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Multiple biomarker panels for early detection of breast cancer in peripheral blood
Fan Zhang1, Youping Deng2, Renee Drabier3
1Department of Academic and Institutional Resources and Technology, University of North Texas Health Science Center, Fort Worth, 76107, USA ; Department of Forensic and Investigative Genetics, University of North Texas Health Science Center, Fort Worth, 76107, USA.
Abstract:
Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers.
