TEST:

Oncotype DX Breast Recurrence Score®Test

P2, N=77, Recruiting, Asan Medical Center

P=N/A, N=80, Recruiting, Maisonneuve-Rosemont Hospital | Phase classification: P2 --> P=N/A

According to literature, and TailorX trial data, our study confirms the importance of ODX as a tool able to guide therapeutic choices and ensure patients the most appropriate adjuvant treatment.

The Oncotype DX Breast RS result significantly influenced treatment decisions, with 44.3% of patients changing treatment, thus avoiding overtreatment or undertreatment. The Oncotype DX Breast RS test improves patient management and increases physician confidence in treatment recommendations.

Within HR + HER2- breast cancer, HER2-low tumors are associated with high RS, especially for histologically invasive ductal carcinoma. A prognostic influence of HER2-low expression among HR + HER2- breast cancer remains as an area that requires further study.

A cost-effectiveness evaluation comparing the widely used ODX with BCT revealed that BCT is the dominant option in South Korea.

Implementing the Oncotype DX test for women with ER-positive and HER2-negative early breast cancer is of great value. Delayed implementation leads to increased costs, reduced quality of life, and life-years lost.

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We also show that the CLCox model trained with the whole transcriptome significantly outperforms the Cox model trained with the 16 genes of Oncotype DX that is in clinical use for breast cancer patients. The trained models and the Python codes are publicly accessible and provide a valuable resource that will potentially find clinical applications for many types of cancer.

In the high-risk cohort, chemotherapy administration was associated with improved overall survival than those who did not (p = 0.038). Our study highlights the significant role of RS testing in guiding treatment decisions and improving survival outcomes for patients with T3N0 luminal BC.

The multi-model approach achieved an AUC of 0.91 (95% CI: 0.87-0.95) on the internal set and an AUC of 0.84 (95% CI: 0.78-0.89) on the external cohort for predicting low- and high-breast cancer recurrence risk categories based on the Oncotype DX recurrence score. With further validation, the proposed methodology could provide an alternative to assist clinicians in personalizing treatment for breast cancer patients and potentially improving their outcomes.

Examination of our real-world HR+ HER2- "SOUND-eligible" population suggests that nodal disease burden and oncologic outcomes are similar to the SOUND trial population, supporting careful implementation of trial results into multidisciplinary practice. In postmenopausal patients, omission of SLNB does not appear to impact adjuvant chemotherapy recommendations.

These findings highlight the potential of computational pathology as a cost-effective alternative for recurrence risk assessment, broadening access to personalized treatment strategies. This study underscores the clinical utility of integrating deep learning-based computational pathology into routine pathological assessment for breast cancer prognosis across diverse clinical settings.

Between 2011 and 2022, assay use resulted in a 58% reduction in chemotherapy administration and net savings of over €3.3 million.

The efficacy of neoadjuvant treatment with letrozole plus palbociclib does not seem to depend on pretreatment RS for patients with RS ≥18. However, around half of patients with HR-positive/HER2-negative early breast cancer with an RS 26-100 at baseline achieved molecular downstaging with this regimen.

P2; Trial completion date: Aug 2024 --> Aug 2025 | Trial primary completion date: Aug 2024 --> Aug 2025

This study highlights significant differences in gene expression profiles and spatially resolved transcriptional activities between ORS-H and ORS-NH breast carcinomas. The significant up-regulation of genes and pathways associated with cell-mediated immunity, IFN response, and complement C1q in the stromal compartment of the ORS-H group warrants further evaluation with larger population cohorts.

With the evolving landscape of neoadjuvant therapies in development for HR-positive/HER2-negative breast cancer, ongoing work using quantitative biomarkers and genomic assay scores is needed to select the right neoadjuvant systemic therapy for the right patient. Given the increasing amount of data available at the time of breast cancer diagnosis, novel computational approaches are needed to integrate patient demographic and tumor-specific factors to predict the optimal treatment strategy and likelihood of BCS.

This paper reviews evidence for several genomic tests, including Oncotype DX, MammaPrint, Breast Cancer Index, RucurIndex, and EndoPredict, which assist in tailoring adjuvant therapy. Additionally, we explore the role of liquid biopsies in personalizing treatment, emphasizing the importance of considering late relapse risks and potential benefits of extended systemic therapy for HR+/HER2- breast cancer patients.

Our study highlights the possible role of the 21-gene RS in predicting the survival outcomes of PORT following BCS in elderly patients with T1N0 luminal breast cancer.

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The Oncotype DX test substantially improves decision accuracy in recommending adjuvant chemotherapy. It may be further improved with a consensus decision. In the case of pre-RS consensus against chemotherapy, the test can be spared.