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Tumor models help predict response to immune checkpoint blockade

Dana-Farber Cancer Institute Mar 22, 2017

Although checkpoint–blocking immunotherapy drugs can have dramatic benefits in some cancer patients, they often don’t work at all, and there is a need for better methods of predicting who will respond to the expensive drugs.

Scientists at Dana–Farber have developed a laboratory model system for measuring the response to drugs that block the PD–1 checkpoint, which is a target of the most potent immunotherapy agents in use currently – drugs like nivolumab and pembrolizumab.

Led by David Barbie, MD, and Kwok–Kin Wong, MD, PhD, the investigators sought to create miniature three–dimensional clusters, called spheroids, containing tumor cells as well as immune cells that surround and attempt to invade tumors to destroy them. Using both mouse and human tumor cells, they constructed tumor spheroids in the laboratory within a three–dimensional microfluidic system to which drugs and antibodies could be introduced. In addition, they studied mouse cancer models that did or did not respond to PD–1 checkpoint blockade, to determine what changes to look for in the tumor spheroids when they were exposed to the drugs. Using these results, the scientists analyzed the immune response to PD–1–inhibiting drugs in a large number of tumor spheroids made using samples from patients. They discovered in the laboratory cultured spheroids that induction of cytokines that recruit immune suppressive cells correlated with a lack of response in the patients to PD–1 blocking drugs. They further demonstrated the potential to this system to identify combination therapies with PD–1 blockade that could block these factors and reactivate the immune system in resistant tumors.

“Together, these data demonstrate the ability to profile the response to tumor PD–1 blockade ex vivo and unveil a novel strategy to advance precision immuno–oncology,” said Barbie and Wong.

The research will be presented in a poster session at the 2017 American Association for Cancer Research (AACR) Annual Meeting.
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