A time-series analysis of altered histone H3 acetylation and gene expression during the course of MMAIII-induced malignant transformation of urinary bladder cells.

Our previous studies have shown that chronic exposure to low doses of monomethylarsonous acid (MMAIII) causes global histone acetylation dysregulation in urothelial cells (UROtsa cells) during the course of malignant transformation. To reveal the relationship between altered histone acetylation patterns and aberrant gene expression, more specifically, the carcinogenic relevance of these alterations, we performed a time-course analysis of the binding patterns of histone 3 lysine 18 acetylation (H3K18ac) across the genome and generated global gene-expression profiles from this UROtsa cell malignant transformation model. We showed that H3K18ac, one of the most significantly upregulated histone acetylation sites following MMAIII exposure, was enriched at gene promoter-specific regions across the genome and that MMAIII-induced upregulation of H3K18ac led to an altered binding pattern in a large number of genes that was most significant during the critical window for MMAIII-induced UROtsa cells' malignant transformation. Some genes identified as having a differential binding pattern with H3K18ac, acted as upstream regulators of critical gene networks with known functions in tumor development and progression. The altered H3K18ac binding patterns not only led to changes in expression of these directly affected upstream regulators but also resulted in gene-expression changes in their regulated networks. Collectively, our data suggest that MMAIII-induced alteration of histone acetylation patterns in UROtsa cells led to a time- and malignant stage-dependent aberrant gene-expression pattern, and that some gene regulatory networks were altered in accordance with their roles in carcinogenesis, probably contributing to MMAIII-induced urothelial cell malignant transformation and carcinogenesis.

Systemic manifestations of primary Sjögren's syndrome in the NOD.B10Sn-H2b/J mouse model.

Animal models that recapitulate human disease are crucial for the study of Sjögren's Syndrome (SS). While several SS mouse models exist, there are few primary SS (pSS) models that mimic systemic disease manifestations seen in humans. Similar to pSS patients, NOD.B10Sn-H2b/J (NOD.B10) mice develop exocrine gland disease and anti-nuclear autoantibodies. However, the disease kinetics and spectrum of extra-glandular disease remain poorly characterized in this model. Our objective was to characterize local and systemic SS manifestations in depth in NOD.B10 female mice at early and late disease time points. To this end, sera, exocrine tissue, lung, and kidney were analyzed. NOD.B10 mice have robust lymphocytic infiltration of salivary and lacrimal tissue. In addition, they exhibit significant renal and pulmonary inflammation. We identified numerous autoantibodies, including those directed against salivary proteins. In conclusion, the NOD.B10 model recapitulates both local and systemic pSS disease and represents an excellent model for translational studies.

Belief propagation in genotype-phenotype networks.

Graphical models have proven to be a valuable tool for connecting genotypes and phenotypes. Structural learning of phenotype-genotype networks has received considerable attention in the post-genome era. In recent years, a dozen different methods have emerged for network inference, which leverage natural variation that arises in certain genetic populations. The structure of the network itself can be used to form hypotheses based on the inferred direct and indirect network relationships, but represents a premature endpoint to the graphical analyses. In this work, we extend this endpoint. We examine the unexplored problem of perturbing a given network structure, and quantifying the system-wide effects on the network in a node-wise manner. The perturbation is achieved through the setting of values of phenotype node(s), which may reflect an inhibition or activation, and propagating this information through the entire network. We leverage belief propagation methods in Conditional Gaussian Bayesian Networks (CG-BNs), in order to absorb and propagate phenotypic evidence through the network. We show that the modeling assumptions adopted for genotype-phenotype networks represent an important sub-class of CG-BNs, which possess properties that ensure exact inference in the propagation scheme. The system-wide effects of the perturbation are quantified in a node-wise manner through the comparison of perturbed and unperturbed marginal distributions using a symmetric Kullback-Leibler divergence. Applications to kidney and skin cancer expression quantitative trait loci (eQTL) data from different mus musculus populations are presented. System-wide effects in the network were predicted and visualized across a spectrum of evidence. Sub-pathways and regions of the network responded in concert, suggesting co-regulation and coordination throughout the network in response to phenotypic changes. We demonstrate how these predicted system-wide effects can be examined in connection with estimated class probabilities for covariates of interest, e.g. cancer status. Despite the uncertainty in the network structure, we demonstrate the system-wide predictions are stable across an ensemble of highly likely networks. A software package, geneNetBP, which implements our approach, was developed in the R programming language.

