# Personalizing immunotherapy in HER2+ breast cancer through quantitative imaging

> **NIH NIH R01** · UNIVERSITY OF ALABAMA AT BIRMINGHAM · 2020 · $414,223

## Abstract

PROJECT SUMMARY/ABSTRACT
The overall goal of this proposal is to integrate advanced imaging and mathematical modeling to
optimize combination treatments involving immunotherapy in human epidermal growth factor receptor
type 2 positive (HER2+) breast cancer. Current standard-of-care therapeutic regimens and even clinical trials
are limited because they are not personalized based on the tumor biology of the individual patient, potentially
diminishing the efficacy of the treatment. This proposed research will employ noninvasive, quantitative magnetic
resonance imaging (MRI) and positron emission tomography (PET) to inform mathematical models to direct
timing for multi-modal therapies in HER2+ breast cancer. Overexpression of HER2 is indicative of more
aggressive disease with five times higher risk of metastasis, with increased risk of breast-to-brain metastases,
compared to HER2- patients. We have extensive experience and expertise in using quantitative medical imaging
techniques to assess and predict treatment response to anti-cancer therapies. Additionally, we have shown that
trastuzumab dosing prior to cytotoxic treatment (instead of simultaneous dosing of combination therapies) has
potential to improve vascular delivery and oxygenation in HER2+ breast cancer tumors, which in turns sensitizes
the tumor for cytotoxic therapies, reduces metastatic potential, improves drug delivery and reduces systemic
toxicity. As immunotherapy becomes mainstream for many solid tumors, it is essential to develop techniques to
both personalize and optimize therapeutic efficacy and decrease systemic toxicity. Thus, our central hypothesis
is that quantitative imaging integrated with mathematical modeling can enhance personalization of treatment
strategies and increase efficacy (additive and synergistic) of combination therapies with immunotherapy in
HER2+ breast cancer. To achieve this goal, we have identified the following specific aims: 1) Quantify biological
changes to immuno- and targeted therapy in HER2+ breast cancer with quantitative imaging, 2) Build a
mathematical model of biological alterations to immunotherapy in HER2+ breast cancer, and 3) Employ model
forecasting and quantitative imaging to guide combination therapy. We will exploit the alterations in biological
changes, such as vascular delivery (evaluated with dynamic contrast enhanced (DCE)- MRI pharmacokinetic
parameter, Ktrans) and oxygenation (evaluated with fluoromisonidazole (FMISO)-PET imaging metric, SUV) to
inform a mathematical model in order to identify (and validate) optimal sequencing (order, timing, dose) to
combination therapy (targeted, immunotherapy) for enhanced synergistic effects. Completion of this project
provides a pathway to dramatically improve the efficacy of treatment strategies with immunotherapy for primary
HER2+ breast cancer. Importantly, the proposed techniques provide a straightforward route for patient
translation and potential to enhance care for HER2+ breast cancer pa...

## Key facts

- **NIH application ID:** 9972584
- **Project number:** 1R01CA240589-01A1
- **Recipient organization:** UNIVERSITY OF ALABAMA AT BIRMINGHAM
- **Principal Investigator:** Anna C Sorace
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $414,223
- **Award type:** 1
- **Project period:** 2020-03-01 → 2024-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9972584

## Citation

> US National Institutes of Health, RePORTER application 9972584, Personalizing immunotherapy in HER2+ breast cancer through quantitative imaging (1R01CA240589-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9972584. Licensed CC0.

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