Using a 3D Model of Mammary Tissue to Understand the Role of Mechanotransduction in Breast Cancer Initiation

Student thesis: Phd


High mammographic density (HMD) is the second largest independent risk factor for breast cancer in women. Notably, unlike other risk factors, HMD can be therapeutically modified with treatments such as Tamoxifen which can decrease breast cancer risk in some women. However, not all patients respond to therapy and there is currently no means to accurately identify which women will benefit from treatment. How HMD increases cancer risk is unclear. The identification of the mechanisms underlying this increased risk may lead to the discovery of novel stratification biomarkers or therapeutic targets for the prevention and early detection of breast cancer. Crucially, there is significant evidence that increased mammographic density correlates with increased extracellular matrix (ECM) stiffness. We also know that the mechanisms by which cells sense and transduce force are key in regulating a range of cellular functions including cell migration, differentiation, and proliferation. Therefore, we and others hypothesised that increased ECM stiffness and altered mechanotransduction may play a role in the increased breast cancer risk in women with HMD. To this end, we developed a 3D model of HMD to allow us to explore how increased matrix stiffness promotes mammary epithelial cell malignant transformation in polarised acini. The results presented in this thesis demonstrate how increased matrix stiffness leads to loss of apical-basal polarity and decreased DNA damage repair in mammary epithelial cells. We also demonstrated that loss of apical-basal polarity is reversible following a reduction in matrix stiffness. We then used this 3D model system to screen potential hits from a mechanosensitive proximity-dependent biotin-identification screen. Based on the evidence presented in this thesis I hypothesise that MISP and iASPP may regulate the mammary epithelial cell responses to increased matrix stiffness. We also present evidence to suggest that tight regulation of RSU1 expression and localisation may act as a mechanical sensor for changes in matrix stiffness. I finally present a transcriptomic dataset which provides insights into how downstream signalling pathways, induced by changes in matrix stiffness, may drive early breast cancer initiation. This dataset will serve as a database for further study. Future investigations building on the work presented in this thesis can now be focused on screening mechanosensitive pathways and differentially expressed genes to determine their potential roles in the transformation of mammary epithelial cells.
Date of Award1 Aug 2024
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorAndrew Gilmore (Supervisor), Sacha Howell (Supervisor) & Robert Clarke (Supervisor)


  • Breast Cancer Initiation
  • Mammographic Density
  • Mammary Epithelial Cell Transformation
  • Mechanotransduction

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