Hutch, UW Scientists Find Elusive Cancers With Adaptive Diagnostic

Xconomy Seattle — 

Doctors often ask themselves, after a leukemia or lymphoma patient gets high-dose chemotherapy, whether they really wiped out every last rugged cancer cell in the patient. That’s always been a difficult question, but now a team of Seattle researchers is showing they might have found a powerful new technology to consistently deliver that answer.

Scientists at the Fred Hutchinson Cancer Research Center, the University of Washington and Seattle-based Adaptive Biotechnologies are reporting they’ve found what could become a more clear and consistent way to spot “minimal residual disease” that doesn’t show up on imaging scans, but can be deadly. Researchers looked at blood samples from 43 leukemia patients who got high-dose chemo, and found that a new DNA sequencing-based technology was able to spot trace amounts of cancer in 22 patients. For comparison, the gold standard flow cytometry method was only sensitive enough to spot residual cancer cells in 12 patients. The detailed findings are being reported in Science Translational Medicine.

More accurate detection of “minimal residual disease” is important to cancer treatment, because it can influence a physician’s decision on whether or not another round of chemotherapy is really necessary for an individual patient. So if the Seattle scientists can go on to reproduce these findings in other cancers, it could open the door to a potentially lucrative new diagnostic line of business for Adaptive Biotechnologies, a company that has already made some headway by marketing its test to scientists.

“We’re excited, we think this is an important step in the right direction,” says Adaptive co-founder Harlan Robins, a computational biologist at the Fred Hutchinson Cancer Research Center and lead author of the study.

Harlan Robins

Researchers sought to get this answer through a new technology based on advances in DNA sequencing. Adaptive Biotechnologies, a Fred Hutch spinoff, was founded on the idea that while the 6 billion letters of DNA that make up a human genome are consistent in almost every cell of the body, the immune system’s B cells and T cells are an exception. In these cells, DNA gets shuffled around in wildly complex combinations, allowing T cells to recognize specific invaders, such as viruses and bacteria that people get exposed to over time, and enabling B cells to produce specific antibodies against those intruders.

Most of the time, those adaptations are what keep us healthy and able to fend off the wily pathogens in the environment. But sometimes those mutations lead to T cells or B cells that divide out of control, leading to leukemia or lymphoma.

To look for those nasty T and B cells, Adaptive has built a new kind of technology platform based on DNA sequencing, which it calls ImmunoSEQ. The company uses San Diego-based Illumina’s high-speed HiSeq DNA sequencing instruments, and it has custom chemical reagents and software that enable researchers to look specifically at DNA sequences of these variable T and B cells, Robins says. Adaptive found demand for this new technology from scientists looking to answer basic immunology questions. But there’s long been interest in extending this technology into a bigger commercial opportunity with diagnostics.

Adaptive is hopeful that today’s findings will help open that door to the diagnostic world. Flow cytometry, a technique that scientists have used for years, looks for certain biomarkers that can be found on the surface of cancer cells. While it’s not as sensitive at detecting rare cancer cells, that’s not its only weakness, Robins says. The technology isn’t easy to standardize from lab to lab, depends a lot on the skill of the technician running the test, and therefore is subject to human error. Adaptive’s bet is that its technology will be more automated, and easier to standardize, largely because it’s one of only a handful of organizations developing this sort of T and B cell genomic technology (San Francisco-based Sequenta is another).

Still, Adaptive has a ways to go before … Next Page »

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