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With dramatic advancements in biological data generation, genetic rescue and reproductive technologies, and inter-institutional coordination of care across entire animal populations, zoos, aquariums, and their collaborators are uniquely positioned to lead population-wide research benefiting animal wellbeing and species survival. However, procedural and inter-institutional barriers make it exceedingly difficult to access existing zoological biospecimens and data at scale. To address this, the Zoonomics Working Group, representing diverse roles across three zoological associations (AZA, EAZA, WAZA), proposes a biodiversity biobank alliance that develops and delivers shared resources to support the collection, storage, and sharing of biological samples and associated data across the zoological and conservation community. By biobank alliance, we mean a community-guided effort that develops shared resources, standards, ethos, and practices for collecting, storing, and sharing biological samples and associated data voluntarily through transparent processes, consistent with professional accreditation standards and international best practices. While initially focused on addressing the needs and regulatory landscape of U.S. institutions, the alliance is designed to create frameworks that are adaptable and adoptable for international expansion. Such a framework would help the zoological community navigate the ethical, legal, and practical challenges of managing biospecimen collections, making access more efficient, reliable, and robust. Achieving this vision requires collective agreement on ethical principles such as reciprocity, transparency, and data stewardship, ensuring that research is both feasible and proactively supported. Such coordination will drive advances in fundamental biology and accelerate progress in animal health, welfare, management, and biodiversity conservation. 

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.