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3:34 PM
 | 
Jan 25, 2018
 |  BC Innovations  |  Targets & Mechanisms

Unexpected combinations

How two studies could change thinking on cancer combo strategies

Editor's Note: This article was updated on Jan 26, 2018 at 2:24 PM PST

Two studies are prompting a rethink of how combination therapies target cancer at both the level of individual cells, and across a patient population. The papers are pushing drug developers to parse data from preclinical and clinical combo studies with a new perspective, and could lead to new strategies for pairing compounds.

The rise of next-generation sequencing and other technologies has provided a wealth of molecular information about variability in cancer. But analyses of those data have not yet translated into a step change in drug development strategy, according to Daniel Peeper, an author on one of the studies and head of the Division of Molecular Oncology at the Netherlands Cancer Institute.

“We know that many drug resistant tumors are highly heterogeneous. But we have not come to the point where we use that information to combat those tumors more effectively,” Peeper told BioCentury.

At a cellular level, drug combinations are often designed to act on multiple pathways in the same cell to block growth or cause cell death.

But a publication this month in Nature Medicine from Peeper’s group showed that, rather than acting within the same cell, two compounds targeting different kinases acted cooperatively by killing different populations of cells in the same tumor.

“We observe that distinct populations each have their own therapy response profile. That is another layer of personalized medicine,” said Peeper.

At the patient level, the hope has been that combinations will have a more potent effect on hard-to-treat tumors by producing synergistic or additive efficacy within individuals. However, that idea was challenged by an analysis published in Cell in December that concluded many cancer combos increase patient survival by giving a larger proportion of patients the opportunity to get the right monotherapy. The study was produced by Harvard Medical School researchers Adam Palmer and Peter Sorger, who are research fellow and director at the school’s Laboratory of Systems Pharmacology, respectively.

Using mathematical models and clinical data, the authors showed many drug combinations were simply able to treat a larger fraction of a variable patient population than either component alone, without increasing efficacy in individual patients.

The number of combination trials in cancer has ballooned in the last decade on the premise that patients who don’t respond to monotherapy will benefit from an additional hit in an intersecting pathway. The new studies make the case that a lot of ground is gained by inducing parallel effects in separate cell and patient populations.

Incyte Corp. EVP and CSO Reid Huber told BioCentury the Cell study generated “heated hallway discussions,” and he thinks it should spur drug developers to re-examine how they assess a combination’s potential for synergy.

“The authors make a fairly convincing statistical argument that in a majority of clinical trials to date, you’re giving patients two chances rather than one chance for a drug to work. That’s a very contrarian concept to where the field is going,” said Huber.

“We observe that distinct populations each have their own therapy response profile. That is another layer of personalized medicine.”

Daniel Peeper, Netherlands Cancer Institute

Cooperating with AXL

Peeper’s study described an example of a combination therapy that had cooperative activity in different cell populations within patient-derived xenografts (PDXs) -- mouse models that can recapitulate patients’ tumor variability.

Previously, his group had shown melanomas resistant to inhibitors of MAP kinase pathway proteins, such as BRAF or MEK, expressed high levels of the receptor tyrosine kinase AXL. “By coincidence, we got...

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