US researchers have discovered two genes that appear to work together as master switches to turn on hundreds of other genes that drive the most aggressive forms of brain cancer: they hope their findings will help develop completely new approaches to treat these incurable tumors.
These are the findings of a study published in the 23 December advanced online issue of the journal Nature, that was led by Dr Antonio Iavarone, associate professor of neurology in the Herbert Irving Comprehensive Cancer Center, and Dr Andrea Califano, director of the Columbia Initiative in Systems Biology, both at Columbia University Medical Center, New York, New York.
The research team, which included physicists and biologists, used a new method called systems biology to help them find the genes from a mass of data representing a comprehensive network of trillions of interactions among molecules.
For the study they focused on glioblastoma multiforme, one of the most lethal types of cancer that develops very quickly. This was the cancer that claimed the life of Senator Edward Kennedy on 25 August this year, only 16 months after he was diagnosed.
Glioblastoma rapidly invades the normal brain and quickly forms tumors that are inoperable. Before this discovery cancer researchers had little notion of why brain cancer was so aggressive.
By bringing together ideas from the fields of information theory and computational biology, Iavarone, Califano and colleagues assembled and experimentally validated a cellular network for a glioblastoma cell.
Such an advance is a bit like for the first time being able to observe traffic flows in a large city and pinpoint the main congestion points instead of watching cars as a way to figure out what causes traffic jams.
Iavarone said that:
“Armed with such a blueprint of the cell machinery, we can now ask pointed questions, such as which genes are responsible for the most deadly features of these tumors.”
The researchers found that two genes, C/EPB and Stat3, behaved like “master control knobs”.
“When simultaneously activated, they work together to turn on hundreds of other genes that transform brain cells into highly aggressive, migratory cells,” explained Iavarone.
Not everyone with glioblastoma has both genes active: the researchers found both genes were active in about 60 per cent of patients with this form of cancer, and this helped to identify those with a poor prognosis.
All the patients in the study who had both genes active died within 140 weeks of diagnosis, while half of the patients that did not fall into that category were still alive at that stage.
The finding may open new avenues for combination therapy that targets both genes at the same time. The researchers have already tried this in mice: injecting them with drugs that silenced both genes blocked their ability to form tumors.
As Califano explained:
“The finding means that suppressing both genes simultaneously, using a combination of drugs, may be a powerful therapeutic approach for these patients, for whom no satisfactory treatment exists.”
After finding the two genes with the systems biology approach, Iavarone and colleagues confirmed their role by experimenting on brain cancer cells and mice.
Iavarone said that:
“The identification of C/EPB and Stat3 came as a complete surprise to us, since these genes had never been implicated before in brain cancer.”
He said if they had used traditional methods, it would have taken a long time to find these genes: they would probably still be looking for them.
“From a therapeutic perspective, it means we are no longer wasting time developing drugs against minor actors in brain cancer,” he said, adding that:
“We can now attack the major players.”
The new approach has the potential to change not only cancer research but also research into other diseases.
The last decade has seen enormous strides in our knowledge of genes and how they behave thanks to the mass of data that has emerged from the human genome project and new high-throughput technologies that observe how individual genes behave inside cells. But to the team at Columbia, scientists were still engrossed in using this information to simply compare data from cancer cells with data from normal cells as a way to find out which genes are responsible for cancer.
But, as they explained to the press, this was a bit like ” investigating a plane crash and blaming the wing because it has the most damage”. In the new approach it is possible to analyze the network of molecular interactions and trace back from effects to root causes, following the principle of “reverse engineering”, to find the trigger genes.
In fact, the two genes have very subtle effects, and these appear to be very similar in normal cells and cancer cells. It is only when they work together, that the two almost imperceptible effects become massive, like a tiny control switch causing a plane crash, they said.
“The transcriptional network for mesenchymal transformation of brain tumours.”
Maria Stella Carro, Wei Keat Lim, Mariano Javier Alvarez, Robert J. Bollo, Xudong Zhao, Evan Y. Snyder, Erik P. Sulman, Sandrine L. Anne, Fiona Doetsch, Howard Colman, Anna Lasorella, Ken Aldape, Andrea Califano & Antonio Iavarone.
DOI:10.1038/nature08712
Source: Columbia University Medical Center.
Written by: Catharine Paddock, PhD