BASE--2nd generation software for microarray data management and analysis

Clinical associations of ESR2 (estrogen receptor beta) expression across thousands of primary breast tumors

Estrogen receptor alpha (ERα, encoded by ESR1) is a well-characterized transcription factor expressed in more than 75% of breast tumors and is the key biomarker to direct endocrine therapies. On the other hand, much less is known about estrogen receptor beta (ERβ, encoded by ESR2) and its importance in cancer. Previous studies had some disagreement, however most reports suggested a more favorable prognosis for patients with high ESR2 expression. To add further clarity to ESR2 in breast cancer, we interrogated a large population-based cohort of primary breast tumors (n = 3207) from the SCAN-B study. RNA-seq shows ESR2 is expressed at low levels overall with a slight inverse correlation to ESR1 expression (Spearman R = −0.18, p = 2.2e−16), and highest ESR2 expression in the basal- and normal-like PAM50 subtypes. ESR2-high tumors had favorable overall survival (p = 0.006), particularly in subgroups receiving endocrine therapy (p = 0.03) and in triple-negative breast cancer (p = 0.01). These results were generally robust in multivariable analyses accounting for patient age, tumor size, node status, and grade. Gene modules consistent with immune response were associated to ESR2-high tumors. Taken together, our results indicate that ESR2 is generally expressed at low levels in breast cancer but associated with improved overall survival and may be related to immune response modulation.

Minimizing inequality in access to precision medicine in breast cancer by real-time population-based molecular analysis in the SCAN-B initiative

BACKGROUND

Selection of systemic therapy for primary breast cancer is currently based on clinical biomarkers along with stage. Novel genomic tests are continuously being introduced as more precise tools for guidance of therapy, although they are often developed for specific patient subgroups. The Sweden Cancerome Analysis Network - Breast (SCAN-B) initiative aims to include all patients with breast cancer for tumour genomic analysis, and to deliver molecular subtype and mutational data back to the treating physician.

METHODS

An infrastructure for collection of blood and fresh tumour tissue from all patients newly diagnosed with breast cancer was set up in 2010, initially including seven hospitals within the southern Sweden regional catchment area, which has 1.8 million inhabitants. Inclusion of patients was implemented into routine clinical care, with collection of tumour tissue at local pathology departments for transport to the central laboratory, where routines for rapid sample processing, RNA sequencing and biomarker reporting were developed.

RESULTS

More than 10 000 patients from nine hospitals have currently consented to inclusion in SCAN-B with high (90 per cent) inclusion rates from both university and secondary hospitals. Tumour samples and successful RNA sequencing are being obtained from more than 70 per cent of patients, showing excellent representation compared with the national quality registry as a truly population-based cohort. Molecular biomarker reports can be delivered to multidisciplinary conferences within 1 week.

CONCLUSION

Population-based collection of fresh tumour tissue is feasible given a decisive joint effort between academia and collaborative healthcare groups, and with governmental support. An infrastructure for genomic analysis and prompt data output paves the way for novel systemic therapy for patients from all hospitals, irrespective of size and location.

Daily Rhythms of TNFα Expression and Food Intake Regulate Synchrony of Plasmodium Stages with the Host Circadian Cycle

The Plasmodium cell cycle, wherein millions of parasites differentiate and proliferate, occurs in synchrony with the vertebrate host's circadian cycle. The underlying mechanisms are unknown. Here we addressed this question in a mouse model of Plasmodium chabaudi infection. Inflammatory gene expression and carbohydrate metabolism are both enhanced in interferon-γ (IFNγ)-primed leukocytes and liver cells from P. chabaudi-infected mice. Tumor necrosis factor α (TNFα) expression oscillates across the host circadian cycle, and increased TNFα correlates with hypoglycemia and a higher frequency of non-replicative ring forms of trophozoites. Conversely, parasites proliferate and acquire biomass during food intake by the host. Importantly, cyclic hypoglycemia is attenuated and synchronization of P. chabaudi stages is disrupted in IFNγ-/-, TNF receptor-/-, or diabetic mice. Hence, the daily rhythm of systemic TNFα production and host food intake set the pace for Plasmodium synchronization with the host's circadian cycle. This mechanism indicates that Plasmodium parasites take advantage of the host's feeding habits.

Cell-Type-Specific Gene Programs of the Normal Human Nephron Define Kidney Cancer Subtypes

Comprehensive transcriptome studies of cancers often rely on corresponding normal tissue samples to serve as a transcriptional reference. In this study, we performed in-depth analyses of normal kidney tissue transcriptomes from the TCGA and demonstrate that the histological variability in cellularity, inherent in the kidney architecture, lead to considerable transcriptional differences between samples. This should be considered when comparing expression profiles of normal and cancerous kidney tissues. We exploited these differences to define renal-cell-specific gene signatures and used these as a framework to analyze renal cell carcinoma (RCC) ontogeny. Chromophobe RCCs express FOXI1-driven genes that define collecting duct intercalated cells, whereas HNF-regulated genes, specific for proximal tubule cells, are an integral part of clear cell and papillary RCC transcriptomes. These networks may be used as a framework for understanding the interplay between genomic changes in RCC subtypes and the lineage-defining regulatory machinery of their non-neoplastic counterparts.

Assessment of early response biomarkers in relation to long-term survival in patients with HER2-negative breast cancer receiving neoadjuvant chemotherapy plus bevacizumab: Results from the Phase II PROMIX trial

Pathologic complete response (pCR) is a predictor for favorable outcome after neoadjuvant treatment in early breast cancer. Modulation of gene expression may also provide early readouts of biological activity and prognosis, offering the possibility for timely response-guided treatment adjustment. The role of early transcriptional changes in predicting response to neoadjuvant chemotherapy plus bevacizumab was investigated. One-hundred-and-fifty patients with large, operable and locally advanced HER2-negative breast cancer received epirubicin and docetaxel, with the addition of bevacizumab. Patients underwent tumor biopsies at baseline, after Cycle 2 and at the time of surgery. The primary end point, pCR, and its relation with the secondary endpoints event-free survival (EFS), overall survival (OS) and gene expression profiles, are reported. The pCR rate was 13% (95% CI 8.6-20.2), with significantly more pCRs among triple-negative [28% (95% CI 14.8-45.4)] than among hormone receptor positive (HR+) tumors [9% (95% CI 4.6-16.3); (OR = 3.9 [CI = 1.5-10.3])]. pCR rates were not associated with EFS or OS. PAM50 subtypes significantly changed after Cycle 2 (p = 0.03) and an index of absolute changes in PAM50 correlations between these time-points was associated with EFS [HR = 0.62 (CI = 0.3-1.1)]. In univariable analyses, signatures for angiogenesis, proliferation, estrogen receptor signaling, invasion and metastasis, and immune response, measured after Cycle 2, were associated with pCR in HR+ tumors. Evaluation of changes in molecular subtypes and other signatures early in the course of neoadjuvant treatment may be predictive of pCR and EFS. These factors may help guide further treatment and should be considered when designing neoadjuvant trials.

