Integrated study of copy number states and genotype calls using high-density SNP arrays

We propose a statistical framework, named genoCN, to simultaneously dissect copy number states and genotypes using high-density SNP (single nucleotide polymorphism) arrays. There are at least two types of genomic DNA copy number differences: copy number variations (CNVs) and copy number aberrations (CNAs). While CNVs are naturally occurring and inheritable, CNAs are acquired somatic alterations most often observed in tumor tissues only. CNVs tend to be short and more sparsely located in the genome compared with CNAs. GenoCN consists of two components, genoCNV and genoCNA, designed for CNV and CNA studies, respectively. In contrast to most existing methods, genoCN is more flexible in that the model parameters are estimated from the data instead of being decided a priori. GenoCNA also incorporates two important strategies for CNA studies. First, the effects of tissue contamination are explicitly modeled. Second, if SNP arrays are performed for both tumor and normal tissues of one individual, the genotype calls from normal tissue are used to study CNAs in tumor tissue. We evaluated genoCN by applications to 162 HapMap individuals and a brain tumor (glioblastoma) dataset and showed that our method can successfully identify both types of copy number differences and produce high-quality genotype calls

Differential in vivo tumorigenicity of distinct subpopulations from a luminal-like breast cancer xenograft

Intratumor heterogeneity caused by genetic, phenotypic or functional differences between cancer cell subpopulations is a considerable clinical challenge. Understanding subpopulation dynamics is therefore central for both optimization of existing therapy and for development of new treatment. The aim of this study was to isolate subpopulations from a primary tumor and by comparing molecular characteristics of these subpopulations, find explanations to their differing tumorigenicity. Cell subpopulations from two patient derived in vivo models of primary breast cancer, ER+ and ER-, were identified. EpCAM+ cells from the ER+ model gave rise to tumors independently of stroma cell support. The tumorigenic fraction was further divided based on SSEA-4 and CD24 expression. Both markers were expressed in ER+ breast cancer biopsies. FAC-sorted cells based on EpCAM, SSEA-4 and CD24 expression were subsequently tested for differences in functionality by in vivo tumorigenicity assay. Three out of four subpopulations of cells were tumorigenic and showed variable ability to recapitulate the marker expression of the original tumor. Whole genome expression analysis of the sorted populations disclosed high similarity in the transcriptional profiles between the tumorigenic populations. Comparing the non-tumorigenic vs the tumorigenic populations, 44 transcripts were, however, significantly differentially expressed. A subset of these, 26 identified and named genes, highly expressed in the non-tumorigenic population, predicted longer overall survival (N = 737, p<0.0001) and distant metastasis free survival (DMFS) (N = 1379, p<0.0001) when performing Kaplan-Meier survival analysis using the GOBO online database. The 26 gene set correlated with longer DMFS in multiple breast cancer subgroups. Copy number profiling revealed no aberrations that could explain the observed differences in tumorigenicity. This study emphasizes the functional variability among cell populations that are otherwise genomically similar, and that the risk of breast cancer recurrence can only be eliminated if the tumorigenic abilities in multiple cancer cell subpopulations are inhibited

Genes harbouring susceptibility SNPs are differentially expressed in the breast cancer subtypes

Recently, genome-wide association studies of breast cancer revealed single nucleotide polymorphisms (SNPs) in five genes with novel association to susceptibility. While there is little doubt that the novel susceptibility markers produced from such highly powered studies are true, the mechanisms by which they cause the susceptibility remain undetermined. We have looked at the expression levels of the identified genes in tumours and found that they are highly significantly differentially expressed between the five established breast cancer subtypes. Also, a significant association between SNPs in these genes and their expression in tumours was seen as well as a significantly different frequency of the SNPs between the subtypes. This suggests that the observed genes are associated with different breast cancer subtypes, and may exert their effect through their expression in the tumours. Thus, future studies stratifying patients by their molecular subtypes may give much more power to classic case control studies, and genes of no or borderline significance may appear to be high-penetrant for certain subtypes and, therefore, be identifiable

Basal-like Breast cancer DNA copy number losses identify genes involved in genomic instability, response to therapy, and patient survival

