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Updated: Jun 23, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Characterisation of HER2-Driven Morphometric Signature in Breast Cancer and Prediction of Risk of Recurrence
N M Atallah1,2, S Makhlouf1,3, M Nabil4
1Translational Medical Science, School of Medicine, The University of Nottingham and Nottingham University Hospitals NHS Trust, Nottingham, UK.
Introduction:
Human epidermal growth factor receptor 2-positive (HER2-positive) breast cancer (BC) is a heterogeneous disease. In this study, we hypothesised that the degree of HER2 oncogenic activity, and hence response to anti-HER2 therapy is translated into a morphological signature that can be of prognostic/predictive value.
Methods:
We developed a HER2-driven signature based on a set of morphometric features identified through digital image analysis and visual assessment in a sizable cohort of BC patients. HER2-enriched molecular sub-type (HER2-E) was used for validation, and pathway enrichment analysis was performed to assess HER2 pathway activity in the signature-positive cases. The predictive utility of this signature was evaluated in post-adjuvant HER2-positive BC patients.
Results:
A total of 57 morphometric features were evaluated; of them, 22 features were significantly associated with HER2 positivity. HER2 IHC score 3+/oestrogen receptor-negative tumours were significantly associated with HER2-related morphometric features compared to other HER2 classes including HER2 IHC 2+ with gene amplification, and they showed the least intra-tumour morphological heterogeneity. Tumours displaying HER2-driven morphometric signature showed the strongest association with PAM50 HER2-E sub-type and were enriched with ERBB signalling pathway compared to signature-negative cases. BC patients with positive HER2 morphometric signature showed prolonged distant metastasis-free survival post-adjuvant anti-HER2 therapy (p = 0.007). The clinico-morphometric prognostic index demonstrated an 87% accuracy in predicting recurrence risk.
Conclusion:
Our findings underscore the strong prognostic and predictive correlation between HER2 histo-morphometric features and response to targeted anti-HER2 therapy.

