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Breast Cancer Index and prediction of benefit from extended endocrine therapy in breast cancer patients treated in the Adjuvant Tamoxifen-To Offer More? (aTTom) trial. ​

Literature Information ​

DOI10.1093/annonc/mdz289
PMID31504126
JournalAnnals of oncology : official journal of the European Society for Medical Oncology
Impact Factor65.4
JCR QuartileQ1
Publication Year2019
Times Cited85
KeywordsBCI, early-stage breast cancer, endocrine benefit, molecular signature, predictive biomarker
Literature TypeClinical Trial, Phase III, Journal Article, Randomized Controlled Trial, Research Support, Non-U.S. Gov't
ISSN0923-7534
Pages1776-1783
Issue30(11)
AuthorsJ M S Bartlett, D C Sgroi, K Treuner, Y Zhang, I Ahmed, T Piper, R Salunga, E F Brachtel, S J Pirrie, C A Schnabel, D W Rea

TL;DR ​

This study evaluates the Breast Cancer Index (BCI) as a predictive biomarker for the benefit of extended endocrine therapy in early-stage hormone receptor-positive breast cancer patients, finding that those with high BCI (H/I) significantly benefited from 10 years of tamoxifen compared to 5 years, while low BCI patients did not. These findings support the use of BCI as a valuable tool for patient selection in extended therapy, thus enhancing personalized treatment strategies and potentially improving outcomes.

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BCI · early-stage breast cancer · endocrine benefit · molecular signature · predictive biomarker

Abstract ​

BACKGROUND Extending the duration of adjuvant endocrine therapy reduces the risk of recurrence in a subset of women with early-stage hormone receptor-positive (HR+) breast cancer. Validated predictive biomarkers of endocrine response could significantly improve patient selection for extended therapy. Breast cancer index (BCI) [HOXB13/IL17BR ratio (H/I)] was evaluated for its ability to predict benefit from extended endocrine therapy in patients previously randomized in the Adjuvant Tamoxifen-To Offer More? (aTTom) trial.

PATIENTS AND METHODS Trans-aTTom is a multi-institutional, prospective-retrospective study in patients with available formalin-fixed paraffin-embedded primary tumor blocks. BCI testing and central determination of estrogen receptor (ER) and progesterone receptor (PR) status by immunohistochemistry were carried out blinded to clinical outcome. Survival endpoints were evaluated using Kaplan-Meier analysis and Cox regression with recurrence-free interval (RFI) as the primary endpoint. Interaction between extended endocrine therapy and BCI (H/I) was assessed using the likelihood ratio test.

RESULTS Of 583 HR+, N+ patients analyzed, 49% classified as BCI (H/I)-High derived a significant benefit from 10 versus 5 years of tamoxifen treatment [hazard ratio (HR): 0.35; 95% confidence interval (CI) 0.15-0.86; 10.2% absolute risk reduction based on RFI, P = 0.027]. BCI (H/I)-low patients showed no significant benefit from extended endocrine therapy (HR: 1.07; 95% CI 0.69-1.65; -0.2% absolute risk reduction; P = 0.768). Continuous BCI (H/I) levels predicted the magnitude of benefit from extended tamoxifen, whereas centralized ER and PR did not. Interaction between extended tamoxifen treatment and BCI (H/I) was statistically significant (P = 0.012), adjusting for clinicopathological factors.

CONCLUSION BCI by high H/I expression was predictive of endocrine response and identified a subset of HR+, N+ patients with significant benefit from 10 versus 5 years of tamoxifen therapy. These data provide further validation, consistent with previous MA.17 data, establishing level 1B evidence for BCI as a predictive biomarker of benefit from extended endocrine therapy.

TRIAL REGISTRATION ISRCTN17222211; NCT00003678.

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Primary Questions Addressed ​

  1. What are the implications of the Breast Cancer Index (BCI) findings for future clinical practice in managing hormone receptor-positive breast cancer?
  2. How might the predictive value of BCI (H/I) influence the decision-making process for extending endocrine therapy in different patient populations?
  3. What other biomarkers could be explored alongside BCI to enhance the prediction of treatment benefits in breast cancer patients?
  4. In what ways could the results of the aTTom trial inform future research on personalized treatment strategies for breast cancer?
  5. How does the interaction between extended tamoxifen treatment and BCI (H/I) compare with other predictive factors in breast cancer therapy?

Key Findings ​

Background and Objectives ​

The study investigates the predictive value of the Breast Cancer Index (BCI), specifically the HOXB13/IL17BR ratio (H/I), in determining the benefit of extended endocrine therapy in early-stage hormone receptor-positive (HR+) breast cancer patients. This research aims to improve patient selection for extended tamoxifen treatment, building on findings from the Adjuvant Tamoxifen—To Offer More? (aTTom) trial.

