A collaboration between the Koch Institute and Dana-Farber Precision Medicine Programs has that subtle changes in cell mass can be used as a functional biomarkers of patients’ responses to cancer treatments. The retrospective study, published recently in Cell Reports, shows the diagnostic test based on a “functional precision medicine” approach could match patients to the most effective available therapy and is particularly helpful for cancers and drugs that lack genomic biomarkers.

“The idea behind functional precision medicine is that, for cancer, you could take a patient’s tumor cells, give them the drugs that the patient might get, and predict what would happen, before giving them to the patient,” said Keith Ligon, M.D., Ph.D., director of the Center for Patient Derived Models at Dana-Farber, associate professor at Harvard Medical School, and co-senior author of the study.

Scott Manalis, Ph.D., a senior author of the study and professor in the departments of biological engineering and mechanical engineering, and a member of the Koch Institute for Integrative Cancer Research, said the new ex vivo technique that involves removing tumor cells from patients, treating the cells with a drug, and measuring changes in the cells’ mass, could be applied to a wide variety of cancers and drug treatments.

“Essentially all of the clinically used cancer drugs either directly or indirectly stop the growth of cancer cells,” Manalis said. “That’s why we think measuring mass could offer a universal readout of the effects of a lot of different types of drug mechanisms.”

In the current study, the researchers validated this novel approach by measuring the response to the chemotherapy drug temozolomide in neurosphere models derived from 69 patients with an aggressive form of brain cancer (glioblastoma), with existing matched data on patient survival and genomics.

Every year nearly 13,000 Americans are diagnosed with glioblastoma. Although radio- and chemotherapy extend survival, most patients die within one to two years. “With this disease, you don’t have much time to make adjustments. So, if you take an ineffective drug for six months, that’s pretty significant,” said Lignon. “This kind of assay could help to speed up the learning process for each individual patient and help with decision-making.”

Temozolomide, a drug that arrests cell cycle progression, is only effective in one of two patients with glioblastoma. Methylation of a gene called MGMT is currently used to predict whether patients will respond to the drug, but the marker doesn’t offer reliable predictions for all patients because of other genetic factors.

In the new approach, the team used a technology developed by Manalis’ lab for weighing single cells with extremely high accuracy by flowing them through vibrating microchannels. In earlier studies, the team used the technology to compute changes in the growth rate of individual cancer cells of glioblastoma and lymphoblastic leukemia over time following multiple treatments of a drug. However, a drawback of the initial approach was that the cancer cells needed to remain in the system for several hours, so they could be weighed repeatedly to calculate the growth rate over time.

The current study used a simpler and faster, high-throughput version of this system that measures subtle changes in single-cell mass distributions between drug-treated and untreated cancer cells to predict patient survival. The authors reported, by simply measuring the mass difference between 2,000 live glioblastomas cells before and after temozolomide treatment, that they can accurately predict whether the patient had responded to the drug or not.

Mass measurement is just as accurate as the MGMT methylation marker in predicting a patient’s response to the drug, the authors noted, but it has the added advantage of working in patients in whom the genetic marker doesn’t reveal temozolomide susceptibility.

“Most cancers do not have a genomic marker that can be used at all. What we argue is that this functional approach could work in other situations where you don’t have any option of a genomic marker,” said Manalis.

“Ideally we would test the drug the patient was most likely to get, but we would also test for things that would be the backup plan: first-, second-, and third-line therapies, or different combinations of drugs,” said Ligon, who also serves as chief of neuropathology at the Brigham and Women’s Hospital and a consultant in pathology at Boston Children’s Hospital.

Manalis and Ligon have co-founded a company called Travera, which has licensed this technology. They hope this approach can be used to develop clinically validated lab tests that predict the best treatment option for patients.