# Telomere dysfunction induced breast cancer pathogenesis

> **NIH NIH R01** · YALE UNIVERSITY · 2020 · $383,156

## Abstract

   
DESCRIPTION (provided by applicant): Triple negative breast cancers (TNBCs) are highly aggressive and often strike young women. This disease is highly heterogeneous, characterized by profound genomic instability. These complex genetic alterations are thought to arise from the stepwise accumulation of mutational changes in favor of tumor progression. Despite genome wide association and recent genome sequencing studies, known breast cancer loci explain only one-third of the cancer risk, thus limiting the identification of many high risk individuals. It isthus imperative to identify additional breast cancer susceptibility genes and elucidate their mechanisms of action to develop comprehensive cancer risk assessment and targeted therapeutics. Our recent discovery that telomere dysfunction is present in a subset of TNBCs leads us to hypothesis that dysfunctional telomeres promote aberrant DNA repair, generating chromosomal fusions and pro-oncogenic genomic rearrangements permissive for breast cancer initiation and progression. We will test this hypothesis using novel mouse models of breast cancer and cutting edge genomic tools, including CRISPR/Cas9 mediated gene editing and RNA sequencing, to detect additional genetic changes needed to promote breast tumorigenesis.

## Key facts

- **NIH application ID:** 9829086
- **Project number:** 5R01CA202816-05
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Sandy S Chang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $383,156
- **Award type:** 5
- **Project period:** 2015-12-10 → 2020-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9829086

## Citation

> US National Institutes of Health, RePORTER application 9829086, Telomere dysfunction induced breast cancer pathogenesis (5R01CA202816-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9829086. Licensed CC0.

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