Map making has long been the domain of explorers, cartographers and treasure buriers, but a Stanford cancer researcher has recently gotten into the act.
Garry Nolan, PhD, a professor of microbiology and immunology, has developed a novel method for graphically plotting the data generated by analyzing individual cell characteristics. He uses a customized computer-design program to sort the types and numbers of cells making up individual cancer tumors. The resulting “maps” can identify cancer sub-types and even “family trees” among tumor cells in individual patients, and may one day be used to personalize treatments for cancer and other diseases.
“Our message is that cancers can be organized [and] can be mapped, and we can finally understand which cells a given drug has activity against and map this to the molecular biology of particular cancers,” Nolan said.
Nolan’s cell data is derived using an innovative variation on a common cell-sorting technique called flow cytometry. He has devised a way – which he terms single-cell mass cytometry – to measure dozens of biological parameters, including cell size, DNA content and protein expression in individual cells. Mass cytometry enables a more detailed profile of cells’ molecular makeup and activity than previous technologies.
The potential of Nolan’s work has been recognized. He is the first recipient of the Department of Defense’s Ovarian Cancer Research Program’s Teal Innovator Award, a five-year, $3.2 million grant to advance the understanding and treatment of ovarian cancer. Nolan’s research is also featured in the just-released Fall edition (.pdf) of the Stanford Cancer Institute’s newsletter, SCI News.
Michael Claeys is the senior communications manager for the Stanford Cancer Institute.