Breast cancer is a heterogeneous disease with known expression-defined tumor subtypes. DNA copy number studies have suggested that tumors within gene expression subtypes share similar DNA Copy number aberrations (CNA) and that CNA can be used to further sub-divide expression classes. To gain further insights into the etiologies of the intrinsic subtypes, we classified tumors according to gene expression subtype and next identified subtype-associated CNA using a novel method called SWITCHdna, using a training set of 180 tumors and a validation set of 359 tumors. Fisher’s exact tests, Chi-square approximations, and Wilcoxon rank-sum tests were performed to evaluate differences in CNA by subtype. To assess the functional significance of loss of a specific chromosomal region, individual genes were knocked down by shRNA and drug sensitivity, and DNA repair foci assays performed. Most tumor subtypes exhibited specific CNA. The Basal-like subtype was the most distinct with common losses of the regions containing RB1, BRCA1, INPP4B, and the greatest overall genomic instability. One Basal-like subtype-associated CNA was loss of 5q11–35, which contains at least three genes important for BRCA1-dependent DNA repair (RAD17, RAD50, and RAP80); these genes were predominantly lost as a pair, or all three simultaneously. Loss of two or three of these genes was associated with significantly increased genomic instability and poor patient survival. RNAi knockdown of RAD17, or RAD17/RAD50, in immortalized human mammary epithelial cell lines caused increased sensitivity to a PARP inhibitor and carboplatin, and inhibited BRCA1 foci formation in response to DNA damage. These data suggest a possible genetic cause for genomic instability in Basal-like breast cancers and a biological rationale for the use of DNA repair inhibitor related therapeutics in this breast cancer subtype.Electronic supplementary materialThe online version of this article (doi:10.1007/s10549-011-1846-y) contains supplementary material, which is available to authorized users

Seed 1-Cysteine Peroxiredoxin Antioxidants Are Not Involved in Dormancy, But Contribute to Inhibition of Germination during Stress

Peroxiredoxins (Prx) are thiol-dependent antioxidants containing one (1-cysteine [-Cys]) or two (2-Cys) conserved Cys residues that protect lipids, enzymes, and DNA against reactive oxygen species. In plants, the 1-Cys Prxs are highly expressed during late seed development, and the expression pattern is dormancy related in mature seeds. We have expressed the Arabidopsis 1-Cys Prx AtPER1 in Escherichia coli and show that this protein has antioxidant activity in vitro and protects E. coli in vivo against the toxic oxidant cumene hydroperoxide. Although some 1-Cys Prxs are targeted to the nucleus, a green fluorescent protein-AtPER1 fusion protein was also localized to the cytoplasm in an onion epidermis subcellular localization assay. It has been proposed that seed Prxs are involved in maintenance of dormancy and/or protect the embryo and aleurone layer surviving desiccation against damage caused by reactive oxygen species. These hypotheses were tested using transgenic Arabidopsis lines overexpressing the barley (Hordeum vulgare) 1-Cys PER1 protein and lines with reduced levels of AtPER1 due to antisensing or RNA interference. We found no correlation between Prx levels and the duration of the after-ripening period required before germination. Thus, Prxs are unlikely to contribute to maintenance of dormancy. RNA interference lines almost devoid of AtPER1 protein developed and germinated normally under standard growth room conditions. However, seeds from lines overexpressing PER1 were less inclined to germinate than wild-type seeds in the presence of NaCl, mannitol, and methyl viologen, suggesting that Prx can sense harsh environmental surroundings and play a part in the inhibition of germination under unfavorable conditions

Analyzing cancer samples with SNP arrays

Single nucleotide polymorphism (SNP) arrays are powerful tools to delineate genomic aberrations in cancer genomes. However, the analysis of these SNP array data of cancer samples is complicated by three phenomena: (a) aneuploidy: due to massive aberrations, the total DNA content of a cancer cell can differ significantly from its normal two copies; (b) nonaberrant cell admixture: samples from solid tumors do not exclusively contain aberrant tumor cells, but always contain some portion of nonaberrant cells; (c) intratumor heterogeneity: different cells in the tumor sample may have different aberrations. We describe here how these phenomena impact the SNP array profile, and how these can be accounted for in the analysis. In an extended practical example, we apply our recently developed and further improved ASCAT (allele-specific copy number analysis of tumors) suite of tools to analyze SNP array data using data from a series of breast carcinomas as an example. We first describe the structure of the data, how it can be plotted and interpreted, and how it can be segmented. The core ASCAT algorithm next determines the fraction of nonaberrant cells and the tumor ploidy (the average number of DNA copies), and calculates an ASCAT profile. We describe how these ASCAT profiles visualize both copy number aberrations as well as copy-number-neutral events. Finally, we touch upon regions showing intratumor heterogeneity, and how they can be detected in ASCAT profiles. All source code and data described here can be found at our ASCAT Web site ( http://www.ifi.uio.no/forskning/grupper/bioinf/Projects/ASCAT/).status: publishe

genotype calls using high-density

SNP array