Doxorubicin-induced cardiomyopathy (DIC) is a severe complication following anthracycline chemotherapy, and its main pathogenesis is inflammatory responses and ferroptosis. This study constructed hyaluronic acid-based macrophage biomimetic nanoparticles (M@HCDA) to co-delivery of Celastrol (Cel) and siADAM17 for the treatment of DIC. This research revealed that Cel exerted an anti-ferroptosis effect by regulating GPX4 and SLC7A11, while siADAM17 inhibited TAK1-MAPK pathway activation by silencing ADAM17. Meanwhile, the synergistic effect of Cel and siADAM17 significantly alleviated oxidative stress, myocardial fibrosis, apoptosis, and mitochondrial dysfunction, thereby relieving myocardial injury caused by DOX-induced cardiotoxicity and providing effective early cardioprotection. In vitro and in vivo experiments indicated that M@HCDA exhibited good stability, biocompatibility, and targeting capability, showing the clinical application potential. The design and development of M@HCDA provide new experimental evidence and candidate strategy for treating DIC.
Tumor progression is accompanied by adaptive metabolic rewiring that extends beyond energy and amino acid metabolism to lipid networks. Among these alterations, disrupted cholesterol homeostasis has emerged as a key driver of tumor proliferation, migration, invasion, chemoresistance and immune escape. Cholesterol metabolism also shapes immune cell function, thereby linking tumor-intrinsic metabolic adaptation to immune remodeling in the tumor microenvironment. Recent advances in biomaterial-based therapeutics have expanded the scope of cholesterol-targeted cancer therapy. This Review summarizes how engineered biomaterials regulate cholesterol supply and uptake, intracellular cholesterol trafficking, membrane organization and cholesterol oxidation, and how these strategies reshape tumor cell survival, therapeutic resistance and antitumor immunity. We further discuss the integration of cholesterol-targeted biomaterials with chemotherapy, photodynamic therapy, sonodynamic therapy and immunotherapy, as well as key translational challenges, including metabolic compensation, preservation of cholesterol balance in normal tissues, the context-dependent biological effects of sterol products and the need for product-resolved analysis, since changes in total cholesterol or ROS alone cannot establish their identity or activity, and therapeutic heterogeneity across cholesterol-dependent tumor phenotypes. Biomaterials that target cholesterol metabolism offer a promising route to overcome therapy resistance and improve combination immunotherapy, but their clinical translation will require precise definition of responsive tumor types, target cell populations and actionable metabolic vulnerabilities.
Ageing is a major determinant of cancer risk and outcome, yet age-associated changes in the extracellular matrix (ECM) remain poorly represented in most preclinical cancer models. Throughout life, the ECM undergoes alterations in composition, architecture, biochemical modification, mechanics and turnover that influence cell behaviour and tissue function. Although advanced three-dimensional (3D) cancer models increasingly incorporate ECM components, ageing is rarely considered as an independent biological variable, and the terms aged, ageing-associated and age-mimetic ECM are often applied to biologically distinct experimental systems.Here, we review current evidence describing ECM remodelling across the lifespan and evaluate how age-associated matrix states have been incorporated into 3D cancer models. We propose a framework that distinguishes four principal modelling strategies: chronologically aged ECM models, defined age-associated ECM modification models, cell-mediated ECM remodelling models, and mixed multicomponent ageing models. These approaches differ substantially in the ageing-associated features they reproduce, the degree of biological fidelity they provide and the strength of mechanistic inference they permit.Analysis of published studies provides evidence that age-associated ECM states can influence tumour invasion, proliferation, signalling and therapeutic response across many cancer types. At the same time, the available evidence indicates that ECM ageing is a multidimensional process that no single molecular or mechanical surrogate can capture. Hence, we argue that age-aware cancer models should be classified and interpreted according to the specific ageing-associated ECM features they reproduce and experimentally validate. By establishing ECM ageing as a definable biological variable, this framework provides practical guidance for designing, validating, and interpreting next-generation age-aware 3D in vitro cancer models.
