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SYSTEMS BIOLOGY Random ResistanceGenetically Identical Cancer Cells Show Different Responses to Drug In certain respects, cells are less like machines and more like people. True, they have lots of components, but they also have lots of personality. For example, when specific groups of people are studied in aggregate (conservatives, liberals, atheists, evangelicals), they appear to be fairly uniform and predictable. But when looked at one person at a time, individuals often break the preconceptions. Same with cells.
From left, Sabrina Spencer, John Albeck and Suzanne Gaudet, members of Peter Sorger’s lab, have found that genetically identical cells can have vastly different reactions to the same cancer drug due to their varying protein levels. Often ignored is the limitation that not every cell in either group behaves in ways that the aggregate indicates. In a group of cells shown to be vulnerable to a particular cancer treatment, perhaps 10 percent resist it while 90 percent succumb. While researchers have offered various explanations for this, few have studied it.
Now a group of scientists in the lab of HMS professor of systems biology Peter Sorger have studied such outlier cells in the context of TRAIL, a highly touted cancer drug now in clinical trials. They have found that vastly disparate reactions occur within genetically homogeneous cell groups. These discrepancies result from protein levels that vary from cell to cell, even among cells that are identical genetic twins. What is more, these protein levels and their subsequent traits can be passed down to daughter cells—a heritability that has nothing to do with genetics. “Genetics are permanently heritable, while these protein levels are
temporarily heritable,” said Sorger. “But this temporary inheritance
can make all the difference in the world when it comes to the effectiveness
of certain medications.” Tracking TRAIL Though TRAIL continues to be a promising drug candidate, its success rate is not 100 percent, and the researchers wanted to figure out why. They took both cancerous and noncancerous cells and exposed them to varying doses of TRAIL. These cell lines were known to be vulnerable to the molecule, but a fraction always managed to survive. The researchers noticed that when this surviving group was isolated and once again exposed to TRAIL, the cells and their immediate progeny continued to remain highly resistant for a short time. An explanation might be that this group had developed some sort of genetic defense. However, when this resistant group was given several days to reproduce, the pattern soon reset to the original: 90 percent died, 10 percent survived. “We knew that there were clearly factors at work here that were not genetic,” said Spencer. “Genetic resistance would remain uniform in subsequent generations. But the factors at work here were clearly more dynamic.” A Layer of Inheritance
As for what actually causes these protein levels to vary among identical cells, the researchers cited a simple explanation: it’s completely random. “For decades biologists have had this notion that cells produce proteins in orderly, uniform ways, like an assembly line, but they don’t,” said Sorger. “Rather, cells produce proteins in fits and starts, and the timing and degree varies from one cell to the next—even cells that are identical in every way. This randomness is something that we’re just beginning to appreciate.” These findings offer an alternative to the cancer stem cell hypothesis. Scientists have posited that certain cancers survive standard treatments because a population of tumor-specific stem cells evades chemotherapy or radiation. This paper, however, suggests that purely through chance, certain cells produce quantities of proteins that fundamentally alter the cell’s response to treatment. Sorger and his group believe that this insight will ultimately make it possible to design anticancer treatments that are more effective than those available today. A movie is available online at http://hms.harvard.edu/public/video/ps041209.mov. Students may contact Peter Sorger at peter_sorger@hms.harvard.edu for more information. Conflict Disclosure: The authors declare no conflicts of interest. Funding Sources: The National Institutes of Health; the content of the work is the responsibility solely of the authors.
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