Short-duration preoperative endocrine therapy alters molecular profiles to predict favourable outcome in ER+/HER2+ early breast cancer: a POETIC translational study.

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Embargo End Date

2025-08-31

Authors

Sirvén, MB
López-Knowles, E
Zhu, X
Tovey, H
Kilburn, L
Holcombe, C
Skene, A
Robertson, J
Bliss, JM
Alataki, A
Smith, I
Schuster, EF
Dowsett, M
Cheang, MCU

Document Type

Journal Article

Date

2025-07-01

Date Accepted

2025-02-26

Abstract

BACKGROUND: About 15-20% of breast cancers (BC) overexpress Human Epidermal Growth Factor Receptor 2 (HER2+), and 50% of them are also oestrogen receptor positive (ER+). Patients with ER+/HER2+ BC with a limited response to systemic therapies are at an increased risk of relapse, thus understanding the mechanisms of resistance is crucial. This study investigates the changes in gene signature expression (ΔGSE) within ER+/HER2+ tumours and their intrinsic subtype (IS) in response to peri-operative aromatase inhibitors (POAI). METHODS: We analysed paired pre-treatment (baseline) and on-treatment (2wk) samples from 313 ER+/HER2+ BC from the POETIC trial using the BC360™ codeset. Early biological response to aromatase inhibitors (AI) was assessed by immunohistochemical Ki67 levels. Association of ΔGSE with biological response was evaluated using T-test and time to recurrence (TTR) with multivariable Cox regression models adjusted for clinicopathological variables. FINDINGS: The immunity-related signatures were significantly upregulated, while proliferation, TP53 surrogate mutational status and ER-signalling were downregulated (FDR <0·05) among POAI tumours with low Ki672wk. In the POAI, 79% (59/75) of Luminal B (LumB) at baseline shifted to Luminal A (LumA) at 2wk and LumA2wk was associated with better TTR compared to LumB2wk (HR 0·2; CI 95% 0·06-0·72, p = 0·01). Based on Akaike Information Criterion scores, Ki67 and IS at 2wk provided better fit of the multivariable Cox models over the variables at baseline when predicting TTR. INTERPRETATION: Assessing on-treatment IS after POAI for ER+HER2+ BC can help to identify a group of low-risk patients with LumA2wk with good outcomes on de-escalated treatment and patients that require additional treatments. FUNDING: Cancer Research UK (CRUK/07/015).

Citation

EBioMedicine,

DOI

Source Title

EBioMedicine

Publisher

ELSEVIER

ISSN

2352-3964

eISSN

2352-3964

Collections

Research Team

Clin Trials & Stats Unit

Notes