Cell-ECM interactions and their relevance to cancer

Perturbed microenvironmental conditions play important roles in tumor initiation, progression, and therapy response; however, the underlying molecular, cellular, and tissue-level mechanisms remain relatively poorly understood. By integrating biomaterials, tissue engineering, and microfabrication strategies our lab has developed a variety of in vitro and in vivo models to study tumorigenesis under pathologically relevant conditions. In particular, we are applying these model systems to evaluate the regulatory roles of extracellular matrix (ECM) physicochemical properties on tumor-stroma interactions with a focus on tumor angiogenesis and metastasis. This talk will summarize some of our efforts in this area and discuss tumor-mediated differences in ECM physicochemical properties, and the resulting functional consequences on tumor cell behavior

Stiffening and unfolding of early deposited-fibronectin increase proangiogenic factor secretion by breast cancer-associated stromal cells.

Fibronectin (Fn) forms a fibrillar network that controls cell behavior in both physiological and diseased conditions including cancer. Indeed, breast cancer-associated stromal cells not only increase the quantity of deposited Fn but also modify its conformation. However, (i) the interplay between mechanical and conformational properties of early tumor-associated Fn networks and (ii) its effect on tumor vascularization remain unclear. Here, we first used the Surface Forces Apparatus to reveal that 3T3-L1 preadipocytes exposed to tumor-secreted factors generate a stiffer Fn matrix relative to control cells. We then show that this early matrix stiffening correlates with increased molecular unfolding in Fn fibers, as determined by Förster Resonance Energy Transfer. Finally, we assessed the resulting changes in adhesion and proangiogenic factor (VEGF) secretion of newly seeded 3T3-L1s, and we examined altered integrin specificity as a potential mechanism of modified cell-matrix interactions through integrin blockers. Our data indicate that tumor-conditioned Fn decreases adhesion while enhancing VEGF secretion by preadipocytes, and that an integrin switch is responsible for such changes. Collectively, our findings suggest that simultaneous stiffening and unfolding of initially deposited tumor-conditioned Fn alters both adhesion and proangiogenic behavior of surrounding stromal cells, likely promoting vascularization and growth of the breast tumor. This work enhances our knowledge of cell - Fn matrix interactions that may be exploited for other biomaterials-based applications, including advanced tissue engineering approaches

A Novel 3-D Mineralized Tumor Model to Study Breast Cancer Bone Metastasis

Metastatic bone disease is a frequent cause of morbidity in patients with advanced breast cancer, but the role of the bone mineral hydroxyapatite (HA) in this process remains unclear. We have developed a novel mineralized 3-D tumor model and have employed this culture system to systematically investigate the pro-metastatic role of HA under physiologically relevant conditions in vitro.MDA-MB231 breast cancer cells were cultured within non-mineralized or mineralized polymeric scaffolds fabricated by a gas foaming-particulate leaching technique. Tumor cell adhesion, proliferation, and secretion of pro-osteoclastic interleukin-8 (IL-8) was increased in mineralized tumor models as compared to non-mineralized tumor models, and IL-8 secretion was more pronounced for bone-specific MDA-MB231 subpopulations relative to lung-specific breast cancer cells. These differences were pathologically significant as conditioned media collected from mineralized tumor models promoted osteoclastogenesis in an IL-8 dependent manner. Finally, drug testing and signaling studies with transforming growth factor beta (TGFbeta) confirmed the clinical relevance of our culture system and revealed that breast cancer cell behavior is broadly affected by HA.Our results indicate that HA promotes features associated with the neoplastic and metastatic growth of breast carcinoma cells in bone and that IL-8 may play an important role in this process. The developed mineralized tumor models may help to reveal the underlying cellular and molecular mechanisms that may ultimately enable more efficacious therapy of patients with advanced breast cancer

Collagen microarchitecture mechanically controls myofibroblast differentiation.