Identification of consistent functional genetic modules.

It is often of scientific interest to find a set of genes that may represent an independent functional module or network, such as a functional gene expression module causing a biological response, a transcription regulatory network, or a constellation of mutations jointly causing a disease. In this paper we are specifically interested in identifying modules that control a particular outcome variable such as a disease biomarker. We discuss the statistical properties that functional networks should possess and introduce the concept of network consistency which should be satisfied by real functional networks of cooperating genes, and directly use the concept in the pathway discovery method we present. Our method gives superior performance for all but the simplest functional networks.

Wide-scale alterations in interchromosomal organization in breast cancer cells: defining a network of interacting chromosomes.

The interchromosomal spatial positionings of a subset of human chromosomes was examined in the human breast cell line MCF10A (10A) and its malignant counterpart MCF10CA1a (CA1a). The nine chromosomes selected (#1, 4, 11, 12, 15, 16, 18, 21 and X) cover a wide range in size and gene density and compose ∼40% of the total human genome. Radial positioning of the chromosome territories (CT) was size dependent with certain of the CT more peripheral in CA1a. Each CT was in close proximity (interaction) with a similar number of other CT except the inactive CTXi. It had lower levels of interchromosomal partners in 10A which increased strikingly in CA1a. Major alterations from 10A to CA1a were detected in the pairwise interaction profiles which were subdivided into five types of altered interaction profiles: overall increase, overall decrease, switching from 1 to ≥2, vice versa or no change. A global data mining program termed the chromatic median calculated the most probable overall association network for the entire subset of CT. This interchromosomal network was drastically altered in CA1a with only 1 of 20 shared connections. We conclude that CT undergo multiple and preferred interactions with other CT in the cell nucleus and form preferred-albeit probabilistic-interchromosomal networks. This network of interactions is highly altered in malignant human breast cells. It is intriguing to consider the relationship of these alterations to the corresponding changes in the gene expression program of these malignant cancer cells.

Arsenic responsive microRNAs in vivo and their potential involvement in arsenic-induced oxidative stress.

Arsenic exposure is postulated to modify microRNA (miRNA) expression, leading to changes of gene expression and toxicities, but studies relating the responses of miRNAs to arsenic exposure are lacking, especially with respect to in vivo studies. We utilized high-throughput sequencing technology and generated miRNA expression profiles of liver tissues from Sprague Dawley (SD) rats exposed to various concentrations of sodium arsenite (0, 0.1, 1, 10 and 100mg/L) for 60days. Unsupervised hierarchical clustering analysis of the miRNA expression profiles clustered the SD rats into different groups based on the arsenic exposure status, indicating a highly significant association between arsenic exposure and cluster membership (p-value of 0.0012). Multiple miRNA expressions were altered by arsenic in an exposure concentration-dependent manner. Among the identified arsenic-responsive miRNAs, several are predicted to target Nfe2l2-regulated antioxidant genes, including glutamate-cysteine ligase (GCL) catalytic subunit (GCLC) and modifier subunit (GCLM) which are involved in glutathione (GSH) synthesis. Exposure to low concentrations of arsenic increased mRNA expression for Gclc and Gclm, while high concentrations significantly reduced their expression, which were correlated to changes in hepatic GCL activity and GSH level. Moreover, our data suggested that other mechanisms, e.g., miRNAs, rather than Nfe2l2-signaling pathway, could be involved in the regulation of mRNA expression of Gclc and Gclm post-arsenic exposure in vivo. Together, our findings show that arsenic exposure disrupts the genome-wide expression of miRNAs in vivo, which could lead to the biological consequence, such as an altered balance of antioxidant defense and oxidative stress.