Hypoxia regulates global membrane protein endocytosis through caveolin-1 in cancer cells

Hypoxia promotes tumour aggressiveness and resistance of cancers to oncological treatment. The identification of cancer cell internalizing antigens for drug targeting to the hypoxic tumour niche remains a challenge of high clinical relevance. Here we show that hypoxia down-regulates the surface proteome at the global level and, more specifically, membrane proteome internalization. We find that hypoxic down-regulation of constitutive endocytosis is HIF-independent, and involves caveolin-1-mediated inhibition of dynamin-dependent, membrane raft endocytosis. Caveolin-1 overexpression inhibits protein internalization, suggesting a general negative regulatory role of caveolin-1 in endocytosis. In contrast to this global inhibitory effect, we identify several proteins that can override caveolin-1 negative regulation, exhibiting increased internalization at hypoxia. We demonstrate antibody-mediated cytotoxin delivery and killing specifically of hypoxic cells through one of these proteins, carbonic anhydrase IX. Our data reveal that caveolin-1 modulates cell-surface proteome turnover at hypoxia with potential implications for specific targeting of the hypoxic tumour microenvironment.

Hypoxia promotes tumour aggressiveness and resistance of cancers to oncological treatment. Here, the authors show that caveolin-1 can down-regulate global membrane protein endocytosis in hypoxic cells with potential implications for targeting the hypoxic 3microenvironment of aggressive tumours.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

BACKGROUND

Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD.

METHODS

CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response.

DISCUSSION

From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research.

TRIAL REGISTRATION

ClinicalTrials.gov identifier NCT01655706 . Registered July 27, 2012.

SaDA: From Sampling to Data Analysis-An Extensible Open Source Infrastructure for Rapid, Robust and Automated Management and Analysis of Modern Ecological High-Throughput Microarray Data

One of the most crucial characteristics of day-to-day laboratory information management is the collection, storage and retrieval of information about research subjects and environmental or biomedical samples. An efficient link between sample data and experimental results is absolutely important for the successful outcome of a collaborative project. Currently available software solutions are largely limited to large scale, expensive commercial Laboratory Information Management Systems (LIMS). Acquiring such LIMS indeed can bring laboratory information management to a higher level, but most of the times this requires a sufficient investment of money, time and technical efforts. There is a clear need for a light weighted open source system which can easily be managed on local servers and handled by individual researchers. Here we present a software named SaDA for storing, retrieving and analyzing data originated from microorganism monitoring experiments. SaDA is fully integrated in the management of environmental samples, oligonucleotide sequences, microarray data and the subsequent downstream analysis procedures. It is simple and generic software, and can be extended and customized for various environmental and biomedical studies.

Systemic Monocytic-MDSCs Are Generated from Monocytes and Correlate with Disease Progression in Breast Cancer Patients

Myeloid-derived suppressor cells (MDSCs) are highly immunosuppressive myeloid cells, which increase in cancer patients. The molecular mechanism behind their generation and function is unclear. Whereas granulocytic-MDSCs correlate with poor overall survival in breast cancer, the presence and relevance of monocytic-MDSCs (Mo-MDSCs) is unknown. Here we report for the first time an enrichment of functional blood Mo-MDSCs in breast cancer patients before they acquire a typical Mo-MDSC surface phenotype. A clear population of Mo-MDSCs with the typical cell surface phenotype (CD14(+)HLA-DR(low/-)CD86(low/-)CD80(low/-)CD163(low/-)) increased significantly first during disease progression and correlated to metastasis to lymph nodes and visceral organs. Furthermore, monocytes, comprising the Mo-MDSC population, from patients with metastatic breast cancer resemble the reprogrammed immunosuppressive monocytes in patients with severe infections, both by their surface and functional phenotype but also at their molecular gene expression profile. Our data suggest that monitoring the Mo-MDSC levels in breast cancer patients may represent a novel and simple biomarker for assessing disease progression.

Loss of CITED1, an MITF regulator, drives a phenotype switch in vitro and can predict clinical outcome in primary melanoma tumours

CITED1 is a non-DNA binding transcriptional co-regulator whose expression can distinguish the ‘proliferative’ from ‘invasive’ signature in the phenotype-switching model of melanoma. We have found that, in addition to other ‘proliferative’ signature genes, CITED1 expression is repressed by TGFβ while the ‘invasive’ signature genes are upregulated. In agreement, CITED1 positively correlates with MITF expression and can discriminate the MITF-high/pigmentation tumour molecular subtype in a large cohort (120) of melanoma cell lines. Interestingly, CITED1 overexpression significantly suppressed MITF promoter activation, mRNA and protein expression levels while MITF was transiently upregulated following siRNA mediated CITED1 silencing. Conversely, MITF siRNA silencing resulted in CITED1 downregulation indicating a reciprocal relationship. Whole genome expression analysis identified a phenotype shift induced by CITED1 silencing and driven mainly by expression of MITF and a cohort of MITF target genes that were significantly altered. Concomitantly, we found changes in the cell-cycle profile that manifest as transient G1 accumulation, increased expression of CDKN1A and a reduction in cell viability. Additionally, we could predict survival outcome by classifying primary melanoma tumours using our in vitro derived ‘CITED1-silenced’ gene expression signature. We hypothesize that CITED1 acts a regulator of MITF, functioning to maintain MITF levels in a range compatible with tumourigenesis.

The Sweden Cancerome Analysis Network - Breast (SCAN-B) Initiative: a large-scale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine

BACKGROUND

Breast cancer exhibits significant molecular, pathological, and clinical heterogeneity. Current clinicopathological evaluation is imperfect for predicting outcome, which results in overtreatment for many patients, and for others, leads to death from recurrent disease. Therefore, additional criteria are needed to better personalize care and maximize treatment effectiveness and survival.

METHODS

To address these challenges, the Sweden Cancerome Analysis Network - Breast (SCAN-B) consortium was initiated in 2010 as a multicenter prospective study with longsighted aims to analyze breast cancers with next-generation genomic technologies for translational research in a population-based manner and integrated with healthcare; decipher fundamental tumor biology from these analyses; utilize genomic data to develop and validate new clinically-actionable biomarker assays; and establish real-time clinical implementation of molecular diagnostic, prognostic, and predictive tests. In the first phase, we focus on molecular profiling by next-generation RNA-sequencing on the Illumina platform.

