A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer

Flow-on-repellent biofabrication of fibrous decellularized breast tumor-stroma models

On-the-fly biofabrication of reproducible 3D tumor models at a pre-clinical level is highly desirable to level-up their applicability and predictive potential. Incorporating ECM biomolecular cues and its complex 3D bioarchitecture in the design stages of such in vitro platforms is essential to better recapitulate the native tumor microenvironment. To materialize these needs, herein we describe an innovative flow-on-repellent (FLORE) 3D extrusion bioprinting technique that leverages expedited and automatized bioink deposition onto a customized superhydrophobic printing bed. We demonstrate that this approach enables the rapid generation of quasi-spherical breast cancer-stroma hybrid models in a mode governed by surface wettability rather than bioink rheological features. For this purpose, an ECM-mimetic bioink comprising breast tissue-specific decellularized matrix in the form of microfiber bundles (dECM-μF) and photocrosslinkable hyaluronan (HAMA), was formulated to generate triple negative breast tumor-stroma models. Leveraging on the FLORE bioprinting approach, a rapid, automated, and reproducible fabrication of physiomimetic breast cancer hydrogel beads was successfully demonstrated. Hydrogel beads size with and without dECM-μF was easily tailored by modelling droplet deposition time on the superhydrophobic bed. Interestingly, in heterotypic breast cancer-stroma beads a self-arrangement of different cellular populations was observed, independent of dECM-μF inclusion, with CAFs clustering overtime within the fabricated models. Drug screening assays showed that the inclusion of CAFs and dECM-μF also impacted the overall response of these living constructs when incubated with gemcitabine chemotherapeutics, with dECM-μF integration promoting a trend for higher resistance in ECM-enriched models. Overall, we developed a rapid fabrication approach leveraging on extrusion bioprinting and superhydrophobic surfaces to process photocrosslinkable dECM bioinks and to generate increasingly physiomimetic tumor-stroma-matrix platforms for drug screening.

Invited Review for 20th Anniversary Special Issue of PLRev "AI for Mechanomedicine"

Mechanomedicine is an interdisciplinary field that combines different areas including biomechanics, mechanobiology, and clinical applications like mechanodiagnosis and mechanotherapy. The emergence of artificial intelligence (AI) has revolutionized mechanomedicine, providing advanced tools to analyze the complex interactions between mechanics and biology. This review explores how AI impacts mechanomedicine across four key aspects, i.e., biomechanics, mechanobiology, mechanodiagnosis, and mechanotherapy. AI improves the accuracy of biomechanical characterizations and models, deepens the understanding of cellular mechanotransduction pathways, and enables early disease detection through mechanodiagnosis. In addition, AI optimizes mechanotherapy that targets biomechanical features and mechanobiological markers by personalizing treatment strategies based on real-time patient data. Even with these advancements, challenges still exist, particularly in data quality and the ethical integration into AI in clinical practice. The integration of AI with mechanomedicine offers transformative potential, enabling more accurate diagnostics and personalized treatments, and discovering novel mechanobiological pathways.

Machine learning and artificial intelligence: Enabling the clinical translation of atomic force microscopy-based biomarkers for cancer diagnosis

The influence of biomechanics on cell function has become increasingly defined over recent years. Biomechanical changes are known to affect oncogenesis; however, these effects are not yet fully understood. Atomic force microscopy (AFM) is the gold standard method for measuring tissue mechanics on the micro- or nano-scale. Due to its complexity, however, AFM has yet to become integrated in routine clinical diagnosis. Artificial intelligence (AI) and machine learning (ML) have the potential to make AFM more accessible, principally through automation of analysis. In this review, AFM and its use for the assessment of cell and tissue mechanics in cancer is described. Research relating to the application of artificial intelligence and machine learning in the analysis of AFM topography and force spectroscopy of cancer tissue and cells are reviewed. The application of machine learning and artificial intelligence to AFM has the potential to enable the widespread use of nanoscale morphologic and biomechanical features as diagnostic and prognostic biomarkers in cancer treatment.

Low-dose tamoxifen treatment reduces collagen organisation indicative of tissue stiffness in the normal breast: results from the KARISMA randomised controlled trial

BACKGROUND

Tissue stiffness, dictated by organisation of interstitial fibrillar collagens, increases breast cancer risk and contributes to cancer progression. Tamoxifen is a standard treatment for receptor-positive breast cancer and is also aproved for primary prevention. We investigated the effect of tamoxifen and its main metabolites on the breast tissue collagen organisation as a proxy for stiffness and explored the relationship between mammographic density (MD) and collagen organisation.

