Spatiotemporal Tumor Analytics for Guiding Sequential Targeted-Inhibitor: Immunotherapy Combinations (ST-Analytics)
Project Number1U54CA274509-01
Contact PI/Project LeaderHEATH, JAMES R.
Awardee OrganizationINSTITUTE FOR SYSTEMS BIOLOGY
Description
Abstract Text
Overall Project Summary
The proposed U54 program Spatiotemporal Tumor Analytics for Guiding Sequential Targeted-Inhibitor --
Immunotherapy Combinations (ST-Analytics) is designed to develop the recent conceptual advance that
targeted inhibitor + cancer immunotherapy (IT) combination treatments may yield significantly greater patient
benefit if those treatments are administered in sequence rather than simultaneously. Analysis of retrospective
clinical data coupled with in vivo therapeutic modeling using syngeneic models of murine melanoma strongly
support this concept. In fact, the picture that has emerged in melanoma is that immune factors can play a strong
role in driving resistance to MAPK inhibitor (MAPKi) therapy, and that lead-in immune checkpoint blockade (ICB)
can ‘prime’ both the primary tumor and distal metastases (including brain metastases) for eradication when the
IT is subsequently combined with MAPKi. This observation opens the doors for immune based strategies, such
as ICB or adoptive cell therapy (ACT), as sequential combinatorial agents to prevent MAPKi resistance.
However, this concept introduces a number of new variables, including dosing, sequence, and timing. This can
make the design and execution of clinical trials that can yield statistically significant outcomes impractical. This
is the scientific and translational problem we address in the proposed ST-Analytics U54.
The ST-Analytics U54 center is populated by leading scientists at the ISB, the UCLA Geffen School of Medicine,
and Yale, and is comprised of two research projects and two research cores, with each project integrating both
state-of-the-art experimentation and computational work. This structure is further designed to bring together the
scientific, experimental, and computational and administrative resources to develop a data base that captures
the kinetics of lead-in monotherapy tumor priming, and apply that data base to the development of predictive in
silico models that can inform the design of such targeted inhibitor – immunotherapy sequence combinations for
clinical trials. This requires close integration and cycles of iteration between of state-of-the-art experimentation,
leading edge computation, and realistic disease models, continuously calibrated through the analysis of highly
relevant, biopsied patient tumors. The resulting science also provides exciting opportunities for high impact
STEM outreach. We propose to act on those opportunities by leveraging a long-standing systems education
outreach program at ISB that already has impacted K-12 STEM education in all 50 states, and places an
emphasis on those communities that have been historically under-represented in STEM.
Public Health Relevance Statement
Overall Narrative
The proposed U54 program Spatiotemporal Tumor Analytics for Guiding Sequential Targeted-Inhibitor --
Immunotherapy Combinations (ST-Analytics) is designed to develop the recent conceptual advance that
targeted inhibitor + cancer immunotherapy (IT) combination treatments may yield significantly greater patient
benefit if those treatments are administered in sequence rather than as monotherapies or as simultaneously
administered combinations.
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