Expression profiling in spondyloarthropathy synovial biopsies highlights changes in expression of inflammatory genes in conjunction with tissue remodelling genes

Background: In the spondyloarthropathies, the underlying molecular and cellular pathways driving disease are poorly understood. By undertaking a study in knee synovial biopsies from spondyloarthropathy (SpA) and ankylosing spondylitis (AS) patients we aimed to elucidate dysregulated genes and pathways. Methods RNA was extracted from six SpA, two AS, three osteoarthritis (OA) and four normal control knee synovial biopsies. Whole genome expression profiling was undertaken using the Illumina DASL system, which assays 24000 cDNA probes. Differentially expressed candidate genes were then validated using quantitative PCR and immunohistochemistry. Results: Four hundred and sixteen differentially expressed genes were identified that clearly delineated between AS/SpA and control groups. Pathway analysis showed altered gene-expression in oxidoreductase activity, B-cell associated, matrix catabolic, and metabolic pathways. Altered «myogene» profiling was also identified. The inflammatory mediator, MMP3, was strongly upregulated (5-fold) in AS/SpA samples and the Wnt pathway inhibitors DKK3 (2.7-fold) and Kremen1 (1.5-fold) were downregulated. Conclusions: Altered expression profiling in SpA and AS samples demonstrates that disease pathogenesis is associated with both systemic inflammation as well as local tissue alterations that may underlie tissue damaging modelling and remodelling outcomes. This supports the hypothesis that initial systemic inflammation in spondyloarthropathies transfers to and persists in the local joint environment, and might subsequently mediate changes in genes directly involved in the destructive tissue remodelling.

Gene expression signatures of radiation response are specific, durable and accurate in mice and humans.

BACKGROUND: Previous work has demonstrated the potential for peripheral blood (PB) gene expression profiling for the detection of disease or environmental exposures. METHODS AND FINDINGS: We have sought to determine the impact of several variables on the PB gene expression profile of an environmental exposure, ionizing radiation, and to determine the specificity of the PB signature of radiation versus other genotoxic stresses. Neither genotype differences nor the time of PB sampling caused any lessening of the accuracy of PB signatures to predict radiation exposure, but sex difference did influence the accuracy of the prediction of radiation exposure at the lowest level (50 cGy). A PB signature of sepsis was also generated and both the PB signature of radiation and the PB signature of sepsis were found to be 100% specific at distinguishing irradiated from septic animals. We also identified human PB signatures of radiation exposure and chemotherapy treatment which distinguished irradiated patients and chemotherapy-treated individuals within a heterogeneous population with accuracies of 90% and 81%, respectively. CONCLUSIONS: We conclude that PB gene expression profiles can be identified in mice and humans that are accurate in predicting medical conditions, are specific to each condition and remain highly accurate over time.

Gene expression disruptions of organism versus organ in Drosophila species hybrids.

Hybrid dysfunctions, such as sterility, may result in part from disruptions in the regulation of gene expression. Studies of hybrids within the Drosophila simulans clade have reported genes expressed above or below the expression observed in their parent species, and such misexpression is associated with male sterility in multigenerational backcross hybrids. However, these studies often examined whole bodies rather than testes or had limited replication using less-sensitive but global techniques. Here, we use a new RNA isolation technique to re-examine hybrid gene expression disruptions in both testes and whole bodies from single Drosophila males by real-time quantitative RT-PCR. We find two early-spermatogenesis transcripts are underexpressed in hybrid whole-bodies but not in assays of testes alone, while two late-spermatogenesis transcripts seem to be underexpressed in both whole-bodies and testes alone. Although the number of transcripts surveyed is limited, these results provide some support for a previous hypothesis that the spermatogenesis pathway in these sterile hybrids may be disrupted sometime after the expression of the early meiotic arrest genes.

Intergenic and genic sequence lengths have opposite relationships with respect to gene expression.

Eukaryotic genomes are mostly composed of noncoding DNA whose role is still poorly understood. Studies in several organisms have shown correlations between the length of the intergenic and genic sequences of a gene and the expression of its corresponding mRNA transcript. Some studies have found a positive relationship between intergenic sequence length and expression diversity between tissues, and concluded that genes under greater regulatory control require more regulatory information in their intergenic sequences. Other reports found a negative relationship between expression level and gene length and the interpretation was that there is selection pressure for highly expressed genes to remain small. However, a correlation between gene sequence length and expression diversity, opposite to that observed for intergenic sequences, has also been reported, and to date there is no testable explanation for this observation. To shed light on these varied and sometimes conflicting results, we performed a thorough study of the relationships between sequence length and gene expression using cell-type (tissue) specific microarray data in Arabidopsis thaliana. We measured median gene expression across tissues (expression level), expression variability between tissues (expression pattern uniformity), and expression variability between replicates (expression noise). We found that intergenic (upstream and downstream) and genic (coding and noncoding) sequences have generally opposite relationships with respect to expression, whether it is tissue variability, median, or expression noise. To explain these results we propose a model, in which the lengths of the intergenic and genic sequences have opposite effects on the ability of the transcribed region of the gene to be epigenetically regulated for differential expression. These findings could shed light on the role and influence of noncoding sequences on gene expression.

Diagnosis of partial body radiation exposure in mice using peripheral blood gene expression profiles.

In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB) can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI). However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79-100%) compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16-43%), suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Radioactive in situ hybridization for detecting diverse gene expression patterns in tissue.

