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Researchers at the Dana-Farber Cancer Institute (Boston) have developed a biomarker that could be broadly useful to test the effectiveness of many different cancer drugs in many different tumor types.

The assay, called Dynamic BH3 Profiling (DBP), is unusual in that it foregoes any sort of molecular analysis of either the tumors or the drugs it tests. Instead, the test predicts whether a tumor will be susceptible to a drug by exposing cancer cells to the drug, and looking for the very earliest signs of apoptosis.

In doing so, beyond its specific use, DBP also represents an alternative, broader view of what sorts of approaches can contribute to precision medicine.

Currently, the term precision medicine and the search for predictive biomarkers are almost synonymous with genomics.

"There has been a nearly monolithic focus on the genome as the source for predictive biomarkers," Anthony Letai told Medical Device Daily's sister publication BioWorld Today. "And that is potentially a big mistake for the precision medicine field. Even though it's not genetics, this is precision medicine."

Letai, who is at the Dana-Farber Cancer Institute, and his colleagues described DBP in detail in the Feb. 26, 2015, issue of Cell.

Genetic studies have led to great scientific advances in the understanding of cancer and, in some cases, clinical progress in treating certain cancers. Targeted drugs such as Xalkori (crizotinib, Pfizer) and Zelboraf (vemurafenib, Roche), the HER2/Neu-targeting drugs and many other targeted therapies are given to patients based on genetic analyses of their tumors.

In the National Cancer Institute's Molecular Analysis for Therapy Choice (MATCH) and Pediatric MATCH trials, which were announced last year, the anatomic origin of the tumor plays no role at all. Patients with rare tumors, and those who have progressed on standard therapies, are assigned to therapies based on next-generation sequencing of their tumors.

But the relationship between a molecular biomarker and a drug's effect remains complex. Neither is a response guaranteed in the presence of a biomarker nor does its absence always mean a drug will not work. Some biomarkers predict a response in some cancer types but not others.

DBP dispenses with genetic matching of tumors to therapies altogether. It makes no assumptions about how or why a given drug, or drug combination, might kill a given type of tumor cell. Neither the cell's genomic profile nor the drug's mechanism of action, in the end, make any difference – and that makes the method extremely broadly applicable.

Letai summed up his team's approach as "let's get back to what really matters here – the drugs and the cancer cells."

The vast majority of targeted cancer drugs and chemotherapies alike ultimately have the same effect on cancer cells: They spur them to commit suicide via apoptosis, or programmed cell death.

Killing itself via apoptosis takes a cell days. But the point of no return comes when its mitochondrial membrane becomes leaky. DBP looks for which drugs are best at setting off that membrane permeabilization in a tumor sample.

Looking for the earliest signs of impending cell death allowed Letai and his colleagues to see relatively quickly which cells were responding to a given drug – long before those cells actually died.

That, in turn, allowed them to test primary tumor cells, which (somewhat ironically) often do not live long enough in culture to test with lengthier protocols.

"A cancer cell may not love growing on plastic, but it can usually manage to do so for 16 hours," which is the time required for DBP profiling.

The assay – which the team used mainly on cell lines, but also on primary tumor cells from biopsies, in the work now reported in Cell – at about 90 percent sensitivity and specificity "probably outperforms any biomarker, genetic or otherwise, being used clinically today" Letai said.

DBP testing takes about 1,000 tumor cells per drug or drug combination that is tested, which means that many biopsies easily deliver enough materials for hundreds or thousands of tests. Letai noted that even for patients whose tumors are harder to biopsy for anatomical reasons, or whose tumors don't contain many actual cells, "if this is a better way, then a much higher priority will be put on giving material to assays like this early in the course of treatment."

DBP testing can contribute to Letai's pithily-stated goal – "more drugs for more people" – in two different ways.

DBP can be used to help make treatment decisions within the current armamentarium of FDA-approved drugs. And the assay can be used in clinical trials, to enrich those trials for patients who will respond to an experimental drug.

"There's all too many trials where response rates are in the 30 percent range," he said. With a good predictive biomarker, those rates might be brought up into the 70% range – a difference that could easily be the difference between failure and success.

Right now, the team is piggybacking onto existing clinical trials to see whether the predictions made by the assay reflect the patient responses that are seen in the trial. The scientists are also working to bring the assay to a point where it is CLIA-approved and can be used as a routine part of patient care at the Dana-Farber.

For DBP to become widespread, though, Letai said he thinks it will need to be licensed and turned into a commercially available test.

"We are definitely interested in licensing the technology," and discussions for such licensing are currently ongoing.

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