I-SPY2 +: Evolving the I-SPY 2 TRIAL to include MRI-directed, adaptive sequential treatment to optimize breast cancer outcomes
Project Number5P01CA210961-04
Contact PI/Project LeaderESSERMAN, LAURA J Other PIs
Awardee OrganizationUNIVERSITY OF CALIFORNIA, SAN FRANCISCO
Description
Abstract Text
The overarching goal of this program project is to advance the science of individualizing treatment to improve
outcomes on the basis of response to therapy. Neoadjuvant chemotherapy (NAC) provides the opportunity to
assess response to systemic therapy prior to surgery in women with high risk early breast cancer. The optimal
outcome is the complete eradication of tumor, (pathologic complete response (pCR)), which is strongly
associated with improved long-term survival and is a surrogate endpoint for accelerated drug approval.
Conversely, women with significant residual cancer burden (RCB 2/3) suffer event free survival of less than
60% at 3-5 years. Redirecting therapy in poor responders could dramatically improve breast cancer survival in
the highest risk women and minimize toxicities in early responders. The neoadjuvant I-SPY 2 adaptive clinical
trial platform, designed to accelerate phase II development of new agents for stage II/III breast cancer is the
ideal setting for this work. MRI will serve as a foundation for an integrated residual cancer burden assessment
tool (“iRCB”), optimized by tumor subtype and pathway. Two decades of MRI imaging research in the I-SPY
program have provided the necessary technology, bioinformatic and statistical approaches, and validation
datasets to optimize the iRCB tool to serve as the trigger to redirect to rationally selected, biologically targeted
agents. The advances from each project coalesce in Project 1, where we have developed the mechanics of
integrating the pieces to determine whether treatment redirection on the basis of pathway abnormalities and
avoiding the additional toxicity of chemotherapeutic agents in the setting of complete or poor response leads to
better outcomes. Project 2 contributes the tools for the optimization of the iRCB, using advances in imaging
methods (diffusion weighted imaging and breast PET) and a longitudinal model that includes molecular data
from diagnosis, and an inter-regimen biopsy to confirm absence or presence of disease and accurately classify
excellent and poor response (RCB 0 and RCB 2/3, respectively). Project 3 will provide an understanding of the
dynamics of the biology of response and treatment resistance, and Project 4 will delineate the rational
selection of `second chance” therapies based on the biology and knowledge of agents already or being
developed. We will work closely with the FDA over the course of this Program Project to establish the subtype
specific thresholds for iRCB. The final result will be an evolution of the existing I-SPY Trial (into “I-SPY2+”) that
employs an innovative Sequential Multiple Assignment Randomization Trial (SMART) design to maximize both
clinical impact and knowledge generation, while closely reflecting the realities of current clinical practice. Taken
together, these projects leverage an established, successful, efficient, and highly innovative clinical trial
platform and an experienced, collaborative research team to address a critical clinical issue in breast cancer.
The innovative approach employed will mark a milestone in the implementation of personalized medicine in
breast cancer and generate an unprecedented view of the molecular evolution of treatment resistance.
Public Health Relevance Statement
NARRATIVE-OVERALL
Building on the successful I-SPY2 clinical trial framework, we will develop, implement and validate a strategy to
address insufficient response to neoadjuvant therapy in high risk breast cancer. An MRI-based assessment,
virtual RCB, will identify poor responders, who will then be re-assigned to new treatments based on the
underlying biology of the tumor and its predicted response. In the process we will develop a comprehensive,
longitudinal view of the dynamics of molecular pathways of resistance and create additional biomarker
resources to fuel better outcomes through the personalization of neoadjuvant therapy.
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