© 2004 National Academies of Science
RNA interference (RNAi) is fast becoming an essential tool for academic and industrial labs searching for genes that promote or inhibit cancer. Munich-based Xantos Biomedicine, for example, once relied on cDNA overexpression, a decades-old approach, to identify novel genes with tumor-suppressor phenotypes. But the small five-year-old company is now supplementing its gain-of-function, high-throughput cDNA technology with loss-of-function RNAi. "I don't see any really stringent advantage of...
SYNTHETIC LETHALITY AND EPISTASIS
In a 2003 study, Marcel Tijsterman and Ronald H.A. Plasterk, scientists at the Center for Biomedical Genetics in Utrecht, the Netherlands, and their colleagues used RNAi to discover which
In a later project, Tijsterman, Plasterk, and colleagues performed synthetic-lethal experiments, wherein two manipulations, neither of which is deadly on its own, are paired to see if the combination is fatal.2 First, the group applied RNAi to a mutant nematode strain that displays increased double-strand DNA breaks; these breaks create the genomic instability characteristic of cancer cells. The goal was to uncover genes essential to repairing such breaks such that their knockdown would kill the worms. A screen of 16,757 genes yielded 32 candidates. To determine whether these genes act downstream of the DNA breaks, the researchers next exposed wild-type
Tijsterman reports that, besides further assaying some of these genes, his lab is testing whether they are mutated in human tumor tissues. He also hypothesizes that in some syndromes, patients have one mutant and one wild-type allele. "So it is the prediction that if you look at blood samples from these patients that they are heterozygous," he says, adding that loss of that heterozygosity could trigger cancer.
The Dutch group's work on double-strand breaks was echoed last year by another
© 2004 Nature Publishing Group
Several high-throughput options exist for applying RNA interference to mammalian cells. First, scientists create plasmids or viral vectors containing either synthetic short-interfering RNAs (siRNAs) or PCR products. In one approach, libraries are pooled and introduced into cells in bulk; an assay then isolates and identifies vectors that have a particular effect on the cells. In another approach, libraries are spotted onto an array, individually transferred to cells, and then assayed. (From A.T. Willingham et al.,
Such analyses are particularly informative "because the genetic networks of double, even triple or quadruple mutations in cancer cells can be very complex," explains Marc Vidal, director of the Dana-Farber Cancer Institute's Center for Cancer Systems Biology in Boston and the paper's last author. His lab is now using RNAi to generate phenotypic profiles. The idea is to knock down many genes, observe the resulting phenotypes, and cluster the genes by how similar those phenotypes are. "What we're pushing very strongly right now is to take such similarity measurements between pairs of genes and overlay that on top of the interactome [protein-interaction] map," Vidal says.
One limitation of
Beachy focuses on the Hedgehog (Hh) pathway, which normally regulates cell differentiation and proliferation but can contribute to endodermally derived human tumors. In a 2003 study, he and colleagues monitored an Hh-responsive luciferase reporter after they exposed
Though major components of the mammalian Hh pathway remain unknown, Beachy cites a problem with using RNAi to identify them. "You can't feed mammalian cells big double-stranded RNA because you induce the interferon response and the cells basically shut down," he observes. "What you have to do is to introduce short RNAs. But that's tricky because you have to figure out which of the many possible short segments of RNA in a particular sequence will work."
Two recent papers illustrate how RNAi can screen for human cancer-related genes. A team headed by Bernards, of the Netherlands Cancer Institute, applied three RNAi molecules for each of the 7,914 genes targeted for suppression; off-target effects were avoided by minimizing homologies among the molecules. The researchers screened modified human fibroblasts for genes encoding components of the p53 tumor suppressor pathway.5
Because inhibiting these genes would give cells a growth advantage, Bernards acknowledges that the study probably did not discover useful targets for cancer drugs. Instead, he regards its findings more as a proof of principle, illustrating how RNAi can yield fresh insights into a pathway that has been intensively examined for 20 years. "In one genetic screen, we put five more genes into that pathway, which is not trivial," he notes. "And right now, this list has grown to well over 20."
Aza-Blanc and colleagues at GNF applied RNAi against 510 human genes to understand another form of protection against cancer: TRAIL, a member of the tumor necrosis factor family, induces apoptosis in various malignant cells but not in normal cells. The GNF project identified genes that make tumor-derived HeLa cells more or less sensitive to TRAIL-induced apoptosis.6 One gene found to be pro-apoptotic, for example, was
Quinn L. Deveraux, an apoptosis specialist at GNF who participated in the study, says that the researchers mapped the genes to portions of the TRAIL pathway "by looking at caspase activation and other cell-death events." In extensive follow-up experiments, Deveraux, Aza-Blanc, and others have demonstrated that knockdown of