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Cell motility plays an essential role in many biological processes as cells move and interact within their local microenvironments. Current methods for quantifying cell motility typically involve tracking individual cells over time, but the results are often presented as averaged values across cell populations. While informative, these ensemble approaches have limitations in assessing cellular heterogeneity and identifying generalizable patterns of single-cell behaviors, at baseline and in response to perturbations. In this study, CaMI is introduced, a computational framework designed to leverage the single-cell nature of motility data. CaMI identifies and classifies distinct spatio-temporal behaviors of individual cells, enabling robust classification of single-cell motility patterns in a large dataset (n = 74 253 cells). This framework allows quantification of spatial and temporal heterogeneities, determination of single-cell motility behaviors across various biological conditions and provides a visualization scheme for direct interpretation of dynamic cell behaviors. Importantly, CaMI reveals insights that conventional cell motility analyses may overlook, showcasing its utility in uncovering robust biological insights. Together, a multivariate framework is presented to classify emergent patterns of single-cell motility, emphasizing the critical role of cellular heterogeneity in shaping cell behaviors across populations., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Aging is a major driver of diseases in humans. Identifying features associated with aging is essential for designing robust intervention strategies and discovering novel biomarkers of aging. Extensive studies at both the molecular and organ/whole-body physiological scales have helped determined features associated with aging. However, the lack of meso-scale studies, particularly at the tissue level, limits the ability to translate findings made at molecular scale to impaired tissue functions associated with aging. In this work, we established a tissue image analysis workflow - quantitative micro-anatomical phenotyping (qMAP) - that leverages deep learning and machine vision to fully label tissue and cellular compartments in tissue sections. The fully mapped tissue images address the challenges of finding an interpretable feature set to quantitatively profile age-related microanatomic changes. We optimized qMAP for skin tissues and applied it to a cohort of 99 donors aged 14 to 92. We extracted 914 microanatomic features and found that a broad spectrum of these features, represented by 10 cores processes, are strongly associated with aging. Our analysis shows that microanatomical features of the skin can predict aging with a mean absolute error (MAE) of 7.7 years, comparable to state-of-the-art epigenetic clocks. Our study demonstrates that tissue-level architectural changes are strongly associated with aging and represent a novel category of aging biomarkers that complement molecular markers. Our results highlight the complex and underexplored multi-scale relationship between molecular and tissue microanatomic scales., Competing Interests: Conflict of Interest The authors declare no financial/commercial conflicts of interest.

Cellular senescence is a major driver of aging and disease. Here we show that substrate stiffness modulates the emergence and magnitude of senescence phenotypes after exposure to senescence inducers. Using a primary dermal fibroblast model, we show that decreased substrate stiffness accelerates senescence-associated cell-cycle arrest and regulates the expression of conventional protein-based biomarkers of senescence. We found that the expression of these senescence biomarkers, namely p21WAF1/CIP1 and p16INK4a are mechanosensitive and are in-part regulated by myosin contractility through focal adhesion kinase (FAK)-ROCK signaling. Interestingly, at the protein level senescence-induced dermal fibroblasts on soft substrates (0.5 kPa) do not express p21WAF1/CIP1 and p16INK4a at comparable levels to induced cells on stiff substrates (4GPa). However, cells express CDKN1a, CDKN2a, and IL6 at the RNA level across both stiff and soft substrates. Moreover, when cells are transferred from soft to stiff substrates, senescent cells recover an elevated expression of p21WAF1/CIP1 and p16INK4a at levels comparable to senescence cells on stiff substrates, pointing to a mechanosensitive regulation of the senescence phenotype. Together, our results indicate that the emergent senescence phenotype depends critically on the local mechanical environments of cells and that senescent cells actively respond to changing mechanical cues.

Tissue stiffness is a critical prognostic factor in breast cancer and is associated with metastatic progression. Here we show an alternative and complementary hypothesis of tumor progression whereby physiologic matrix stiffness affects the quantity and protein cargo of small extracellular vesicles (EV) produced by cancer cells, which in turn aid cancer cell dissemination. Primary patient breast tissue released by cancer cells on matrices that model human breast tumors (25 kPa; stiff EVs) feature increased adhesion molecule presentation (ITGα2β1, ITGα6β4, ITGα6β1, CD44) compared with EVs from softer normal tissue (0.5 kPa; soft EVs), which facilitates their binding to extracellular matrix proteins including collagen IV, and a 3-fold increase in homing ability to distant organs in mice. In a zebrafish xenograft model, stiff EVs aid cancer cell dissemination. Moreover, normal, resident lung fibroblasts treated with stiff and soft EVs change their gene expression profiles to adopt a cancer-associated fibroblast phenotype. These findings show that EV quantity, cargo, and function depend heavily on the mechanical properties of the extracellular microenvironment., Significance: Here we show that the quantity, cargo, and function of breast cancer-derived EVs vary with mechanical properties of the extracellular microenvironment., (© 2024 The Authors; Published by the American Association for Cancer Research.)

