Feature Articles: Sep 15, 2010 (Vol. 30, No. 16)

Finding Promising Protein Biomarkers

Discovery Aided by Availability of Large Patient Databases and Robust Data-Mining Practices

(Page 1 of 3)

    There is an urgent need for robust biomarkers in clinical and companion diagnostics. As a result, there is tremendous interest in improving the processes by which protein biomarkers are identified and validated. Researchers gathered at CHI’s “Next Generation Diagnostics Summit” last month in Washington, D.C., to discuss, among other things, the need for larger databases of patient samples with clinical outcomes and smarter bioinformatics and data-mining tools.

    Stephen A. Williams, M.D., Ph.D., CMO at SomaLogic, talked about his firm’s SOMAscan biomarker discovery platform. Based on specially designed nucleic acids called SOMAmers, the platform can scan a 15 µL sample for up to 1,000 different proteins, identifying individual biomarkers of interest or profiles that can be used to diagnose disease.

    The menu of approximately 1,000 proteins includes cytokines, growth factors, receptors, proteases, protease inhibitors, kinases, structural proteins, and hormones that could potentially be of interest in human disease origins.

    SOMAmers are created by an in vitro competitive process where a single protein is exposed to roughly a quadrillion different synthetic nucleic acids. The strongest binders are isolated and amplified, and the process is repeated until a “winner” is found. This aptamer and protein pair then becomes part of the menu offered in a proteomic profiling scan.

    “We can measure a thousand proteins simultaneously without any fractionation of the sample of serum plasma, CSF, or tissue homogenate,” noted Dr. Williams. The co-efficients of variation are about 5%, and the sensitivity is in the low femtomolar range. “It’s like running a thousand ELISAs simultaneously on a single sample.”

    In order to develop a clinical assay in lung cancer, SomaLogic researchers used archived sample sets, screening 1,400 samples in eight days to find a possible protein signature for lung cancer. The analysis turned up 61 proteins that showed a difference between the diseased and nondiseased state.

    Dr. Williams and his team then whittled that number down to the 12 best markers. “Our demands were that it work just as well in stage 1 and stage 3, and that it work just as well in people with COPD as people with normal lung function.”

    SomaLogic has created similar screens for pancreatic cancer and mesothelioma, and has a number of other screens in the pipeline.


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