# Comprehensive profiling of the tumor microenvironment to predict patient response to immunotherapy

> **NIH NIH F99** · STANFORD UNIVERSITY · 2021 · $40,010

## Abstract

Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer,
and there are few available treatment options for patients with this disease. Recently,
immunotherapy has shown promise in a subset of TNBC patients. However, identifying which
patients will benefit from immunotherapy is currently extremely challenging. In order to
understand why certain patients respond to immunotherapy and others do not, we need to
develop a better understanding of the tumor microenvironment (TME). The TME is made up of
cancer cells, as well as the immune and stromal cells which surround them. Previous work has
demonstrated that changes in the relative abundance of certain cell types in the TME can
predict whether patients will respond to treatment. However, we have lacked the tools to
develop a comprehensive understanding of the patterns of interaction between the different
cells in the TME. For the F99 phase of this proposal, I will combine multiplexed imaging with
exome sequencing to comprehensively profile the TME in TNBC patients. I will analyze 100
TNBC patient samples from a clinical trial testing the anti-PD-1 immunotherapy. I will first link
genetic alterations to changes in the localization of cells in the TME, to increase our
understanding of the relationship between cancer genetics and host cell infiltration. I will then
use these relationships to generate biomarkers of response to immunotherapy. For the K00
phase of this proposal, I will develop an organoid model of the TNBC TME. Using this organoid
model, I will determine how the absence of myeloid cells alters the phenotype of the organoid.
I will then use single-cell sequencing to identify the transcriptional changes that myeloid cells
undergo following treatment with anti-PD-1. This fellowship will provide me with the necessary
training in both computational analysis and experimental methods to lead my own group
studying the interaction between the immune system and cancer.

## Key facts

- **NIH application ID:** 10304556
- **Project number:** 1F99CA264307-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** NOAH GREENWALD
- **Activity code:** F99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $40,010
- **Award type:** 1
- **Project period:** 2021-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10304556

## Citation

> US National Institutes of Health, RePORTER application 10304556, Comprehensive profiling of the tumor microenvironment to predict patient response to immunotherapy (1F99CA264307-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10304556. Licensed CC0.

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