The loss of intercellular adhesion molecule E-cadherin is a hallmark of the epithelial-mesenchymal transition (EMT), during which tumor cells transition into an invasive phenotype. Accordingly, E-cadherin has long been considered a tumor suppressor gene; however, E-cadherin expression is paradoxically correlated with breast cancer survival rates. Using novel multi-compartment organoids and multiple in vivo models, we show that E-cadherin promotes a hyper-proliferative phenotype in breast cancer cells via interaction with the transmembrane receptor EGFR. The E-cad and EGFR interaction results in activation of the MEK/ERK signaling pathway, leading to a significant increase in proliferation via activation of transcription factors, including c-Fos. Pharmacological inhibition of MEK activity in E-cadherin positive breast cancer significantly decreases both tumor growth and macro-metastasis in vivo. This work provides evidence for a novel role of E-cadherin in breast tumor progression and identifies a new target to treat hyper-proliferative E-cadherin-positive breast tumors, thus providing the foundation to utilize E-cadherin as a biomarker for specific therapeutic success., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

The presence of senescent cells within tissues has been functionally linked to malignant transformations. Here, using tension-gauge tethers technology, particle-tracking microrheology, and quantitative microscopy, we demonstrate that senescent-associated secretory phenotype (SASP) derived from senescent fibroblasts impose nuclear lobulations and volume shrinkage on malignant cells, which stems from the loss of RhoA/ROCK/myosin II-based cortical tension. This loss in cytoskeletal tension induces decreased cellular contractility, adhesion, and increased mechanical compliance. These SASP-induced morphological changes are, in part, mediated by Lamin A/C. These findings suggest that SASP induces defective outside-in mechanotransduction from actomyosin fibers in the cytoplasm to the nuclear lamina, thereby triggering a cascade of biophysical and biomolecular changes in cells that associate with malignant transformations., (© The Author(s) 2022. Published by Oxford University Press on behalf of the National Academy of Sciences.)

Simultaneous inhibition of interleukin-6 (IL-6) and interleukin-8 (IL-8) signaling diminishes cancer cell migration, and combination therapy has recently been shown to synergistically reduce metastatic burden in a preclinical model of triple-negative breast cancer. Here, we have engineered two novel bispecific antibodies that target the IL-6 and IL-8 receptors to concurrently block the signaling activity of both ligands. We demonstrate that a first-in-class bispecific antibody design has promising therapeutic potential, with enhanced selectivity and potency compared with monoclonal antibody and small-molecule drug combinations in both cellular and animal models of metastatic triple-negative breast cancer. Mechanistic characterization revealed that our engineered bispecific antibodies have no impact on cell viability, but profoundly reduce the migratory potential of cancer cells; hence they constitute a true anti-metastatic treatment. Moreover, we demonstrate that our antibodies can be readily combined with standard-of-care anti-proliferative drugs to develop effective anti-cancer regimens. Collectively, our work establishes an innovative metastasis-focused direction for cancer drug development., Competing Interests: Declaration of interests The authors have filed intellectual property covering the technologies described herein. E.J.M., D.W., and J.B.S. are co-founders of AbMeta Therapeutics., (Copyright © 2022 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.)

Extracellular vesicles have emerged as prominent regulators of the immune response during tumor progression. EVs contain a diverse repertoire of molecular cargo that plays a critical role in immunomodulation. Here, we identify the role of EVs as mediators of communication between cancer and immune cells. This expanded role of EVs may shed light on the mechanisms behind tumor progression and provide translational diagnostic and prognostic tools for immunologists.

Matrix metalloproteinases (MMPs) may play a critical role in metastatic cancers, yet multiple human clinical trials targeting MMPs have surprisingly failed. Cancer cell density changes dramatically during the early growth of a primary tumor and during the early seeding steps of secondary tumors and has been implicated in playing an important role in regulating metastasis and drug resistance. This study reveals that the expression of MMPs is tightly regulated by local tumor cell density through the synergistic signaling mechanism of Interleukin 6 (IL-6) and Interleukin 8 (IL-8) via the JAK2/STAT3 complex. Local tumor cell density also plays a role in the responsiveness of cells to matrix metalloproteinases inhibitors (MMPI), such as Batimastat, Marimastat, Bryostatin I, and Cipemastat, where different migratory phenotypes are observed in low and high cell density conditions. Cell density-dependent MMP regulation can be directly targeted by the simultaneous inhibition of IL-6 and IL-8 receptors via Tocilizumab and Reparixin to significantly decrease the expression of MMPs in mouse xenograft models and decrease effective metastasis. This study reveals a new strategy to decrease MMP expression through pharmacological intervention of the cognate receptors of IL-6 and IL-8 to decrease metastatic capacity of tumor cells., Competing Interests: CONFLICTS OF INTEREST The authors declare no competing conflicts of interest.