Altered microarchitecture of collagen type I is a hallmark of wound healing and cancer that is commonly attributed to myofibroblasts. However, it remains unknown which effect collagen microarchitecture has on myofibroblast differentiation. Here, we combined experimental and computational approaches to investigate the hypothesis that the microarchitecture of fibrillar collagen networks mechanically regulates myofibroblast differentiation of adipose stromal cells (ASCs) independent of bulk stiffness. Collagen gels with controlled fiber thickness and pore size were microfabricated by adjusting the gelation temperature while keeping their concentration constant. Rheological characterization and simulation data indicated that networks with thicker fibers and larger pores exhibited increased strain-stiffening relative to networks with thinner fibers and smaller pores. Accordingly, ASCs cultured in scaffolds with thicker fibers were more contractile, expressed myofibroblast markers, and deposited more extended fibronectin fibers. Consistent with elevated myofibroblast differentiation, ASCs in scaffolds with thicker fibers exhibited a more proangiogenic phenotype that promoted endothelial sprouting in a contractility-dependent manner. Our findings suggest that changes of collagen microarchitecture regulate myofibroblast differentiation and fibrosis independent of collagen quantity and bulk stiffness by locally modulating cellular mechanosignaling. These findings have implications for regenerative medicine and anticancer treatments

Obesity-dependent changes in interstitial ECM mechanics promote breast tumorigenesis.

Obesity and extracellular matrix (ECM) density are considered independent risk and prognostic factors for breast cancer. Whether they are functionally linked is uncertain. We investigated the hypothesis that obesity enhances local myofibroblast content in mammary adipose tissue and that these stromal changes increase malignant potential by enhancing interstitial ECM stiffness. Indeed, mammary fat of both diet- and genetically induced mouse models of obesity were enriched for myofibroblasts and stiffness-promoting ECM components. These differences were related to varied adipose stromal cell (ASC) characteristics because ASCs isolated from obese mice contained more myofibroblasts and deposited denser and stiffer ECMs relative to ASCs from lean control mice. Accordingly, decellularized matrices from obese ASCs stimulated mechanosignaling and thereby the malignant potential of breast cancer cells. Finally, the clinical relevance and translational potential of our findings were supported by analysis of patient specimens and the observation that caloric restriction in a mouse model reduces myofibroblast content in mammary fat. Collectively, these findings suggest that obesity-induced interstitial fibrosis promotes breast tumorigenesis by altering mammary ECM mechanics with important potential implications for anticancer therapies

Integrated approach to designing growth factor delivery systems

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154661/1/fsb2fj067873com-sup-0001.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154661/2/fsb2fj067873com.pd

Stiffening and unfolding of early deposited-fibronectin increase proangiogenic factor secretion by breast cancer-associated stromal cells

Fibronectin (Fn) forms a fibrillar network that controls cell behavior in both physiological and diseased conditions including cancer. Indeed, breast cancer-associated stromal cells not only increase the quantity of deposited Fn but also modify its conformation. However, (i) the interplay between mechanical and conformational properties of early tumor-associated Fn networks and (ii) its effect on tumor vascularization remain unclear. Here, we first used the Surface Forces Apparatus to reveal that 3T3-L1 preadipocytes exposed to tumor-secreted factors generate a stiffer Fn matrix relative to control cells. We then show that this early matrix stiffening correlates with increased molecular unfolding in Fn fibers, as determined by Förster Resonance Energy Transfer. Finally, we assessed the resulting changes in adhesion and proangiogenic factor (VEGF) secretion of newly seeded 3T3-L1s, and we examined altered integrin specificity as a potential mechanism of modified cell–matrix interactions through integrin blockers. Our data indicate that tumor-conditioned Fn decreases adhesion while enhancing VEGF secretion by preadipocytes, and that an integrin switch is responsible for such changes. Collectively, our findings suggest that simultaneous stiffening and unfolding of initially deposited tumor-conditioned Fn alters both adhesion and proangiogenic behavior of surrounding stromal cells, likely promoting vascularization and growth of the breast tumor. This work enhances our knowledge of cell – Fn matrix interactions that may be exploited for other biomaterials-based applications, including advanced tissue engineering approaches

Reproducibility and day time bias correction of optoelectronic leg volumetry: a prospective cohort study

