Abstract 1905: Defining a therapeutic classification of breast cancer by actionable targets

Manuel Salto-Tellez, David P. Boyle, Darragh McArt, Gareth Irwin, Charlotte Charlotte Wilhelm-Benartzi, Tong G. Lloe, Martha Minter, Stephen McQuaid, Paul Mullan, Richard D. Kennedy, Peter Hamilton, D P. Harkin

Research output: Contribution to journalMeeting abstract

Abstract

Breast cancer remains a frequent cause of female cancer death despite the great strides in elucidation of biological subtypes and their reported clinical and prognostic significance. We have defined a general cohort of breast cancers in terms of putative actionable targets, involving growth and proliferative factors, the cell cycle, and apoptotic pathways, both as single biomarkers across a general cohort and within intrinsic molecular subtypes.

We identified 293 patients treated with adjuvant chemotherapy. Additional hormonal therapy and trastuzumab was administered depending on hormonal and HER2 status respectively. We performed immunohistochemistry for ER, PR, HER2, MM1, CK5/6, p53, TOP2A, EGFR, IGF1R, PTEN, p-mTOR and e-cadherin. The cohort was classified into luminal (62%) and non-luminal (38%) tumors as well as luminal A (27%), luminal B HER2 negative (22%) and positive (12%), HER2 enriched (14%) and triple negative (25%). Patients with luminal tumors and co-overexpression of TOP2A or IGF1R loss displayed worse overall survival (p=0.0251 and p=0.0008 respectively). Non-luminal tumors had much greater heterogeneous expression profiles with no individual markers of prognostic significance. Non-luminal tumors were characterised by EGFR and TOP2A overexpression, IGF1R, PTEN and p-mTOR negativity and extreme p53 expression.

Our results indicate that only a minority of intrinsic subtype tumors purely express single novel actionable targets. This lack of pure biomarker expression is particular prevalent in the triple negative subgroup and may allude to the mechanism of targeted therapy inaction and myriad disappointing trial results. Utilising a combinatorial biomarker approach may enhance studies of targeted therapies providing additional information during design and patient selection while also helping decipher negative trial results.
Original languageEnglish
Article number1905
JournalCancer Research
Volume74
Issue number19 (Suppl)
DOIs
Publication statusPublished - 01 Oct 2014
Event105th Annual Meeting of the American-Association-for-Cancer-Research (AACR) - San Diego, United States
Duration: 05 Apr 201409 Apr 2014

Bibliographical note

In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research

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