Outlier Analysis and Top Scoring Pairfor Integrated Data Analysisand Biomarker Discovery - Ochs, Michael F; Farrar, Jason E; Considine, Michael; Wei, Yingying; Meshinchi, Soheil; Arceci, Robert J (IEEE/ACM transactions on computational biology and bioinformatics, 2014)
Pathway deregulation has been identified as a key driver of carcinogenesis, with proteins in signaling pathways serving as primary targets for drug development. Deregulation can be driven by a number of molecular events, including gene mutation, epigenetic changes in gene promoters, overexpression, and gene amplifications or deletions. We demonstrate a novel approach that identifies pathways of interest by integrating outlier analysis within and across molecular data types with gene set analysis. We use the results to seed the top-scoring pair algorithm to identify robust biomarkers associated with pathway deregulation. We demonstrate this methodology on pediatric acute myeloid leukemia (AML) data. We develop a biomarker in primary AML tumors, demonstrate robustness with an independent primary tumor data set, and show that the identified biomarkers also function well in relapsed pediatric AML tumors.