# A systems biology approach to elucidate the biology of immune-associated outcomes in breast cancer

> **NIH NIH K01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2024 · $173,620

## Abstract

PROJECT SUMMARY
 This K01 application seeks protected time for mentored research and career development training for Dr.
Rosalyn Sayaman, PhD to successfully transition to tenure-track faculty with an independent research program
in computational and systems biology, supported by the Chair of Department of Laboratory Medicine. Leveraging
the advances in computational and Machine Learning methods and spearheading multi-omic technologies, Dr.
Sayaman seeks to develop a highly integrative research program that can bridge the gap between in-silico
research and translational medicine, with specific focus on advancing personalized medicine in breast cancer.
As a computational biologist with broad training and methodological experience, and a solid experimental
background, Dr. Sayaman is uniquely positioned to carry out this comprehensive study incorporating the parallel
multi-omic dataset for ~2000 women from the I-SPY 2 Trial. The I-SPY 2 neoadjuvant breast cancer clinical trial
is a personalized, adaptive trial designed to improve outcomes in high-risk breast cancer patients.
 Dr. Sayaman’s research proposal employs computational and Machine Learning approaches to dissect
the complex interactions between intrinsic host germline and tumor somatic mutations, and extrinsic tumor
microenvironment (TME) features that mediate the tumor immune response. In Aim 1, Dr. Sayaman elucidates
the role of genomic and TME features in determining the topography of immune populations in the tumor bed. In
Aim 2, she assesses the relative predictive value of these genomic and TME features in predicting subtype-
specific response to neoadjuvant therapy, and 5-year survival in patients who do not respond to therapy. This
work has the potential to generate response-predictive biomarkers that could inform optimal treatment decisions.
 To address the multi-disciplinary aspect of this study, Dr. Sayaman has assembled an exemplary team
of mentors who have complementary domains of expertise. Dr. Sayaman’s primary mentor is Dr. Laura van ‘t
Veer, the Co-Leader of the NCI-designated Breast Oncology Program (BOP) and Director of Applied Genomics
at the University of California, San Francisco (UCSF), and Chair of the I-SPY 2 Biomarker Committee. Dr. van ‘t
Veer is the inventor of the FDA-cleared MammaPrint® test included in many national and international breast
cancer guidelines. Dr. Sayaman’s co-mentors include Dr. Laura Esserman, the Director of the UCSF Breast
Care Center, the Clinical Co-Leader of the BOP, and the national Principal Investigator of the I-SPY 2 trial; Dr.
Elad Ziv, a leading cancer geneticist with expertise in statistical genetics and computational approaches in
cancer genomics; and Dr. Michael Campbell, an expert in cancer immunology, who leads the development of
multiplex Immune-Fluorescence assays for immune profiling in breast cancer. Dr. Sayaman’s proposed work
benefits from the world-class research and clinical expertise of the I-SPY 2 Trial Consortium an...

## Key facts

- **NIH application ID:** 10898863
- **Project number:** 5K01CA279498-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Rosalyn Wong Sayaman
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $173,620
- **Award type:** 5
- **Project period:** 2023-08-03 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10898863

## Citation

> US National Institutes of Health, RePORTER application 10898863, A systems biology approach to elucidate the biology of immune-associated outcomes in breast cancer (5K01CA279498-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10898863. Licensed CC0.

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