Fwd: Interesting Article On Likely Course of CLL/ More confusion Re: the clock

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ScienceDaily (Dec. 18, 2008) - Rather than testing for individual marker

genes or proteins, researchers at the University of California, San Diego

(UC San Diego) and the s UCSD Cancer Center have evidence that groups,

or networks, of interactive genes may be more reliable in determining the

likelihood that a form of leukemia is fast-moving or slow-growing.

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One of the problems in deciding on the right therapy for chronic lymphocytic

leukemia (CLL) is that it is difficult to know which type a patient has. One

form progresses slowly, with few symptoms for years. The other form is more

aggressive and dangerous. While tests exist and are commonly used to help

predict which form a patient may have, their usefulness is limited.

Han-Yu Chuang, a Ph.D. candidate in bioinformatics and systems biology

program in the department of bioengineering in the UC San Diego s

School of Engineering, senior author Kipps, M.D., Ph.D., professor of

medicine and deputy director for research at the s UCSD Cancer Center,

and their colleagues analyzed the activity and patterns of gene expression

in cancer cells from 126 patients with aggressive or slow-growing CLL. The

researchers, using complex algorithms, matched these gene activity profiles

with a huge database of 50,000 known protein complexes and signaling

pathways among nearly 10,000 genes/proteins, searching for " subnetworks " of

aggregate gene expression patterns that separated groups of patients. They

found 30 such gene subnetworks that, they say, were better in predicting

whether a disease is aggressive or slow-growing than current techniques

based on gene expression alone.

They presented their results Monday, December 8, 2008 at the annual meeting

of the American Society of Hematology in San Francisco.

" We wanted to integrate the gene expression from the disease and a large

network of human protein interactions to reconstruct the pathways involved

in disease progression, " Chuang explained. " By introducing the relevant

pathway information, we can do a better job in prognosis. " Chuang, co-author

Trey Ideker, Ph.D., professor of bioengineering at UCSD, and their

co-workers have previously shown the potential of this method in predicting

breast cancer metastasis risk.

" When you are analyzing just the gene expression, you are analyzing it in

isolation, " Chuang explained. " Genes act in concert and are functionally

linked together. We have suggested that it makes more sense to analyze the

genes' expression in a more mechanistic view, based on information about

genes acting together in a particular pathway. We are looking for new

markers - no longer individual genes - but a set of co-functional,

interconnected genes, " she said. " We would like to be able to model

treatment-free survival. "

The current work is " proof of principle, " Chuang said. Clinical trials will

be needed to validate whether specific subnetworks of genes can actually

predict disease CLL progression in patients. She thinks that the subnetworks

can be used to provide " small scale biological models of disease

progression, " enabling researchers to better understand the process.

Eventually, she said, a diagnostic chip might be designed to test blood

samples for such genetic subnetworks that indicate the likely course of

disease. The involved biological pathways could be drug targets as well.

The American Cancer Society estimates that, in 2008, there will be about

15,110 new cases of CLL in the United States, with about 4,390 deaths from

the disease.

Rassenti, Ph.D., UCSD, was also a co-author on the study.

Jim Lawson

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