Research partnerships between universities and communities following the principles of community-based participatory research (CBPR) have the potential to eliminate cycles of health disparities. The purpose of this article is to describe the process of establishing a community-campus network with a distinct mission and vision of developing trusting and successful research partnerships that are sustained and effective. In 2019, Morgan CARES was established to facilitate community engagement by founding a community center “within” a low-income residential neighborhood as a safe and accessible hub for creating a vibrant learning community. A community needs assessment and asset mapping was conducted and several necessary resources and services were provided to maximize networking opportunities, nurture innovative ideas and proposals, and provide seed funding. Lessons learned informed the optimization of a theoretical model that has guided the development and implementation of the program’s key components. By December 2021, Morgan CARES had recruited 222 community and 137 academic members representing diverse expertise from across Baltimore City. We also successfully established new partnerships and funded a total of 17 small community-academic awards. Although in its early stages, Morgan CARES has established a dynamic learning community following a conceptual framework that could guide future similar initiatives.

Background: Vulnerable communities are susceptible to and disproportionately affected by the impacts of the COVID-19 pandemic. Understanding the challenges faced, perceptions, lessons learned, and recommendations of the organizations that provide services in response to COVID-19 to vulnerable communities is critical to improving emergency response and preparedness in these communities. Methods: This study employed GIS mapping to identify the needs and assets that exist in communities in Baltimore City, where vulnerabilities related to social determinants of health and the burden of the COVID-19 pandemic were greatest. We also conducted an online survey between September 1, 2021, and May 30, 2022, to assess the COVID-19-related services provided by local organizations, challenges faced, perceptions, lessons learned, and recommendations to inform policies, programs, and funding related to improving the COVID-19 response in underserved communities. The survey was disseminated through the online Kobo Toolbox platform to leaders and representatives of organizations in Baltimore City. Results: Based on GIS mapping analysis, we identified three communities as the most vulnerable and 522 organizations involved in the COVID-19 response across Baltimore City. 247 surveys were disseminated, and 50 survey responses were received (20.24% response rate). Out of these organizations, nearly 80% provided services in response to COVID-19 to the identified vulnerable communities. Challenges experienced ranged from funding (29%), and outreach/recruitment (26%), to not having access to updated and accurate information from local officials (32%). Conclusions: This research highlights critical insights gained related to the experiences of vulnerable populations and suggests ways forward to address challenges faced during the emergency response by providing recommendations for policy and program changes. Furthermore, the findings will help better prepare vulnerable communities for public health emergencies and build more community resilience.

Metastatic prostate cancer (mPCa) is a leading cause of mortality, partly due to its resistance to anti-androgens like enzalutamide. Snail can promote this resistance by increasing full-length AR and AR-V7. High Mobility Group AT-hook 2 (HMGA2), a DNA-binding protein upstream of Snail, is crucial in proliferation and epithelial–mesenchymal transition (EMT). This study examines HMGA2’s role in enzalutamide resistance. LNCaP and 22Rv1 cells overexpressing wild-type HMGA2, but not truncated HMGA2, showed EMT. Both variants led to a decreased sensitivity to enzalutamide but not alisertib compared to Neo control cells. The overexpression of HMGA2 did not alter AR expression. Enzalutamide-resistant C4-2B cells (C4-2B MDVR) had higher HMGA2 and AR/AR variant expression than enzalutamide-sensitive C4-2B cells but remained sensitive to alisertib. The HMGA2 knockdown in C4-2B MDVR cells increased sensitivity to both enzalutamide and alisertib without changing AR expression. A clinical analysis via cBioPortal revealed HMGA2 alterations in 3% and AR alterations in 59% of patients. The HMGA2 changes were linked to treatments like enzalutamide, abiraterone, or alisertib, with amplifications more prevalent in bone, lymph node, and liver metastases. Conclusively, HMGA2 is a potential biomarker for enzalutamide resistance in mPCa, independent of Snail and AR signaling, and alisertib may be an effective treatment for mPCa that expresses HMGA2.

RNA In Situ Hybridization (RISH) is a powerful tool for spatial gene expression analysis, yet its quantitative use remains limited by the high cost and inaccessibility of commercial software, particularly in under-resourced settings. This study developed an Artificial Intelligence/Machine Learning (AI/ML)-assisted RISH quantification pipeline to evaluate expression patterns of High Mobility Group AT Hook-2 (HMGA2) in prostate cancer (PCa), focusing on racial disparities. We created a machine learning model capable of analyzing RISH images. Expressions of full-length (wild-type) and truncated HMGA2 isoforms were assessed in tissues from 85 men of African descent, European American, and Asian descent. A training dataset was generated for supervised learning analysis of the full cohort. RISH findings revealed that the wild-type HMGA2 isoform was significantly more abundant in tumors from men of African descent and positively correlated with increasing Gleason grade. The truncated isoform was less abundant and did not display a consistent expression pattern across racial groups. These results demonstrate the feasibility of AI/ML-based RISH quantification and suggest that elevated wild-type HMGA2 expression may represent a biomarker linked to prostate cancer aggressiveness and racial disparities. These findings highlight the importance of interdisciplinary collaboration and equitable computational tools in advancing biomarker discovery and addressing cancer health inequities.