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A predictive endocrine resistance index accurately stratifies luminal breast cancer treatment responders and non-responders
Guokun Zhang, … , Nadia Harbeck, Hans H. Kreipe
Guokun Zhang, … , Nadia Harbeck, Hans H. Kreipe
Published July 24, 2025
Citation Information: J Clin Invest. 2025. https://doi.org/10.1172/JCI177813.
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Clinical Research and Public Health In-Press Preview Clinical Research Oncology

A predictive endocrine resistance index accurately stratifies luminal breast cancer treatment responders and non-responders

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Abstract

BACKGROUND. Endocrine therapy (ET) with tamoxifen (TAM) or aromatase inhibitors (AI) is highly effective against hormone receptor (HR) positive early breast cancer (BC), but resistance remains a major challenge. The primary objectives of our study were to understand the underlying mechanisms of primary resistance and to identify potential biomarkers. METHODS. We selected >800 patients in three sub-cohorts (Discovery, N=364, matched pairs), Validation 1, N=270, Validation 2, N= 176) of the West German Study Group (WSG) Adjuvant Dynamic marker-Adjusted Personalized Therapy (ADAPT) trial who underwent short-term pre-operative TAM or AI treatment. Treatment response was assessed by immunohistochemical labeling of proliferating cells with Ki67 before and after ET. We performed comprehensive molecular profiling, including targeted next-generation sequencing (NGS) and DNA methylation analysis using EPIC arrays, on post-treatment tumor samples. RESULTS.TP53 mutations were strongly associated with primary resistance to both TAM and AI. In addition, we identified distinct DNA methylation patterns in resistant tumors, suggesting alterations in key signaling pathways and tumor microenvironment composition. Based on these findings and patient age, we developed the Predictive Endocrine ResistanCe Index (PERCI). PERCI accurately stratified responders and non-responders in both treatment groups in all three sub-cohorts and predicted progression-free survival in an external validation cohort and in the combined sub-cohorts. CONCLUSION. Our results highlight the potential of PERCI to guide personalized endocrine therapy and improve patient outcomes. TRIAL REGISTRATION. WSG-ADAPT, ClinicalTrials.gov NCT01779206, Registered 2013-01-25, retrospectively registered.

Authors

Guokun Zhang, Vindi Jurinovic, Stephan Bartels, Matthias Christgen, Henriette Christgen, Leonie Donata Kandt, Lidiya Mishieva, Hua Ni, Mieke Raap, Janin Klein, Anna-Lena Katzke, Winfried Hofmann, Doris Steinemann, Ronald E. Kates, Oleg Gluz, Monika Graeser, Sherko Kuemmel, Ulrike Nitz, Christoph Plass, Ulrich Lehmann, Christine zu Eulenburg, Ulrich Mansmann, Clarissa Gerhauser, Nadia Harbeck, Hans H. Kreipe

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