A novel characterization of the generalized family wise error rate using empirical null distributions.

We present a novel characterization of the generalized family wise error rate: kFWER. The interpretation allows researchers to view kFWER as a function of the test statistics rather than current methods based on p-values. Using this interpretation we present several theorems and methods (parametric and non-parametric) for estimating kFWER in various data settings. With this version of kFWER, researchers will have an estimate of kFWER in addition to knowing what tests are significant at the estimated kFWER. Additionally, we present methods that use empirical null distributions in place of parametric distributions in standard p-value kFWER controlling schemes. These advancements represent an improvement over common kFWER methods which are based on parametric assumptions and merely report the tests that are significant under a given value for kFWER.

Brain or strain? Symptoms alone do not distinguish physiologic concussion from cervical/vestibular injury.

OBJECTIVE: To compare symptoms in patients with physiologic postconcussion disorder (PCD) versus cervicogenic/vestibular PCD. We hypothesized that most symptoms would not be equivalent. In particular, we hypothesized that cognitive symptoms would be more often associated with physiologic PCD. DESIGN: Retrospective review of symptom reports from patients who completed a 22-item symptom questionnaire. SETTING: University-based concussion clinic. PATIENTS: Convenience sample of 128 patients who had symptoms after head injury for more than 3 weeks and who had provocative treadmill exercise testing. INDEPENDENT VARIABLES: Subjects were classified as either physiologic PCD (abnormal treadmill performance and a normal cervical/vestibular physical examination) or cervicogenic/vestibular PCD (CGV, normal treadmill performance, and an abnormal cervical/vestibular physical examination). MAIN OUTCOME MEASURES: Self-reported symptoms. Univariate and multivariate methods, including t tests, tests of equivalence, a logistic regression model, k-nearest neighbor analysis, multidimensional scaling, and principle components analysis were used to see whether symptoms could distinguish PCD from CGV. RESULTS: None of the statistical methods used to analyze self-reported symptoms was able to adequately distinguish patients with PCD from patients with CGV. CONCLUSIONS: Symptoms after head injury, including cognitive symptoms, have traditionally been ascribed to brain injury, but they do not reliably discriminate between physiologic PCD and cervicogenic/vestibular PCD. Clinicians should consider specific testing of exercise tolerance and perform a physical examination of the cervical spine and the vestibular/ocular systems to determine the etiology of postconcussion symptoms. CLINICAL RELEVANCE: Symptoms after head injury, including cognitive symptoms, do not discriminate between concussion and cervical/vestibular injury.

The Collaborative Cross, a community resource for the genetic analysis of complex traits.

The goal of the Complex Trait Consortium is to promote the development of resources that can be used to understand, treat and ultimately prevent pervasive human diseases. Existing and proposed mouse resources that are optimized to study the actions of isolated genetic loci on a fixed background are less effective for studying intact polygenic networks and interactions among genes, environments, pathogens and other factors. The Collaborative Cross will provide a common reference panel specifically designed for the integrative analysis of complex systems and will change the way we approach human health and disease.

Differential copy number aberrations in novel candidate genes associated with progression from in situ to invasive ductal carcinoma of the breast.

Only a minority of intraductal carcinomas of the breast give rise to stromally invasive disease. We microdissected 206 paraffin blocks representing 116 different cases of low-grade ductal carcinoma in situ (DCIS). Fifty-five were pure DCIS (PD) cases without progression to invasive carcinoma. Sixty-one cases had a small invasive component. DNA was extracted from microdissected sections and hybridized to high-density bacterial artificial chromosome arrays. Array comparative genomic hybridization analysis of 118 hybridized DNA samples yielded data on 69 samples that were suitable for further statistical analysis. This cohort included 20 pure DCIS cases, 25 mixed DCIS (MD), and 24 mixed invasive carcinoma samples. PD cases had a higher frequency of DNA copy number changes than MD cases, and the latter had similar DNA profiles compared to paired invasive carcinomas. Copy number changes on 13 chromosomal arms occurred at different rates in PD versus MD lesions. Eight of 19 candidate genes residing at those loci were confirmed to have differential copy number changes by quantitative PCR. NCOR2/SMRT and NR4A1 (both on 12q), DYNLRB2 (16q), CELSR1, UPK3A, and ST13 (all on 22q) were more frequently amplified in PD. Moreover, NCOR2, NR4A1, and DYNLRB2 showed more frequent copy number losses in MD. GRAP2 (22q) was more often amplified in MD, whereas TAF1C (16q) was more commonly deleted in PD. A multigene model comprising these candidate genes discriminated between PD and MD lesions with high accuracy. These findings suggest that the propensity to invade the stroma may be encoded in the genome of intraductal carcinomas.

