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Accurate Identification of Tumor Origin Using MicroRNAs is Published by Rosetta Genomics' Scientists.

Rosetta Genomics, Ltd. (Rehovot, Israel), announced that the results of a research study, conducted by its scientists and collaborators and describing the use of microRNAs in accurately identifying tumor origin, have been published in Nature Biotechnology. . The study findings demonstrate microRNAs' significant potential to act as effective biomarkers that may be applied in a diagnostic test designed to identify the primary tumor site in patients with cancer of unknown primary (CUP). Rosetta Genomics is currently developing a technology that will be the basis of a CUP diagnostic tests that will be submitted by a CLIA certified lab in the US in 2008.

"Accurately identifying the origin of a metastasis in CUP patients can be critical for determining appropriate treatment, and currently presents a true unmet diagnostic need for patients and physicians," said Amir Avniel, President and CEO of Rosetta Genomics. "This research demonstrates the tremendous potential of microRNAs as effective biomarkers, and is a significant step towards the development of the first microRNA-based diagnostic tests."

Each year approximately 70,000 patients in the United States are diagnosed with CUP. A patient typically is diagnosed with CUP only after undergoing a wide range of tests, including various imaging tests such as x-ray, CT, MRI, and PET, which have failed to identify the origin of the cancer. Accurately identifying the origin of a metastasis can be critical in guiding treatment decisions.

The study results published in Nature Biotechnology describe the development and test validation of microRNA expression profiles for identification of tumor origin. Rosetta Genomics' scientists measured microRNA expression in RNA extracted from hundreds of formalin-fixed, paraffin-embedded samples from more than 20 different known primary tumor tissues and metastases. These results were used to build a classifier which assigns a primary site to a cancer sample based on the microRNA expression in the sample. The paper demonstrates, based on a blinded test set, that the overall sensitivity of this classifier is approximately 85%, with two-thirds of the samples being classified with high-confidence, reaching accuracy exceeding 90% and specificity of 99%.

"The recognition of our research work by a leading, peer-reviewed journal like Nature Biotechnology is truly exciting," noted Dr. Dalia Cohen, Chief Scientific Officer of Rosetta Genomics. "As a leader in the microRNA field, Rosetta Genomics continues to advance and develop microRNA-based technologies that can potentially be applied in a wide range of diagnostics and therapeutics."

MicroRNAs are recently discovered, naturally occurring, small RNAs that act as master regulators and have the potential to form the basis for a new class of diagnostics and therapeutics. Since many diseases are caused by the abnormal activity of proteins, the ability to selectively regulate protein activity through microRNAs could provide the means to treat a wide range of human diseases. In addition, microRNAs have been shown to have different expression in various pathological conditions. As a result, these differences may provide for a novel diagnostic strategy for many diseases.

Rosetta Genomics is a leader in the field of microRNA. Founded in 2000, the company's integrative research platform combining bioinformatics and state-of-the-art laboratory processes has led to the discovery of hundreds of biologically validated novel human microRNAs . Building on its strong IP position and proprietary platform technologies, Rosetta Genomics is working to develop a full range of microRNA-based diagnostic and therapeutic tools, focusing primarily on cancer and various women's health indications. The company expects that the first microRNA diagnostic tests applying its technology will be launched by CLIA-certified laboratories in the United States in 2008.

Rosetta Genomics, Ltd.

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Publication:BIOTECH Patent News
Date:Mar 1, 2008
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