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