Abstract 313P
Background
Breast cancer is a heterogeneous disease with regard to diagnosis, therapy and survival. Complementary to the histopathological classifications of the tumours, molecular biological tests specify individualised therapy recommendations. Our aim was to classify tumours into intrinsic subtypes and to analyse the association of grouping with disease progression.
Methods
Intrinsic subtypes were determined from 1,070 tumours by mRNA expression profiling (PAM50 algorithm) from fresh tumour tissue or FFPE tissue in a prospective, multicenter cohort study (n=1,270; NCT 01592825). mRNA expression evaluation was performed either by nCounter®NanoString or GenChip™ HG U133 Plus 2.0 or BioMark™ Fluidigm. Endpoints were recurrence free interval (RFI) and overall survival (OS). Median follow-up time was 60.3 months. Survival analyses were done by Kaplan-Meier method and Cox model adjusting for age, nodal status, tumour size, and tumour differentiation.
Results
The PAM50 analysis resulted in 44.9% in Luminal A (n=480), 23.9% Luminal B (n=256), 14.4% HER2-enriched (n=154), and 16.8% in Basal-like (n=180). In the total cohort, 89.9% (95% CI 87.9-91.9) of patients were free of RFI event and 87.5% (95% CI 85.3-89.7) were alive at 5 years of observation. Of patients with a Luminal A tumour, 93% were free of RFI event (95% CI 88.1-97.9). The remaining patients had a substantially higher risk of RFI events: Luminal B, HR=3.3 (95% CI 1.78-6.01); HER2-enriched, HR=3.8 (95% CI 2.01-7.21); Basal-like, HR=4.7 (95% CI 2.53-8.7). In the Cox model, only tumour size (HR=2.5) and nodal status (HR=2.2) had a significant additional prognostic impact. Also with regard to OS, PAM50 subtypes, tumour size, and nodal status were the only significant prognostic factors.
Conclusions
Even after guideline-based therapy, the intrinsic subtypes still have prognostic significance. Nearly half the patients can be identified as Luminal A with an excellent course of disease, whilst patients with Luminal B, HER2-enriched, Basal-like still have a substatial risk of recurrence, requiring further improvement of therapy concepts.
Clinical trial identification
NCT01592825 (release date: 16.12.09).
Editorial acknowledgement
Legal entity responsible for the study
M. Vetter and E. Kantelhardt.
Funding
Wilhelm Roux Program of the Medical Faculty, Martin-Luther-University Halle-Wittenberg (grant number: FKZ 25/36) German Federal Ministry of Education and Research (grant number: Med FKZ 031A429).
Disclosure
C. Thomssen: Financial Interests, Personal, Speaker, Consultant, Advisor: Amgen, AstraZeneca, Aurikamed, Daiichi Sankyo, Gilead, Jörg Eickeler, Hexal, Lilly, Medupdate, MSD, Nanostring, Novartis, Onkowiisen, Pfizer, Roche, Seagen, Vifor; Financial Interests, Personal, Financially compensated role: Forum Sanitas; Non-Financial Interests, Personal, Member: AGO Breast Committee, ASCO, DGGG (Germ Soc OB/GYN), DGS (Germ Soc Senology), DKG (Germ Cancer Soc), EORTC PathoBiomarker Group; Non-Financial Interests, Personal, Member of Board of Directors: AGO -B Breast Study Group; Non-Financial Interests, Personal, Officer, representing AGO-B: BIG; Non-Financial Interests, Personal, Invited Speaker: ESO; Non-Financial Interests, Personal, Steering Committee Member: ESMO. All other authors have declared no conflicts of interest.
Resources from the same session
272P - Primary prevention of bone fractures in patients (pts) with hormone receptor (HR)+ early breast cancer (EBC) during adjuvant hormonal therapy (HT): The predict & prevent project (P&P)
Presenter: Stefania Gori
Session: Poster session 02
273P - A preoperative window-of-opportunity (WOO) study of imlunestrant in ER+, HER2- early breast cancer (EBC): Final analysis from EMBER-2
Presenter: Patrick Neven
Session: Poster session 02
274P - Impact of dose reductions on efficacy of adjuvant abemaciclib for patients with high-risk early breast cancer (EBC): Analyses from the monarchE study
Presenter: Joyce O'Shaughnessy
Session: Poster session 02
275P - Clinical and molecular impact of neoadjuvant chemotherapy (NACT) or endocrine therapy (NET) on hormone receptor positive (HR+)/HER2-negative (-) breast cancer (BC)
Presenter: Francesco Schettini
Session: Poster session 02
276P - Development and external validation of an artificial intelligence (AI)-based machine learning model (ML) for predicting pathological complete response (pCR) in hormone-receptor (HoR)-positive/HER2-negative early breast cancer (EBC) undergoing neoadjuvant chemotherapy (NCT)
Presenter: Luca Mastrantoni
Session: Poster session 02
277P - Fat body mass independently predicts incident vertebral fractures in breast cancer patients given adjuvant aromatase inhibitor therapy and denosumab
Presenter: Greta Schivardi
Session: Poster session 02
278P - Association between tamoxifen and endoxifen plasma levels and clotting proteins in patients with primary breast cancer
Presenter: Daan van Dorst
Session: Poster session 02
279P - Early changes in bone turnover biomarkers during AI therapy are related to loss bone mineral density, data of the B-ABLE cohort
Presenter: Tamara Martos Cardenas
Session: Poster session 02
280P - Adjuvant aromatase inhibitors in patients with PIK3CA mutation early breast cancer
Presenter: Kristin Reinhardt
Session: Poster session 02