Y. Zhang (San Diego, CA, United States of America)

Biotheranostics, Inc.

Author Of 2 Presentations

 On-Demand ePoster Display

7P - An optimized Breast Cancer Index node-positive (BCIN+) prognostic model for late distant recurrence in patients with hormone receptor-positive (HR+) node-positive breast cancer

Abstract

Background

BCI is a gene expression-based assay that reports a prognostic BCI score that significantly predicts risk of overall (10y), early (0-5y), and late (≥5y) distant recurrence (DR) in HR+, node-negative (N0) and node-positive (N1) breast cancer. The BCIN+ prognostic model was trained in the Trans-ATAC cohort, which evaluated primary adjuvant anastrozole versus tamoxifen. The current study optimized the BCIN+ prognostic model for late DR in N+ patients from the arm treated with 7.5 years of endocrine therapy in the translational cohort of the IDEAL trial.

Methods

Patients with 1 to 3 positive nodes (N1) in the 7.5-year endocrine treatment arm of the translational IDEAL cohort were used to examine cut-points for BCIN+ model across the range of 1 to 9 to classify patients into Low- and High-risk groups. Kaplan-Meier analysis was used to calculate the 15-year (post-diagnosis, 10-year post-randomization) late DR free interval (DRFI) as the primary endpoint. The cut-point was selected based on the classification of a low-risk group with <5% 15-year late DRFI. Initial validation of the optimized prognostic model was performed in a single institution retrospective cohort using Cox proportional hazards regression.

Results

241 N1 IDEAL patients (85% ≥ 55 y, 54% T1, 52% G2) were included. Evaluation of the BCIN+ prognostic model led to an adjusted cut-point, which classified 44 patients as BCIN+ Low Risk with a 15-year late DRFI of 3.2%, and 197 patients as BCIN+ High Risk with a DRFI of 19.0% (HR: 7.11, 95% CI: 0.97-52.17; p=0.024). Independent validation in a retrospective cohort of 349 patients (64% ≥55 y, 66% T1, 58% G2) showed that the optimized BCIN+ model was significantly prognostic for late DR (HR: 9.25, 95% CI: 1.27-67.45; p=0.007), and classified 66 and 283 patients as BCI Low- and High-risk with 1.6% and 15.2% 15-year late DRFI, respectively.

Conclusions

An optimized BCIN+ prognostic model was determined from patients in the randomized IDEAL trial, which was significantly prognostic for late DR in HR+ N1 patients. Additional studies in randomized N+ cohorts are required for further validation of this BCIN+ model optimized for late DR.

Clinical trial identification

BOOG 2006-05.

Legal entity responsible for the study

Biotheranostics, Inc.

Funding

Biotheranostics Inc.; Leiden University Medical Center Institutional Grant; Novartis.

Disclosure

G-J. Liefers: Advisory/Consultancy, Research grant/Funding (institution): Biotheranostics, Inc. Y. Zhang: Travel/Accommodation/Expenses, Shareholder/Stockholder/Stock options, Licensing/Royalties, Full/Part-time employment: Biotheranostics, Inc. D.C. Sgroi: Advisory/Consultancy: Merrimack Pharmaceuticals; Licensing/Royalties: Biotheranostics, Inc. K. Treuner: Travel/Accommodation/Expenses, Shareholder/Stockholder/Stock options, Licensing/Royalties, Full/Part-time employment: Biotheranostics, Inc. J. Wong: Travel/Accommodation/Expenses, Shareholder/Stockholder/Stock options, Full/Part-time employment: Biotheranostics, Inc. C.A. Schnabel: Leadership role, Travel/Accommodation/Expenses, Shareholder/Stockholder/Stock options, Licensing/Royalties, Full/Part-time employment, Officer/Board of Directors: Biotheranostics, Inc. All other authors have declared no conflicts of interest.

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11P - A Breast Cancer Index (BCI) prognostic model for N0 HR+ breast cancer optimized for late distant recurrence

Abstract

Background

BCI is a gene expression-based assay that reports a prognostic score for risk of overall (10y) and late (≥5y) distant recurrence (DR) in HR+ early-stage breast cancer. The current study optimized the BCI prognostic model for late DR utilizing N0 patients from the translational aTTom (Trans-aTTom) study.

Methods

N0 patients in the 5y tamoxifen arm of the Trans-aTTom cohort were used to examine BCI assay cut-points based on classification of a Low-risk group with >95% 15y (10y post-randomization) late DR free survival (DRFS) as estimated by Kaplan-Meier analysis. Validation was performed in an independent multi-institutional cohort using Cox proportional hazards regression.

