Assessing the Roles of Collagen Fiber Morphology and Matrix Stiffness on Ovarian Cancer Cell Migration Dynamics Using Multiphoton Fabricated Orthogonal Image-Based Models.

Ovarian cancer remains the deadliest of the gynecological cancers, where this arises from poor screening and imaging tools that can detect early disease, and also limited understanding of the structural and functional aspects of the tumor microenvironment. To gain insight into the underlying cellular dynamics, we have used multiphoton excited fabrication to create Second Harmonic Generation (SHG) image-based orthogonal models from collagen/GelMA that represent both the collagen matrix morphology and stiffness (similar to 2-8 kPa) of normal ovarian stroma and high grade serous ovarian cancers (HGSOC). These scaffolds are used to study migration/cytoskeletal dynamics of normal (IOSE) and ovarian cancer (OVCA433) cell lines. We found that the highly aligned fiber morphology of HGSOC promotes aspects of motility (motility coefficient, motility, and focal adhesion expression) through a contact guidance mechanism and that stiffer matrix further promotes these same processes through a mechanosensitive mechanism, where these trends were similar for both normal and cancer cells. However, cell specific differences were found on these orthogonal models relative to those providing only morphology, showing the importance of presenting both morphology and stiffness cues. Moreover, we found increased cadherin expression and decreased cell alignment only for cancer cells on scaffolds of intermediate modulus suggesting different stiffness-dependent mechanotransduction mechanisms are engaged. This overall approach affords decoupling the roles of matrix morphology, stiffness and cell genotype and affords hypothesis testing of the factors giving rise to disease progression and metastasis. Further, more established fabrication techniques cannot simultaneously reproduce both the 3D collagen fiber morphology and stiffness. (c) 2022 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.