PROJECT SUMMARY/ABSTRACT
Recurrence of cancer cells that evade therapy is a leading cause of death. Given that residual disease can
persist for years to decades following therapy, it presents a second therapeutic window where the vulnerabilities
of residual cells can be exploited to identify novel, actionable targets, thus reducing or delaying recurrence.
Unfortunately, mechanisms of residual disease survival remain under-studied, partly due to the lack of tools and
models to precisely study the evolutionary nature of residual disease. To this end, metabolic and vascular
reprogramming have been observed to occur in parallel to therapy resistance and precede anatomical changes
after treatment, and thus hold promise as targets to be leveraged to improve clinical outcomes. This proposal
will develop novel functional imaging tools to understand the dynamic behaviors of residual tumors (F99 phase)
and how metabolic and vascular vulnerabilities can be targeted during residual disease to mitigate recurrence
(K00 phase). The emergence of residual disease reflects the spatiotemporal heterogeneities of the tumor
microenvironment and the evolutionary property of cancer cells to adapt to therapy-induced selective pressures.
Therefore, to effectively monitor treatment responses, a systems-level approach to image metabolism and the
associated vasculature of the tumor microenvironment at a spatial resolution capable of visualizing intra-tumoral
heterogeneity in vivo is necessary, but currently unavailable. In the F99 phase of this proposal, I aim to design
novel optical imaging methodologies to track metabolic and vascular shifts to identify metabolically distinct
residual tumor subpopulations that emerge following chemotherapy. In aim 1.1 (previous work), I show that
longitudinal assessment of bulk tumor metabolism and intra-tumoral heterogeneity enables chemotherapy
induced metabolic shifts to be captured during disease regression, residual disease, and recurrence. In aim 1.2
(proposed work), I will develop image segmentation approaches to quantify 1) cellular-level metabolic features
and 2) vascular characteristics that lead to poor perfusion. I will examine whether resistance to treatment leads
to the emergence of specialized niches of metabolically distinct residual tumor subpopulations that could be
targeted. While functional imaging approaches are desirable due to their ability to reflect cellular, and tissue-
level dynamics, they are insufficient to elucidate all the molecular mechanisms that drive recurrence. In the K00
phase of this proposal, I will take a molecular approach to delve into the mechanisms of residual disease in PDX
models of Triple Negative Breast Cancer (TNBC). I will focus on targeting MYC oncogenic signaling pathways
to identify novel, actionable metabolic and vascular targets of residual disease for a subset of TNBC tumors. In
addition to filling a critical need for the treatment of residual disease in TNBC, this training plan will provide
exceptional training by leaders in the imaging and cancer biology fields, positioning me to become an
accomplished independent researcher at the interface of these two fields.
