Breast cancer metastasis to the brain is one of the most lethal forms of metastases. Metastasis is regarded as a non-random process governed by several biomechanical factors including tissue stiffness. As brain tissue is ultrasoft and extremely heterogeneous compared to breast cancer primary sites; how are breast cancer cells able to colonize the vastly different microenvironment of the brain? As a key protein of the Hippo pathway, YAP is regarded as a mechanotransducer that is sensitive to changes in substrate stiffness. Its biochemical activity is intertwined with Piezo1, a mechanosensitive ion channel activated through plasma membrane deformation. To impact cellular function, YAP enters the nucleus and binds to the TEAD transcription domain triggering downstream expression of proteins involved in cell motility, wound healing, and metastasis. In this work, triple-negative breast cancers (TNBC) were shown to experience greater migration rates on stiff surfaces compared to soft PDMS substrates. Concurrently, cells showed YAP nuclear localization in a stiffness dependent manner. Then, mechanical characterization of human brain tissue was performed to characterize the stiffness heterogeneity in the brain associated with region specific metastasis. Five to six regions of the brain from two different patients showed similar patterns of stiffness heterogeneity with the anterior regions being generally stiffer than posterior regions. As Piezo1 is directly linked with detecting changes in biomechanical stimuli, it was used as a readout of surface stiffness to examine if cells in the brain could detect different regional stiffnesses. Comparisons of grey and white matter showed no significant difference in Piezo1 expression. As a drug screening framework, molecular dynamic simulations were performed to evaluate drug efficacy on well-characterized inflammatory mediators that are implicated in metastasis. These findings contribute to understanding the gap in knowledge surrounding the interplay between tissue stiffness and YAP mechanotransduction in the context of breast-to-brain metastasis. / Thesis / Master of Applied Science (MASc) / Breast cancer is the most common cause of cancer related deaths in women particularly when it spreads to the brain. The brain is composed of many different sub-locations comprised of different proteins that can change the tissue’s stiffness. Breast cancer can detect these changes and become more aggressive in its growth using a combination of proteins such as yes associated protein (YAP) and Piezo1. How these proteins interact in the context of breast to brain cancer metastasis however is poorly understood. This project examined the effects of surface stiffness, on YAP, and Piezo1 activity to understand how breast cancer and brain cells react to changes in surface stiffness. Results showed that on stiff surfaces YAP activity affects cancer cell migration. Also, human brain tissue was found to vary in stiffness depending on the region examined. Future investigations may shed light on therapies that could take advantage of learnings in this area to better target the spread of breast cancer.

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<p> Musculoskeletal injuries are one of the leading causes of human disability. Tissue engineers aim to restore damaged musculoskeletal tissues by creating scaffolds that promote cellular adhesion, proliferation, and eventual differentiation into functional tissue. It is known that the extracellular matrix (ECM) regulates cellular behavior and is often used as a basis for biological scaffolds; however, current scaffolds often mimic the ECM of adult, homeostatic tissue and frequently lead to poor tissue restoration. What is rarely taken into consideration is that the ECM undergoes extensive remodeling during development to facilitate growth.</p> <p>In the musculoskeletal system, myogenic progenitors (<em>Pax3</em>+) and connective tissue cells (<em>Prx1</em>+) proliferate and differentiate into muscle, tendon, cartilage, and conjoining interfaces (<em>e.g.</em> myotendinous junction), while depositing and remodeling the ECM. As tissues mature, cells continue to refine ECM networks to withstand the functional demands to facilitate movement. The ECM composition and architecture of adult musculoskeletal tissues have been studied individually and are thought to be distinct; however, there has yet to be a comprehensive comparative analysis of the ECM in adult muscle, tendon, and the myotendinous junction (MTJ) in a single study. Additionally, how the matrisome of adult musculoskeletal system compares to the ECM dynamics during forelimb development, remain largely unknown due to lack of techniques to analyze embryonic matrisome composition and synthesis. </p> <p>To address these research gaps, we (1) used quantitative proteomics to map the matrisome composition in the mature murine MTJ, relative to the tendon and muscle; (2) adapted tissue fractionation and biorthogonal non-canonical amino acid tagging techniques to embryonic tissues as a method to quantify the global and nascent embryonic matrisome; and (3) subsequently used these techniques to establish a baseline of ECM dynamics during forelimb morphogenesis (embryonic day, E11.5-E14.5) and growth (postnatal day, P3 and P35). We hypothesized that proteomic evaluation of ECM composition and synthesis in developing and adolescent limbs would resolve differences between embryonic and growing tissues. Indeed, we saw significant differences in global and nascent matrisome composition between embryonic and adolescent forelimbs. Notably, the relative abundance and ratios of collagens associated with type I fibrillogenesis (I, III, and V) were significantly different as a function of development embryogenesis and across the adult muscle, MTJ, and tendon.</p> <p>Type I collagen fibrils are critical for tissue architecture and function. Using genetic mouse models, the regulatory roles of COL5A1 in the initiation of type I collagen fibrillogenesis, and organization of subsequent fibrils, have been well characterized in tendons and ligaments; however, is it unknown which cell types contribute COL5A1 to the ECM in the forelimb. To identify the functional contribution of COL5A1 by myogenic or connective tissue cell populations, we generated conditional (cre-flox) knock-out mouse models to inactivate <em>Col5a1</em> using <em>Pax3</em>- or <em>Prx1</em>-drivers, respectively. Haploinsufficiency of <em>COL5A1</em> in humans is associated classical Ehlers-Danlos syndrome, characterized by skin fragility and join instability; similar, albeit more severe, phenotypes were present in <em>Prx1Cre/+;Col5a1fl/fl</em> mutants, but not in <em>Pax3Cre/+;Col5a1fl/fl</em> mutants or controls. Interestingly, THBS4+ and COL22A1+ networks at the MTJ were morphologically affected in <em>Prx1Cre/+;Col5a1fl/fl</em> limbs. Additional work needs to be conducted to characterize the systematic phenotypes observed in <em>Prx1Cre/+;Col5a1fl/fl</em> limbs.</p> <p>Together, our results indicate that there are distinct, complex ECM dynamics, originating from distinct cell-types, that drive musculoskeletal morphogenesis in the forelimb. Further, the tools developed here will serve as a foundation for quantitative proteomic analyses of the matrisome composition in embryonic tissues. Collectively, this work provides a baseline of ECM protein dynamics during musculoskeletal morphogenesis, a helpful guide for tissue engineers in designing scaffolds to promote restoration of damaged tissues, with enhanced integration into the host tissue.</p>

