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Heterogeneity in cancer: molecular mechanisms and therapeutic strategies

Sep 2026 · Signal Transduction and Targeted Therapy · Vol 11 · 0 citations · 321 references
Medicine

Abstract

Cancer heterogeneity drives therapeutic failure, resistance, and relapse and encompasses variation across genetic, cellular, tissue, organ, and systemic scales. Existing frameworks define malignant capabilities and tumor–microenvironment interactions but less explicitly address how heterogeneity propagates across scales and informs therapeutic design. Here, we propose the Holistic Integrative Tumor Ecosystem Theory (HITET), a five-dimensional framework connecting these scales through functional interfaces. Its organizing principle is the niche–flow–feedback triad: niches define selective habitats; flows transmit cells, resources, and signals across scales; and feedback loops amplify or constrain heterogeneity by reshaping niches and flows. HITET generates several provisional predictions: interventions targeting three or more active dimensions may produce more durable responses than narrower strategies; tumors with strong vascular–immune coupling may be particularly sensitive to combined vascular normalization and immune activation; and clonal or phenotypic diversification may correlate with the number and strength of positive feedback loops. We use HITET to synthesize how genetic alterations, cellular plasticity, metabolic programs, immune and stromal interactions, spatial gradients, organ-specific environments, microbiota, and host physiology jointly shape cancer heterogeneity. Therapeutically, HITET organizes strategies as vertical integration within a dimension, horizontal integration across dimensions, and modulation of host–tumor interfaces. HITET does not replace existing cancer frameworks or constitute a validated predictive model. Its current contribution is organizational and hypothesis-generating, providing a structured basis for linking mechanisms and measurements and developing predictions that require prospective experimental and clinical validation.

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