Targeted cancer therapies work by singling out gene mutations that drive tumor growth, then using a drug to block the effects of the mutant gene. But tumors consist of millions of cells that may collectively harbor hundreds of different “driver” mutations. That means therapies for some cancers will have to target more than one mutation at a time to be successful. To help solve the problem, researchers at Oregon Health & Science University devised a way to rapidly screen combinations of drugs to identify pairs of agents most likely to work synergistically against some of the most difficult to treat forms of leukemia.
In a paper published this week in the Proceedings of the National Academy of Sciences, the researchers describe their strategy and report several previously unrecognized drug combinations that they consider high priority for testing in clinical trials for patients with acute myeloid leukemia. AML is the most frequently diagnosed leukemia in adults, and less than a third of newly diagnosed patients survive beyond five years.
“By and large, most single-agent therapies in AML have been failures, despite the fact that many have been tested in the past few decades,” says senior author Jeffrey Tyner, Ph.D., an associate professor of cell, developmental and cancer biology in the OHSU School of Medicine. “What are needed are combination therapies.”
The cancer drug sensitivity assay provides data within four days, making it potentially useful as a tool to support treatment decisions for individual patients.
People with AML typically have more than one driver mutation and their leukemia cell populations are constantly evolving, with multiple lineages of cells competing for dominance. In one study including about 1,500 patients with AML, researchers identified 5,234 driver mutations involving 76 different genes or DNA regions. While one targeted drug may halt the effect of a cancer-associated gene mutation, new mutations can arise quickly to continue driving the progression of AML.
Tyner and colleagues, including first author Stephen Kurtz, Ph.D., a research assistant professor at OHSU, put together a panel of 48 pairs of drugs, with each member of a pair targeting a non-overlapping cellular pathway. The researchers developed several iterations of the panel, using computational modeling and biological reasoning to make predictions about what drugs might work synergistically together. They tried to include as many FDA-approved agents as possible.
Rather than using animal models or immortalized cell lines to test the effectiveness of the drug combinations, the researchers used leukemia cells taken directly from 122 patients with AML, chronic lymphocytic leukemia, and other blood cancers who gave their consent to participate. The use of fresh, primary samples makes the testing platform more indicative of the state of cancer cells in real patients, Tyner says. They designed the test to compare whether two-drug combinations worked better than either drug used alone.
Among the key findings was the revelation that myeloid-derived tumors appear vulnerable to the combination of the drug venetoclax with several of the drugs in the class called kinase inhibitors. The researchers confirmed the capacity of select venetoclax combinations to augment programmed cell death in human AML cell lines. They showed that combinations such as dasatinib, doramapimod, sorafenib, or idelalisib with venetoclax are broadly effective on myeloid-derived tumor samples and may be useful for treatment of AML in particular.
Against chronic lymphocytic leukemia, the researchers showed that the drug ibrutinib and the multikinase inhibitor quizartinib may represent a promising combination treatment. Ibrutinib already is established as an effective single-agent drug for CLL. The new data suggest that adding quizartinib could make it even more effective for patient with CLL.
The researchers say that a key feature of their testing platform is that it provides drug sensitivity data within four days – making it potentially useful as a tool to support treatment decisions. “Targeted drug therapies exist for only a subset of the mutations known to be important in hematologic malignancies,” Kurtz says. “With our method, drug sensitivity patterns determined within days of diagnosis can be integrated with other clinical and genetic features to align interventions for individual patients.”
Validation of the drug combinations will require testing in clinical trials. The researchers are already in discussions with drug companies. “We hope to be testing some of the most promising combinations in trials within the next 6 to 12 months,” Tyner says.
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Funding for this study was provided by The Leukemia & Lymphoma Society. The authors are also funded by the V Foundation for Cancer Research, Gabrielle’s Angel Foundation for Cancer Research, National Cancer Institute, and the Howard Hughes Medical Institute.
Molecularly-targeted drug combinations demonstrate selective effectiveness for myeloid and lymphoid-derived hematologic malignancies by Stephen E. Kurtz, Christopher A. Eide, Andy Kaempf, Vishesh Khanna, Samantha Savage, Angela Rofelty, Isabel English, Hibery Ho, Ravi Pandya, William J. Bolosky, Hoifung Poon, Michael W. Deininger, Robert Collins, Ronan T. Swords, Justin Watts, Daniel A. Pollyea, Bruno C. Medeiros, Elie Traer, Cristina Tognon, Motomi Mori, Brian J. Druker, and Jeffrey W. Tyner. PNAS (August 7, 2017)
Genomic Classification and Prognosis in Acute Myeloid Leukemia by Elli Papaemmanuil and others. NEJM (June 9, 2016)