RESULTS

In the first 3 years from 30 August 2010 through 31 August 2013, we have consented and enrolled 3,979 patients with primary breast cancer at the seven hospital sites in South Sweden, representing approximately 85% of eligible patients in the catchment area. Preoperative blood samples have been collected for 3,942 (99%) patients and primary tumor specimens collected for 2,929 (74%) patients. Herein we describe the study infrastructure and protocols and present initial proof of concept results from prospective RNA sequencing including tumor molecular subtyping and detection of driver gene mutations. Prospective patient enrollment is ongoing.

CONCLUSIONS

We demonstrate that large-scale population-based collection and RNA-sequencing analysis of breast cancer is feasible. The SCAN-B Initiative should significantly reduce the time to discovery, validation, and clinical implementation of novel molecular diagnostic and predictive tests. We welcome the participation of additional comprehensive cancer treatment centers.

TRIAL REGISTRATION

ClinicalTrials.gov identifier NCT02306096.

VectorBase: an updated bioinformatics resource for invertebrate vectors and other organisms related with human diseases

VectorBase is a National Institute of Allergy and Infectious Diseases supported Bioinformatics Resource Center (BRC) for invertebrate vectors of human pathogens. Now in its 11th year, VectorBase currently hosts the genomes of 35 organisms including a number of non-vectors for comparative analysis. Hosted data range from genome assemblies with annotated gene features, transcript and protein expression data to population genetics including variation and insecticide-resistance phenotypes. Here we describe improvements to our resource and the set of tools available for interrogating and accessing BRC data including the integration of Web Apollo to facilitate community annotation and providing Galaxy to support user-based workflows. VectorBase also actively supports our community through hands-on workshops and online tutorials. All information and data are freely available from our website at https://www.vectorbase.org/.

A digital repository with an extensible data model for biobanking and genomic analysis management

Motivation

Molecular biology laboratories require extensive metadata to improve data collection and analysis. The heterogeneity of the collected metadata grows as research is evolving in to international multi-disciplinary collaborations and increasing data sharing among institutions. Single standardization is not feasible and it becomes crucial to develop digital repositories with flexible and extensible data models, as in the case of modern integrated biobanks management.

Results

We developed a novel data model in JSON format to describe heterogeneous data in a generic biomedical science scenario. The model is built on two hierarchical entities: processes and events, roughly corresponding to research studies and analysis steps within a single study. A number of sequential events can be grouped in a process building up a hierarchical structure to track patient and sample history. Each event can produce new data. Data is described by a set of user-defined metadata, and may have one or more associated files. We integrated the model in a web based digital repository with a data grid storage to manage large data sets located in geographically distinct areas. We built a graphical interface that allows authorized users to define new data types dynamically, according to their requirements. Operators compose queries on metadata fields using a flexible search interface and run them on the database and on the grid. We applied the digital repository to the integrated management of samples, patients and medical history in the BIT-Gaslini biobank. The platform currently manages 1800 samples of over 900 patients. Microarray data from 150 analyses are stored on the grid storage and replicated on two physical resources for preservation. The system is equipped with data integration capabilities with other biobanks for worldwide information sharing.

Conclusions

Our data model enables users to continuously define flexible, ad hoc, and loosely structured metadata, for information sharing in specific research projects and purposes. This approach can improve sensitively interdisciplinary research collaboration and allows to track patients' clinical records, sample management information, and genomic data. The web interface allows the operators to easily manage, query, and annotate the files, without dealing with the technicalities of the data grid.

STATegra EMS: an Experiment Management System for complex next-generation omics experiments

High-throughput sequencing assays are now routinely used to study different aspects of genome organization. As decreasing costs and widespread availability of sequencing enable more laboratories to use sequencing assays in their research projects, the number of samples and replicates in these experiments can quickly grow to several dozens of samples and thus require standardized annotation, storage and management of preprocessing steps. As a part of the STATegra project, we have developed an Experiment Management System (EMS) for high throughput omics data that supports different types of sequencing-based assays such as RNA-seq, ChIP-seq, Methyl-seq, etc, as well as proteomics and metabolomics data. The STATegra EMS provides metadata annotation of experimental design, samples and processing pipelines, as well as storage of different types of data files, from raw data to ready-to-use measurements. The system has been developed to provide research laboratories with a freely-available, integrated system that offers a simple and effective way for experiment annotation and tracking of analysis procedures.

Confero: an integrated contrast data and gene set platform for computational analysis and biological interpretation of omics data

Background

High-throughput omics technologies such as microarrays and next-generation sequencing (NGS) have become indispensable tools in biological research. Computational analysis and biological interpretation of omics data can pose significant challenges due to a number of factors, in particular the systems integration required to fully exploit and compare data from different studies and/or technology platforms. In transcriptomics, the identification of differentially expressed genes when studying effect(s) or contrast(s) of interest constitutes the starting point for further downstream computational analysis (e.g. gene over-representation/enrichment analysis, reverse engineering) leading to mechanistic insights. Therefore, it is important to systematically store the full list of genes with their associated statistical analysis results (differential expression, t-statistics, p-value) corresponding to one or more effect(s) or contrast(s) of interest (shortly termed as ” contrast data”) in a comparable manner and extract gene sets in order to efficiently support downstream analyses and further leverage data on a long-term basis. Filling this gap would open new research perspectives for biologists to discover disease-related biomarkers and to support the understanding of molecular mechanisms underlying specific biological perturbation effects (e.g. disease, genetic, environmental, etc.).

Results

To address these challenges, we developed Confero, a contrast data and gene set platform for downstream analysis and biological interpretation of omics data. The Confero software platform provides storage of contrast data in a simple and standard format, data transformation to enable cross-study and platform data comparison, and automatic extraction and storage of gene sets to build new a priori knowledge which is leveraged by integrated and extensible downstream computational analysis tools. Gene Set Enrichment Analysis (GSEA) and Over-Representation Analysis (ORA) are currently integrated as an analysis module as well as additional tools to support biological interpretation. Confero is a standalone system that also integrates with Galaxy, an open-source workflow management and data integration system. To illustrate Confero platform functionality we walk through major aspects of the Confero workflow and results using the Bioconductor estrogen package dataset.

Conclusion

Confero provides a unique and flexible platform to support downstream computational analysis facilitating biological interpretation. The system has been designed in order to provide the researcher with a simple, innovative, and extensible solution to store and exploit analyzed data in a sustainable and reproducible manner thereby accelerating knowledge-driven research. Confero source code is freely available from http://sourceforge.net/projects/confero/.

