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| Cancer Biomarker
Identification Software Tools Earn Certification by Abby Vogel |
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The explosive growth of genomic and proteomic data has ushered in a new era of molecular medicine in which cancer detection, diagnosis and treatment are tailored to each individual’s molecular profile. But this personalized medicine approach requires that researchers discover and link biomarkers – such as genes or proteins – to specific disease behaviors, such as the rate of tumor progression and different responses to treatments.
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Two new software programs that help address that challenge have recently earned silver-level compatibility certification from the National Cancer Institute’s cancer Biomedical Informatics Grid®, also known as caBIG®.
Developed by May Dongmei Wang and her team in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University, the programs – caCORRECT and omniBio-Marker – remove noise and artifacts, and identify and validate biomarkers from microarray data. Funding to develop the programs was provided by the National Institutes of Health – primarily the Emory-Georgia Tech National Cancer Institute Center for Cancer Nanotechnology Excellence (CCNE), the Georgia Cancer Coalition, Microsoft Research and Hewlett-Packard.
“Certification by caBIG means the tools can be easily used by everyone in the cancer community to improve approaches to cancer detection, diagnosis, treatment and prevention,” says Wang, an associate professor in the Coulter Department, a Georgia Cancer Coalition Distinguished Cancer Scholar and director of the CCNE biocomputing and bioinformatics core.
caCORRECT – chip artifact CORRECTion – is a software program that improves the quality of collected microarray data, ultimately leading to improved biomarker selection. Because each microarray chip contains thousands of spots, it is easy for a few spots to become marred due to experimental variations by different laboratory technicians or errors that create scratches, edge effects and bubble effects on the data.
caCORRECT removes the noise and artifacts from the data, while retaining high-quality genes on the array. The software can also effectively recover lost information that has been obscured by artifacts. In collaboration with Andrew N. Young, an associate professor in pathology and laboratory medicine at Emory University’s School of Medicine and clinical laboratory director at Grady Health System, Wang and graduate students Todd Stokes, Martin Ahrens and Richard Moffitt validated the caCORRECT software.
The caBIG-certified omniBioMarker software identifies and validates biomarkers from high-throughput gene expression data. Candidate cancer biomarkers are typically genes expressed at different levels in cancer patients compared to healthy subjects.
omniBioMarker searches these groups of patient data for genes with the highest potential for accurately determining whether a patient has cancer. However, because individual genes are not expressed independently, the software also identifies groups of genes that act in concert. Wang, Young and graduate student John Phan tested the ability of the software to identify biomarkers in clinical renal cancer microarray data.
Since receiving caBIG silver-level compatibility certification for caCORRECT and omniBioMarker, Wang and her team have been working on getting two more software programs certified: Q-IHC and omniVisGrid.
This work was funded by grant numbers R01CA108468, P20GM072069 and U54CA119338 from the National Institutes of Health (NIH). The content is solely the responsibility of the principal investigator and does not necessarily represent the official view of the NIH.
Contact: May Dongmei Wang (404-385-2954); E-mail: (maywang <at> bme.gatech.edu).
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Last updated: November
14, 2009