SiDCoN: A Tool to Aid Scoring of DNA Copy Number Changes in SNP Chip Data

The recent application of genome-wide, single nucleotide polymorphism (SNP) microarrays to investigate DNA copy number aberrations in cancer has provided unparalleled sensitivity for identifying genomic changes. In some instances the complexity of these changes makes them difficult to interpret, particularly when tumour samples are contaminated with normal (stromal) tissue. Current automated scoring algorithms require considerable manual data checking and correction, especially when assessing uncultured tumour specimens. To address these limitations we have developed a visual tool to aid in the analysis of DNA copy number data. Simulated DNA Copy Number (SiDCoN) is a spreadsheet-based application designed to simulate the appearance of B-allele and logR plots for all known types of tumour DNA copy number changes, in the presence or absence of stromal contamination. The system allows the user to determine the level of stromal contamination, as well as specify up to 3 different DNA copy number aberrations for up to 5000 data points (representing individual SNPs). This allows users great flexibility to assess simple or complex DNA copy number combinations. We demonstrate how this utility can be used to estimate the level of stromal contamination within tumour samples and its application in deciphering the complex heterogeneous copy number changes we have observed in a series of tumours. We believe this tool will prove useful to others working in the area, both as a training tool, and to aid in the interpretation of complex copy number changes

Allele-specific disparity in breast cancer

Background In a cancer cell the number of copies of a locus may vary due to amplification and deletion and these variations are denoted as copy number alterations (CNAs). We focus on the disparity of CNAs in tumour samples, which were compared to those in blood in order to identify the directional loss of heterozygosity. Methods We propose a numerical algorithm and apply it to data from the Illumina 109K-SNP array on 112 samples from breast cancer patients. B-allele frequency (BAF) and log R ratio (LRR) of Illumina were used to estimate Euclidian distances. For each locus, we compared genotypes in blood and tumour for subset of samples being heterozygous in blood. We identified loci showing preferential disparity from heterozygous toward either the A/B-allele homozygous (allelic disparity). The chi-squared and Cochran-Armitage trend tests were used to examine whether there is an association between high levels of disparity in single nucleotide polymorphisms (SNPs) and molecular, clinical and tumour-related parameters. To identify pathways and network functions over-represented within the resulting gene sets, we used Ingenuity Pathway Analysis (IPA). Results To identify loci with a high level of disparity, we selected SNPs 1) with a substantial degree of disparity and 2) with substantial frequency (at least 50% of the samples heterozygous for the respective locus). We report the overall difference in disparity in high-grade tumours compared to low-grade tumours (p-value < 0.001) and significant associations between disparity in multiple single loci and clinical parameters. The most significantly associated network functions within the genes represented in the loci of disparity were identified, including lipid metabolism, small-molecule biochemistry, and nervous system development and function. No evidence for over-representation of directional disparity in a list of stem cell genes was obtained, however genes appeared to be more often altered by deletion than by amplification. Conclusions Our data suggest that directional loss and amplification exist in breast cancer. These are highly associated with grade, which may indicate that they are enforced with increasing number of cell divisions. Whether there is selective pressure for some loci to be preferentially amplified or deleted remains to be confirmed

Mapping and sequencing of structural variation from eight human genomes

Genetic variation among individual humans occurs on many different scales, ranging from gross alterations in the human karyotype to single nucleotide changes. Here we explore variation on an intermediate scale - particularly insertions, deletions and inversions affecting from a few thousand to a few million base pairs. We employed a clone- based method to interrogate this intermediate structural variation in eight individuals of diverse geographic ancestry. Our analysis provides a comprehensive overview of the normal pattern of structural variation present in these genomes, refining the location of 1,695 structural variants. We find that 50% were seen in more than one individual and that nearly half lay outside regions of the genome previously described as structurally variant. We discover 525 new insertion sequences that are not present in the human reference genome and show that many of these are variable in copy number between individuals. Complete sequencing of 261 structural variants reveals considerable locus complexity and provides insights into the different mutational processes that have shaped the human genome. These data provide the first high- resolution sequence map of human structural variation - a standard for genotyping platforms and a prelude to future individual genome sequencing projects

Linear and non-linear dependencies between copy number aberrations and mRNA expression reveal distinct molecular pathways in breast cancer