The genomic relationship between primary breast carcinomas and their nodal metastases.

We screened the whole tumor genome to identify DNA copy number gains and losses that discriminate between primary breast carcinomas (MP) and their nodal metastases (ML). Six candidate genes were confirmed by quantitative PCR to have differentially distributed copy number changes. Three of the genes (ERRγ, DDX6, and TIAM1) were more commonly amplified in nodal metastases. Principal component analysis revealed that MP-ML pairs varied markedly in their genomic divergence. The latter was larger in PR-negative tumors. Nodal metastases may form early or late in the development of breast carcinomas and PR-negative tumors may metastasize earlier or are genomically less stable.

A new normalizing algorithm for BAC CGH arrays with quality control metrics.

The main focus in pin-tip (or print-tip) microarray analysis is determining which probes, genes, or oligonucleotides are differentially expressed. Specifically in array comparative genomic hybridization (aCGH) experiments, researchers search for chromosomal imbalances in the genome. To model this data, scientists apply statistical methods to the structure of the experiment and assume that the data consist of the signal plus random noise. In this paper we propose "SmoothArray", a new method to preprocess comparative genomic hybridization (CGH) bacterial artificial chromosome (BAC) arrays and we show the effects on a cancer dataset. As part of our R software package "aCGHplus," this freely available algorithm removes the variation due to the intensity effects, pin/print-tip, the spatial location on the microarray chip, and the relative location from the well plate. removal of this variation improves the downstream analysis and subsequent inferences made on the data. Further, we present measures to evaluate the quality of the dataset according to the arrayer pins, 384-well plates, plate rows, and plate columns. We compare our method against competing methods using several metrics to measure the biological signal. With this novel normalization algorithm and quality control measures, the user can improve their inferences on datasets and pinpoint problems that may arise in their BAC aCGH technology.

Estimating the arm-wise false discovery rate in array comparative genomic hybridization experiments.

Array Comparative Genomic Hybridization (aCGH) is an array-based technology which provides simultaneous spot assays of relative genetic abundance (RGA) levels at multiple sites across the genome. These spot assays are spatially correlated with respect to genomic location and, as a result, the univariate tests conducted using data generated from these spot assays are also spatially correlated. In the context of multiple hypothesis testing, this spatial correlation complicates the question of how best to define a 'discovery' and consequently, how best to estimate the false discovery rate (FDR) corresponding to a given rejection region. One can quantify the number of discoveries as the total number of spots for which the spot-based univariate test statistic falls within a given rejection region. Under this spot-based method, separate but correlated discoveries are identified. We show via a simulation study that the method of Benjamini and Hochberg (1995) can provide a reasonable estimate of the spot-wise FDR, but these results require that the simulated spot assays are categorized as true or false discoveries in a particular way. However, laboratory researchers may actually be interested in estimating a 'regional' FDR, rather than a 'local' spot-wise FDR. We describe an example of such circumstances, and present a method for estimating the (chromosome) arm-wise False Discovery Rate. In this framework, one can quantify the number of discoveries as the total number of chromosome arms for which at least one spot-based test statistic falls into a given rejection region. Defining the discoveries in this way, both the biological and testing objectives coincide. We provide results from a series of simulations which involved the analysis of preferentially re-sampled spot assay values from a real aCGH dataset.

The Complexity of the Spanish Subjunctive in Bilingual Children with SLI.

