Integrated Analysis of Tumor Samples Sheds Light on Tumor Heterogeneity

The heterogeneity of tumor samples is a major challenge in the analysis ofhigh-throughput profiling of tumor biopsies and cell lines. The measuredaggregate signals of multigenerational progenies often represent an average ofseveral tumor subclones with varying genomic aberrations and different geneexpression levels. The goal of the present study was to integrate copy numberanalyses from SNP-arrays and karyotyping, gene expression profiling, and pathwayanalyses to detect heterogeneity, identify driver mutations, and explorepossible mechanisms of tumor evolution. We showed the heterogeneity of thestudied samples, characterized the global copy number alteration profiles, andidentified genes whose copy number status and expression levels were aberrant.In particular, we identified a recurrent association between twoBRAF^V600E and BRAF^V600K mutations and changes in DKK1gene expression levels, which might indicate an association between the BRAF andWNT pathways. These findings show that the integrated approaches used in thepresent study can robustly address the challenging issue of tumor heterogeneityin high-throughput profiling.