Functional exploration of copy number alterations in a Drosophila model of triple-negative breast cancer

Author:

Diaz Jennifer E. L.12,Barcessat Vanessa13,Bahamon Christian1,Hecht Chana1,Das Tirtha K.1,Cagan Ross L.14ORCID

Affiliation:

1. Icahn School of Medicine at Mount Sinai 1 Department of Cell, Development, and Regenerative Biology , , New York, NY 10029 , USA

2. Internal Medicine, UCLA David Geffen School of Medicine 2 , CA 90095 , USA

3. Precision Immunology Institute, Icahn School of Medicine at Mount Sinai 3 , New York, NY 10029 , USA

4. School of Cancer Sciences and Wolfson Wohl Cancer Research Centre, University of Glasgow 4 , Glasgow G61 1BD , UK

Abstract

ABSTRACT Accounting for 10-20% of breast cancer cases, triple-negative breast cancer (TNBC) is associated with a disproportionate number of breast cancer deaths. One challenge in studying TNBC is its genomic profile: with the exception of TP53 loss, most breast cancer tumors are characterized by a high number of copy number alterations (CNAs), making modeling the disease in whole animals challenging. We computationally analyzed 186 CNA regions previously identified in breast cancer tumors to rank genes within each region by likelihood of acting as a tumor driver. We then used a Drosophila p53-Myc TNBC model to identify 48 genes as functional drivers. To demonstrate the utility of this functional database, we established six 3-hit models; altering candidate genes led to increased aspects of transformation as well as resistance to the chemotherapeutic drug fluorouracil. Our work provides a functional database of CNA-associated TNBC drivers, and a template for an integrated computational/whole-animal approach to identify functional drivers of transformation and drug resistance within CNAs in other tumor types.

Funder

Mary Kay Ash Foundation.

Publisher

The Company of Biologists

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