Traditional clinical trials reflect a traditional way of thinking about cancer. Patients diagnosed with cancer in the same tissue or organ receive the same therapy under the assumption that they share the same disease. But under the microscope, no two cancers are actually the same; tumors differ from patient to patient. A few patients may noticeably improve with treatment, whereas most experience no benefit at all [see “Capturing cancer’s complexity” in PNAS (1)]. As researchers learn more about cancer’s heterogeneity, they’re calling for sharper investigational strategies that match a genetic understanding of the disease. One result has been “basket trials,” a strategy that groups patients not by tumor site, but by genetic signature, in the hope of better identifying the population most likely to benefit from a drug (2).

In hopes of zeroing in on patient populations likely to benefit from a given drug, researchers are attempting a strategy that groups patients primarily by genetic signature rather than tumor site. Image courtesy of Jane Ades (National Human Genome Research Institute, Bethesda).

Chemotherapy typically targets wide swaths of fast-dividing cells. As early as the late 1980s, researchers began developing drugs to target specific molecular culprits that drive a tumor. One of the first of these drugs was trastuzumab (Herceptin), which increases survival for patients with breast cancer whose tumors overexpress a protein called HER2. Approved in 1998, that drug has saved many lives: about a quarter of all breast cancer patients overexpress HER2. A string of drugs has followed, each targeting particular molecules within the tumor’s cells. But testing them has been difficult, as many cancer drugs fail to deliver results in one-size-fits-all studies in people.

In retrospect, that’s not surprising, says oncologist Keith Flaherty, who directs the Termeer Center for Targeted Therapies at the Massachusetts General Hospital Cancer Center. “Most early attempts to develop targeted therapies didn’t have a clear path for being investigated in a biomarker-defined population,” says Flaherty. Those attempts focused on clinical diagnosis and cancer type rather than mutations. It took about a decade, he says, for the field to catch up to the reality that clinicians needed a new strategy.

Group Therapy In the last five years or so, says Flaherty, researchers at major cancer centers and universities have begun to take a different approach. Instead of traditional phase I trials, which assess a drug’s safety, they began to run so-called “phase I/II” trials, which allow for the dose of a targeted drug to be increased in patients who clinicians predicted would respond positively. These sorts of trials helped measure results in a small patient population—such as a subset with a particular mutation—but were often still limited to a single cancer-affected organ or tissue. That phase I/II approach, combined with genetic information about a patient’s tumors, evolved into the idea of putting patients into defined groups, called “baskets.” Flaherty says two new technologies made basket trials possible. First, researchers needed a suite of targeted therapies from which to choose. Second, researchers needed a catalog of mutations that were likely drivers of the disease. With those two pieces in place, Flaherty and other researchers could design new clinical trials around that portfolio, matching the patients and the drugs as quickly as possible. The basket trial is a tool of the age of precision medicine, based on the idea that a targeted drug needs a targeted trial. In a basket trial, researchers group patients primarily according to genetic mutations that may drive their disease, rather than by disease site or histology. [Thus far, researchers have identified about 140 genes that, when mutated, give the cell a small growth advantage (3).] So-called “truncal mutations” in these genes occur in the original cancerous cell and all of its clones. For the most part, targeted drugs target truncal mutations. Patients then receive an experimental therapy that targets molecules associated with those mutations. Basket trials do have limitations: Because tumors are so heterogeneous, actionable mutations may be missed in the biopsy, for example. Nevertheless, the hope is to greatly increase the chances of identifying the patient population most likely to benefit from the drug. Last August, in some of the first published results from a basket trial, researchers from Memorial Sloan Kettering Cancer Center in New York City reported that a drug that targets a mutation in melanoma may also be effective in patients with lung cancer (4). Flaherty, whose work has focused on targeted treatments for melanoma and kidney cancers, says basket trials grew out of a need for more targeted therapies in patient populations that needs them the most. “Once you have 10 or 20 or 30 more investigational agents in the pipeline, it becomes really inefficient to [be] hunting biomarker by biomarker, patient subpopulation by subpopulation, even before you knew if a drug had legs,” he says. “Now it makes more sense for patients to enter the pipeline with some broad genetic characterization.” Researchers need to figure out which patients are mostly likely to benefit from the drugs the Food and Drug Administration (FDA) has approved, ranging from immunotherapies to gene-expression modulators to monoclonal antibodies. Flaherty has an idea of how to do that. He says researchers need to develop preclinical models that indicate which drugs will be effective for which cancer type and which targeted populations. Vemurafenib and dabrafenib, for example, both inhibit a protein called BRAF kinase. These drugs were originally shown to be effective in patients with metastatic melanoma; the FDA went on to approve them both. Now researchers are trying to determine if the drugs may also play a role in the treatment of colorectal cancer patients with the same mutation.