Title: Cancer progression analysis based on ordinal relationship of cancer stages and co-expression network modularity

Authors: Yoon Soo Pyon, Xin Li, Jing Li

Addresses: Department of Electrical Engineering and Computer Science, Case Western Reserve University, 10900 Euclid Avenue, Olin 514, Cleveland, OH 44106, USA. ' Department of Electrical Engineering and Computer Science, Case Western Reserve University, 10900 Euclid Avenue, Olin 514, Cleveland, OH 44106, USA. ' Department of Electrical Engineering and Computer Science, Case Western Reserve University, 10900 Euclid Avenue, Olin 509, Cleveland, OH 44106, USA; Joint Institute of Systems Biology, College of Computer Science and Technology, Jilin University, 2699 Qianjin St., Changchu, Jilin Provience 130012, China

Abstract: A comprehensive understanding of cancer progression may shed light on genetic and molecular mechanisms of oncogenesis, and provide important information for effective diagnosis and prognosis. We propose a multicategory logit model to identify genes that show significant correlations across multiple cancer stages. We have applied the approach on a Prostate Cancer (PCA) progression data and obtained a set of genes that show consistent trends across multiple stages. Further analysis based on multiple evidences demonstrates that our candidate list includes not only some well-known prostate-cancer-related genes, but also novel genes that have been confirmed very recently.

Keywords: ordinal analysis; gene expression; cancer progression; network modularity; cancer stages; oncogenesis; prostate cancer; cancer-related genes; bioinformatics.

DOI: 10.1504/IJDMB.2011.040382

International Journal of Data Mining and Bioinformatics, 2011 Vol.5 No.3, pp.233 - 251

Published online: 25 May 2011 *

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