N-6-adenine-specific DNA methyltransferase 1 (N6AMT1) polymorphisms and arsenic methylation in Andean women

BACKGROUND

In humans, inorganic arsenic is metabolized to methylated metabolites mainly by arsenic (+3 oxidation state) methyltransferase (AS3MT). AS3MT polymorphisms are associated with arsenic metabolism efficiency. Recently, a putative N-6-adenine-specific DNA methyltransferase 1 (N6AMT1) was found to methylate arsenic in vitro.

OBJECTIVE

We evaluated the role of N6AMT1 polymorphisms in arsenic methylation efficiency in humans.

METHODS

We assessed arsenic methylation efficiency in 188 women exposed to arsenic via drinking water (~ 200 µg/L) in the Argentinean Andes by measuring the relative concentrations of arsenic metabolites in urine [inorganic arsenic, methylarsonic acid (MMA), and dimethylarsinic acid] by high-performance liquid chromatography coupled with hydride generation and inductively coupled plasma mass spectrometry. We performed genotyping for N6AMT1 and AS3MT polymorphisms by Taqman assays, and gene expression (in blood; n = 63) with Illumina HumanHT-12 v4.0.

RESULTS

Five N6AMT1 single nucleotide polymorphisms (SNPs; rs1997605, rs2205449, rs2705671, rs16983411, and rs1048546) and two N6AMT1 haplotypes were significantly associated with the percentage of MMA (%MMA) in urine, even after adjusting for AS3MT haplotype. %MMA increased monotonically according to the number of alleles for each SNP (e.g., for rs1048546, mean %MMA was 7.5% for GG, 8.8% for GT, and 9.7% for TT carriers). Three SNPs were in linkage disequilibrium (R2 > 0.8). Estimated associations for joint effects of N6AMT1 (haplotype 1) and AS3MT (haplotype 2) were generally consistent with expectations for additive effects of each haplotype on %MMA. Carriers of N6AMT1 genotypes associated with lower %MMA showed the lowest N6AMT1 expression, but associations were monotonic according to copy number for only one genotype and one haplotype.

CONCLUSIONS

N6AMT1 polymorphisms were associated with arsenic methylation in Andean women, independent of AS3MT. N6AMT1 polymorphisms may be susceptibility markers for arsenic-related toxic effects.

Djeen (Database for Joomla!'s Extensible Engine): a research information management system for flexible multi-technology project administration

BACKGROUND

With the advance of post-genomic technologies, the need for tools to manage large scale data in biology becomes more pressing. This involves annotating and storing data securely, as well as granting permissions flexibly with several technologies (all array types, flow cytometry, proteomics) for collaborative work and data sharing. This task is not easily achieved with most systems available today.

FINDINGS

We developed Djeen (Database for Joomla!'s Extensible Engine), a new Research Information Management System (RIMS) for collaborative projects. Djeen is a user-friendly application, designed to streamline data storage and annotation collaboratively. Its database model, kept simple, is compliant with most technologies and allows storing and managing of heterogeneous data with the same system. Advanced permissions are managed through different roles. Templates allow Minimum Information (MI) compliance.

CONCLUSION

Djeen allows managing project associated with heterogeneous data types while enforcing annotation integrity and minimum information. Projects are managed within a hierarchy and user permissions are finely-grained for each project, user and group.Djeen Component source code (version 1.5.1) and installation documentation are available under CeCILL license from http://sourceforge.net/projects/djeen/files and supplementary material.

Polymorphisms in iron homeostasis genes and urinary cadmium concentrations among nonsmoking women in Argentina and Bangladesh

BACKGROUND

Cadmium (Cd) is a human toxicant and carcinogen. Genetic variation might affect long-term accumulation. Cd is absorbed via iron transporters.

OBJECTIVES

We evaluated the impact of iron homeostasis genes [divalent metal transporter 1 (SLC11A2), transferrin (TF), transferrin receptors (TFR2 and TFRC), and ferroportin (SLC40A1)] on Cd accumulation.

METHODS

Subjects were nonsmoking women living in the Argentinean Andes [n = 172; median urinary Cd (U-Cd) = 0.24 µg/L] and Bangladesh (n = 359; U-Cd = 0.54 µg/L) with Cd exposure mainly from food. Concentrations of U-Cd and Cd in whole blood or in erythrocytes (Ery-Cd) were measured by inductively coupled plasma mass spectrometry. Fifty polymorphisms were genotyped by Sequenom. Gene expression was measured in whole blood (n = 72) with Illumina DirectHyb HumanHT-12 v4.0.

RESULTS

TFRC rs3804141 was consistently associated with U-Cd. In the Andean women, mean U-Cd concentrations were 22% (95% CI: -2, 51%), and they were 56% (95% CI: 10, 120%) higher in women with GA and AA genotypes, respectively, relative to women with the GG genotype. In the Bangladeshi women, mean U-Cd concentrations were 22% (95% CI: 1, 48%), and they were 58% (95% CI: -3, 157%) higher in women with GA and AA versus GG genotype, respectively [adjusted for age and plasma ferritin in both groups; ptrend = 0.006 (Andes) and 0.009 (Bangladesh)]. TFRC expression in blood was negatively correlated with plasma ferritin (rS = -0.33, p = 0.006), and positively correlated with Ery-Cd (significant at ferritin concentrations of < 30 µg/L only, rS = 0.40, p = 0.046). Rs3804141 did not modify these associations or predict TFRC expression. Cd was not consistently associated with any of the other polymorphisms evaluated.

CONCLUSIONS

One TFRC polymorphism was associated with urine Cd concentration, a marker of Cd accumulation in the kidney, in two very different populations. The consistency of the findings supports the possibility of a causal association.

XperimentR: painless annotation of a biological experiment for the laboratory scientist

Background

Today’s biological experiments often involve the collaboration of multidisciplinary researchers utilising several high throughput ‘omics platforms. There is a requirement for the details of the experiment to be adequately described using standardised ontologies to enable data preservation, the analysis of the data and to facilitate the export of the data to public repositories. However there are a bewildering number of ontologies, controlled vocabularies, and minimum standards available for use to describe experiments. There is a need for user-friendly software tools to aid laboratory scientists in capturing the experimental information.

Results

A web application called XperimentR has been developed for use by laboratory scientists, consisting of a browser-based interface and server-side components which provide an intuitive platform for capturing and sharing experimental metadata. Information recorded includes details about the biological samples, procedures, protocols, and experimental technologies, all of which can be easily annotated using the appropriate ontologies. Files and raw data can be imported and associated with the biological samples via the interface, from either users’ computers, or commonly used open-source data repositories. Experiments can be shared with other users, and experiments can be exported in the standard ISA-Tab format for deposition in public databases. XperimentR is freely available and can be installed natively or by using a provided pre-configured Virtual Machine. A guest system is also available for trial purposes.

