SAN DIEGO, May 29, 2015 /PRNewswire/ -- Epic Sciences announced today that the company will present single cell sequencing data, from metastatic castrate resistant prostate cancer patients, at the 2015 annual meeting of the American Society for Clinical Oncology. This application expands the investigational utility of Epic Sciences' no cell left behind™ platform to characterize circulating tumor cell (CTC) genomic alterations. The study revealed that late stage patients have heterogeneous clonal CTC populations harboring separate genetic alterations. Furthermore, the data show an association between CTC copy number alterations and phenotypic features, in terms of both cellular morphology and resistance to therapy. The study, titled "Intra-patient genomic heterogeneity of single circulating tumor cells (CTCs) associated to phenotypic CTC heterogeneity in metastatic castrate resistant prostate cancer (mCRPC)," was conducted in collaboration with clinical investigators at Memorial Sloan Kettering Cancer Center.
"The data presented at ASCO underscore the importance of evaluating an individual patient's disease on a cell by cell basis to identify the frequency of specific clonal populations that influence prognosis and sensitivity to different forms of therapy," said Dr. Howard I. Scher, Chief of the Genitourinary Oncology Service at the Sidney Kimmel Center for Urologic and Prostate Cancers at Memorial Sloan Kettering and senior author. "There is a great deal of tumor heterogeneity in late stage cancer and identifying the individual clones and the genetic alterations driving their continued growth may help guide treatment selection and accelerate or better enable drug development."
In the study, 337 CTCs from 17 patients were individually isolated and characterized for cell morphology, molecular and genomic markers. Genetic material from each individual cell was sequenced and analyzed for genome wide copy number variation (CNV). The observed genomic variants correlated with CTC molecular and morphologic features previously associated with therapeutic resistance in subclonal populations.
Within individual patients up to four distinct subclonal populations were detected harboring distinct sets of genomic alterations, many associated with therapeutic resistance. The presence of multiple distinct clonal populations was highly associated to patients with primary resistance to therapy and absent in patients responding to therapy. Further, CNV alterations associated with tumor suppressor loss or oncogene amplification were predominantly observed in resistant patients.
"Successful treatment of cancer depends on understanding the heterogeneity of the patient's tumor burden and the driving genetic alterations behind their disease progression," said Murali Prahalad, Ph.D., president and CEO of Epic Sciences. "Our data show that the disease heterogeneity frequently present in late stage mCRPC patients may contain multiple CTC subtypes driven by multiple, and sometimes rare genetic alterations, which would likely be missed by analytical methods that only look at cell free DNA or other bulk measures of allelic frequency versus those examining single cells."
The study will be presented in Poster #247 (Abstract #11035), Tumor Biology Session on May 31, 8:00 a.m.
About Epic Sciences
Epic Sciences, Inc. is developing novel diagnostics to personalize and advance the treatment and management of cancer. Epic's mission is to enable the rapid and non-invasive detection of genetic and molecular changes in cancer throughout a patient's journey. The company was founded on a powerful platform to identify and characterize rare cells, including circulating tumor cells (CTCs). Epic's no cell left behind™ technology helps match patients to targeted therapies and monitor for drug resistance, so that the best treatment path can be chosen at every clinical decision point. Today, we partner with leading pharmaceutical companies and major cancer centers around the world. Epic's goal is to commercialize our technology to increase the success rate of cancer drugs in clinical trials and improve patient outcomes by providing physicians real-time information to guide treatment choices.
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