Cambridge, Mass.—Researchers of the RNAi Consortium, led by scientists at the Broad Institute, have found a very efficient and cost-effective way to conduct RNA interference-based screens as a way to explore the functional underpinning of cancer cells.
The research, published online in early December in the Proceedings of the National Academy of Sciences, discussed their use of RNAi screening with short hairpin RNAs to explore essential genes in a dozen cancer cell lines.
"What we have done is not so much a new approach in general but a better way to do these kinds of screen," says David Root, a senior author and director of the RNAi platform at the Broad Institute, as well as project leader of The RNAi Consortium. "Anything you might have been able to with RNAi screening before you can do with this method but a lot more time- and cost-effectively so that it costs you less per RNAi reagent or gene or sample. It could be very useful for taking multiple different time points in your screens or different dosage levels."
In addition to exploring 12 different cancer lines, the team also used the screen to find a small number of genes involved in chronic myelogenous leukemia cell response to Novartis' drug Gleevec.
The Cancer Genome Atlas and International Cancer Genome Consortium have worked on structural genetic changes underlying various cancer types, Root notes, but he says the research community and drug development community also need studies on the associated functional changes in these cells.
What the researchers did was apply a pooled screening approach, using the RNAi Consortium's shRNA libraries, which house some 170,000 shRNAs targeting more than 17,000 human genes and thousands more targeting 16,000 mouse genes.
The team also looked at a smaller sub-library with 45,000 shRNAs targeting about 9,500 human genes. They determined which shRNAs were over- and under-represented in surviving cells after a given amount of time and, by examining the genes targeted by these shRNAs, they were able to get a better handle on what influences survival under different conditions in different cell lines.
"Pooled approaches aren't new, but because we able to extract a higher amount of robust data to figure out which genes were necessary in making cancer cells susceptible to therapeutic approaches," Root explains. "This helps give a better idea of what to target so that we can have therapeutics that are more likely to affect only the cancer and not normal tissues. It isn't a foolproof way to avoid unwanted side effects and damage to normal cells, because there are just too many 'normal' tissues to screen along with the cancer drugs. But it is a start." DDN
The research, published online in early December in the Proceedings of the National Academy of Sciences, discussed their use of RNAi screening with short hairpin RNAs to explore essential genes in a dozen cancer cell lines.
"What we have done is not so much a new approach in general but a better way to do these kinds of screen," says David Root, a senior author and director of the RNAi platform at the Broad Institute, as well as project leader of The RNAi Consortium. "Anything you might have been able to with RNAi screening before you can do with this method but a lot more time- and cost-effectively so that it costs you less per RNAi reagent or gene or sample. It could be very useful for taking multiple different time points in your screens or different dosage levels."
In addition to exploring 12 different cancer lines, the team also used the screen to find a small number of genes involved in chronic myelogenous leukemia cell response to Novartis' drug Gleevec.
The Cancer Genome Atlas and International Cancer Genome Consortium have worked on structural genetic changes underlying various cancer types, Root notes, but he says the research community and drug development community also need studies on the associated functional changes in these cells.
What the researchers did was apply a pooled screening approach, using the RNAi Consortium's shRNA libraries, which house some 170,000 shRNAs targeting more than 17,000 human genes and thousands more targeting 16,000 mouse genes.
The team also looked at a smaller sub-library with 45,000 shRNAs targeting about 9,500 human genes. They determined which shRNAs were over- and under-represented in surviving cells after a given amount of time and, by examining the genes targeted by these shRNAs, they were able to get a better handle on what influences survival under different conditions in different cell lines.
"Pooled approaches aren't new, but because we able to extract a higher amount of robust data to figure out which genes were necessary in making cancer cells susceptible to therapeutic approaches," Root explains. "This helps give a better idea of what to target so that we can have therapeutics that are more likely to affect only the cancer and not normal tissues. It isn't a foolproof way to avoid unwanted side effects and damage to normal cells, because there are just too many 'normal' tissues to screen along with the cancer drugs. But it is a start." DDN
