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Related Experiment Video

Updated: May 26, 2026

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
07:45

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Published on: May 18, 2020

Development and Validation of a Multimodal Clinical, Pathologic, and Genomic Model for Breast Cancer Recurrence.

Ngoc-Kim Nguyen, Anran Li, Sara Kochanny

    Medrxiv : the Preprint Server for Health Sciences
    |May 25, 2026
    PubMed
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    A new AI-powered model integrating digital pathology and genomic testing improves breast cancer recurrence prediction, outperforming existing genomic assays and identifying more patients for personalized therapy.

    Area of Science:

    • Oncology
    • Digital Pathology
    • Genomic Medicine

    Background:

    • Accurate prediction of breast cancer recurrence is crucial for effective treatment planning.
    • Existing clinicogenomic tools have limitations in identifying all patients who may benefit from specific therapies.
    • Whole-slide imaging (WSI) and genomic testing offer complementary prognostic information.

    Purpose of the Study:

    • To develop and validate a multimodal recurrence-risk model integrating digital histopathology (AI-Path), genomic testing (Oncotype DX Recurrence Score), and clinical variables.
    • To assess the performance of the novel PathClinRS model compared to existing methods in predicting distant recurrence-free interval.

    Main Methods:

    • AI-Path, a WSI biomarker, was developed and validated in multiple independent cohorts (CALGB 9344, TAILORx, Chicago, MDX-BRCA).

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    Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
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    Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

    Published on: May 17, 2019

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    Last Updated: May 26, 2026

    Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
    07:45

    Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

    Published on: May 18, 2020

    Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
    07:41

    Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

    Published on: May 17, 2019

  • AI-Path was integrated with Oncotype DX Recurrence Score (RS), tumor size, and nodal status to create the PathClinRS Cox model.
  • Model performance was evaluated using Harrell's concordance index (C-index) and Kaplan-Meier analyses.

    • Main Results:

    • In the TAILORx cohort, AI-Path demonstrated superior prediction of distant recurrence (C-index, 0.682) compared to RS (0.647), particularly for late recurrence.
    • PathClinRS outperformed RSClin in both node-negative and node-positive disease across validation cohorts, showing significantly higher predictive accuracy.
    • PathClinRS identified nearly twice as many high-risk node-negative patients compared to NATALEE eligibility criteria and reclassified a substantial proportion of intermediate-risk patients as low-risk, potentially sparing them unnecessary chemotherapy.

    Conclusions:

    • Digital histopathology provides prognostic information that complements genomic assays.
    • The PathClinRS model offers enhanced personalization of breast cancer therapy beyond current clinicogenomic tools.
    • This multimodal approach has the potential to optimize treatment decisions and improve patient outcomes.