Ovarian cancer is routinely diagnosed long after the disease has metastasized through the fibrous submesothelium. Despite extensive research in the field linking ovarian cancer progression to increasingly poor prognosis, there are currently no validated cellular markers or hallmarks of ovarian cancer that can predict metastatic potential. To discern disease progression across a syngeneic mouse ovarian cancer progression model, here we fabricated extracellular matrix mimicking suspended fiber networks: cross-hatches of mismatch diameters for studying protrusion dynamics, aligned same diameter networks of varying interfiber spacing for studying migration, and aligned nanonets for measuring cell forces. We found that migration correlated with disease while a force-disease biphasic relationship exhibited F-actin stress fiber network dependence. However, unique to suspended fibers, coiling occurring at the tips of protrusions and not the length or breadth of protrusions displayed the strongest correlation with metastatic potential. To confirm that our findings were more broadly applicable beyond the mouse model, we repeated our studies in human ovarian cancer cell lines and found that the biophysical trends were consistent with our mouse model results. Altogether, we report complementary high throughput and high content biophysical metrics capable of identifying ovarian cancer metastatic potential on a timescale of hours.
|Original language||English (US)|
|Journal||Molecular biology of the cell|
|State||Published - May 15 2022|
Bibliographical noteFunding Information:
This work is partially supported by the National Science Foundation awarded to A.S.N. (1762634). B.B. acknowledges partial support from the National Science Foundation (CAREER award, CBET-1454226). A.S.N., B.B., and ES acknowledge the Institute of Critical Technologies and Sciences (ICTAS) and the Macromolecules Innovative Institute at Virginia Tech for their support in conducting this study. A.M. and A.S.N. thank members of the STEP Lab for their helpful suggestions and discussions. A.S.N. dedicates this manuscript to the memory of Dolly Batra Kapahi and others who courageously fought ovarian cancer.
© 2022 Mukherjee et al.
PubMed: MeSH publication types
- Journal Article
- Research Support, U.S. Gov't, Non-P.H.S.
- Research Support, N.I.H., Extramural