Conclusion

We present a web based software application to aid the laboratory scientist to capture, describe and share details about their experiments.

Efficient arsenic metabolism--the AS3MT haplotype is associated with DNA methylation and expression of multiple genes around AS3MT

Arsenic is a very potent toxicant. One major susceptibility factor for arsenic-related toxicity is the efficiency of arsenic metabolism. The efficiency, in turn, is associated with non-coding single nucleotide polymorphisms (SNPs) in the arsenic methyltransferase AS3MT on chromosome 10q24. However, the mechanism of action for these SNPs is not yet clarified. Here, we assessed the influence of genetic variation in AS3MT on DNA methylation and gene expression within 10q24, in people exposed to arsenic in drinking water. DNA was extracted from peripheral blood from women in the Argentinean Andes (N = 103) and from cord blood from new-borns in Bangladesh (N = 127). AS3MT SNPs were analyzed with Sequenom or Taqman assays. Whole genome epigenetic analysis with Infinium HumanMethylation450 BeadChip was performed on bisulphite-treated DNA. Whole genome gene expression analysis was performed with Illumina DirectHyb HumanHT-12 v4.0 on RNA from peripheral blood. Arsenic exposure was assessed by HPLC-ICPMS. In the Argentinean women, the major AS3MT haplotype, associated with more efficient arsenic metabolism, showed increased methylation of AS3MT (p = 10(-6)) and also differential methylation of several other genes within about 800 kilobasepairs: CNNM2 (p<10(-16)), NT5C2 (p<10(-16)), C10orf26 (p = 10(-8)), USMG5 (p = 10(-5)), TRIM8 (p = 10(-4)), and CALHM2 (p = 0.038) (adjusted for multiple comparisons). Similar, but weaker, associations between AS3MT haplotype and DNA methylation in 10q24 were observed in cord blood (Bangladesh). The haplotype-associated altered CpG methylation was correlated with reduced expression of AS3MT and CNNM2 (r(s) = -0.22 to -0.54), and with increased expression of NT5C2 and USMG5 (r(s) = 0.25 to 0.58). Taking other possibly influential variables into account in multivariable linear models did only to a minor extent alter the strength of the associations. In conclusion, the AS3MT haplotype status strongly predicted DNA methylation and gene expression of AS3MT as well as several genes in 10q24. This raises the possibility that several genes in this region are important for arsenic metabolism.

Interferome v2.0: an updated database of annotated interferon-regulated genes

Interferome v2.0 (http://interferome.its.monash.edu.au/interferome/) is an update of an earlier version of the Interferome DB published in the 2009 NAR database edition. Vastly improved computational infrastructure now enables more complex and faster queries, and supports more data sets from types I, II and III interferon (IFN)-treated cells, mice or humans. Quantitative, MIAME compliant data are collected, subjected to thorough, standardized, quantitative and statistical analyses and then significant changes in gene expression are uploaded. Comprehensive manual collection of metadata in v2.0 allows flexible, detailed search capacity including the parameters: range of -fold change, IFN type, concentration and time, and cell/tissue type. There is no limit to the number of genes that can be used to search the database in a single query. Secondary analysis such as gene ontology, regulatory factors, chromosomal location or tissue expression plots of IFN-regulated genes (IRGs) can be performed in Interferome v2.0, or data can be downloaded in convenient text formats compatible with common secondary analysis programs. Given the importance of IFN to innate immune responses in infectious, inflammatory diseases and cancer, this upgrade of the Interferome to version 2.0 will facilitate the identification of gene signatures of importance in the pathogenesis of these diseases.

Efficient arsenic metabolism--the AS3MT haplotype is associated with DNA methylation and expression of multiple genes around AS3MT

Arsenic is a very potent toxicant. One major susceptibility factor for arsenic-related toxicity is the efficiency of arsenic metabolism. The efficiency, in turn, is associated with non-coding single nucleotide polymorphisms (SNPs) in the arsenic methyltransferase AS3MT on chromosome 10q24. However, the mechanism of action for these SNPs is not yet clarified. Here, we assessed the influence of genetic variation in AS3MT on DNA methylation and gene expression within 10q24, in people exposed to arsenic in drinking water. DNA was extracted from peripheral blood from women in the Argentinean Andes (N = 103) and from cord blood from new-borns in Bangladesh (N = 127). AS3MT SNPs were analyzed with Sequenom or Taqman assays. Whole genome epigenetic analysis with Infinium HumanMethylation450 BeadChip was performed on bisulphite-treated DNA. Whole genome gene expression analysis was performed with Illumina DirectHyb HumanHT-12 v4.0 on RNA from peripheral blood. Arsenic exposure was assessed by HPLC-ICPMS. In the Argentinean women, the major AS3MT haplotype, associated with more efficient arsenic metabolism, showed increased methylation of AS3MT (p = 10(-6)) and also differential methylation of several other genes within about 800 kilobasepairs: CNNM2 (p<10(-16)), NT5C2 (p<10(-16)), C10orf26 (p = 10(-8)), USMG5 (p = 10(-5)), TRIM8 (p = 10(-4)), and CALHM2 (p = 0.038) (adjusted for multiple comparisons). Similar, but weaker, associations between AS3MT haplotype and DNA methylation in 10q24 were observed in cord blood (Bangladesh). The haplotype-associated altered CpG methylation was correlated with reduced expression of AS3MT and CNNM2 (r(s) = -0.22 to -0.54), and with increased expression of NT5C2 and USMG5 (r(s) = 0.25 to 0.58). Taking other possibly influential variables into account in multivariable linear models did only to a minor extent alter the strength of the associations. In conclusion, the AS3MT haplotype status strongly predicted DNA methylation and gene expression of AS3MT as well as several genes in 10q24. This raises the possibility that several genes in this region are important for arsenic metabolism.

Data management strategies for multinational large-scale systems biology projects

Good accessibility of publicly funded research data is essential to secure an open scientific system and eventually becomes mandatory [Wellcome Trust will Penalise Scientists Who Don’t Embrace Open Access. The Guardian 2012]. By the use of high-throughput methods in many research areas from physics to systems biology, large data collections are increasingly important as raw material for research. Here, we present strategies worked out by international and national institutions targeting open access to publicly funded research data via incentives or obligations to share data. Funding organizations such as the British Wellcome Trust therefore have developed data sharing policies and request commitment to data management and sharing in grant applications. Increased citation rates are a profound argument for sharing publication data. Pre-publication sharing might be rewarded by a data citation credit system via digital object identifiers (DOIs) which have initially been in use for data objects. Besides policies and incentives, good practice in data management is indispensable. However, appropriate systems for data management of large-scale projects for example in systems biology are hard to find. Here, we give an overview of a selection of open-source data management systems proved to be employed successfully in large-scale projects.

graph2tab, a library to convert experimental workflow graphs into tabular formats

Motivations: Spreadsheet-like tabular formats are ever more popular in the biomedical field as a mean for experimental reporting. The problem of converting the graph of an experimental workflow into a table-based representation occurs in many such formats and is not easy to solve.