MATERIAL AND METHODS

This sub-study of the double-blinded dose-determination trial, KARISMA, included 83 healthy women randomised to 6 months of 20, 10, 5, 2.5, and 1 mg of tamoxifen or placebo. Ultrasound-guided core-needle breast biopsies collected before and after treatment were evaluated for collagen organisation by polarised light microscopy.

RESULTS

Tamoxifen reduced the amount of organised collagen and overall organisation, reflected by a shift from heavily crosslinked thick fibres to thinner, less crosslinked fibres. Collagen remodelling correlated with plasma concentrations of tamoxifen metabolites. MD change was not associated with changes in amount of organised collagen but was correlated with less crosslinking in premenopausal women.

CONCLUSIONS

In this study of healthy women, tamoxifen decreased the overall organisation of fibrillar collagens, and consequently, the breast tissue stiffness. These stromal alterations may play a role in the well-established preventive and therapeutic effects of tamoxifen. Trial registration ClinicalTrials.gov ID: NCT03346200. Registered November 1st, 2017. Retrospectively registered.

Understanding and measuring mechanical signals in the tumor stroma

The tumor microenvironment (TME) is well known for its immune suppressive role, especially in solid tumors which are characterized by a thick, dense stroma. Apart from cell-cell interactions and biochemical signals, the tumor stroma is also characterized by its distinct mechanical properties, which are dictated by the composition and architecture of its extracellular matrix (ECM). Cancer-associated fibroblasts (CAFs) are the main producers and remodelers of the stromal ECM, and their heterogeneity has recently become a focus of intense research. This review describes recent findings highlighting CAF subtypes and their specific functions, as well as the development of 3D models to study tumor stroma mechanics in vitro. Finally, we discuss the quantitative techniques used to measure tissue mechanical properties at different scales. Given the diagnostic and prognostic value of stroma stiffness and composition, and the recent development of anti-tumor therapeutic strategies targeting the stroma, understanding and measuring tumor stroma mechanical properties has never been more timely or relevant.

Have plastic culture models prevented the discovery of effective cancer therapeutics?

Conventional cell culture techniques generally fail to recapitulate the expression profiles or functional phenotypes of the in vivo equivalents they are meant to model. These cell culture models are indispensable for preclinical drug discovery and mechanistic studies. However, if our goal is to develop effective therapies that work as intended in the human body, we must revise our cell culture models to recapitulate normal and disease physiology to ensure that we identify compounds that are useful and effective beyond our in vitro models.

Defining and modeling dynamic spatial heterogeneity within tumor microenvironments

Many solid tumors exhibit significant genetic, cellular, and biophysical heterogeneity which dynamically evolves during disease progression and after treatment. This constant flux in cell composition, phenotype, spatial relationships, and tissue properties poses significant challenges in accurately diagnosing and treating patients. Much of the complexity lies in unraveling the molecular changes in different tumor compartments, how they influence one another in space and time and where vulnerabilities exist that might be appropriate to target therapeutically. Recent advances in spatial profiling tools and technologies are enabling new insight into the underlying biology of complex tumors, creating a greater understanding of the intricate relationship between cell types, states, and the microenvironment. Here we reflect on some recent discoveries in this area, where the key knowledge and technology gaps lie, and the advancements in spatial measurements and in vitro models for the study of spatial intratumoral heterogeneity.

Epithelial-Mesenchymal Plasticity and Epigenetic Heterogeneity in Cancer

The tumor microenvironment comprises various cell types and experiences dynamic alterations in physical and mechanical properties as cancer progresses. Intratumoral heterogeneity is associated with poor prognosis and poses therapeutic challenges, and recent studies have begun to identify the cellular mechanisms that contribute to phenotypic diversity within tumors. This review will describe epithelial-mesenchymal (E/M) plasticity and its contribution to phenotypic heterogeneity in tumors as well as how epigenetic factors, such as histone modifications, histone modifying enzymes, DNA methylation, and chromatin remodeling, regulate and maintain E/M phenotypes. This review will also report how mechanical properties vary across tumors and regulate epigenetic modifications and E/M plasticity. Finally, it highlights how intratumoral heterogeneity impacts therapeutic efficacy and provides potential therapeutic targets to improve cancer treatments.

