Genomic characterisation of hormone receptor-positive breast cancer arising in very young women.

BACKGROUND: Very young premenopausal women diagnosed with hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+HER2-) early breast cancer (EBC) have higher rates of recurrence and death for reasons that remain largely unexplained. PATIENTS AND METHODS: Genomic sequencing was applied to HR+HER2- tumours from patients enrolled in the Suppression of Ovarian Function Trial (SOFT) to determine genomic drivers that are enriched in young premenopausal women. Genomic alterations were characterised using next-generation sequencing from a subset of 1276 patients (deep targeted sequencing, n = 1258; whole-exome sequencing in a young-age, case-control subsample, n = 82). We defined copy number (CN) subgroups and assessed for features suggestive of homologous recombination deficiency (HRD). Genomic alteration frequencies were compared between young premenopausal women (<40 years) and older premenopausal women (≥40 years), and assessed for associations with distant recurrence-free interval (DRFI) and overall survival (OS). RESULTS: Younger women (<40 years, n = 359) compared with older women (≥40 years, n = 917) had significantly higher frequencies of mutations in GATA3 (19% versus 16%) and CN amplifications (CNAs) (47% versus 26%), but significantly lower frequencies of mutations in PIK3CA (32% versus 47%), CDH1 (3% versus 9%), and MAP3K1 (7% versus 12%). Additionally, they had significantly higher frequencies of features suggestive of HRD (27% versus 21%) and a higher proportion of PIK3CA mutations with concurrent CNAs (23% versus 11%). Genomic features suggestive of HRD, PIK3CA mutations with CNAs, and CNAs were associated with significantly worse DRFI and OS compared with those without these features. These poor prognostic features were enriched in younger patients: present in 72% of patients aged <35 years, 54% aged 35-39 years, and 40% aged ≥40 years. Poor prognostic features [n = 584 (46%)] versus none [n = 692 (54%)] had an 8-year DRFI of 84% versus 94% and OS of 88% versus 96%. Younger women (<40 years) had the poorest outcomes: 8-year DRFI 74% versus 85% and OS 80% versus 93%, respectively. CONCLUSION: These results provide insights into genomic alterations that are enriched in young women with HR+HER2- EBC, provide rationale for genomic subgrouping, and highlight priority molecular targets for future clinical trials.

Determining epithelial contribution to in vivo mesenchymal tumour expression signature using species-specific microarray profiling analysis of xenografts.

Gene expression profiling using microarrays and xenograft transplants of human cancer cell lines are both popular tools to investigate human cancer. However, the undefined degree of cross hybridization between the mouse and human genomes hinders the use of microarrays to characterize gene expression of both the host and the cancer cell within the xenograft. Since an increasingly recognized aspect of cancer is the host response (or cancer-stroma interaction), we describe here a bioinformatic manipulation of the Affymetrix profiling that allows interrogation of the gene expression of both the mouse host and the human tumour. Evidence of microenvironmental regulation of epithelial mesenchymal transition of the tumour component in vivo is resolved against a background of mesenchymal gene expression. This tool could allow deeper insight to the mechanism of action of anti-cancer drugs, as typically novel drug efficacy is being tested in xenograft systems.

A DNA resequencing array for genes involved in Parkinson's disease.

Parkinson's disease (PD) is aetiologically complex with both familial and sporadic forms. Familial PD results from rare, highly penetrant pathogenic mutations whereas multiple variants of low penetrance may contribute to the risk of sporadic PD. Common variants implicated in PD risk appear to explain only a minor proportion of the familial clustering observed in sporadic PD. It is therefore plausible that combinations of rare and/or common variants in genes already implicated in disease pathogenesis may help to explain the genetic basis of PD. We have developed a CustomSeq Affymetrix resequencing array to enable high-throughput sequencing of 13 genes (44 kb) implicated in the pathogenesis of PD. Using the array we sequenced 269 individuals, including 186 PD patients and 75 controls, achieving an overall call rate of 96.5% and 93.6%, for two respective versions of the array, and >99.9% accuracy for five samples sequenced by capillary sequencing in parallel. We identified modest associations with common variants in SNCA and LRRK2 and a trend suggestive of an overrepresentation of rare variants in cases compared to controls for several genes. We propose that this technology offers a robust and cost-effective alternative to targeted sequencing using traditional sequencing methods, and here we demonstrate the potential of this approach for either routine clinical investigation or for research studies aimed at understanding the genetic aetiology of PD.