Results: We describe graph2tab, a library that implements methods to realise such a conversion in a size-optimised way. Our solution is generic and can be adapted to specific cases of data exporters or data converters that need to be implemented.

Availability and Implementation: The library source code and documentation are available at http://github.com/ISA-tools/graph2tab.

Contact:brandizi@ebi.ac.uk.

Supplementary Information: A supplementary document describes the theoretical and technical details about the library implementation.

Integrated genomic and gene expression profiling identifies two major genomic circuits in urothelial carcinoma

Similar to other malignancies, urothelial carcinoma (UC) is characterized by specific recurrent chromosomal aberrations and gene mutations. However, the interconnection between specific genomic alterations, and how patterns of chromosomal alterations adhere to different molecular subgroups of UC, is less clear. We applied tiling resolution array CGH to 146 cases of UC and identified a number of regions harboring recurrent focal genomic amplifications and deletions. Several potential oncogenes were included in the amplified regions, including known oncogenes like E2F3, CCND1, and CCNE1, as well as new candidate genes, such as SETDB1 (1q21), and BCL2L1 (20q11). We next combined genome profiling with global gene expression, gene mutation, and protein expression data and identified two major genomic circuits operating in urothelial carcinoma. The first circuit was characterized by FGFR3 alterations, overexpression of CCND1, and 9q and CDKN2A deletions. The second circuit was defined by E3F3 amplifications and RB1 deletions, as well as gains of 5p, deletions at PTEN and 2q36, 16q, 20q, and elevated CDKN2A levels. TP53/MDM2 alterations were common for advanced tumors within the two circuits. Our data also suggest a possible RAS/RAF circuit. The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype. Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.

Low-level environmental cadmium exposure is associated with DNA hypomethylation in Argentinean women

BACKGROUND

Cadmium, a common food pollutant, alters DNA methylation in vitro. Epigenetic effects might therefore partly explain cadmium's toxicity, including its carcinogenicity; however, human data on epigenetic effects are lacking.

OBJECTIVE

We evaluated the effects of dietary cadmium exposure on DNA methylation, considering other environmental exposures, genetic predisposition, and gene expression.

METHODS

Concentrations of cadmium, arsenic, selenium, and zinc in blood and urine of nonsmoking women (n = 202) from the northern Argentinean Andes were measured by inductively coupled mass spectrometry. Methylation in CpG islands of LINE-1 (long interspersed nuclear element-1; a proxy for global DNA methylation) and promoter regions of p16 [cyclin-dependent kinase inhibitor 2A (CDKN2A)] and MLH1 (mutL homolog 1) in peripheral blood were measured by bisulfite polymerase chain reaction pyrosequencing. Genotyping (n = 172) for the DNA (cytosine-5-)-methyltransferase 1 gene (DNMT1 rs10854076 and rs2228611) and DNA (cytosine-5-)-methyltransferase 3 beta gene (DNMT3B rs2424913 and rs2424932) was performed with Sequenom iPLEX GOLD SNP genotyping; and gene expression (n = 90), with DirectHyb HumanHT-12 (version 3.0).

RESULTS

Cadmium exposure was low: median concentrations in blood and urine were 0.36 and 0.23 µg/L, respectively. Urinary cadmium (natural log transformed) was inversely associated with LINE-1 methylation (β = -0.50, p = 0.0070; β = -0.44, p = 0.026, adjusted for age and coca chewing) but not with p16 or MLH1 methylation. Both DNMT1 rs10854076 and DNMT1 rs2228611 polymorphisms modified associations between urinary cadmium and LINE-1 (p-values for interaction in adjusted models were 0.045 and 0.064, respectively). The rare genotypes demonstrated stronger hypomethylation with increasing urinary cadmium concentrations. Cadmium was inversely associated with DNMT3B (r(S) = -0.28, p = 0.0086) but not with DNMT1 expression (r(S) = -0.075, p = 0.48).

CONCLUSION

Environmental cadmium exposure was associated with DNA hypomethylation in peripheral blood, and DNMT1 genotypes modified this association. The role of epigenetic modifications in cadmium-associated diseases needs clarification.

Gene expression profiling of primary male breast cancers reveals two unique subgroups and identifies N-acetyltransferase-1 (NAT1) as a novel prognostic biomarker

INTRODUCTION

Male breast cancer (MBC) is a rare and inadequately characterized disease. The aim of the present study was to characterize MBC tumors transcriptionally, to classify them into comprehensive subgroups, and to compare them with female breast cancer (FBC).

METHODS

A total of 66 clinicopathologically well-annotated fresh frozen MBC tumors were analyzed using Illumina Human HT-12 bead arrays, and a tissue microarray with 220 MBC tumors was constructed for validation using immunohistochemistry. Two external gene expression datasets were used for comparison purposes: 37 MBCs and 359 FBCs.

RESULTS

Using an unsupervised approach, we classified the MBC tumors into two subgroups, luminal M1 and luminal M2, respectively, with differences in tumor biological features and outcome, and which differed from the intrinsic subgroups described in FBC. The two subgroups were recapitulated in the external MBC dataset. Luminal M2 tumors were characterized by high expression of immune response genes and genes associated with estrogen receptor (ER) signaling. Luminal M1 tumors, on the other hand, despite being ER positive by immunohistochemistry showed a lower correlation to genes associated with ER signaling and displayed a more aggressive phenotype and worse prognosis. Validation of two of the most differentially expressed genes, class 1 human leukocyte antigen (HLA) and the metabolizing gene N-acetyltransferase-1 (NAT1), respectively, revealed significantly better survival associated with high expression of both markers (HLA, hazard ratio (HR) 3.6, P = 0.002; NAT1, HR 2.5, P = 0.033). Importantly, NAT1 remained significant in a multivariate analysis (HR 2.8, P = 0.040) and may thus be a novel prognostic marker in MBC.

CONCLUSIONS

We have detected two unique and stable subgroups of MBC with differences in tumor biological features and outcome. They differ from the widely acknowledged intrinsic subgroups of FBC. As such, they may constitute two novel subgroups of breast cancer, occurring exclusively in men, and which may consequently require novel treatment approaches. Finally, we identified NAT1 as a possible prognostic biomarker for MBC, as suggested by NAT1 positivity corresponding to better outcome.

