Elena Landoni
Foundation IRCCS National Cancer Institute, Italy
Title: A comprehensive pipeline for biomarker discovery using circulating miRNA microarray data
Biography
Biography: Elena Landoni
Abstract
Circulating miRNAs have the potential as cancer biomarkers but no consolidated guidelines are established for discovery analyses. Several issues (e.g. data normalization, expected miRNA up-regulation in one of classes, sample size limitation) can affect results making many approaches unsuitable. We developed a structured pipeline with innovative applications of existing bioinformatics methods including: 1) an assumption-independent normalization method based on miRNA ratios in data pre-processing; 2) the combination of the results of two statistical tests (t- and Anderson Darling) to detect miRNAs with significant fold change or general distributional differences in class comparison; 3) the application of a bootstrap selection procedure together with machine learning techniques to guarantee result generalizability and study the interconnections among the selected miRNAs in class prediction. We applied the pipeline to compare hemolized and non-hemolized plasma samples, identifying four miRNAs known to be hemolysis-related (miR-486-5p, miR-92a, miR-451, miR-16) together with a new one, miR-22.