Replication of KIAA0350, IL2RA, RPL5 and CD58 as multiple sclerosis susceptibility genes in Australians.

A recent genome-wide association study (GWAS) conducted by the International Multiple Sclerosis Genetics Consortium (IMSGC) identified a number of putative MS susceptibility genes. Here we have performed a replication study in 1134 Australian MS cases and 1265 controls for 17 risk-associated single nucleotide polymorphisms (SNPs) reported by the IMSGC. Of 16 SNPs that passed quality control filters, four, each corresponding to a different non-human leukocyte antigen (HLA) gene, were associated with disease susceptibility: KIAA0350 (rs6498169) P=0.001, IL2RA (rs2104286) P=0.033, RPL5 (rs6604026) P=0.041 and CD58 (rs12044852) P=0.042. There was no association (P=0.58) between rs6897932 in the IL7R gene and the risk of MS. No interactions were detected between the replicated IMSGC SNPs and HLA-DRB1*15, gender, disease course, disease progression or age-at-onset. We used a novel Bayesian approach to estimate the extent to which our data increased or decreased evidence for association with the six most-associated IMSGC loci. These analyses indicated that even modest P-values, such as those reported here, can contribute markedly to the posterior probability of 'true' association in replication studies. In conclusion, these data provide support for the involvement of four non-HLA genes in the pathogenesis of MS, and combined with previous data, increase to genome-wide significance (P=3 x 10(-8)) evidence of an association between KIAA0350 and risk of disease.

FIRMA: a method for detection of alternative splicing from exon array data.

MOTIVATION: Analyses of EST data show that alternative splicing is much more widespread than once thought. The advent of exon and tiling microarrays means that researchers now have the capacity to experimentally measure alternative splicing on a genome wide level. New methods are needed to analyze the data from these arrays. RESULTS: We present a method, finding isoforms using robust multichip analysis (FIRMA), for detecting differential alternative splicing in exon array data. FIRMA has been developed for Affymetrix exon arrays, but could in principle be extended to other exon arrays, tiling arrays or splice junction arrays. We have evaluated the method using simulated data, and have also applied it to two datasets: a panel of 11 human tissues and a set of 10 pairs of matched normal and tumor colon tissue. FIRMA is able to detect exons in several genes confirmed by reverse transcriptase PCR. AVAILABILITY: R code implementing our methods is contributed to the package aroma.affymetrix.

Estimation and assessment of raw copy numbers at the single locus level.

MOTIVATION: Although copy-number aberrations are known to contribute to the diversity of the human DNA and cause various diseases, many aberrations and their phenotypes are still to be explored. The recent development of single-nucleotide polymorphism (SNP) arrays provides researchers with tools for calling genotypes and identifying chromosomal aberrations at an order-of-magnitude greater resolution than possible a few years ago. The fundamental problem in array-based copy-number (CN) analysis is to obtain CN estimates at a single-locus resolution with high accuracy and precision such that downstream segmentation methods are more likely to succeed. RESULTS: We propose a preprocessing method for estimating raw CNs from Affymetrix SNP arrays. Its core utilizes a multichip probe-level model analogous to that for high-density oligonucleotide expression arrays. We extend this model by adding an adjustment for sequence-specific allelic imbalances such as cross-hybridization between allele A and allele B probes. We focus on total CN estimates, which allows us to further constrain the probe-level model to increase the signal-to-noise ratio of CN estimates. Further improvement is obtained by controlling for PCR effects. Each part of the model is fitted robustly. The performance is assessed by quantifying how well raw CNs alone differentiate between one and two copies on Chromosome X (ChrX) at a single-locus resolution (27kb) up to a 200kb resolution. The evaluation is done with publicly available HapMap data. AVAILABILITY: The proposed method is available as part of an open-source R package named aroma.affymetrix. Because it is a bounded-memory algorithm, any number of arrays can be analyzed.

