A painstakingly constructed network map of yeast’s molecular responses to DNA damage is providing a glimpse into how cells might thwart cancer. Since most cancer is caused by the failure of cells to repair DNA damage due to aging, toxins, radiation, and other exposures, researchers can now turn to this new map to help pinpoint which cancer networks to target for therapeutics.
The map, which documents interactions between genes and regulatory proteins involved in repairing DNA, was prepared by Trey Ideker, assistant professor of bioengineering at the University of California, San Diego (see “Comparative Interactomics”). Ideker’s group exposed yeast cells to a DNA-damaging substance and carefully mapped the ensuing interactions between regulatory proteins and genes.
[For a diagram of the complex reactions of yeast cells to DNA damage, click here.]
The map represents an early success for the young field of interactomics, a branch of systems biology in which researchers attempt to understand cellular processes in all their complexity by examining the networks of interaction between genes, proteins, RNA, and other molecules.
Systems biology “tries to look at the complexity of diseases not in a reductive way, but by encompassing all components to get a comprehensive understanding [of their molecular basis],” says Dan Gallahan, chief of the National Cancer Institute’s Integrative Cancer Biology Program. “Cancer is so complex, and we’ve learned the hard way that we have to have a systems approach.”
Ideker and colleagues at MIT and the Whitehead Institute started with 30 proteins whose activity seemed to be associated with DNA damage response. These proteins were transcription factors – regulatory proteins that can bind to genes and turn them on and off. Ideker used a new protein-analysis technology called ChIP-chip to uncover which genes the transcription factors bound to after being exposed to a mutagen. This analysis turned up more than 5,200 candidate genes.
Most large-scale systems biology studies would stop at this point. But “the problem with these technologies when you’re looking at very many genes is that 50 percent of the time they’re wrong,” says Ideker. “Even when the proteins really bind, that doesn’t mean anything happens,” he says. “It could just be molecules bumping around. One molecule will kiss another and it’s completely inconsequential.” Ideker knew that not all 5,272 genes bound by the transcription factors would go through the transcription process and generate proteins – so he spent four years narrowing the field. His final wiring diagram shows a web of interactions between the proteins and 82 genes (see accompanying illustration).
Ideker’s study confirmed some of what was suspected about DNA damage: for example, that it activates genes not directly involved in DNA repair themselves. More importantly, though, says Gallahan, “by doing this kind of analysis you actually raise questions, you don’t answer them. This proposes a lot of new hypotheses that can be tested.” Gallahan was particularly struck by the involvement of genes that create and break down lipid molecules. The involvement of these pathways “would not have been identified by serendipity. They came forth because of this careful work,” says Gallahan.
Maps like Ideker’s can be used not only to provide new therapeutic targets but also to help researchers understand how drugs already being prescribed actually work. James Collins, professor of biomedical engineering at Boston University, says “drug companies are good at seeing if their drug hits its molecular target,” but, beyond that, they don’t investigate what the drug compound affects. Collins says Ideker is “laying a nice foundation for finding out how drugs interact with cells.”
A better understanding of all the molecular-level effects of drugs would give insights into their side effects and also help researchers understand how drugs might be combined for a double whammy. If two drugs have an effect on two different parts of the DNA repair pathway, for example, they could be given to a cancer patient concurrently.
Ideker says he’s expanding on this work to find out what influences the transcription factors in his map have before they start interacting with DNA. Richard Pelroy, program director in the DNA and Chromosome Aberrations Branch of the NCI’s Division of Cancer Biology, says that what happens after genes are expressed is also an important avenue to explore. Ideker’s approach is based on the regulation of gene expression, he says, “but so much happens after genes are expressed.” Many proteins aren’t active the instant they’re made, but must be modified by other proteins.
The big new idea for making self-driving cars that can go anywhere
The mainstream approach to driverless cars is slow and difficult. These startups think going all-in on AI will get there faster.
Inside Charm Industrial’s big bet on corn stalks for carbon removal
The startup used plant matter and bio-oil to sequester thousands of tons of carbon. The question now is how reliable, scalable, and economical this approach will prove.
The dark secret behind those cute AI-generated animal images
Google Brain has revealed its own image-making AI, called Imagen. But don't expect to see anything that isn't wholesome.
The hype around DeepMind’s new AI model misses what’s actually cool about it
Some worry that the chatter about these tools is doing the whole field a disservice.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.