High-sensitivity blood-based detection of breast cancer by multi photon detection diagnostic proteomics |
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Authors: | Drukier Andrzej K Ossetrova Nathasha Schors Elena Krasik Galya Grigoriev Ivan Koenig Christina Sulkowski Miko Holcman Jerzy Brown Larry R Tomaszewski John E Schnall Mitchell D Sainsbury Richard Lokshin Anne E Godovac-Zimmermann Jasminka |
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Institution: | BioTraces Inc., 12455 Sunrise Valley Dr., Herndon, Virginia 20171, USA. |
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Abstract: | We have developed several new methods for blood-based cancer detection by diagnostic proteomics. Ultrasensitive methods of immunoassay using multiphoton-detection (IA/MPD) increase sensitivity by 200- to 1,000-fold (1 femtogram/mL). This has allowed the measurement of cancer biomarkers with very low concentrations in blood that could not be measured for full patient cohorts with conventional immunoassays. Sensitivity and specificity in cancer detection have been found to be potentiated by use of immunoassay panels which include tissue-specific cancer biomarkers as well as cytokines and angiogenic factors. The ultrasensitive immunoassays revealed that patient to patient variations in the concentrations of individual biomarkers in blood can extend over many orders of magnitude (up to six) and that the distributions of biomarker concentrations over patient cohorts are non-Gaussian. New methods of data analysis which correlate abundances of multiple, different biomarkers have been developed to deal with such data sets. Sensitivity and specificity of about 95% have been achieved for blood-based detection of breast cancer in pilot studies on 250 patients and 95 controls. Pilot studies indicate that this methodology may also allow differentiation of malignant breast cancer from benign lesions and can provide similar sensitivity and specificity for other epithelial cancers such as prostate cancer, ovarian cancer and melanoma. The methods developed for selection, application, and evaluation of very high sensitivity biomarker panels are expected to have general relevance for diagnostic proteomics. |
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