Distinct contributions of mesenchymal cell niches in the therapeutic potential of the hedgehog pathway in triple negative breast cancer

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PROJECT SUMMARY Breast cancer remains a leading cause of death in the US. Among the breast cancer types, triple-negative breast cancer (TNBC) is considered to have a poorer prognosis due to its rapid growth, invasiveness, and rate of metastasis. Also, the TNBC subtype is more likely to relapse than other types of breast cancer. Recent studies support the tumor-associated extracellular matrix (ECM) as a critical factor in cancer development and relapse mechanisms. The ECM of normal or tumorigenic tissue comprises a complex mixture of biomolecules, such as the extracellular vesicles within the ECM known as the matrix-bound nanovesicles (MBVs). However, tumor- ECM, MBVs and their impact on the mechanism of breast cancer and TNBC remain poorly understood. ECMs, if appropriately processed, can be used as naturally derived biomaterials that promote a relevant microenvironment for cell and mechanistic research with a safe record of clinical use. Tissue-specific ECM hydrogels are ideal for clinical application, particularly given the emerging need to develop tools for precision medicine. We hypothesize that extracellular vesicles within the ECM (tumor or normal) work as an oncogenic seed that will modulate cellular behavior impacting drug test models. This proposal aims to define how tumor and stromal ECM and associated MBV components impact the Hedgehog pathway in TNBC as a potential route to develop relevant models for drug-testing treatments in breast cancer. Also, the diversity proposal looks to strengthen the clinical relevancy of the candidate's work, paving the way to become an independent investigator in the biomedical field while securing tenure in the institution. At the end of this supplemental diversity proposal and under the PI's mentoring plan, the candidate (faculty) will obtain publications in the field of cancer, build strategic networking, and gather preliminary data to support R-level grant submission.