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Johns Hopkins Kimmel Cancer Center Researchers Using Big Data to Predict Immunotherapy Responses - 08/08/2018

Johns Hopkins Kimmel Cancer Center Researchers Using Big Data to Predict Immunotherapy Responses

Release Date: August 8, 2018
Cancer Cells
Credit: Johns Hopkins Kimmel Cancer Center

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In the age of Big Data, cancer researchers are discovering new ways to monitor the effectiveness of immunotherapy treatments.

Researchers at the Johns Hopkins Bloomberg~Kimmel Institute for Cancer Immunotherapy developed a new way to use bioinformatics as a gathering tool to determine how a patient’s immune system responds to immunotherapy and recognizes its own tumor.

The study was published by Cancer Immunology Research June 12, 2018.

Senior author Kellie Smith, Ph.D., instructor of oncology at Johns Hopkins Kimmel Cancer Center, hopes enough data can be recovered to allow clinicians to determine the best course of treatment for patients by using a technique called MANAFEST.

“Once people are diagnosed with cancer, we hope to use this procedure to develop the best treatment options for them,” Smith said. “Previously, the technology (for MANAFEST) wasn’t there. In the last few years, the technology has evolved to enable us to come up with the way to analyze the data to help patients.”

Mutation-associated neoantigens (MANAs) are a target of antitumor T-cell immunity. However, there was a need to find out how well T-cells can recognize these MANAs in cancer patients.

The scientists changed how cultures were gathered to improve the accuracy of data for bioinformatics, creating the FEST (Functional Expansion of Specific T-cells) analysis. They said this combined information can be used to create a database to figure out what types of immunotherapy-related responses are associated with clinical benefit, improving the effectiveness of treatment for patients.

The FEST method was adapted specifically to detect a MANA-specific sequence in blood, tumor and normal tissue of patients receiving immunotherapy. Smith said the technique could be used to serve as a predictor of responses to immunotherapy in many types of cancers.

She cautioned this is only the first generation for FEST to be used. The hope is it will lead to a central repository of data that could monitor how well cancer patients mount immune responses to their disease.

In addition to Smith, other investigators for the study included Ludmila Danilova, Valsamo Anagnostou, Justina X. Caushi, John-William Sidhom, Haidan Guo, Hok Yee Chan, Prerna Suri, Ada Tam, Jiajia Zhang, Margueritta El Asmar, Kristen A. Marrone, Jarushka Naidoo, Julie R. Brahmer, Patrick M. Forde, Alexander S. Baras, Leslie Cope, Victor E. Velculescu, Drew M. Pardoll and Franck Housseau.

All authors were funded by The Bloomberg~Kimmel Institute for Cancer Immunotherapy, Bloomberg Philanthropies, and NIH Cancer Center Support Grant P30 CA006973. In addition, Smith and Chan were funded by The Lung Cancer Foundation of America/International Association for the Study of Lung Cancer. Housseau was funded by NIH R01 CA203891-01A1. Smith, Guo, Forde and Brahmer were funded by SU2C/AACR (SU2C-AACR-DT1012). Smith, Sidhom, Zhang, Baras and Pardoll were funded by the Mark Foundation for Cancer Research grant MFCR-MIC-001. Anagnostou was funded by the Eastern Cooperative Oncology Group-American College of Radiology Imaging Network and MacMillan Foundation. Velculescu was funded by U.S. National Institutes of Health grants CA121113, CA180950, the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation and the Commonwealth Foundation.

For the Media

Contacts:

Larry Frum
443-287-2539
lfrum1@jhmi.edu

Amy Mone
410-614-2915
amone@jhmi.edu