This study investigated the use of the Spanish subjunctive in bilingual children with and without specific language impairments (SLI). Using an elicited production task, we examined: (1) the potential of the subjunctive as a grammatical marker of SLI in Spanish-English bilingual children, (2) the extent to which degree of bilingualism affects performance, and (3) the specific patterns of errors across groups. The participants in this study were 16 children with SLI and 16 typically developing children (TD) matched on age, English language proficiency, and mother's education level. Bilingual children were selected based on their English proficiency and were classified either as Spanish-dominant children with intermediate English proficiency (asymmetrical bilinguals, AsyBi), or near-balanced bilinguals (BalBi). A completion task elicited the subjunctive in complement, purpose and temporal clauses. Results suggest that (1) level of bilingual proficiency, language clinical status, and age predicted of the accurate production of the subjunctive, (2) temporal clauses might have a better potential to discriminate between TD children and children with SLI in bilingual settings, and (3) tense underspecification errors were common in children with SLI. This study provides general support for grammatically targeted approaches to assessment in bilingual populations, and for theoretical approaches that link SLI to tense deficits.

Multi-generational impacts of arsenic exposure on genome-wide DNA methylation and the implications for arsenic-induced skin lesions.

As a nonmutagenic human carcinogen, arsenic (As)'s carcinogenic activity is likely the result of epigenetic changes, particularly alterations in DNA methylation. While increasing studies indicate a potentially important role for timing of As exposure on DNA methylation patterns and the subsequent differential risks for As toxicity and carcinogenesis, there is a lack of research that tackles these critical questions, particularly in human based populations. Here we reported a family-based study including three generations, in which each generation living in the same household had a distinctive timing of As exposure: in adulthood, in utero and during early childhood, and in germlines exposure for grandparents, parents, and grandchildren, respectively. We generated genome-wide DNA methylation data for 18 As-exposed families, nine control families, as well as 18 arsenical skin lesion patients. Our analysis showed that As exposure may leave detectable DNA methylation changes even though exposure occurred decades ago, and the most significant changes of global DNA methylation were observed among patients afflicted with arsenical skin lesions. As exposure across generations shared common differentially methylated DNA loci and regions (744 DML and 15 DMRs) despite the distinctive exposure timing in each generation. Importantly, based on these DML, clustering analysis grouped skin lesion patients together with grandparents in exposed families in the same cluster, separated from grandparents in control families. Further analysis identified a number of DML and several molecular pathways that were significantly distinguished between controls, exposed populations, as well as skin lesion patients. Finally, our exploratory analysis suggested that some of these DML altered by As exposure, may have the potential to be inherited affecting not only those directly exposed but also later generations. Together, our results suggest that common DML and/or DMRs associated with an increased risk for disease development could be identified regardless of when exposure to As occurred during their life span, and thus may be able to serve as biomarkers for identifying individuals at risk for As-induced skin lesions and possible cancers.

Putative null distributions corresponding to tests of differential expression in the Golden Spike dataset are intensity dependent.