SNP mapping and candidate gene sequencing in the class I region of the HLA complex: searching for multiple sclerosis susceptibility genes in Tasmanians.

This study is an extension to previously published work that has linked variation in the human leukocyte antigen (HLA) class I region with susceptibility to multiple sclerosis (MS) in Australians from the Island State of Tasmania. Single nucleotide polymorphism (SNP) mapping was performed on an 865-kb candidate region (D6S1683-D6S265) in 166 Tasmanian MS families, and seven candidate genes [ubiquitin D (UBD), olfactory receptor 2H3 (OR2H3), gamma-aminobutyric acid B receptor 1 (GABBR1), myelin oligodendrocyte glycoprotein (MOG), HLA-F, HLA complex group 4 (HCG4) and HLA-G] were resequenced. SNPs tagging the extended MS susceptibility haplotype were genotyped in an independent sample of 356 Australian MS trios and SNPs in the MOG gene were significantly over-transmitted to MS cases. We identified significant effects on MS susceptibility of HLA-A*2 (OR: 0.51; P = 0.05) and A*3 (OR: 2.85; P = 0.005), and two coding polymorphisms in the MOG gene (V145I: P = 0.01, OR: 2.2; V142L: P = 0.04, OR: 0.45) after full conditioning on HLA-DRB1. We have therefore identified plausible candidates for the causal MS susceptibility allele, and although not conclusive at this stage, our data provide suggestive evidence for multiple class I MS susceptibility genes.

A genetic screen for behavioral mutations that perturb dopaminergic homeostasis in mice.

Disruption of dopaminergic (DA) systems is thought to play a central role in the addictive process and in the pathophysiology of schizophrenia. Although inheritance plays an important role in the predisposition to these disorders, the genetic basis of this is not well understood. To provide additional insight, we have performed a modifier screen in mice designed to identify mutations that perturb DA homeostasis. With a genetic background sensitized by a mutation in the dopamine transporter (DAT), we used random chemical mutagenesis and screened for mutant mice with locomotor abnormalities. Four mutant lines were identified with quantitatively elevated levels of locomotor activity. Mapping of mutations in these lines identified two loci that alter activity only when dopamine levels are elevated by a DAT mutation and thus would only have been uncovered by this type of approach. One of these quantitative trait loci behaves as an enhancer of DA neurotransmission, whereas the other may act as a suppressor. In addition, we also identified three loci which are not dependent on the sensitized background but which also contribute to the overall locomotor phenotype.

A comparison of match-only algorithms for the analysis of Plasmodium falciparum oligonucleotide arrays.

This study is motivated by two data sets which employ a custom Plasmodium falciparum version of the Affymetrix GeneChip, containing only perfect match (PM) oligonucleotides. A PM-only chip cannot be analysed using the standard Affymetrix-supplied software. We compared the performance of three match-only algorithms on these data: the Match Only Integral Distribution (MOID) algorithm, Robust Multichip Analysis (RMA), and the Model Based Expression Index (MBEI). We validated the differential expression of several genes using quantitative reverse transcriptase-PCR. We also performed a comparison using two publicly available 'benchmarking' data sets: the Latin Square spike-in data set generated by Affymetrix, and the Gene Logic dilution series. Since we know what the true fold changes are in these special data sets, they are helpful for assessment of expression algorithms.

Deriving statistical models for predicting peptide tandem MS product ion intensities.

Improved search algorithms and scoring functions are required before the identification of peptide tandem MS data can be considered to be fully reliable and automatable. The development of models that can accurately predict product ion spectra from a peptide sequence would certainly help achieve this goal, but this firstly requires a better understanding of the process of fragmentation of peptides in the gas-phase. We summarize recent developments in this area and show that the prediction of product ion spectra is feasible and should improve the identification of peptide tandem MS data, especially for peptides that currently give low or insignificant scores with current search algorithms.

