Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance

Richard Marcotte, Azin Sayad, Kevin R. Brown, Felix Sanchez-Garcia, Jüri Reimand, Maliha Haider, Carl Virtanen, James E. Bradner, Gary D. Bader, Gordon B. Mills, Dana Pe'Er, Jason Moffat, Benjamin G. Neel

Research output: Contribution to journalArticlepeer-review

218 Scopus citations

Abstract

Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole-genome small hairpin RNA (shRNA) "dropout screens" on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate "drivers," and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer and PIK3CA mutations as a resistance determinant for BET-inhibitors.

Original languageEnglish (US)
Pages (from-to)293-309
Number of pages17
JournalCell
Volume164
Issue number1-2
DOIs
StatePublished - Jan 14 2016
Externally publishedYes

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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