Resistance to AR Signaling Inhibitors
There are multiple mechanisms driving resistance to FDA approved Androgen Receptor Signaling inhibitors (ARSi), such as Zytiga® (Abiraterone Acetate) and Xtandi® (Enzalutamide). Numerous novel therapeutics are being developed for metastatic castration resistance prostate cancer (mCRPC) to target these specific mechanisms of resistance which may be exploited for the development of therapy selection devices or utilized to demonstrate therapeutic pharmacodynamics and efficacy during the drug development process.
At Epic Sciences, we work with leading academic and government investigators to develop strategies for identifying resistance mechanisms and creating non-invasive tests that aid in the selection and monitoring of patients during clinical trials. These include tests to measure the following:
Constitutively Active AR Signaling
AR C Terminal Loss: Measure of AR N terminal and AR C terminal on single CTCs from mCRPC patients
Additional AR splice variants beyond AR-V7 may also contribute to resistance to AR inhibitors. To identify other mechanisms of ligand binding domain alterations (such as AR-V567es), we developed a single CTC analysis for simultaneous protein expression of the AR N and AR C terminus to pinpoint patients who harbor a C terminus loss (AR ligand binding domain alteration) and would therefore demonstrate resistance to AR inhibition.
AR/PI3K Reciprocal Feedback
AR/PTEN CTC Analysis
AR resistance can occur through reciprocal feedback between PI3K and AR signaling. To measure cooperative AR/PI3K signaling we have developed single CTC phenotype and genotypic tools to assess AR protein expression, AR amplification and PTEN deletions within single CTCs.
CTC Phenotypic Heterogeneity
A subset of mCRPC patients harbor high tumor heterogeneity at any line of therapy, in which multiple drivers of disease are present. This could potentially thwart a narrow, targeted therapeutic approach.
To assess this phenomenon, high resolution digital pathology was used to identify patients with a high degree of phenotypic heterogeneity in their circulating tumor cells. In a 221 sample cohort presented at ASCO GU 2016, patients with high phenotypic CTC phenotypic heterogeneity demonstrated worse overall survival rates on AR signaling inhibitors than patients with low phenotypic heterogeneity (HR = 5.5, p < 0.00001). Multivariate analyses revealed a 68% reduction of risk of death on taxane therapy for patients with high phenotypic heterogeneity.
Neuroendocrine Prostate Cancer (NEPC) CTC Classifier
CTCs from patients with NEPC determined through metastatic biopsy that confirmes Small Cell Prostate Cancer Pathology or NE expressing tumor cells have a unique morphologic phenotype. While analysis of this cell type is specific to NEPC patients, ~10% of mCRPC patients have sub-clonal populations of NEPC CTCs. These patients demonstrate a worse response to AR inhibitors and are more likely to harbor visceral metastases.
Cell Type-K Classifier
The presence of a single specific CTC phenotype (Cell Type K, shown left) was found to be predictive of resistance to both AR Tx and taxane chemotherapy. The KM curves below show the overall survival rate of patients with a prevalence of this CTC phenotype after they are given either standard of care drugs, AR Tx (HR=6.4) or taxane chemotherapy (HR=5.2).
Every time Epic’s AR-V7 test is administered the healthcare system saves about $15,000 per year of life extended. In other words approximately $7,000 to $9,000 per patient tested.
Of the roughly 30 million cells in a typical blood sample, about 5 are cancer cells on their way to form tumors elsewhere in the body. Modern cancer diagnostics technology can't see them.
We spend about $100 billion a year on cancer drugs. But because we’re not matching the right drug to the right patient and their disease in a personalized way, about 3/4ths of that drug spend is wasted.
The Epic approach answers a critical question for a doctor: When is a patient resistant? By answering that question accurately and precisely we increase patient life and save the system money at the same time.
Today, Epic Sciences is embedded in clinical trials with 48 leading producers of oncology drugs and 35 of the top academic cancer hospitals.
It takes only 7 minutes to acquire an entire image of 6 million stained cells on a 1 x 3 slide. Then that image, which is about 20GB of data, gets sent up to the cloud where the algorithms run and find the rare events in about 2 more minutes.