ArticleEuropean journal of cancer (Oxford, England : 1990)2025
Pathogenomic fingerprinting to identify associations between tumor morphology and epigenetic states.
Article in European journal of cancer (Oxford, England : 1990), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- AI-assisted multimodal data integration for precision oncology.Frontiers in artificial intelligence · 2026Review
- Methylation profiling in neuropathological tumors diagnosis: a comprehensive review.Frontiers in oncology · 2025Review
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11 authors.
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Abstract
introductionMeasuring the chromatin state of a tumor provides a powerful map of its epigenetic commitments; however, as these are generally bulk measurements, it has not yet been possible to connect changes in chromatin accessibility to the pathological signatures of complex tumors. In parallel, recent advances in computational pathology have enabled the identification of spatial features and immune cells within oral cavity tumors and their microenvironment.
methodsHere, we present pathogenomic fingerprinting (PaGeFin), a novel method that integrates morphological tumor features with chromatin states using ATAC-seq. This framework links spatial morphologic and epigenetic features, offering insights into tumor progression and immune evasion within and across tumors. Morphologic features describing spatial relationships between tumor and lymphocyte cells that are prognostic of oral cavity squamous cell carcinoma (OSCC) were identified through AI-driven pathology analysis. These pathomic features were spatially colocalized within the epigenome of 4 distinct sections of 4 OSCC tumors.
resultsThese key features pinpointed chromatin regions responsible for critical immune cell function through peak locations and enrichment analysis, highlighting loci of CD27+ memory B cells, helper CD4+ T cells, and cytotoxic CD8 naïve T cells that likely drive morphologic changes in the distribution of lymphocytes in the tumor microenvironment and promote aggressive tumor behavior. Gene Ontology analysis revealed that the CTLA4, CD79A, CD3D, and CCR7 genes were embedded in these regions.
conclusionThis computational approach is the first to assess the correlation between pathomic and epigenetic features in the context of cancer.
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