BACKGROUND: We provide a re-analysis of the Golden Spike dataset, a first generation "spike-in" control microarray dataset. The original analysis of the Golden Spike dataset was presented in a manuscript by Choe et al. and raised questions concerning the performance of several statistical methods for the control of the false discovery rate (across a set of tests for differential expression). These original findings are now in question as it has been reported that the p-values associated with the tests of differential expression for null probesets (i.e., probesets designed to be fold change 1 across the two arms of the experiment) are not uniformly distributed. Two recent publications have speculated as to the reasons the null distributions are non-uniform. A publication by Dabney and Storey concludes that the non-uniform distributions of null p-values are the direct consequence of an experimental design which requires technical replicates to approximate biological replicates. Irizarry et al. identify four characteristics of the feature level data (three related to experimental design and one artifact). Irizarry et al. argue that the four observed characteristics imply that the assumptions common to most pre-processing algorithms are not satisfied and hence the expression measure methodologies considered by Choe et al. are likely to be flawed. RESULTS: We replicate and extend the analyses of Dabney and Storey and present our results in the context of a two stage analysis. We provide evidence that the Stage I pre-processing algorithms considered in Dabney and Storey fail to provide expression values that are adequately centered or scaled. Furthermore, we demonstrate that the distributions of the p-values, test statistics, and probabilities associated with the relative locations and variabilities of the Stage II expression values vary with signal intensity. We provide diagnostic plots and a simple logistic regression based test statistic to detect these intensity related defects in the processed data. CONCLUSION: We agree with Dabney and Storey that the null p-values considered in Choe et al. are indeed non-uniform. We also agree with the conclusion that, given current pre-processing technologies, the Golden Spike dataset should not serve as a reference dataset to evaluate false discovery rate controlling methodologies. However, we disagree with the assessment that the non-uniform p-values are merely the byproduct of testing for differential expression under the incorrect assumption that chip data are approximate to biological replicates. Whereas Dabney and Storey attribute the non-uniform p-values to violations of the Stage II model assumptions, we provide evidence that the non-uniformity can be attributed to the failure of the Stage I analyses to correct for systematic biases in the raw data matrix. Although we do not speculate as to the root cause of these systematic biases, the observations made in Irizarry et al. appear to be consistent with our findings. Whereas Irizarry et al. describe the effect of the experimental design on the feature level data, we consider the effect on the underlying multivariate distribution of putative null p-values. We demonstrate that the putative null distributions corresponding to the pre-processing algorithms considered in Choe et al. are all intensity dependent. This dependence serves to invalidate statistical inference based upon standard two sample test statistics. We identify a flaw in the characterization of the appropriate "null" probesets described in Choe et al. and we provide a corrected analysis which reduces (but does not eliminate) the intensity dependent effects.

Challenges in array comparative genomic hybridization for the analysis of cancer samples.

PURPOSE: To address some of the challenges facing the incorporation of array comparative genomic hybridization technology as a clinical tool, including archived tumor tissue, tumor heterogeneity, DNA quality and quantity, and array comparative genomic hybridization platform selection and performance. METHODS: Experiments were designed to assess the impact of DNA source (e.g., archival material), quantity, and amplification on array comparative genomic hybridization results. Two microdissection methods were used to isolate tumor cells to minimize heterogeneity. These data and other data sets were used in a further performance comparison of two commonly used array comparative genomic hybridization platforms: bacterial artificial chromosome (Roswell Park Cancer Institute) and oligonucleotide (Agilent Technologies, Santa Clara, CA). RESULTS: Array comparative genomic hybridization data from as few as 100 formalin-fixed, paraffin-embedded cells isolated by laser capture microdissection and amplified were remarkably similar to array comparative genomic hybridization copy number alterations detected in the bulk (unamplified) population. Manual microdissection from frozen sections provided a rapid and inexpensive means to isolate tumor from adjacent DNA for amplification and array comparative genomic hybridization. Whole genome amplification introduced no appreciable allele bias on array comparative genomic hybridization. The array comparative genomic hybridization results provided by the bacterial artificial chromosome and Agilent platforms were concordant in general, but bacterial artificial chromosome array comparative genomic hybridization showed far fewer outliers and overall less technical noise, which could adversely affect the statistical interpretation of the data. CONCLUSIONS: This study demonstrates that copy number alterations can be robustly and reproducibly detected by array comparative genomic hybridization in DNA isolated from challenging tumor types and sources, including archival materials, low DNA yield, and heterogeneous tissues. Furthermore, bacterial artificial chromosome array comparative genomic hybridization offers the advantage over the Agilent oligonucleotide platform of presenting fewer outliers, which could affect data interpretation.

Loss of breast cancer metastasis suppressor 1 protein expression predicts reduced disease-free survival in subsets of breast cancer patients.

