At the annual American Society of Clinical Oncology meeting last June, Bristol-Myers Squibb (BMS) researchers presented data on a cohort of patients not responding to the company’s approved checkpoint inhibitor nivolumab (Opdivo). Layering on a novel immunotherapy antibody was effective in half of patients tested, the team reported, with no major increase in side effects compared to nivolumab alone.1 Each of the therapies aims to unleash an immune cell–fueled tumor attack by targeting a molecule that normally suppresses T-cell activation—programmed death 1 (PD-1) in the case of nivolumab, and lymphocyte-activation gene 3 (LAG-3) in the case of the new, investigational antibody. The combination worked particularly well in patients whose T cells displayed LAG-3 on their surface. “We now have a population that we can sensitize to immunotherapy that was resistant to anti-PD-1 treatment,” says Nils Lonberg, who heads the immune oncology and targeted drug discovery efforts at BMS in Redwood City, CA.
BMS has several newer checkpoint inhibitors, targeting other immune pathways, that trigger T cells to home in on tumors, and company researchers are accumulating data on combining each with nivolumab. “We focus on both innate and acquired immunity pathways to treat more patients with tumors we know can respond to immunotherapy, and also to open up other cancer types to immunotherapy,” says Lonberg. “From basic-science principles, what we look for first in a combination are drugs with nonredundant mechanisms.”
Other companies, including those with their own FDA-approved checkpoint inhibitors, such as AstraZeneca, Merck, and Roche, are taking similar approaches. The US Food and Drug Administration (FDA) approved the first checkpoint inhibitor antibody—ipilimumab (Yervoy), which targets cytotoxic T-lymphocyte antigen 4 (CTLA-4)—for advanced melanoma in 2011. Five other checkpoint inhibitor antibodies followed—six in total—targeting the PD-1 pathway for numerous cancer types. In 2015, the first and thus far only FDA-approved combination of two immunotherapies hit the US market: nivolumab plus ipilimumab for metastatic melanoma patients.
Combining multiple treatments for patients with recalcitrant cancers is not a new concept. Among the first pairings of anticancer drugs were two or more different chemotherapies. As drug companies developed additional types of cancer drugs, combinations of different modalities—including chemotherapy, radiation, targeted small molecules, and eventually immunotherapies—followed. (See illustration below.) “There has long been a feeling that drug combinations will be needed to have the type of impact in cancer patient care that we would like to see,” says David Hyman, a medical oncologist who specializes in early drug development at the Memorial Sloan Kettering Cancer Center in New York City.
But only a handful of cancer drug combos have so far been approved by the FDA, in part because many of the tested combinations were conceived largely at random—an inefficient approach given the dizzying number of approved and investigational therapies that could be combined. In fact, of the hundreds or even thousands of novel combos currently in clinical trials, many, if not most, were designed based on little more than convenience, depending on what drugs a company owns, says Charles Swanton, a cancer geneticist at The Francis Crick Institute in London. “My view is that there are too many trials, especially immunotherapy ones, being conducted in a serendipitous manner,” he says. “It’s more about, ‘We’ve got these two cancer drugs, so let’s put them together and see what happens.’”
Only recently have researchers adopted more-systematic approaches. One method that’s growing in popularity is the use of high-throughput screens that allow researchers to quickly evaluate interactions between different cancer therapies to predict which might form a successful combo. Alternatively or in addition, some researchers are relying on knowledge of the underlying biology to determine which therapies are likely to make the strongest pairings, as is the case for BMS’s checkpoint inhibitor combos. “We have to start from fundamental principles of tumor biology,” says Swanton. “Once we know this information, then we can start to come up with rational combo approaches.”
Ross Camidge, a thoracic oncologist at the University of Colorado Denver, agrees. “Our chances of successful combination therapies are only as good as the science going into the selection of the combinations.”
Casting a wide net
In vitro screening of large numbers of drug combinations is one of the approaches to sort through a vast ocean of drug-pairing possibilities. In silico screening methods typically rely on compiling data generated by in vitro experiments and animal studies, then using the data as a basis for computer algorithms to predict promising interactions. But these methods are labor intensive and in vitro drug combination screening is also expensive, which is why they have not been widely adopted. “There are not many academic labs with the capability to do [large-scale] combination screens, and not many pharmaceutical companies are doing it either, for that matter,” says Marc Ferrer, a researcher at the Chemical Genomics Center within the National Center for Advancing Translational Sciences.
