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bioRxiv · 10.1101/2025.08.29.672994

Extracellular Matrix-Guided Tumor Stratification and Network Models Reveal Clinical Molecular Grades

Dansik, A.·Sarica, S.·Ozturk, E.·Tuncbag, N.
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Abstract

The extracellular matrix (ECM) critically shapes tumor fate and treatment outcome, serving as a potent prognostic factor. Yet, its compositional heterogeneity across tumors makes it difficult to assess its impact on tumor dynamics. To address this, we introduce an ECM-guided patient stratification pipeline through integration of multi-omic data in lung cancer patients. We obtained four patient groups, representing ECM-grades that showed distinct clinical features, mutation profiles, and cellular heterogeneity. Investigation of patient-specific ECM-induced intracellular signaling via network modeling revealed strong enrichment of pathways and transcriptional regulators related to epithelial-mesenchymal transition (EMT) and cancer stemness in higher ECM-grades. Drug proximity analysis on ECM-grade specific networks predicted olaparib as an ECM-grade dependent therapeutic while erlotinib to be ECM-insensitive which were validated experimentally on lung tumor cells with distinct mutational profiles in response to differing ECM microenvironments. Overall, our ECM-mediated stratification approach is a robust system for capturing ECM heterogeneity and identifying patient groups that can be selectively targeted by distinct therapeutic strategies.

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Dansik, A., Sarica, S., Ozturk, E., Tuncbag, N.. 2025-09-03. Extracellular Matrix-Guided Tumor Stratification and Network Models Reveal Clinical Molecular Grades. https://doi.org/10.1101/2025.08.29.672994

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