The extracellular matrix (ECM) is an abundant noncellular component of most solid tumors known to support tumor progression and metastasis. The interplay between the ECM and cancer therapeutics opens up new avenues in understanding cancer biology. While the ECM is known to protect the tumor from anticancer agents by serving as a biomechanical barrier, emerging studies show that various cancer therapies induce ECM remodeling, resulting in therapy resistance and tumor progression. This review discusses critical issues in this field including how the ECM influences treatment outcome, how cancer therapies affect ECM remodeling, and the challenges associated with targeting the ECM. Significance: The intricate relationship between the extracellular matrix (ECM) and cancer therapeutics reveals novel insights into tumor biology and its effective treatment. While the ECM may protect tumors from anti-cancer agents, recent research highlights the paradoxical role of therapy-induced ECM remodeling in promoting treatment resistance and tumor progression. This review explores the key aspects of the interplay between ECM and cancer therapeutics.

Despite the remarkable success of anti-cancer immunotherapy, its effectiveness remains confined to a subset of patients-emphasizing the importance of predictive biomarkers in clinical decision-making and further mechanistic understanding of treatment response. Current biomarkers, however, lack the power required to accurately stratify patients. Here, we identify interferon-stimulated, Ly6E^hi neutrophils as a blood-borne biomarker of anti-PD1 response in mice at baseline. Ly6E^hi neutrophils are induced by tumor-intrinsic activation of the STING (stimulator of interferon genes) signaling pathway and possess the ability to directly sensitize otherwise non-responsive tumors to anti-PD1 therapy, in part through IL12b-dependent activation of cytotoxic T cells. By translating our pre-clinical findings to a cohort of patients with non-small cell lung cancer and melanoma (n = 109), and to public data (n = 1440), we demonstrate the ability of Ly6E^hi neutrophils to predict immunotherapy response in humans with high accuracy (average AUC ≈ 0.9). Overall, our study identifies a functionally active biomarker for use in both mice and humans.