Mesenchymal Stem Cell-Secreted Exosomes and Soluble Signals Regulate Breast Cancer Metastatic Dormancy: Current Progress and Future Outlook

Breast cancer is most common in women, and in most cases there is no evidence of spread and the primary tumor is removed, resulting in a 'cure'. However, in 10% to 30% of these women, distant metastases recur after years to decades. This is due to breast cancer cells disseminating to distant organs and lying quiescent. This is called metastatic dormancy. Dormant cells are generally resistant to chemotherapy, hormone therapy and immunotherapy as they are non-cycling and receive survival signals from their microenvironment. In this state, they are clinically irrelevant. However, risk factors, including aging and inflammation can awaken dormant cells and cause breast cancer recurrences, which may happen even more than ten years after the primary tumor removal. How these breast cancer cells remain in dormancy is being unraveled. A key element appears to be the mesenchymal stem cells in the bone marrow that have been shown to promote breast cancer metastatic dormancy in recent studies. Indirect co-culture, direct co-culture and exosome extraction were conducted to investigate the modes of signal operation. Multiple signaling molecules act in this process including both protein factors and microRNAs. We integrate these studies to summarize current findings and gaps in the field and suggest future research directions for this field.

Mechanosensitive hormone signaling promotes mammary progenitor expansion and breast cancer risk

Tissue stem-progenitor cell frequency has been implicated in tumor risk and progression, but tissue-specific factors linking these associations remain ill-defined. We observed that stiff breast tissue from women with high mammographic density, who exhibit increased lifetime risk for breast cancer, associates with abundant stem-progenitor epithelial cells. Using genetically engineered mouse models of elevated integrin mechanosignaling and collagen density, syngeneic manipulations, and spheroid models, we determined that a stiff matrix and high mechanosignaling increase mammary epithelial stem-progenitor cell frequency and enhance tumor initiation in vivo. Augmented tissue mechanics expand stemness by potentiating extracellular signal-related kinase (ERK) activity to foster progesterone receptor-dependent RANK signaling. Consistently, we detected elevated phosphorylated ERK and progesterone receptors and increased levels of RANK signaling in stiff breast tissue from women with high mammographic density. The findings link fibrosis and mechanosignaling to stem-progenitor cell frequency and breast cancer risk and causally implicate epidermal growth factor receptor-ERK-dependent hormone signaling in this phenotype.

Atomic force microscopy-mediated mechanobiological profiling of complex human tissues

Tissue mechanobiology is an emerging field with the overarching goal of understanding the interplay between biophysical and biochemical responses affecting development, physiology, and disease. Changes in mechanical properties including stiffness and viscosity have been shown to describe how cells and tissues respond to mechanical cues and modify critical biological functions. To quantitatively characterize the mechanical properties of tissues at physiologically relevant conditions, atomic force microscopy (AFM) has emerged as a highly versatile biomechanical technology. In this review, we describe the fundamental principles of AFM, typical AFM modalities used for tissue mechanics, and commonly used elastic and viscoelastic contact mechanics models to characterize complex human tissues. Furthermore, we discuss the application of AFM-based mechanobiology to characterize the mechanical responses within complex human tissues to track their developmental, physiological/functional, and diseased states, including oral, hearing, and cancer-related tissues. Finally, we discuss the current outlook and challenges to further advance the field of tissue mechanobiology. Altogether, AFM-based tissue mechanobiology provides a mechanistic understanding of biological processes governing the unique functions of tissues.

Mechanotransduction pathways in regulating epithelial-mesenchymal plasticity

The extracellular matrix (ECM) provides structural support for cells and mediates cell-stromal communications. In addition to ECM proteins, mechanical force exerted from the ECM serves as a critical regulator of many biological processes. Epithelial-mesenchymal transition (EMT) is a cellular process by which epithelial cells loosen their cellular junctions and migrate and invade in a more mesenchymal fashion. Recent studies show that increasing ECM stiffness can impinge on cellular signaling pathways through mechanotransduction to promote carcinoma cells to undergo EMT, suggesting that mechanical force exerted by the ECM plays a critical role in tumor invasion and metastasis. Here, we highlight recent work utilizing innovative approaches to study mechanotransduction and summarize newly discovered mechanisms by which mechanosensors and responders regulate EMT during tumor progression and metastasis.