# Exploiting replication stress at telomeres in triple negative breast cancer

> **NIH NIH R03** · YALE UNIVERSITY · 2020 · $167,500

## Abstract

Project Summary
Approximately 57,000 American women will succumb to triple negative breast cancer (TNBC) in
2020. While only a subset of all breast cancers, they are highly aggressive and offer the worst
prognosis. Recurrence rate is high, especially in African-American women, and to date no
targeted therapies are available. There is thus an urgent need to develop new treatment options.
Despite large-scale genome sequencing efforts, known breast cancer loci still explain only one-
third of breast cancer risk. It is therefore imperative to identify additional breast cancer
susceptibility genes and elucidate their mechanisms of action to enable the development of
comprehensive cancer risk assessment and targeted therapeutics. We recent discovered that
Claspin, PCNA and DONSON, components of the DNA replication machinery, specifically interact
with the telomere binding protein TRF2 at dysfunctional telomeres in BRCA1 null TNBCs. This
novel discovery provides new insights into mechanisms of how the replisome complex confers a
survival advantage to BRCA1 null TNBCs. Understanding how the replisome protects newly
replicated telomeres in BRCA1 null TNBCs will be highly valuable for the generation of new
therapeutics against this deadly disease.

## Key facts

- **NIH application ID:** 10046540
- **Project number:** 1R03CA252689-01
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Sandy S Chang
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $167,500
- **Award type:** 1
- **Project period:** 2020-07-13 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10046540

## Citation

> US National Institutes of Health, RePORTER application 10046540, Exploiting replication stress at telomeres in triple negative breast cancer (1R03CA252689-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10046540. Licensed CC0.

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