A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.

MOTIVATION: When running experiments that involve multiple high density oligonucleotide arrays, it is important to remove sources of variation between arrays of non-biological origin. Normalization is a process for reducing this variation. It is common to see non-linear relations between arrays and the standard normalization provided by Affymetrix does not perform well in these situations. RESULTS: We present three methods of performing normalization at the probe intensity level. These methods are called complete data methods because they make use of data from all arrays in an experiment to form the normalizing relation. These algorithms are compared to two methods that make use of a baseline array: a one number scaling based algorithm and a method that uses a non-linear normalizing relation by comparing the variability and bias of an expression measure. Two publicly available datasets are used to carry out the comparisons. The simplest and quickest complete data method is found to perform favorably. AVAILABILITY: Software implementing all three of the complete data normalization methods is available as part of the R package Affy, which is a part of the Bioconductor project http://www.bioconductor.org. SUPPLEMENTARY INFORMATION: Additional figures may be found at http://www.stat.berkeley.edu/~bolstad/normalize/index.html

Phat--a gene finding program for Plasmodium falciparum.

We describe and assess the performance of the gene finding program pretty handy annotation tool (Phat) on sequence from the malaria parasite Plasmodium falciparum. Phat is based on a generalized hidden Markov model (GHMM) similar to the models used in GENSCAN, Genie and HMMgene. In a test set of 44 confirmed gene structures Phat achieves nucleotide-level sensitivity and specificity of greater than 95%, performing as well as the other P. falciparum gene finding programs Hexamer and GlimmerM. Phat is particularly useful for P. falciparum and other eukaryotes for which there are few gene finding programs available as it is distributed with code for retraining it on new organisms. Moreover, the full source code is freely available under the GNU General Public License, allowing for users to further develop and customize it.

Power and robustness of a score test for linkage analysis of quantitative traits using identity by descent data on sib pairs.

Identification of genes involved in complex traits by traditional (lod score) linkage analysis is difficult due to many complicating factors. An unfortunate drawback of non-parametric procedures in general, though, is their low power to detect genetic effects. Recently, Dudoit and Speed [2000] proposed using a (likelihood-based) score test for detecting linkage with IBD data on sib pairs. This method uses the likelihood for theta, the recombination fraction between a trait locus and a marker locus, conditional on the phenotypes of the two sibs to test the null hypothesis of no linkage (theta = (1/2)). Although a genetic model must be specified, the approach offers several advantages. This paper presents results of simulation studies characterizing the power and robustness properties of this score test for linkage, and compares the power of the test to the Haseman-Elston and modified Haseman-Elston tests. The score test is seen to have impressively high power across a broad range of true and assumed models, particularly under multiple ascertainment. Assuming an additive model with a moderate allele frequency, in the range of p = 0.2 to 0.5, along with heritability H = 0.3 and a moderate residual correlation rho = 0.2 resulted in a very good overall performance across a wide range of trait-generating models. Generally, our results indicate that this score test for linkage offers a high degree of protection against wrong assumptions due to its strong robustness when used with the recommended additive model.

Analysis of cDNA microarray images.

Microarrays are part of a new class of biotechnologies that allow the monitoring of expression levels for thousands of genes simultaneously. Image analysis is an important aspect of microarray experiments, one that can have a potentially large impact on subsequent analyses, such as clustering or the identification of differentially expressed genes. This paper reviews a number of existing image analysis methods used on cDNA microarray data. In particular, it describes and discusses the different segmentation and background adjustment methods. It was found that in some cases background adjustment can substantially reduce the precision--that is, increase the variability of low-intensity spot values. In contrast, the choice of segmentation procedure seems to have a smaller impact.

Microarray expression profiling identifies genes with altered expression in HDL-deficient mice.

