Alison P. McGuigan

Alison McGuiganProfessor
MEng. (Oxford), PhD (Toronto), Post-Doc (Harvard, Stanford)
Principal InvestigatorMcGuigan Lab and
BioZone – Centre for Applied Bioscience and Bioengineering
Room: WB338 | Tel.: 416-978-7552 | Email: alison.mcguigan@utoronto.ca

 

Memberships

Tissue Engineering and Regenerative Medicine International Society
Society for Biomaterials
Professional Engineers Ontario

Research Interests

Cell behaviour in standard 2D plastic experimental systems is often not predictive of in vivo response. This is because cell behaviour is determined by a combination of intrinsic molecular properties and the local microenvironment, which in a tissue is complex and heterogeneous: tissues are composed of multiple cell types and matrix proteins organized into specific architectures. It is therefore not surprising that homogenous cell populations cultured in monolayers on the surface of plastic dishes, a microenvironment that has little resemblance to that in vivo, often fail to produce data predictive of cellular response in humans. Physiologically relevant, personalized, tissue mimetic systems offer the opportunity to systematically dissect fundamental mechanisms of tissue assembly, disease and regeneration to allow identification of novel therapy targets to manipulate these processes for therapeutic benefit. Furthermore, such systems offer the potential to improve the effectiveness of therapy discovery and to enable the design of personalized treatments.

Our mission in the McGuigan lab is to use tissue-engineering strategies to assemble multicellular tissue mimetic platforms that are both physiologically relevant and allow acquisition of high value data for both drug discovery and fundamental research.

Our team develops technologies to control cell organization at the tissue scale and the cellular scale and strategies to stratify and visualize complex datasets from these heterogeneous tissue systems. Further we are establishing approaches to scale our tissue models to enable integration with AI and machine learning tools. Using these platforms, we are exploring the rules of tissue self-assembly and mechanisms of disease and regeneration with a view to developing novel therapeutics.

Selected Publications

Pieters VM, Rjaibi ST, Singh K, Li NT, Khan ST, Nunes SS, Dal Cin A, Gilbert PM*, McGuigan AP (co-corresponding author), A three-dimensional human adipocyte model of fatty acid-induced obesity, Biofabrication 2022 Aug 19;14(4).

Wu NC, Cadavid JL, Tan X, Latour S, Scaini S, Makhijani P, McGaha TL, Ailles L, McGuigan AP. (Corresponding author), 3D microgels to quantify tumor cell properties and therapy response dynamics., Biomaterials 2022, 283, 121417.

Davoudi S, Xu B, Jacques E, Cadavid JL, McFee M, Chin C-Y, Meysami A, Ebrahimi M, Bakooshli MA, Tung K, Ahn H, Ginsberg HJ, McGuigan AP, Gilbert PM (Co-corresponding author) MEndR: An In Vitro Functional Assay to Predict In Vivo Muscle Stem Cell-Mediated Repair, Adv. Func. Mater., 2022, 32 (2), 2106548

An Engineered Patient-Derived Tumor Organoid Model That Can Be Disassembled to Study Cellular Responses in a Graded 3D Microenvironment, Natalie Landon-Brace, Jose L. Cadavid, Simon Latour, Ileana L. Co, Darren Rodenhizer, Nancy T. Li, Nila C. Wu, Eryn Bugbee, Aleks Chebotarev, Ji Zhang, Bradly G. Wouters, Alison P. McGuigan, Adv. Funct. Mater., 2021, 31 (41), 2105349

A three-dimensional engineered tumour for spatial snapshot analysis of cell metabolism and phenotype in hypoxic gradients., Rodenhizer D, Gaude E, Cojocari D, Mahadevan R, Frezza C, Wouters BG, McGuigan AP., Nat Mater. 2016 Feb;15(2):227-34. doi: 10.1038/nmat4482.

Assembly of lung progenitors into developmentally-inspired geometry drives differentiation via cellular tension., Soleas JP, D’Arcangelo E, Huang L, Karoubi G, Nostro MC, McGuigan AP, Waddell TK., Biomaterials. 2020:120128.

Design of biomimetic substrates for long-term maintenance of alveolar epithelial cells. Poon JCH, Liao Z, Suzuki T, Carleton MM, Soleas JP, Aitchison JS, Karoubi G, Mcguigan AP, Waddell TK. Biomater Sci. 2018 Jan; 6(2):292-303. doi: 10.1039/C7BM00647K

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