Main Methods/Materials/Experimental Design ​

The Trans-aTTom study is a multi-institutional, prospective-retrospective analysis of patients from the aTTom trial. The methodology involved:

  1. Patient Selection: Patients with available formalin-fixed paraffin-embedded tumor blocks were included.
  2. BCI Testing: The BCI (H/I) status was determined through gene expression analysis.
  3. Hormone Receptor Status: Centralized immunohistochemistry (IHC) determined estrogen and progesterone receptor status, conducted blind to clinical outcomes.
  4. Statistical Analysis: Kaplan-Meier and Cox regression analyses evaluated recurrence-free intervals (RFI) as the primary endpoint. The interaction between BCI (H/I) and extended tamoxifen treatment was assessed using likelihood ratio tests.
Mermaid diagram

Key Results and Findings ​

  • Out of 583 HR+, node-positive patients analyzed, 49% were classified as BCI (H/I)-High. This group showed a significant benefit from extending tamoxifen treatment from 5 to 10 years, with a hazard ratio (HR) of 0.35 (95% CI: 0.15–0.86) and an absolute risk reduction of 10.2% (P = 0.027).
  • Conversely, BCI (H/I)-Low patients did not benefit from extended therapy, showing no significant difference in recurrence risk (HR: 1.07; 95% CI: 0.69–1.65; P = 0.768).
  • Continuous BCI (H/I) levels were correlated with the magnitude of benefit from extended tamoxifen, demonstrating a significant interaction (P = 0.012) after adjusting for clinicopathological factors.

Main Conclusions/Significance/Innovation ​

The study confirms that BCI (H/I) is a predictive biomarker for endocrine response in HR+ breast cancer patients. High BCI (H/I) expression identifies a subset of patients who derive significant benefit from prolonged tamoxifen therapy, providing strong evidence for the clinical utility of BCI in optimizing treatment decisions.

Limitations and Future Directions ​

  • Limitations: The study primarily focuses on node-positive patients, and ongoing collection of data may enhance the overall cohort analysis. Additionally, it reflects treatment protocols that may not align with current recommendations emphasizing aromatase inhibitors (AIs).
  • Future Directions: Further validation of BCI across diverse patient populations and treatment modalities is essential. Exploration of the BCI's predictive capabilities in premenopausal women and its integration into clinical practice guidelines for personalized treatment strategies is warranted.

Summary Table of Key Findings ​

ParameterBCI (H/I)-HighBCI (H/I)-Low
Significant Benefit from 10y TamoxifenYes (HR: 0.35; P = 0.027)No (HR: 1.07; P = 0.768)
Absolute Risk Reduction10.2%-0.2%
Statistical Significance of InteractionSignificant (P = 0.012)Not applicable

This structured summary encapsulates the study's critical components, emphasizing the significance of BCI as a predictive biomarker in breast cancer treatment.

References ​

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Literatures Citing This Work ​

  1. Update Breast Cancer 2019 Part 4 - Diagnostic and Therapeutic Challenges of New, Personalised Therapies for Patients with Early Breast Cancer. - Florian Schütz;Peter A Fasching;Manfred Welslau;Andreas D Hartkopf;Achim Wöckel;Michael P Lux;Wolfgang Janni;Johannes Ettl;Diana Lüftner;Erik Belleville;Hans-Christian Kolberg;Friedrich Overkamp;Florin-Andrei Taran;Sara Y Brucker;Markus Wallwiener;Hans Tesch;Tanja N Fehm;Andreas Schneeweiss;Volkmar Müller - Geburtshilfe und Frauenheilkunde (2019)
  2. Breast cancer: are long-term and intermittent endocrine therapies equally effective? - Jutta Engel;Gabriele Schubert-Fritschle;Rebecca Emeny;Dieter Hölzel - Journal of cancer research and clinical oncology (2020)
  3. The Clinical Relevance and Function of Krüppel-Like Factor 16 in Breast Cancer. - Soyeon Bang;Junhong Li;Meiqin Zhang;Renjie Cui;Xingwen Wu;Zhaochen Xin;Duan Ma;Jin Zhang;Hongwei Zhang - Cancer management and research (2020)
  4. Endocrine Therapy in Early Breast Cancer. - Katja Krauss;Elmar Stickeler - Breast care (Basel, Switzerland) (2020)
  5. Prognostic and predictive parameters in breast pathology: a pathologist's primer. - Kimberly H Allison - Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc (2021)
  6. Clinical Implications of Serum 25-Hydroxyvitamin D Status after 5-Year Adjuvant Endocrine Therapy for Late Recurrence of Hormone Receptor-positive Breast Cancer. - Seung Taek Lim;Ye Won Jeon;Hongki Gwak;Young Jin Suh - Journal of breast cancer (2020)
  7. Epigenetics in Breast Cancer Therapy-New Strategies and Future Nanomedicine Perspectives. - Verona Buocikova;Ivan Rios-Mondragon;Eleftherios Pilalis;Aristotelis Chatziioannou;Svetlana Miklikova;Michal Mego;Karlis Pajuste;Martins Rucins;Naouale El Yamani;Eleonora Marta Longhin;Arkadij Sobolev;Muriel Freixanet;Victor Puntes;Aiva Plotniece;Maria Dusinska;Mihaela Roxana Cimpan;Alena Gabelova;Bozena Smolkova - Cancers (2020)
  8. The role of capecitabine-based neoadjuvant and adjuvant chemotherapy in early-stage triple-negative breast cancer: a systematic review and meta-analysis. - Xingfa Huo;Jinming Li;Fuxing Zhao;Dengfeng Ren;Raees Ahmad;Xinyue Yuan;Feng Du;Jiuda Zhao - BMC cancer (2021)
  9. Genomic Assays in Node Positive Breast Cancer Patients: A Review. - Maroun Bou Zerdan;Maryam Ibrahim;Clara El Nakib;Rayan Hajjar;Hazem I Assi - Frontiers in oncology (2020)
  10. Advanced Approaches to Breast Cancer Classification and Diagnosis. - M Zubair;S Wang;N Ali - Frontiers in pharmacology (2020)

... (75 more literatures)

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