Clara Theresa Vincent

Metastasis is the leading cause of cancer-related mortality, accounting for nearly 90 percent of cancer deaths. My research program is centered on a fundamental question in cancer biology: how do tumor cells acquire the plasticity, resilience, and adaptability required to escape the primary tumor, survive systemic dissemination, and colonize distant organs? By addressing this question, we aim to uncover core mechanisms of disease progression while identifying actionable vulnerabilities that can be translated into better therapies for patients with advanced cancer.

Our work focuses on the dynamic cell-state changes that underlie metastatic competence, with particular emphasis on epithelial-to-mesenchymal transition (EMT) and tumor cell plasticity. As cancers progress, tumor cells often lose the defining features of their tissue of origin and adopt more aggressive, migratory, stem-like, and therapy-resistant states. EMT is a central component of this process, enabling epithelial cancer cells to acquire invasive capacity while evading conventional treatments. We seek to define the molecular circuitry and cellular mechanisms that initiate, sustain, and reverse these transitions, with the long-term goal of disrupting metastasis at its roots.

Breast cancer metastasis serves as a major model system in this work. Although treatment of primary breast cancer has advanced substantially, metastatic breast cancer remains largely incurable and is responsible for the vast majority of patient deaths. Once disseminated to distant organs such as the lung, liver, brain, and bone, metastatic cells frequently become resistant to endocrine therapies, chemotherapy, and other standard interventions. There is therefore an urgent need for new biological insights and therapeutic strategies that can both prevent metastatic spread and more effectively target metastatic disease once it has emerged.

A major advance from our studies has been the identification of a previously underappreciated and potentially targetable dependency of metastatic tumor cells: the reprogramming of ribosome biogenesis. We have found that EMT and metastatic progression are accompanied by a profound and essential rewiring of ribosomal DNA transcription and ribosome production. While ribosome biogenesis has classically been associated with cell growth and proliferation, our work demonstrates that even non-proliferative metastatic cancer cells remain critically dependent on this machinery for survival, plasticity, and metastatic outgrowth. These findings reveal a highly druggable axis in aggressive cancer and challenge conventional assumptions about the biology of metastatic cells.

More broadly, our research is helping redefine the role of ribosomes and translational control in cell-state regulation. Rather than serving as passive components of protein synthesis, ribosomes may act as active regulators of how cells adapt to stress, transition between phenotypic states, and survive hostile microenvironments. By understanding how translation and ribosome function shape cancer cell behavior, we aim to establish a deeper mechanistic framework for metastasis and treatment resistance.

In parallel with these mechanistic studies, we are building a next-generation Clinical-to-Model Precision & AI Platform that bridges discovery science, translational modeling, and patient-centered precision medicine. The platform is designed as an integrated translational ecosystem linking clinical biospecimen acquisition with patient-derived model development, molecular profiling, functional assays, advanced imaging, and AI-driven computational analysis. Its overarching goal is to convert clinical samples into mechanistic insight and patient-specific therapeutic strategies

More than a technical resource, this platform is intended to serve as a scalable framework for translational oncology. By integrating clinical data, treatment history, molecular signatures, and functional behavior in patient-derived systems, it will support biomarker discovery, predictive modeling, and real-time therapeutic testing in models that more faithfully capture the complexity and heterogeneity of human disease. The platform is also being developed with broader applicability across multiple disease areas over time. 

At a broader level, this work reflects our vision for the future of cancer research: a deeply integrated and interdisciplinary approach in which basic science, engineering, computational biology, and clinical medicine converge to address the hardest problems in metastatic disease. By combining mechanistic insight into tumor plasticity and metastasis with a robust precision modeling infrastructure, we aim to enable a new generation of translational advances and more personalized treatment strategies for patients with aggressive cancers.