<p dir="ltr">The goal of this dissertation is to develop precision technologies to facilitate establishing, in the context of stochastic organismal dynamics, organizational principles that govern basic regulatory processes in living systems. We focus on biological timekeeping, the interplay of biological lengths and timescales, and strategies governing the control of rapid vs. precise adaptation to changing phenomena supporting complex phenotypes. In particular, individual cells of unicellular organisms respond with remarkable precision and plasticity in their growth and division to changes in their noisy environments. Cells rely on scalable timekeepers and quantitative tradeoffs to accomplish this precision. In this dissertation we will address longstanding open questions in cell biology, such as: How does an individual cell maintain size homeostasis across multigenerational dynamics, as it repeatedly grows and divides? How does an organism adapt its growth rate to reflect changing environmental conditions? The development of understanding of systems-level organizational principles in a controlled experimental system in turn advances our general ability to predict and control stochastic organismal dynamics, and thus develop functional synthetic adaptive systems.</p>

Stroke is a chronic illness which often impairs survivors for extended periods of time, leaving the individual limited in motor function. The ability to perform daily activities (ADL) is closely linked to motor recovery following a stroke. The objective of this work is to employ surface electromyography (sEMG) gathered through a novel, wearable armband sensor to monitor and quantify ADL performance. The first contribution of this work seeks to develop a relationship between sEMG and and grip aperture, a metric tied to the success of post-stroke individuals’ functional independence. The second contribution of this work aims to develop a deep learning model to classify RTG movements in the home setting using continuous EMG and acceleration data. In contribution one, ten non-disabled participants (10M, 22.5 0.5 years) were recruited. We performed a correlation analysis between aperture and peak EMG value, as well as a one-way non parametric analysis to determine cylinder diameter effect on aperture. In contribution two, one non-disabled participant is instructed to wash a set of dishes. The EMG and acceleration data collected is input into a recurrent neural network (RNN) machine learning model to classify movement patterns. The first contribution’s analysis demonstrated a strong positive correlation between aperture and peak EMG value, as well as a statistically significant effect of diameter (p < 0.001). The RNN model built in contribution two demonstrated high capability at classifying movement at 94% accuracy and an F1-score of 86%. These results demonstrate promising feasibility for long-term, in-home classification of daily tasks. Future applications of this approach should consider extending the procedure to include post-stroke individuals, as this could offer valuable insight into motor recovery within the home setting.

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<p>The purpose of this thesis was to evaluate musculoskeletal contributions to joint stiffness in the distal upper extremity. An <em>in-vitro</em> and <em>in-vivo</em> approach was used to examine muscle and ligament contributions to mechanical joint stiffness at the elbow and wrist. In Chapters 2 and 3 an <em>in-vitro</em> approach was used to evaluate ligament contributions to carpal tunnel mechanics. Chapter 2 documented transverse carpal ligament (TCL) mechanical properties and provided a calculation of TCL length when stretched, which confirmed the ligaments importance in carpal tunnel mechanics and carpal bone stability. Chapter 3 quantified mechanical properties of the TCL at six different locations using a biaxial tensile testing method. It was found that the complex TCL fibre arrangement makes the tissue properties location dependent. The TCL contributes to carpal tunnel mechanics and carpal stability and the ligament contributions are different depending on the tissue location tested. Chapters 4 and 5 focused on the effects of hand loads and arm postures on the muscular response to sudden arm perturbations. The elbow flexors demonstrated stiffness contributions immediately prior to a perturbation and were influenced by posture and hand loading. The forearm muscles provided a small contribution to elbow joint stiffness. Chapter 6 also found muscular contributions that increased wrist joint stiffness immediately prior to a sudden perturbation. Additionally, for a small grip-demanding task, forearm muscle co-contraction resulted in large increases in wrist joint stiffness.</p> <p>This thesis has provided a detailed analysis of the TCL which improves our understanding of the carpal tunnel and specific mechanisms of injury. It is the first to document individual muscle contributions to elbow and wrist joint stiffness. The comprehensive analysis of ligament and muscular contributions to joint stiffness has provided insight into joint stability in the distal upper extremity. This can improve our understanding of injury caused by sudden joint loading.</p> / Doctor of Philosophy (PhD)