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Network Biomarkers for Diagnosis and Prognosis of Human Prostate Cancer

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Bioinformatics for Diagnosis, Prognosis and Treatment of Complex Diseases

Part of the book series: Translational Bioinformatics ((TRBIO,volume 4))

Abstract

Prostate cancer is one of the most lethal malignancies worldwide, owing to the lack of precise markers for early diagnosis. Researchers are now routinely identifying biomarkers for prostate cancer using whole-genome expression profiling along with proteomic technologies. Although there has been some success in this field, many efforts have been complicated by the fact that individual markers are highly divergent. Prostate cancer is a systems biology disease that results from the accumulated mutations acting in concert. Hence the individual markers would fail to capture the heterogeneity of carcinogenesis. As molecular interaction networks become available for human, network-level biomarker evolves as a promising methodology that can address this challenge. In this chapter we first describe some foundations of network analysis, and then introduce the recent progress in network biomarker discovery for diagnosis and prognosis of human prostate cancer.

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Authors and Affiliations

  1. Center for Systems Biology, Soochow University, No. 1 Shizi Street, Suzhou, P.O. Box 206, 215006, Jiangsu, China

    Jiajia Chen & Bairong Shen

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  1. Jiajia Chen
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  2. Bairong Shen
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Correspondence to Bairong Shen .

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  1. Center for Systems Biology, Soochow University, Suzhou, People's Republic of China

    Bairong Shen

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Chen, J., Shen, B. (2013). Network Biomarkers for Diagnosis and Prognosis of Human Prostate Cancer. In: Shen, B. (eds) Bioinformatics for Diagnosis, Prognosis and Treatment of Complex Diseases. Translational Bioinformatics, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7975-4_11

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