The research will be published on June 11, 2021, in the journal Science.

In doing so, it also advances diagnostic pathology from uniparameter to multiparameter assays.” This facilitates precision cancer immunotherapy - identifying the unique features of each patient’s cancer to predict who will respond to a given immunotherapy, such as anti-PD-1, and who will not. Leveraging new technology, including instrumentation to image up to 12 markers simultaneously, the AstroPath imaging algorithms provide 1,000 times the information content from a single biopsy than is currently available through routine pathology. “For the last 40 years, pathology analysis of cancer has examined one marker at a time, which provides limited information. “This platform has the potential to transform how oncologists will deliver cancer immunotherapy,” says Drew Pardoll, M.D., Ph.D., director of the Bloomberg~Kimmel Institute for Cancer Immunotherapy. The research team was led by Janis Taube, M.D., M.Sc., professor of dermatology and co-director of the Tumor Microenvironment Laboratory at the Bloomberg~Kimmel Institute, and Alexander Szalay, Ph.D., director of the Institute for Data Intensive Engineering and Science (IDIES) at Johns Hopkins University. The AstroPath platform is also being applied to study in lung cancer and potentially can provide therapeutic guidance for many other cancers.

Only some patients with melanoma respond to anti-PD-1 therapy, and the ability to predict response or resistance is critical to choosing the best treatments for each patient’s cancer, the researchers explain.

Anti-PD-1 drugs block the PD-1 protein and can help the immune system see and kill cancer cells. PD-1 (programmed cell death 1) is a protein found on immune system T cells which, when bound to another protein called PD-L1 (programmed death ligand), helps cancer cells evade attack by the immune system.

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