Background Leg edema is a common manifestation of various underlying pathologies. Reliable measurement tools are required to quantify edema and monitor therapeutic interventions. Aim of the present work was to investigate the reproducibility of optoelectronic leg volumetry over 3 weeks' time period and to eliminate daytime related within-individual variability. Methods Optoelectronic leg volumetry was performed in 63 hairdressers (mean age 45 ± 16 years, 85.7% female) in standing position twice within a minute for each leg and repeated after 3 weeks. Both lower leg (legBD) and whole limb (limbBF) volumetry were analysed. Reproducibility was expressed as analytical and within-individual coefficients of variance (CVA, CVW), and as intra-class correlation coefficients (ICC). Results A total of 492 leg volume measurements were analysed. Both legBD and limbBF volumetry were highly reproducible with CVA of 0.5% and 0.7%, respectively. Within-individual reproducibility of legBD and limbBF volumetry over a three weeks' period was high (CVW 1.3% for both; ICC 0.99 for both). At both visits, the second measurement revealed a significantly higher volume compared to the first measurement with a mean increase of 7.3 ml ± 14.1 (0.33% ± 0.58%) for legBD and 30.1 ml ± 48.5 ml (0.52% ± 0.79%) for limbBF volume. A significant linear correlation between absolute and relative leg volume differences and the difference of exact day time of measurement between the two study visits was found (P < .001). A therefore determined time-correction formula permitted further improvement of CVW. Conclusions Leg volume changes can be reliably assessed by optoelectronic leg volumetry at a single time point and over a 3 weeks' time period. However, volumetry results are biased by orthostatic and daytime-related volume changes. The bias for day-time related volume changes can be minimized by a time-correction formula

Measuring self-regulation in everyday life: reliability and validity of smartphone-based experiments in alcohol use disorder

Self-regulation, the ability to guide behavior according to one’s goals, plays an integral role in understanding loss of control over unwanted behaviors, for example in alcohol use disorder (AUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors usually occur, namely outside the laboratory, and in clinical populations such as people with AUD. Moreover, lab-based tasks have been criticized for poor test–retest reliability and lack of construct validity. Smartphones can be used to deploy tasks in the field, but often require shorter versions of tasks, which may further decrease reliability. Here, we show that combining smartphone-based tasks with joint hierarchical modeling of longitudinal data can overcome at least some of these shortcomings. We test four short smartphone-based tasks outside the laboratory in a large sample (N = 488) of participants with AUD. Although task measures indeed have low reliability when data are analyzed traditionally by modeling each session separately, joint modeling of longitudinal data increases reliability to good and oftentimes excellent levels. We next test the measures’ construct validity and show that extracted latent factors are indeed in line with theoretical accounts of cognitive control and decision-making. Finally, we demonstrate that a resulting cognitive control factor relates to a real-life measure of drinking behavior and yields stronger correlations than single measures based on traditional analyses. Our findings demonstrate how short, smartphone-based task measures, when analyzed with joint hierarchical modeling and latent factor analysis, can overcome frequently reported shortcomings of experimental tasks

Measuring self-regulation in everyday life: Reliability and validity of smartphone-based experiments in alcohol use disorder

Self-regulation, the ability to guide behavior according to one's goals, plays an integral role in understanding loss of control over unwanted behaviors, for example in alcohol use disorder (AUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors usually occur, namely outside the laboratory, and in clinical populations such as people with AUD. Moreover, lab-based tasks have been criticized for poor test-retest reliability and lack of construct validity. Smartphones can be used to deploy tasks in the field, but often require shorter versions of tasks, which may further decrease reliability. Here, we show that combining smartphone-based tasks with joint hierarchical modeling of longitudinal data can overcome at least some of these shortcomings. We test four short smartphone-based tasks outside the laboratory in a large sample (N = 488) of participants with AUD. Although task measures indeed have low reliability when data are analyzed traditionally by modeling each session separately, joint modeling of longitudinal data increases reliability to good and oftentimes excellent levels. We next test the measures' construct validity and show that extracted latent factors are indeed in line with theoretical accounts of cognitive control and decision-making. Finally, we demonstrate that a resulting cognitive control factor relates to a real-life measure of drinking behavior and yields stronger correlations than single measures based on traditional analyses. Our findings demonstrate how short, smartphone-based task measures, when analyzed with joint hierarchical modeling and latent factor analysis, can overcome frequently reported shortcomings of experimental tasks