Based on the assumption that severe alterations in the expression of genes known to be involved in high-density lipoprotein (HDL) metabolism may affect the expression of other genes, we screened an array of >5000 mouse expressed sequence tags for altered gene expression in the livers of two lines of mice with dramatic decreases in HDL plasma concentrations. Labeled cDNA from livers of apolipoprotein AI (apoAI)-knockout mice, scavenger receptor BI (SR-BI) transgenic mice, and control mice were cohybridized to microarrays. Two-sample t statistics were used to identify genes with altered expression levels in the knockout or transgenic mice compared with control mice. In the SR-BI group we found nine array elements representing at least five genes that were significantly altered on the basis of an adjusted P value < 0.05. In the apoAI-knockout group, eight array elements representing four genes were altered compared with the control group (adjusted P < 0.05). Several of the genes identified in the SR-BI transgenic suggest altered sterol metabolism and oxidative processes. These studies illustrate the use of multiple-testing methods for the identification of genes with altered expression in replicated microarray experiments.

Power of a score test for quantitative trait linkage analysis of relative pairs.

The score test of Dudoit and Speed [(2000) Biostatistics 1:1-26] to detect linkage between a trait locus and a marker locus, using identity by descent data on sib pairs, is extended to other types of relative pairs (grandparent/grandchild, avuncular, and half-sib relationships). The test is based on the likelihood of the recombination fraction theta between trait and marker loci, conditional on phenotypes of the relatives. We present results of simulation studies characterizing power and robustness properties of this linkage score test, and compare the power of the score test to that of the classical and modified Haseman-Elston tests. The score test has considerable power, particularly under sampling schemes where selection is on double probands. Use of a generic additive model [Goldstein et al., submitted] with allele frequency p = 0.2, heritability H = 0.3, and a moderate residual correlation of rho = 0.2 resulted in a very good overall performance across a wide range of trait-generating models.

The current state of multiple sclerosis genetic research.

INTRODUCTION: Multiple sclerosis (MS) is the most common genetic disease of the nervous system with onset usually in young adulthood. Four genome-wide searches in different Caucasian populations for MS susceptibility loci have been performed, but none reported any linkage at a level that would be regarded as significant according to current criteria. Significant linkage of MS to allelic variants of the major histocompatibility (MHC) locus on chromosome 6p21 has been established although its overall contribution to MS susceptibility has proven difficult to quantify. The objective of this review is not only to provide the reader with an update of MS genetics research, but also to provide a basic knowledge of the techniques being employed to map MS susceptibility genes. The different methodologies are discussed, and specific studies are reviewed in context. METHODS: This review is based on findings from original articles, however, the results of recent candidate gene studies are intended to update previous review articles. RESULTS: There remains no concrete non-MHC locus for MS, although there are enough findings of sufficient interest to warrant further investigation and optimism. Stratification of genome scan data based on MHC class II suggests that it interacts differentially with non-MHC loci and that it contributes moderately to disease susceptibility. Candidate gene studies have continued to return negative and ambiguous results, and follow-up fine mapping of suggestive linkages from the UK genome scan has proven unsuccessful in identifying significant linkages. Genetic analysis of crosses between mouse strains that are differentially susceptible to experimental allergic encephalomyelitis (EAE) has yielded linkages corresponding to putative MS susceptibility loci. However, recent successes in transgenic mice may provide an alternative to EAE, regarded by some as a poor model of MS. CONCLUSION: The first whole genome search for a common human disease was performed over five years ago, and it is now clear, from the lack success in this field, that the genetic complexity of these traits has been underestimated. The genome-wide searches for MS susceptibility genes have suffered from insufficient statistical power, which has probably been compounded by disease and genetic heterogeneity. Studies in isolated populations and better laboratory and clinical definitions of disease are both steps in the right direction to solving these problems. Not withstanding the negative effects of genetic heterogeneity, pooling of resources for meta-analyses may provide the increase in statistical power required for detection of loci that exert a moderate or small effect on disease predisposition.