Abstract 40: Similarity-based exploration of genomic profiles in glioblastoma multiforme samples

Abstract

Abstract The main goal of this study is to deploy similarity-driven methodologies to explore data in public repositories such as The Cancer Genome Atlas (TCGA). One of the research goals of the In Silico Research Center of Excellence at TGen and 5am Solutions is to explore the differences and similarities between genomic profiles of glioblastoma xenografts, glioblastoma patient, and non-tumor samples and use that information to select a diverse but representative population of xenografts for drug-treatment experiments. The first step consists in designing similarity-driven methodologies to describe the relations in genomic datasets publicly available such as The Cancer Genome Atlas (TCGA). This contribution presents a workflow through which the similarity relationships amongst gene expression profiles from TCGA GBM and non-tumor samples are explored. The method consists in (1) representing the data as feature vectors, (2) calculating the pair-wise similarity between the objects based on the chosen representation and a similarity metric (e.g., euclidean distance), (3) projecting the obtained similarity matrix in the 3D space of its three first principal components, calculated by Principal Component Analysis (PCA). The 3D similarity spaces obtained lead to several interesting interpretations: the different phenotypes (GBM, non-tumor, xenografts) were accurately depicted and reduced pools of genes (gene sets) could be used as sufficient description (Gene set enrichment analysis, caBIO gene sets) to conserve the initial representation. These observations allowed us to validate the exploratory power of the method and to use it in further analysis such as the assessment of the similarity between xenografts and GBM samples to select appropriate treatments on a genomic likeness basis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 40. doi:10.1158/1538-7445.AM2011-40