From mimicry to mechanism: Digital pathology and multi-omics perspectives on cutaneous T-cell lymphoma
Primary cutaneous lymphoma, particularly cutaneous T-cell lymphoma (CTCL), represents a malignancy long defined by protean manifestations, diagnostic delay, clinical deception, and therapeutic ambiguity. Despite being confined to the skin at presentation, CTCL exhibits marked biological heterogeneity and phenotypic variation. Diagnostic workflows reliant on serial biopsies and stage-based classifications fail to adequately capture this complexity, contributing to suboptimal intervention. In this perspective, we position CTCL as a discovery problem, highlighting the limitations of single-layer diagnostics in distinguishing malignant disease from inflammatory mimics. We discuss how emerging digital pathology, artificial intelligence-enabled imaging, and integrative interdisciplinary approaches can interrogate disease across spatial and molecular scales. By reframing CTCL through a systems-level lens, such strategies have the potential to enable earlier biological stratification, inform mechanism-driven therapeutic targeting, and guide the rational use of skin-directed and systemic treatments. Without such integrative frameworks, innovation in CTCL treatment risks remaining fragmented and incomplete.
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