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Patient Stratification Case Study: Breast Cancer

To demonstrate Selventa’s approach to biomarker discovery for patient stratification, the Selventa Discovery Platform (SDP) was used to stratify breast cancer patients using inferred estrogen receptor (ER) activity strength scores derived from transcriptomic GEO data set GSE5460 (Figure 1). The ER activity strength scores computed by the SDP (and described in the attached poster presentation) for individual patients were compared to the measured presence of ER as detected by immunohistochemical (IHC) staining, which represents a clinically validated diagnostic biomarker for therapeutic decisions regarding treatment with anti-estrogen therapy, such as tamoxifen.  The stratification of breast cancer patients with inferred ER strength scores demonstrated the relevance of the approach to an established clinical diagnostic biomarker for tamoxifen therapy as a proof-of-concept case study (Figure 1).  This approach can be applied to biomarker development with additional therapeutic agents and/or target of interest across multiple disease areas where predictive biomarkers are not available or molecular patient classes are not easily distinguished through gene expression changes alone (e.g., in prostate cancer).

Figure 1.  Patient Stratification by the inferred activity of estrogen receptor (ER) in breast cancer is highly relevant to the established immunohistochemistry ER biomarker.  Each bar represents a single patient and the height of the bar indicates the inferred measure of ER activity for that patient. Activity is scaled from lowest to highest.