Detecting copy number status and uncovering subclonal markers in heterogeneous tumor biopsies

摘要: Genomic aberrations can be used to determine cancer diagnosis and prognosis. Clinically relevant novel discovered using high-throughput assays such as Single Nucleotide Polymorphism (SNP) arrays next-generation sequencing, which typically provide aggregate signals of many cells at once. However, heterogeneity tumor subclones dramatically complicates the task detecting aberrations. The signal a population described linear system equations. We employed measure allelic imbalance total amount DNA characterize each locus by copy number status (gain, loss or neither) strongest subclonal component. designed simulated data compare our existing approaches we analyzed SNP-arrays from 30 melanoma samples transcriptome sequencing (RNA-Seq) one sample. showed that any describing is underdetermined, leading non-unique solutions for exact profile subclones. For this reason, illustrative was more robust than Hidden Markov Model (HMM) based tools in inferring aberration status, indicated tests on data. This higher robustness contributed identifying numerous several loci samples. validated within single biopsies fluorescent situ hybridization four affected transcriptionally up-regulated genes E2F8, ETV4, EZH2 FAM84B 11 cell lines. Heterogeneity further demonstrated analysis changes along exons RNA-Seq. These studies demonstrate how heterogeneity, prevalent samples, reflected measured techniques. Our proposed approach yields high alterations technologies has potential identify specific markers