Abstract P6-07-01: Development of a Prosigna® (PAM50)-based classifier for the selection of advanced triple negative breast cancer (TNBC) patients for treatment with enzalutamide
Authors: P Danaher, L Skewis, A Mashadi-Hossein, N Ram, J Gowen-MacDonald, E Harris, S Ferree, W Buckingham
Journal: Cancer Research (2017)

Abstract Background: Enzalutamide is an orally administered androgen receptor (AR) inhibitor approved by the FDA for use in men with metastatic castrate-resistant prostate cancer. A recent phase II study of enzalutamide in patients with advanced, AR positive, TNBC (NCT01889238) demonstrated significant improvements in both PFS and OS for patients whose tumors exhibited a gene expression (Gx) profile enriched in AR signaling and luminal biology. A PAM50-based signature was developed from the phase 2 study which used next generation RNA sequencing (NGS) to identify patients likely to respond to enzalutamide. We transitioned the test to the NanoString (NS) nCounter® Analysis System using Prosigna reagents to support clinical validation in a phase 3 trial. Here we describe the development and analytical performance of the NanoString Androgen Gene Expression Profiling Assay-1 (NS-AR-01). Methods: The NS-AR-01 algorithm coefficients were calibrated from the Predict AR algorithm by testing FFPE tumor tissue from patients who were pre-screened but not enrolled in the phase II study with both platforms (NGS and NS). Three unique algorithms were developed and subsequently challenged with an independent sample set with NGS data to provide an unbiased evaluation of the concordance of the platforms. A pre-specified clinical accuracy verification study was performed through prediction of NS-AR-01 scores from the NGS Gx data from the patients included in the phase 2 study efficacy analysis. The final NS-AR-01 algorithm was selected based on performance in the clinical accuracy verification. The final NS-AR-01 algorithm was evaluated in the 118 patients included in the ITT analysis, as well as those treated with 0-1 lines of prior therapy. The analytical performance of the assay was characterized by testing precision from RNA, reproducibility from FFPE tissue, sensitivity to RNA input amounts, and the impact of common interferents. Results: All three algorithm translations met the pre-specified clinical accuracy verification acceptance criteria. The final NS-AR-01 algorithm generated a hazard ratio most similar to that observed from the NGS algorithm. The total standard deviation when testing multiple FFPE sections from the same block was &amp;lt; 1.5% of the score range with an empirical concordance rate of 100% for biomarker status. The range of RNA input specified for Prosigna was successfully verified for NS-AR-01 (125ng–500ng total RNA). The assay was demonstrated to be robust to common interferents including non-tumor tissue. Conclusions: Based on these results, NS-AR-01 is an accurate, precise, and robust assay for the identification of advanced TNBC patients who may respond to treatment with enzalutamide. The assay is well suited to clinical applications, and its ability to identify responders to enzalutamide will be evaluated in future investigational studies.Background: Enzalutamide is an orally administered androgen receptor (AR) inhibitor approved by the FDA for use in men with metastatic castrate-resistant prostate cancer. A recent phase II study of enzalutamide in patients with advanced, AR positive, TNBC (NCT01889238) demonstrated significant improvements in both PFS and OS for patients whose tumors exhibited a gene expression (Gx) profile enriched in AR signaling and luminal biology. A PAM50-based signature was developed from the phase 2 study which used next generation RNA sequencing (NGS) to identify patients likely to respond to enzalutamide. We transitioned the test to the NanoString (NS) nCounter® Analysis System using Prosigna reagents to support clinical validation in a phase 3 trial. Here we describe the development and analytical performance of the NanoString Androgen Gene Expression Profiling Assay-1 (NS-AR-01). Methods: The NS-AR-01 algorithm coefficients were calibrated from the Predict AR algorithm by testing FFPE tumor tissue from patients who were pre-screened but not enrolled in the phase II study with both platforms (NGS and NS). Three unique algorithms were developed and subsequently challenged with an independent sample set with NGS data to provide an unbiased evaluation of the concordance of the platforms. A pre-specified clinical accuracy verification study was performed through prediction of NS-AR-01 scores from the NGS Gx data from the patients included in the phase 2 study efficacy analysis. The final NS-AR-01 algorithm was selected based on performance in the clinical accuracy verification. The final NS-AR-01 algorithm was evaluated in the 118 patients included in the ITT analysis, as well as those treated with 0-1 lines of prior therapy. The analytical performance of the assay was characterized by testing precision from RNA, reproducibility from FFPE tissue, sensitivity to RNA input amounts, and the impact of common interferents. Results: All three algorithm translations met the pre-specified clinical accuracy verification acceptance criteria. The final NS-AR-01 algorithm generated a hazard ratio most similar to that observed from the NGS algorithm. The total standard deviation when testing multiple FFPE sections from the same block was &amp;lt; 1.5% of the score range with an empirical concordance rate of 100% for biomarker status. The range of RNA input specified for Prosigna was successfully verified for NS-AR-01 (125ng–500ng total RNA). The assay was demonstrated to be robust to common interferents including non-tumor tissue. Conclusions: Based on these results, NS-AR-01 is an accurate, precise, and robust assay for the identification of advanced TNBC patients who may respond to treatment with enzalutamide. The assay is well suited to clinical applications, and its ability to identify responders to enzalutamide will be evaluated in future investigational studies. Citation Format: Danaher P, Skewis L, Mashadi-Hossein A, Ram N, Gowen-MacDonald J, Harris E, Ferree S, Buckingham W. Development of a Prosigna® (PAM50)-based classifier for the selection of advanced triple negative breast cancer (TNBC) patients for treatment with enzalutamide [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-07-01.