

Abstract

Colorectal cancer (CRC) liver metastasis (CRLM) represents a major clinical challenge, and acquired resistance to radiotherapy (RT) significantly limits therapeutic efficacy. A deep and comprehensive understanding of the cellular and molecular mechanisms driving RT resistance is urgently required to develop effective combination strategies. Here, we aimed to dissect the dynamic cellular landscape of the tumor microenvironment (TME) and identify key epigenetic regulators mediating radioresistance in CRLM by integrating cutting-edge single-cell and spatial omics technologies. We performed integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) on matched pre- and post-radiotherapy tumor tissues collected from three distinct CRLM patients. Employing a robust machine-learning framework on the multi-omics data, we successfully identified (Mortality Factor 4 Like 1), an epigenetic reader, as a critical epigenetic mediator of acquired radioresistance. High-resolution scRNA-seq analysis of the tumor cell compartment revealed that the -high subpopulation exhibited significant enrichment in DNA damage repair (DDR) pathways, heightened activity of multiple pro-survival metabolic pathways, and robust signatures of immune evasion. Pseudotime trajectory analysis further confirmed that RT exposure drives tumor cells toward a highly resistant state, marked by a distinct increase in expression. Furthermore, cell-cell communication inference demonstrated a pronounced, systemic upregulation of various immunosuppressive signaling axes within the TME following RT. Crucially, high-resolution ST confirmed these molecular and cellular interactions in their native context, revealing a significant spatial co-localization of -expressing tumor foci with multiple immunosuppressive immune cell types, including regulatory T cells (Tregs) and tumor-associated macrophages (TAMs), thereby underscoring its role in TME-mediated resistance. Our comprehensive spatial and single-cell profiling establishes as a pivotal epigenetic regulator underlying acquired radioresistance in CRLM. These findings provide a compelling mechanistic rationale for combining radiotherapy with the targeted inhibition of , presenting a promising new therapeutic avenue to overcome treatment failure and improve patient outcomes in CRLM.

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