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Inferring Relative Activity between Pathway and Downstream Genes to Classify Melanoma Cancer Progression
Inkyung Jung1, Jungsul Lee1, Chulhee Choi1 and Dongsup Kim1,*
1Department of Bio and Brain Engineering, KAIST, Daejeon 305-701, Republic of Korea
*Corresponding author
  Received : February 15, 2011
  Accepted : February 18, 2011
  Published : February 28, 2011
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Synopsis

Introduction: Many signal transduction pathways mediate cell's behavior by regulating expression level of involved genes. Abnormal behavior indicates loss of regulatory potential of pathways, and this can be attributed to loss of expression regulation of downstream genes. Therefore, function of pathways should be assessed by activity of a pathway itself and relative activity between a pathway and downstream genes, simultaneously.
Results and Discussion: In this study, we suggested a new method to assess pathway's function by introducing concept of `responsiveness'. The responsiveness was defined as a relative activity between a pathway itself and its downstream genes. The expression level of a downstream gene as a function of an upstream pathway activation characterizes disease status. In this aspect, by using the responsiveness we predicted potential progress in cancer development. We applied our method to predict primary and metastatic status of melanoma cancer. The result shows that the responsiveness-based approach achieves better performance than using gene or pathway information alone. The mean of ROC scores in the responsiveness-based approach was 0.90 for GSE7553 data set, increased more than 40% compared to a gene-based method. Moreover, identifying the abnormal regulatory patterns between pathway and its downstream genes provided more biologically interpretable information compared to gene or pathway based approaches.

Keyword: melanoma cancer progression, biomarker, responsiveness, classifier, drug target
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