Hi everyone,
I have been donating my unused computer power to the World Community Grid since January 2005 and was delighted to see just now that they are taking on improving the targeting of breast, head and neck cancers to ensure that patients get the chemotherapy that is most likely to help them. I think that the major advances against her2 positive breast cancer show how important matching drugs to patients is.
Joining the World Community Grid doesn't cost anything and using the program is pretty convenient, since the program runs like a screensaver in the background. I haven't had any problems with it.
I don't know if this project will benefit her2 patients necessarily, since progress is being made so quickly against early her2-positive breast cancer, but I think of it as a good way of helping to pay back for all of the scientific work that went into my treatments and helping to find better treatments for groups like triple negative patients, who generally seem to feel that their treatment hasn't been researched enough. There are versions of the program for Windows, Macintosh, and Linux, available through the World Community Grid website. It is possible to set it up so your computer only works on the 'Defeat Cancer' project.
The partners for this project include the Lance Armstrong Foundation, Macmillan Cancer Support (a UK-based charity) and the Irish Cancer Society.
Anyway, here is a description of the project from
http://www.worldcommunitygrid.org/pr...HdcResearch.do
"Tissue Microarrays
A relatively new investigative tool called tissue microarrays (TMA) holds great promise in helping doctors in selecting proper treatment strategies and providing accurate prognosis for cancer patients. Although TMA is not currently being used by doctors to render primary diagnoses, it does make it possible for researchers to determine the specific type and stage of cancer present and systematically investigate which therapies or combinations of treatments are most likely to be effective for each kind of cancer based upon the known outcomes of individual patients. Specific courses of treatment can then be prescribed for actual cancer patients based on whether a specific biomarker is present or not.
Much of the difficulty in rendering consistent evaluation of expression patterns in cancer tissue microarrays arises from subjective impressions of observers. It has been shown that when characterizations are based upon computer-aided analysis, objectivity, reproducibility and sensitivity improve considerably.
Professor David J. Foran's laboratory at
The Cancer Institute of New Jersey, UMDNJ – Robert Wood Johnson Medical School leads a collaborative project with a group of investigators at
Rutgers University and the
University of Pennsylvania School. Together they have developed a web-based, robotic prototype for automatically imaging, analyzing, archiving and sharing digitized tissue microarrays. Utilizing a combination of sophisticated image processing and pattern recognition strategies, the system can automatically analyze and characterize expression patterns in cancer tissue microarrays. Through funding from the
National Institutes of Health, contracts 5R01LM007455-03 from the
National Library of Medicine and 1R01EB003587-01A2 from the
National Institute of Biomedical Imaging and Bioengineering, these researchers have begun analyzing breast cancer and will soon proceed to evaluate protein and molecular expression patterns in head and neck cancers.
Currently, when doctors diagnose patients with cancer, they make determinations about the type of cancer and its stage based upon microscopic evaluation of specimens, through consultations with their peers and by utilizing a host of ancillary tests. The diagnosis that is ultimately rendered will affect how aggressively a patient is treated, which medications might be appropriate, and what levels of risk are justified.
Although TMA is not currently being used by doctors to render primary diagnoses, it does make it possible for researchers to determine the specific type and stage of cancer present and systematically investigate which therapies or combinations of treatments are most likely to be effective for each kind of cancer based upon the known outcomes of individual patients. Specific courses of treatment can then be prescribed for actual cancer patients based on whether a specific biomarker is present or not.
TMA also gives researchers improved understanding of cancer biology and uncovers new sub-classifications of cancer that will then point to new courses of treatment, and allows unparalleled insight into which patient populations are most likely to respond to a given treatment regimen, while also providing information needed for future drug design.
Beyond the impact that TMA's are likely to have in the area of drug discovery and improved therapy planning, they offer several advantages over traditional specimen preparation by maximizing limited tissue resources since such small amounts of a biopsy are used and reducing costs for conducting investigative research.
World Community Grid and Tissue Microarrays
Currently, the primary methods used to evaluate tissue microarrays involve manual, interactive review of samples during which they are subjectively evaluated and scored. An alternate, but less utilized strategy is to sequentially digitize specimens for subsequent semi-quantitative assessment. Both procedures ultimately involve the interactive evaluation of TMA samples, which is a slow, tedious process that is prone to human error. Much of the difficulty in rendering consistent evaluation of expression patterns in cancer tissue microarrays is due to subjective impressions of observers.
IBM's World Community Grid will enable the most computationally expensive components of the software to run at optimal speed, thereby increasing the accuracy and sensitivity with which expression calculations and pattern recognition procedures can be conducted. By harnessing the collective computational power of World Community Grid, researchers will be able to analyze a larger set of cancer tissue specimens and conduct experiments using a much broader ensemble of biomarkers and stains than is possible using traditional computer resources.
To date, only a fraction of the known biomarkers have been examined. The long-term goal is to create a library of biomarkers and their expression patterns so that, in the future, physicians can consult the library to help them in rendering diagnoses and providing the most effective treatment for patients with cancer.
In the absence of World Community Grid, TMA's are processed in individual or small batches. Using World Community Grid, analysis can be carried out for hundreds of arrays in parallel, allowing multiple experiments to be conducted simultaneously. This added level of speed and sophistication could potentially enable investigators to detect and track subtle changes in measurable parameters, thereby facilitating discovery of prognostic clues, which are not apparent by human inspection or traditional analysis alone and could advance the fields of cancer biology, drug discovery and therapy planning."
My team is the 'Cancer Fighters,' although I must admit that I am not into the whole team aspect.
Linear Mode