CD44 isoforms are heterogeneously expressed in breast cancer and correlate with tumor subtypes and cancer stem cell markers

Background

The CD44 cell adhesion molecule is aberrantly expressed in many breast tumors and has been implicated in the metastatic process as well as in the putative cancer stem cell (CSC) compartment. We aimed to investigate potential associations between alternatively spliced isoforms of CD44 and CSCs as well as to various breast cancer biomarkers and molecular subtypes.

Methods

We used q-RT-PCR and exon-exon spanning assays to analyze the expression of four alternatively spliced CD44 isoforms as well as the total expression of CD44 in 187 breast tumors and 13 cell lines. ALDH1 protein expression was determined by IHC on TMA.

Results

Breast cancer cell lines showed a heterogeneous expression pattern of the CD44 isoforms, which shifted considerably when cells were grown as mammospheres. Tumors characterized as positive for the CD44⁺/CD24^- phenotype by immunohistochemistry were associated to all isoforms except the CD44 standard (CD44S) isoform, which lacks all variant exons. Conversely, tumors with strong expression of the CSC marker ALDH1 had elevated expression of CD44S. A high expression of the CD44v2-v10 isoform, which retain all variant exons, was correlated to positive steroid receptor status, low proliferation and luminal A subtype. The CD44v3-v10 isoform showed similar correlations, while high expression of CD44v8-v10 was correlated to positive EGFR, negative/low HER2 status and basal-like subtype. High expression of CD44S was associated with strong HER2 staining and also a subgroup of basal-like tumors. Unsupervised hierarchical cluster analysis of CD44 isoform expression data divided tumors into four main clusters, which showed significant correlations to molecular subtypes and differences in 10-year overall survival.

Conclusions

We demonstrate that individual CD44 isoforms can be associated to different breast cancer subtypes and clinical markers such as HER2, ER and PgR, which suggests involvement of CD44 splice variants in specific oncogenic signaling pathways. Efforts to link CD44 to CSCs and tumor progression should consider the expression of various CD44 isoforms.

Breast tumors from CHEK2 1100delC-mutation carriers: genomic landscape and clinical implications

INTRODUCTION

Checkpoint kinase 2 (CHEK2) is a moderate penetrance breast cancer risk gene, whose truncating mutation 1100delC increases the risk about twofold. We investigated gene copy-number aberrations and gene-expression profiles that are typical for breast tumors of CHEK2 1100delC-mutation carriers.

METHODS

In total, 126 breast tumor tissue specimens including 32 samples from patients carrying CHEK2 1100delC were studied in array-comparative genomic hybridization (aCGH) and gene-expression (GEX) experiments. After dimensionality reduction with CGHregions R package, CHEK2 1100delC-associated regions in the aCGH data were detected by the Wilcoxon rank-sum test. The linear model was fitted to GEX data with R package limma. Genes whose expression levels were associated with CHEK2 1100delC mutation were detected by the bayesian method.

RESULTS

We discovered four lost and three gained CHEK2 1100delC-related loci. These include losses of 1p13.3-31.3, 8p21.1-2, 8p23.1-2, and 17p12-13.1 as well as gains of 12q13.11-3, 16p13.3, and 19p13.3. Twenty-eight genes located on these regions showed differential expression between CHEK2 1100delC and other tumors, nominating them as candidates for CHEK2 1100delC-associated tumor-progression drivers. These included CLCA1 on 1p22 as well as CALCOCO1, SBEM, and LRP1 on 12q13. Altogether, 188 genes were differentially expressed between CHEK2 1100delC and other tumors. Of these, 144 had elevated and 44, reduced expression levels.Our results suggest the WNT pathway as a driver of tumorigenesis in breast tumors of CHEK2 1100delC-mutation carriers and a role for the olfactory receptor protein family in cancer progression. Differences in the expression of the 188 CHEK2 1100delC-associated genes divided breast tumor samples from three independent datasets into two groups that differed in their relapse-free survival time.

CONCLUSIONS

We have shown that copy-number aberrations of certain genomic regions are associated with CHEK2 mutation 1100delC. On these regions, we identified potential drivers of CHEK2 1100delC-associated tumorigenesis, whose role in cancer progression is worth investigating. Furthermore, poorer survival related to the CHEK2 1100delC gene-expression signature highlights pathways that are likely to have a role in the development of metastatic disease in carriers of the CHEK2 1100delC mutation.

The Streptococcus pneumoniae pilus-1 displays a biphasic expression pattern

The Streptococcus pneumoniae pilus-1 is encoded by pilus islet 1 (PI-1), which has three clonal variants (clade I, II and III) and is present in about 30% of clinical pneumococcal isolates. In vitro and in vivo assays have demonstrated that pilus-1 is involved in attachment to epithelial cells and virulence, as well as protection in mouse models of infection. Several reports suggest that pilus-1 expression is tightly regulated and involves the interplay of numerous genetic regulators, including the PI-1 positive regulator RlrA. In this report we provide evidence that pilus expression, when analyzed at the single-cell level in PI-1 positive strains, is biphasic. In fact, the strains present two phenotypically different sub-populations of bacteria, one that expresses the pilus, while the other does not. The proportions of these two phenotypes are variable among the strains tested and are not influenced by genotype, serotype, growth conditions, colony morphology or by the presence of antibodies directed toward the pilus components. Two sub-populations, enriched in pilus expressing or not expressing bacteria were obtained by means of colony selection and immuno-detection methods for five strains. PI-1 sequencing in the two sub-populations revealed the absence of mutations, thus indicating that the biphasic expression observed is not due to a genetic modification within PI-1. Microarray expression profile and western blot analyses on whole bacterial lysates performed comparing the two enriched sub-populations, revealed that pilus expression is regulated at the transcriptional level (on/off regulation), and that there are no other genes, in addition to those encoded by PI-1, concurrently regulated across the strains tested. Finally, we provide evidence that the over-expression of the RrlA positive regulator is sufficient to induce pilus expression in pilus-1 negative bacteria. Overall, the data presented here suggest that the observed biphasic pilus expression phenotype could be an example of bistability in pneumococcus.

Managing and querying gene expression data using Curray

Background

In principle, gene expression data can be viewed as providing just the three-valued expression profiles of target biological elements relative to an experiment at hand. Although complicated, gathering expression profiles does not pose much of a challenge from a query language standpoint. What is interesting is how these expression profiles are used to tease out information from the vast array of information repositories that ascribe meaning to the expression profiles. Since such annotations are inherently experiment specific functions, much the same way as queries in databases, developing a querying system for gene expression data appears to be pointless. Instead, developing tools and techniques to support individual assignment has been considered prudent in contemporary research.

