Detecting diseases with no more to work with than a drop of blood

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Detecting diseases with no more to work with than a drop of blood

22-Oct-2004 News-Medical.Net

The dream of monitoring a patient's physical condition through blood

testing has long been realized. But how about detecting diseases in

their very early stages, or evaluating how they are responding to

treatment, with no more to work with than a drop of blood!

That dream is closer to realization than many of us think, according to

several leading experts advocating a new approach known as systems

biology. Writing in the current issue of the journal Science, Institute

for Systems Biology immunologist and technologist Leroy Hood and

California Institute of Technology chemist Jim Heath and their

colleagues explain how a new approach to the way that biological

information is gathered and processed could soon lead to breakthroughs

in the prevention and early treatment of a number of diseases.

The lead author of the Science article is Leroy Hood, a former Caltech

professor and now the founding director of the Institute for Systems

Biology in Seattle. According to Hood, the focus of medicine in the next

few years will shift from treating disease--often after it has already

seriously compromised the patient's health--to preventing it before it

even sets in.

Hood explains that systems biology essentially analyzes a living

organism as if it were an electronic circuit. This approach requires a

gigantic amount of information to be collected and processed, including

the sequence of the organism's genome, and the mRNAs and proteins that

it generates. The object is to understand how all of these molecular

components of the system are interrelated, and then predict how the

mRNAs or proteins, for example, are affected by disturbances such as

genetic mutations, infectious agents, or chemical carcinogens.

Therefore, systems biology should be useful for diseases resulting from

genetics as well as from the environment.

" Patients' individual genome sequences, or at least sections of them,

may be part of their medical files, and routine blood tests will involve

thousands of measurements to test for various diseases and genetic

predispositions to other conditions, " Hood says. " I'll guarantee you

we'll see this predictive medicine in 10 years or so. "

" In this paper, we first describe a predictive model of how a

single-cell yeast organism works, " Heath explains, adding that the model

covers a metabolic process that utilizes copious amounts from data such

as messenger RNA concentrations from all the yeast's 6,000 genes,

protein-DNA interactions, and the like.

" The yeast model taught us many lessons for human disease, " Heath says.

" For example, when yeast is perturbed either genetically or through

exposure to some molecule, the mRNAs and proteins that are generated by

the yeast provide a fingerprint of the perturbation. In addition, many

of those proteins are secreted. The lesson is that a disease, such as a

very early-stage cancer, also triggers specific biological responses in

people. Many of those responses lead to secreted proteins, and so the

blood provides a powerful window for measuring the fingerprint of the

early-stage disease. "

Heath and his colleagues write in the Science article that, with a

sufficient number of measurements, " one can presumably identify distinct

patterns for each of the distinct types of a particular cancer, the

various stages in the progression of each disease type, the partition of

the disease into categories defined by critical therapeutic targets, and

the measurement of how drugs alter the disease patterns. The key is that

the more questions you want answered, the more measurements you need to

make. It is the systems biology approach that defines what needs to be

measured to answer the questions. "

In other words, the systems biology approach should allow therapists to

catch diseases much earlier and treat them much more effectively. " This

allows you to imagine the pathway toward predictive medicine rather than

reactive medicine, which is what we have now, " Heath says.

About 100,000 measurements on yeast were required to construct a

predictive network hypothesis. The authors write that 100,000,000

measurements do not yet enable such a hypothesis to be formulated for a

human disease. In the conclusion of the Science article, the authors

address the technologies that will be needed to fully realize the

systems approach to medicine. Heath emphasizes that most of these

technologies, ranging from microfluidics to nanotechnologies to

molecular-imaging methods, have already been demonstrated, and some are

already having a clinical impact. " It's not just a dream that we'll be

diagnosing multiple diseases, including early stage detection, from a

fingerprick of blood, " Heath says.

" Early-stage versions of these technologies will be demonstrated very

soon. "

http://www.caltech.edu