# Quantifying patient-specific tumor evolutionary dynamics and resistance mechanisms in HER2-positive breast cancers treated with targeted therapy

> **NIH NIH F30** · STANFORD UNIVERSITY · 2022 · $11,633

## Abstract

This proposal addresses the significant clinical and scientific challenge of targeted drug resistance in HER2-
positive breast cancer. Breast cancer is the most common cancer in women in the US and HER2-positive
disease is particularly aggressive. Trastuzumab, a monoclonal antibody targeted at the HER2 receptor, has
revolutionized care for patients with HER2-positive disease, but resistance and subsequent disease
progression occur frequently. While there have been multiple attempts to predict response to trastuzumab,
previous studies often use bulk expression data from a single time point and do not consider the role of tumor
evolution in treatment response. The rich clinical cohort used in this proposal, with longitudinal, multi-region
data for each patient, is ideal for studying the spatio-temporal tumor evolutionary dynamics during treatment.
We aim to (1) characterize the genomic, transcriptomic, and proteomic changes associated with HER2-
targeted therapy and determine if specific alterations are associated with treatment response, (2) use patient
genomic data as input to a spatial computational model of breast tumor evolution under targeted treatment to
quantify the patient-specific evolutionary dynamics of resistance, and (3) use insights from the evolutionary
model to identify drivers of resistance in a unbiased fashion. This proposal addresses the pressing clinical
needs of defining biomarkers to predict which patients will respond to HER2-targeted therapy and
understanding how and why treatment resistance develops in others. A deeper understanding of how tumors
evolve under targeted therapy using HER2-positive breast cancer as a model system will inform more effective
treatment strategies that harness tumor evolution to prevent resistance, with applications to other cancers.
The fellowship training will take place at the Stanford University School of Medicine, which has unparalleled
research, clinical, and student development resources and emphasizes interdisciplinary research and
innovation in both the experimental and computational realms. Dr. Christina Curtis is the ideal sponsor for this
proposal due to her significant expertise in tumor evolution, cancer genomics, and biomarker development, her
federally funded program in modeling therapeutic resistance in breast cancer, as well as her dedication to
student mentorship. Dr. Robert West brings expertise in breast cancer pathology, analysis of archival tissue,
and physician-scientist career mentorship. Technical and scientific reasoning abilities will be expanded through
research, coursework, and faculty mentoring during the training period, facilitating a successful future career in
translational cancer research. Attendance at local and national conferences, together with journal clubs and
workshops, will also lead to improved writing, presentation, and networking skills.

## Key facts

- **NIH application ID:** 10370347
- **Project number:** 5F30CA239313-04
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Katherine Lee McNamara
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $11,633
- **Award type:** 5
- **Project period:** 2019-04-01 → 2022-06-12

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10370347

## Citation

> US National Institutes of Health, RePORTER application 10370347, Quantifying patient-specific tumor evolutionary dynamics and resistance mechanisms in HER2-positive breast cancers treated with targeted therapy (5F30CA239313-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10370347. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*