Results

We propose a gene expression data management and querying system that is able to support pre-expression, expression and post-expression level analysis and reduce impedance mismatch between analysis systems. To this end, we propose a new, platform-independent and general purpose query language called Curray, for Custom Microarray query language, to support online expression data analysis using distributed resources. It includes features to design expression analysis pipelines using language constructs at the conceptual level. The ability to include user defined functions as a first-class language feature facilitates unlimited analysis support and removes language limitations. We show that Curray’s declarative and extensible features nimbly allow flexible modeling and room for customization.

Conclusions

The developments proposed in this article allow users to view their expression data from a conceptual standpoint - experiments, probes, expressions, mapping, etc. at multiple levels of representation and independent of the underlying chip technologies. It also allows transparent roll-up and drill-down along representation hierarchies from raw data to standards such as MIAME and MAGE-ML using linguistic constructs. Curray also allows seamless integration with distributed web resources through its LifeDB system of which it is a part.

Isolation and characterization of progenitor-like cells from human renal proximal tubules

The tubules of the kidney display a remarkable capacity for self-renewal on damage. Whether this regeneration is mediated by dedifferentiating surviving cells or, as recently suggested, by stem cells has not been unequivocally settled. Herein, we demonstrate that aldehyde dehydrogenase (ALDH) activity may be used for isolation of cells with progenitor characteristics from adult human renal cortical tissue. Gene expression profiling of the isolated ALDH(high) and ALDH(low) cell fractions followed by immunohistochemical interrogation of renal tissues enabled us to delineate a tentative progenitor cell population scattered through the proximal tubules (PTs). These cells expressed CD24 and CD133, previously described markers for renal progenitors of Bowman's capsule. Furthermore, we show that the PT cells, and the glomerular progenitors, are positive for KRT7, KRT19, BCL2, and vimentin. In addition, tubular epithelium regenerating on acute tubular necrosis displayed long stretches of CD133(+)/VIM(+) cells, further substantiating that these cells may represent a progenitor cell population. Furthermore, a potential association of these progenitor cells with papillary renal cell carcinoma was discovered. Taken together, our data demonstrate the presence of a previously unappreciated subset of the PT cells that may be endowed with a more robust phenotype, allowing increased resistance to acute renal injury, enabling rapid repopulation of the tubules.

Tools for managing and analyzing microarray data

The microarray-based analysis of gene expression has become a workhorse for biomedical research. Managing the amount and diversity of data that such experiments produce is a task that must be supported by appropriate software tools, which led to the creation of literally hundreds of systems. In consequence, choosing the right tool for a given project is difficult even for the expert. We report on the results of a survey encompassing 78 of such tools, of which 22 were inspected in detail and seven were tested hands-on. We report on our experiences with a focus on completeness of functionality, ease-of-use, and necessary effort for installation and maintenance. Thereby, our survey provides a valuable guideline for any project considering the use of a microarray data management system. It reveals which tasks are covered by mature tools and also shows that important requirements, especially in the area of integrated analysis of different experimental data, are not yet met satisfyingly by existing systems.

LabKey Server: an open source platform for scientific data integration, analysis and collaboration

BACKGROUND

Broad-based collaborations are becoming increasingly common among disease researchers. For example, the Global HIV Enterprise has united cross-disciplinary consortia to speed progress towards HIV vaccines through coordinated research across the boundaries of institutions, continents and specialties. New, end-to-end software tools for data and specimen management are necessary to achieve the ambitious goals of such alliances. These tools must enable researchers to organize and integrate heterogeneous data early in the discovery process, standardize processes, gain new insights into pooled data and collaborate securely.

RESULTS

To meet these needs, we enhanced the LabKey Server platform, formerly known as CPAS. This freely available, open source software is maintained by professional engineers who use commercially proven practices for software development and maintenance. Recent enhancements support: (i) Submitting specimens requests across collaborating organizations (ii) Graphically defining new experimental data types, metadata and wizards for data collection (iii) Transitioning experimental results from a multiplicity of spreadsheets to custom tables in a shared database (iv) Securely organizing, integrating, analyzing, visualizing and sharing diverse data types, from clinical records to specimens to complex assays (v) Interacting dynamically with external data sources (vi) Tracking study participants and cohorts over time (vii) Developing custom interfaces using client libraries (viii) Authoring custom visualizations in a built-in R scripting environment. Diverse research organizations have adopted and adapted LabKey Server, including consortia within the Global HIV Enterprise. Atlas is an installation of LabKey Server that has been tailored to serve these consortia. It is in production use and demonstrates the core capabilities of LabKey Server. Atlas now has over 2,800 active user accounts originating from approximately 36 countries and 350 organizations. It tracks roughly 27,000 assay runs, 860,000 specimen vials and 1,300,000 vial transfers.

CONCLUSIONS

Sharing data, analysis tools and infrastructure can speed the efforts of large research consortia by enhancing efficiency and enabling new insights. The Atlas installation of LabKey Server demonstrates the utility of the LabKey platform for collaborative research. Stable, supported builds of LabKey Server are freely available for download at http://www.labkey.org. Documentation and source code are available under the Apache License 2.0.

A point mutation in the amino terminus of TLR7 abolishes signaling without affecting ligand binding

TLR7 is the mammalian receptor for ssRNA and some nucleotide-like small molecules. We have generated a mouse by N-nitrose-N'-ethyl urea mutagenesis in which threonine 68 of TLR7 was substituted with isoleucine. Cells bearing this mutant TLR7 lost the sensitivity to the small-molecule TLR7 agonist resiquimod, hence the name TLR7(rsq1). In this work, we report the characterization of this mutant protein. Similar to the wild-type counterpart, TLR7(rsq1) localizes to the endoplasmic reticulum and is expressed at normal levels in both primary cells and reconstituted 293T cells. In addition to small-molecule TLR7 agonists, TLR7(rsq1) fails to be activated by ssRNA. Whole-transcriptome analysis demonstrates that TLR7 is the exclusive and indispensable receptor for both classes of ligands, consistent with the fact that both ligands induce highly similar transcriptional signatures in TLR7(wt/wt) splenocytes. Thus, TLR7(rsq1) is a bona fide phenocopy of the TLR7 null mouse. Because TLR7(rsq1) binds to ssRNA, our studies imply that the N-terminal portion of TLR7 triggers a yet to be identified event on TLR7. TLR7(rsq1) mice might represent a valuable tool to help elucidate novel aspects of TLR7 biology.