<p>Abstract</p> <p>Background</p> <p>Elucidating the exact relationship between gene copy number and expression would enable identification of regulatory mechanisms of abnormal gene expression and biological pathways of regulation. Most current approaches either depend on linear correlation or on nonparametric tests of association that are insensitive to the exact shape of the relationship. Based on knowledge of enzyme kinetics and gene regulation, we would expect the functional shape of the relationship to be gene dependent and to be related to the gene regulatory mechanisms involved. Here, we propose a statistical approach to investigate and distinguish between linear and nonlinear dependences between DNA copy number alteration and mRNA expression.</p> <p>Results</p> <p>We applied the proposed method to DNA copy numbers derived from Illumina 109 K SNP-CGH arrays (using the log R values) and expression data from Agilent 44 K mRNA arrays, focusing on commonly aberrated genomic loci in a collection of 102 breast tumors. Regression analysis was used to identify the type of relationship (linear or nonlinear), and subsequent pathway analysis revealed that genes displaying a linear relationship were overall associated with substantially different biological processes than genes displaying a nonlinear relationship. In the group of genes with a linear relationship, we found significant association to canonical pathways, including purine and pyrimidine metabolism (for both deletions and amplifications) as well as estrogen metabolism (linear amplification) and BRCA-related response to damage (linear deletion). In the group of genes displaying a nonlinear relationship, the top canonical pathways were specific pathways like PTEN and PI13K/AKT (nonlinear amplification) and Wnt(B) and IL-2 signalling (nonlinear deletion). Both amplifications and deletions pointed to the same affected pathways and identified cancer as the top significant disease and cell cycle, cell signaling and cellular development as significant networks.</p> <p>Conclusions</p> <p>This paper presents a novel approach to assessing the validity of the dependence of expression data on copy number data, and this approach may help in identifying the drivers of carcinogenesis.</p

Copy-number-variation and copy-number-alteration region detection by cumulative plots

Background: Regions with copy number variations (in germline cells) or copy number alteration (in somatic cells) are of great interest for human disease gene mapping and cancer studies. They represent a new type of mutation and are larger-scaled than the single nucleotide polymorphisms. Using genotyping microarray for copy number variation detection has become standard, and there is a need for improving analysis methods. Results: We apply the cumulative plot to the detection of regions with copy number variation/alteration, on samples taken from a chronic lymphocytic leukemia patient. Two sets of whole-genome genotyping of 317k single nucleotide polymorphisms, one from the normal cell and another from the cancer cell, are analyzed. We demonstrate the utility of cumulative plot in detecting a 9Mb (9 x 10^6 bases) hemizygous deletion and 1Mb homozygous deletion on chromosome 13. We also show the possibility to detect smaller copy number variation/alteration regions below the 100kb range. Conclusions: As a graphic tool, the cumulative plot is an intuitive and a scale-free (window-less) way for detecting copy number variation/alteration regions, especially when such regions are small

Human bone marrow mesenchymal stem cells : a systematic reappraisal via the genostem experience

Genostem (acronym for “Adult mesenchymal stem cells engineering for connective tissue disorders. From the bench to the bed side”) has been an European consortium of 30 teams working together on human bone marrow Mesenchymal Stem Cell (MSC) biological properties and repair capacity. Part of Genostem activity has been dedicated to the study of basic issues on undifferentiated MSCs properties and on signalling pathways leading to the differentiation into 3 of the connective tissue lineages, osteoblastic, chondrocytic and tenocytic. We have evidenced that native bone marrow MSCs and stromal cells, forming the niche of hematopoietic stem cells, were the same cellular entity located abluminally from marrow sinus endothelial cells. We have also shown that culture-amplified, clonogenic and highly-proliferative MSCs were bona fide stem cells, sharing with other stem cell types the major attributes of self-renewal and of multipotential priming to the lineages to which they can differentiate (osteoblasts, chondrocytes, adipocytes and vascular smooth muscle cells/pericytes). Extensive transcription profiling and in vitro and in vivo assays were applied to identify genes involved in differentiation. Thus we have described novel factors implicated in osteogenesis (FHL2, ITGA5, Fgf18), chondrogenesis (FOXO1A) and tenogenesis (Smad8). Another part of Genostem activity has been devoted to studies of the repair capacity of MSCs in animal models, a prerequisite for future clinical trials. We have developed novel scaffolds (chitosan, pharmacologically active microcarriers) useful for the repair of both bone and cartilage. Finally and most importantly, we have shown that locally implanted MSCs effectively repair bone, cartilage and tendonWork supported by the European Community (Key action 1.2.4-3 Integrated Project Genostem, contract No 503161)

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

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

Studying the Underlying Event in Drell-Yan and High Transverse Momentum Jet Production at the Tevatron

We study the underlying event in proton-antiproton collisions by examining the behavior of charged particles (transverse momentum pT > 0.5 GeV/c, pseudorapidity |\eta| < 1) produced in association with large transverse momentum jets (~2.2 fb-1) or with Drell-Yan lepton-pairs (~2.7 fb-1) in the Z-boson mass region (70 < M(pair) < 110 GeV/c2) as measured by CDF at 1.96 TeV center-of-mass energy. We use the direction of the lepton-pair (in Drell-Yan production) or the leading jet (in high-pT jet production) in each event to define three regions of \eta-\phi space; toward, away, and transverse, where \phi is the azimuthal scattering angle. For Drell-Yan production (excluding the leptons) both the toward and transverse regions are very sensitive to the underlying event. In high-pT jet production the transverse region is very sensitive to the underlying event and is separated into a MAX and MIN transverse region, which helps separate the hard component (initial and final-state radiation) from the beam-beam remnant and multiple parton interaction components of the scattering. The data are corrected to the particle level to remove detector effects and are then compared with several QCD Monte-Carlo models. The goal of this analysis is to provide data that can be used to test and improve the QCD Monte-Carlo models of the underlying event that are used to simulate hadron-hadron collisions.Comment: Submitted to Phys.Rev.