PURPOSE: This study aims to determine the effect of loss of breast cancer metastasis suppressor 1 (BRMS1) protein expression on disease-free survival in breast cancer patients stratified by estrogen receptor (ER), progesterone receptor (PR), or HER2 status, and to determine whether loss of BRMS1 protein expression correlated with genomic copy number changes. EXPERIMENTAL DESIGN: A tissue microarray immunohistochemical analysis was done on tumors of 238 newly diagnosed breast cancer patients who underwent surgery at the Cleveland Clinic between January 1, 1995 and December 31, 1996, and a comparison was made with 5-year clinical follow-up data. Genomic copy number changes were determined by array-based comparative genomic hybridization in 47 breast cancer cases from this population and compared with BRMS1 staining. RESULTS: BRMS1 protein expression was lost in nearly 25% of cases. Patients with tumors that were PR negative (P=0.006) or HER2 positive (P=0.039) and <50 years old at diagnosis (P=0.02) were more likely to be BRMS1 negative. No overall correlation between BRMS1 staining and disease-free survival was observed. A significant correlation, however, was seen between loss of BRMS1 protein expression and reduced disease-free survival when stratified by either loss of ER (P=0.008) or PR (P=0.029) or HER2 overexpression (P=0.026). Overall, there was poor correlation between BRMS1 protein staining and copy number status. CONCLUSIONS: These data suggest a mechanistic relationship between BRMS1 expression, hormone receptor status, and HER2 growth factor. BRMS1 staining could potentially be used in patient stratification in conjunction with other prognostic markers. Further, mechanisms other than genomic deletion account for loss of BRMS1 gene expression in breast tumors.

aCGH local copy number aberrations associated with overall copy number genomic instability in colorectal cancer: coordinate involvement of the regions including BCR and ABL.

In order to identify small regions of the genome whose specific copy number alteration is associated with high genomic instability in the form of overall genome-wide copy number aberrations, we have analyzed array-based comparative genomic hybridization (aCGH) data from 33 sporadic colorectal carcinomas. Copy number changes of a small number of specific regions were significantly correlated with elevated overall amplifications and deletions scattered throughout the entire genome. One significant region at 9q34 includes the c-ABL gene. Another region spanning 22q11-q13 includes the breakpoint cluster region (BCR) of the Philadelphia chromosome. Coordinate 22q11-q13 alterations were observed in 9 of 11 tumors with the 9q34 alteration. Additional regions on 1q and 14q were associated with overall genome-wide copy number changes, while copy number aberrations on chromosome 7p, 7q, and 13q21.1-q31.3 were found associated with this instability only in tumors from patients with a smoking history. Our analysis demonstrates there are a small number of regions of the genome where gain or loss is commonly associated with a tumor's overall level of copy number aberrations. Our finding BCR and ABL located within two of the instability-associated regions, and the involvement of these two regions occurring coordinately, suggests a system akin to the BCR-ABL translocation of CML may be involved in genomic instability in about one-third of human colorectal carcinomas.

Myd88 is required for disease development in a primary Sjögren's syndrome mouse model.

Sjögren's syndrome (SS) is an autoimmune disease that often results in diminished exocrine gland function. SS patients also experience systemic disease manifestations, including hypergammaglobulinemia and pulmonary and renal pathoses. MyD88 is a ubiquitously expressed adaptor molecule used by all immune cells that is required for IL-1 receptor (IL-1R), IL-18R, and most TLR signaling. The precise role of MyD88 in SS has not been evaluated, although this adaptor is critical for development of lupus, a related autoimmune disease. This study tested the hypothesis that Myd88-mediated signaling is required for local and systemic SS manifestations. To this end, we generated NOD.B10Sn-H2b /J (NOD.B10) mice that are deficient in Myd88 (NOD.B10 Myd88-/- ). We found that NOD.B10 animals that lack Myd88 show reduced exocrine and extraglandular inflammation. Moreover, these animals are protected from loss of salivary flow. Splenocytes from NOD.B10 Myd88-/- mice did not up-regulate activation markers or secrete IL-6 in response to a Myd88-dependent agonist, although BCR signaling remained intact. Finally, IgM, IgG, and anti-nuclear autoantibodies were reduced in NOD.B10 Myd88-/- mice compared with the parental strain. These data demonstrate that Myd88 is a crucial mediator of local and systemic SS disease manifestations.