Results

697 N0 patients (81% ≥55y, 71% T1, 44% G2) were included. A cut-point was determined with a 15y DRFS of 95.7% and 88.7% in the BCI Low- and -High Risk groups, respectively. At 10y and 20y post-diagnosis, patients were stratified as BCI-Low Risk (45%) with a DRFS of 98.0% and 92.9%, and as BCI-High Risk (55%) with a DRFS of 94.3% and 86.4% (HR: 2.16, [1.23-3.80]; p=0.006), respectively. Independent validation in 312 patients (47% <55y, 67% T1, 62% grade 2) showed that the optimized BCI model was significantly prognostic for late DR (HR: 2.16, p=0.006), stratifying BCI Low- (45%) and High-risk (55%) patients with 96.7% and 87.9% 10-year late DRFS, respectively.

Cohorts BCI Risk Groups 10y late DRFS (95% CI) 15y late DRFS (95% CI) 20y late DRFS (95% CI)
Trans-aTTom (n=697) BCI-Low 98.0% (96.4-99.6%) 95.7% (93.3-98.1%) 92.9% (89.3-96.8%)
    BCI-High 94.3% (91.9-96.7%) 88.7% (85.3-92.2%) 86.4% (82.6-90.4%)
Multi-institutional (n=312) BCI-Low 96.7% (93.6-99.9%)
    BCI-High 87.9% (82.8-93.3%)

Conclusions

In the current study, an optimized BCI prognostic model developed in the Trans-aTTom cohort was significantly prognostic for late DR in HR+ N0 breast cancer. Additional studies in cohorts with extended follow-up are required for further validation of this BCI late DR model.

Clinical trial identification

ISRCTN17222211; NCT00003678.

Legal entity responsible for the study

Biotheranostics, Inc.

Funding

Biotheranostics, Inc.; Breast Cancer Research Foundation; Ontario Institute for Cancer Research.

Disclosure

J.M.S. Bartlett: Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Biotheranostics, Inc.; Honoraria (self), Research grant/Funding (institution), Travel/Accommodation/Expenses: NanoString Technologies; Honoraria (self): Oncology Education; Advisory/Consultancy: BioNTech AG; Advisory/Consultancy: Insight Genetics; Advisory/Consultancy: OncoXchange; Advisory/Consultancy: Pfizer; Advisory/Consultancy: RNA Diagnostics; Research grant/Funding (institution): Agendia; Research grant/Funding (institution): Genoptix; Research grant/Funding (institution): Stratifyer GmbH; Research grant/Funding (institution): Thermo Fisher Scientific; Licensing/Royalties, Patent - Jan 2017: Methods and Devices for Predicting Anthracycline Treatment Efficacy: Other; Licensing/Royalties, Patent - Jan 2017: Systems, Devices and Methods for Constructi (Inst): Constructi. Y. Zhang, K. Treuner: Travel/Accommodation/Expenses, Shareholder/Stockholder/Stock options, Licensing/Royalties, Full/Part-time employment: Biotheranostics, Inc. A.M. Brufsky: Advisory/Consultancy: AstraZeneca; Advisory/Consultancy: Pfizer; Advisory/Consultancy: Eli Lilly; Advisory/Consultancy: Novartis; Advisory/Consultancy: Roche; Advisory/Consultancy: Daiichi Sankyo; Advisory/Consultancy: Myriad; Advisory/Consultancy: Agendia; Advisory/Consultancy: Biotheranostics, Inc. D.C. Sgroi: Advisory/Consultancy: Merrimack Pharmaceuticals; Licensing/Royalties: Biotheranostics, Inc. C.A. Schnabel: Leadership role, Travel/Accommodation/Expenses, Shareholder/Stockholder/Stock options, Licensing/Royalties, Full/Part-time employment, Officer/Board of Directors: Biotheranostics, Inc. D.W. Rea: Honoraria (self), Travel/Accommodation/Expenses: Daiichi Sankyo; Honoraria (self): Eli Lilly; Honoraria (self), Travel/Accommodation/Expenses: Novartis; Honoraria (self), Travel/Accommodation/Expenses: Pfizer; Honoraria (self), Research grant/Funding (institution): Roche; Advisory/Consultancy: Genomic Health; Advisory/Consultancy: MSD Oncology; Research grant/Funding (institution): Biotheranostics, Inc.; Research grant/Funding (institution): Celgene; Travel/Accommodation/Expenses: Eisai. All other authors have declared no conflicts of interest.

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