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The search for cancer genes is increasingly a matter of molecular "To
Tell the Truth," as scientists seek to distinguish genes actually
involved in the disease from those that are imposters. Powerful
gene-scanning technology often reveals hundreds or thousands of genetic
irregularities in tumor tissue, making it critical for investigators to
winnow out the true culprits.
In a new study in the April 8 issue of the journal Cancer Cell,
researchers at Dana-Farber Cancer Institute and Memorial
Sloan-Kettering Cancer Center describe a new algorithm for ranking
abnormal genes according to their likelihood of contributing to a
cancer. And they show that a gene identified by the algorithm as a
likely restrainer of tumor growth does indeed play that role in a common
type of brain cancer, and is not a mere "bystander" to another
"As the Human Cancer Genome Project begins to map the genetic
alterations in different kinds of cancer, we need to be able to
discriminate between alterations that truly are relevant to the disease
and those that are not," says the paper's senior author, Lynda Chin, MD, of Dana-Farber. "Using a new algorithm developed in collaboration with Cameron Brennan, MD, of Memorial Sloan-Kettering, we were able to identify genes with too many or too few copies in cancer cells."
The algorithm can be used to analyze similar genomic data generated
by The Cancer Genome Atlas pilot project, a federally-led effort to
explore genomic changes involved in human cancer. It is also being
submitted to BioConductor, a collection of open-source computational
tools for free download by researchers.
The Cancer Cell paper describes how
the algorithm was applied to a study of glioblastoma, the most common
form of brain cancer in adults and one of the most difficult
malignancies to treat successfully. Chin and her colleagues performed
high-resolution genomic scans of glioblastoma tumor samples and cell
lines, and the results showed dozens of gene copy alterations, some of
which had already been linked to the disease and some of which had not.
To determine which of these "suspect" alterations were most likely to
contribute to cancer, the researchers ran the results through their new
One of the highest-scoring abnormalities – meaning it had a high
potential to cause rampant cell growth – involved a gene known as p18INK4C. Researchers knew that one of p18INK4C's cousins, a tumor-restraining or – suppressing – gene called p16INK4A, is missing in a majority of glioblastoma cases. p18INK4C itself, however, wasn't previously known to be missing in the disease.
Although the two genes are thought to have similar functions,
investigators suspected the co-disappearance was more than a
coincidence, and that the loss of p18INK4C plays a role in glioblastoma.
Based on the algorithmic analysis, lead author Ruprecht Wiedemeyer,
PhD, a postdoctoral fellow in Chin's lab, went in search of a connection
between p16INK4A and p18INK4C that can explain their joint disappearance. It turns out that the loss
of p16INK4A triggers a shutdown of a "pathway" (a series of
interconnected genes) called RB. That, in turn, causes cell
proliferation and a giant step toward cancer. At that point, p18INK4C steps in as a backup system, pulling the reins on the hectic cell growth permitted by the loss of p16INK4A. If p18INK4C is lost, it's as though the emergency brake on growth is gone.
"We found that p16 and p18 are part of a 'feedback' loop that keeps the growth of normal glial
cells in check," Chin states. "When p16 goes out of commission, p18 is signaled to pick up the slack. We demonstrated that the deletion of both genes is required for glioblastoma to develop."
The feedback loop is the latest evidence that cancer gene pathways
are not as straightforward as scientists once thought them to be. "Just a
few years ago, the view was that pathways were largely linear," Chin
comments. "We're increasingly coming to appreciate, however, that they
operate in concert – that each one has multiple tentacles reaching out
to other pathways and they function collectively as a network. When one
pathway goes out of commission, another may switch on to compensate."
Such knowledge means that effective treatment of cancers cannot rely on
inhibiting single pathways, but must anticipate how the network would
The algorithm was designed as a reliable way of determining which
gene alterations are most likely linked to cancer. It filters data from
gene-array studies through a "three-dimensional" type of analysis. In
chromosome regions with extra or missing DNA – indicating too many or
too few copies of key genes – the algorithm looks at how long the region
is, how wide or "thick" it is, and how frequently it turns up in cancer
The Genome-Topography-Scan algorithm, as it is called, can help
investigators prioritize their search for cancer-related genes, Chin
says, and will be refined and improved as research continues. "By
pointing to genes with a high probability of being involved in cancer,
the technique can speed the process by which new cancer genes are
identified and therapies are developed to counter them," she states.
The study was supported by grants from the National Institutes of
Health, Accelerate Brain Cancer Cure, the Goldhirsh Foundation, and the
Chris Elliot Fund for Glioblastoma Brain Cancer Research.
Additional co-authors of the study are: Timothy Heffernan,
PhD, Yonghong Xiao, PhD, John Mahoney, Alexei Protopopov, PhD, Hongwu
Zheng, PhD, William Hahn, MD, PhD, Gerald Chu, MD, PhD, and Keith Ligon, MD, PhD, of Dana-Farber; Graham Bignell, P. Andrew Futreal, PhD, and Michael Stratton, PhD, of the Wellcome Trust Sanger Institute and the Cancer Genome Project; Frank Furnari, PhD, and Webster Cavenee, PhD, of the University of California at San Diego; Koichi Ichimura, MD, PhD, and V. Peter Collins, MD, of the University of Cambridge, England.
Dana-Farber Cancer Institute (www.dana-farber.org)
is a principal teaching affiliate of the Harvard Medical School and is
among the leading cancer research and care centers in the United States.
It is a founding member of the Dana-Farber/Harvard Cancer Center
(DF/HCC), designated a comprehensive cancer center by the National