National Cancer Institute Awards $3.3 Million 5-Year Academic-Industry Grant to Inspirata and Case Western Reserve University for Breast Cancer Risk Assessment Assay

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The NCI grant will be used to develop and validate a digital pathology image-based predictor to identify which breast cancers will respond to hormone therapy alone thus sparing these patients from the adverse effects of adjuvant chemotherapy commonly given to all such patients today.

Photo of Pathologists Reviewing Digital Pathology Image

Digital Pathology Image Analysis Assays Can be Used to Predict Best Cancer Treatment.

These image-based assays can be used to grade the aggressiveness of an individual’s disease signature, which means that patients with less aggressive cancers can be spared more aggressive treatments like chemotherapy.

Cancer diagnostics and digital pathology workflow solution provider Inspirata, Inc., announced today that an R01 grant application entitled “Computerized Histologic Image Predictor of Cancer Outcome” (CHIP), which was co-authored through an academic-industry partnership it has with Case Western Reserve University (CWRU), has received $3.3 million in funding over the next five years from the National Cancer Institute (NCI). The grant will fund the development of advanced computerized image analysis methods to mine sub-visual image features through the digitization of whole slide images (WSI).

According to Inspirata Founder and Executive Vice President, Dr. Mark Lloyd, “This grant was written and awarded based on the increased need for predictive and prognostic assays that can now be developed through recent advances in digital pathology and computational image analysis methods. These image-based assays can be used to grade the aggressiveness of an individual’s disease signature, which means that patients with less aggressive cancers can be spared more aggressive treatments like chemotherapy.”

Today’s treatment guidelines for women with estrogen receptor positive (ER+) breast cancer is chemotherapy in addition to hormone therapy like Tamoxifen®. In spite of this one-size-fits-all approach, it is widely believed that at least 50 percent of ER+ breast cancer patients actually receive no remission or curative benefit from the chemotherapy portion of their treatment and, in fact, would benefit more from having hormone therapy alone. Being able to accurately and cost-effectively identify this subgroup of women can avoid unnecessary chemotherapy and spare these patients its accompanying negative side effects.

Currently, there is a genetic test developed by Genomic Health, Inc., called OncoType Dx (ODx), which can identify the 50 percent of ER+ breast cancer patients who will not benefit from chemotherapy. However, this test is expensive, costing roughly $4,000/patient; it must be conducted in a specialized facility of which there is only one in the U.S.; it only tests a small region of the tissue so it can miss key information; and it requires 10-14 days to deliver results.

The CHIP assay that Inspirata and CWRU are developing and validating uses a digital image of the patient’s tissue sample and evaluates the entire expanse of the tumor region with image analysis algorithms. These algorithms assess morphological features like texture, shape, and structure of glands and nuclei to ascertain which early-stage ER+ breast cancer patients are candidates for hormone therapy alone and which must receive adjuvant chemotherapy. This process doesn’t destroy the tissue, takes minutes vs. weeks to deliver a result, can be made available globally and would be substantially cheaper than ODx.

“This grant is a major boost for cancer imaging research at CWRU, and it also reflects the fact that we are leading the way in translational research and academic-industry partnerships,” says Principle Investigator Dr. Anant Madabhushi, Professor and Director of the Center of Computational Imaging and Personalized Diagnostics (CCIPD) in the Department of Biomedical Engineering at CWRU. “We are delighted to be partnering with Inspirata to develop image-based risk predictors of aggressiveness in ER+ breast cancers based off of H&E stained pathology images alone.”

Dr. Madabhushi is the founder of CCIPD at CWRU and is currently conducting research on more than 30 projects, including ones sponsored by the Department of Defense, NIH, NSF and the QED. CCIPD is involved in various different aspects of developing, evaluating and applying novel quantitative image analysis, computer vision, signal processing, segmentation, multi-modal co-registration tools, pattern recognition, and machine learning tools for disease diagnosis, prognosis, and theragnosis in the context of breast, prostate, head and neck, and brain tumors as well as epilepsy and carotid plaque. The group also is exploring the utility of these methods in studying correlations of disease markers across multiple scales, modalities, and functionalities—from gene and protein expression to spectroscopy to digital pathology and to multi-parametric MRI.

Additionally, Drs. Michael Feldman (UPenn) and Shridar Ganesan (Rutgers) are co-Principle Investigators on the grant; and Drs. Hannah Gilmore (CWRU), Pingfu Fu (CWRU), John Tomaszewski (SUNY Buffalo), Mark Lloyd (Inspirata) and James Monaco (Inspirata) are co-Investigators.

“Inspirata will use its quality management systems and production software standards to create a pre-commercial companion diagnostic test of the CHIP assay,” says Dr. Lloyd. “Additionally, we will build a complete regulatory pathway for successful translation of the CHIP assay in the U.S. and abroad.”

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