Mechanical Fingerprints in Breast Cancer Research: A Multimodal Experimental Approach

Breast cancer remains the leading cause of cancer-related mortality among women worldwide. Tumor biomechanics are not merely a symptom: they represent a functional signature with translational relevance in diagnostic, prognostic, and therapeutic resistance. Despite this, few experimental models are engineered to systematically investigate these physical properties across biological systems. Here, this study presents a multimodal biomechanical platform combining engineered 3D breast cancer spheroids with ex vivo tissue analysis to profiling and compare viscoelastic behavior or of healthy and tumoral environments. Rheometry and compression testing revealed a consistent mechanical shift in tumor-derived samples marked by increased stiffness and force-dependent nonlinear behavior, mirroring the ECM remodeling typical of aggressive phenotypes. This increased rigidity may adversely affect chemotherapy effectiveness by hindering drug delivery and altering cellular mechanotransduction. These biomechanical fingerprints enable quantitative discrimination between healthy and cancerous tissues and can serve as a surrogate maker of malignancy. By supporting the development of mechanics-informed diagnostic tools, our platform offers a reproducible, clinically relevant framework to integrate biomechanical screening into translational breast cancer pipelines. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=166 SRC="FIGDIR/small/680332v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@2c87a3org.highwire.dtl.DTLVardef@17cecc8org.highwire.dtl.DTLVardef@9d56d3org.highwire.dtl.DTLVardef@1af509a_HPS_FORMAT_FIGEXP M_FIG C_FIG Translational Impact StatementWe propose a multimodal experimental approach that combines in vitro 3D breast-cancer models and ex vivo tissue analysis to measure and compare the viscoelastic properties of healthy and malignant breast tissues. By using mechanical behaviour as a fingerprint, this framework discriminates tumour tissue from its healthy counterpart. Revealing how tumour stiffness impacts drug delivery and therapy resistance, the approach provides a clinically relevant tool to inform diagnosis and optimise treatment strategies.