Knowing the timing, level, cellular localization, and cell type that a gene is expressed in contributes to our understanding of the function of the gene. Each of these features can be accomplished with in situ hybridization to mRNAs within cells. Here we present a radioactive in situ hybridization method modified from Clayton et al. (1988)(1) that has been working successfully in our lab for many years, especially for adult vertebrate brains(2-5). The long complementary RNA (cRNA) probes to the target sequence allows for detection of low abundance transcripts(6,7). Incorporation of radioactive nucleotides into the cRNA probes allows for further detection sensitivity of low abundance transcripts and quantitative analyses, either by light sensitive x-ray film or emulsion coated over the tissue. These detection methods provide a long-term record of target gene expression. Compared with non-radioactive probe methods, such as DIG-labeling, the radioactive probe hybridization method does not require multiple amplification steps using HRP-antibodies and/or TSA kit to detect low abundance transcripts. Therefore, this method provides a linear relation between signal intensity and targeted mRNA amounts for quantitative analysis. It allows processing 100-200 slides simultaneously. It works well for different developmental stages of embryos. Most developmental studies of gene expression use whole embryos and non-radioactive approaches(8,9), in part because embryonic tissue is more fragile than adult tissue, with less cohesion between cells, making it difficult to see boundaries between cell populations with tissue sections. In contrast, our radioactive approach, due to the larger range of sensitivity, is able to obtain higher contrast in resolution of gene expression between tissue regions, making it easier to see boundaries between populations. Using this method, researchers could reveal the possible significance of a newly identified gene, and further predict the function of the gene of interest.

Study of gene expression in thyrotropin-stimulated thyroid cells by cDNA expression array: ID3 transcription modulating factor as an early response protein and tumor marker in thyroid carcinomas.

Induction of cell proliferation by mitogen or growth factor stimulation leads to the specific induction or repression of a large number of genes. To identify genes differentially regulated by the cAMP-dependent transduction pathway, which is poorly characterized so far, we used the cDNA expression array technology. Hybridizations of Atlas human cDNA expression arrays with (32)P-labeled cDNA probes derived from control or thyrotropin (TSH)-stimulated dog thyrocytes in primary culture generated expression profiles of hundreds of genes simultaneously. Among the genes that displayed modified expression, we selected the transcription factor ID3, whose expression was increased by a cAMP-dependent stimulus. ID3 overexpression after TSH stimulation was first verified by Northern blotting analysis, and its mRNA regulation was then investigated in response to a variety of agents acting on thyrocyte proliferation and/or differentiation. We show that: (1) ID3 mRNA induction was stronger after stimulation of the cAMP cascade, but was not restricted to this signaling pathway, as phorbol myristate ester (TPA) and insulin also stimulated mRNA accumulation; (2) in contrast, powerful mitogens for thyroid cells, epidermal growth factor and hepatocyte growth factor, did not significantly modify ID3 mRNA levels; (3) ID3 protein levels closely parallelled mRNA levels, as revealed by immunofluorescence experiments showing a nuclear signal regulated by TSH; (4) in papillary thyroid carcinomas, ID3 mRNA was downregulated. Our results suggest that ID3 expression might be more related to the differentiating process induced by TSH than to the proliferative action of this hormone.

Analysis of HSC activity and compensatory Hox gene expression profile in Hoxb cluster mutant fetal liver cells

Overexpression of Hoxb4 in bone marrow cells promotes expansion of hematopoietic stem cell (HSC) populations in vivo and in vitro, indicating that this homeoprotein can activate the genetic program that determines self-renewal. However, this function cannot be solely attributed to Hoxb4 because Hoxb4(-/-) mice are viable and have an apparently normal HSC number. Quantitative polymerase chain reaction analysis showed that Hoxb4(-/-) c-Kit(+) fetal liver cells expressed moderately higher levels of several Hoxb cluster genes than control cells, raising the possibility that normal HSC activity in Hoxb4(-/-) mice is due to a compensatory up-regulation of other Hoxb genes. In this study, we investigated the competitive repopulation potential of HSCs lacking Hoxb4 alone, or in conjunction with 8 other Hoxb genes. Our results show that Hoxb4(-/-) and Hoxb1-b9(-/-) fetal liver cells retain full competitive repopulation potential and the ability to regenerate all myeloid and lymphoid lineages. Quantitative Hox gene expression profiling in purified c-KIt(+) Hoxb1-bg(-/-) fetal liver cells revealed an interaction between the Hoxa, b, and c clusters with variation in expression levels of Hoxa4, -a11, and -c4. Together, these studies show a complex network of genetic interactions between several Hox genes in primitive hematopoietic cells and demonstrate that HSCs lacking up to 30% of the active Hox genes remain fully competent.

Novel breast cancer biomarkers identified by integrative proteomic and gene expression mapping

Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.

Effects of oxidized and glycated LDL on gene expression in human retinal capillary pericytes

Modified (oxidized and/or glycated) low-density lipoproteins (LDLs) have been implicated in retinal pericyte loss, one of the major pathologic features of early-stage diabetic retinopathy. To delineate underlying molecular mechanisms, the present study was designed to explore the global effects of modified LDL on pericyte gene expression.

Identification of Gene Expression-Based Prognostic Markers in the Hematopoietic Stem Cells of Patients With Myelodysplastic Syndromes

The diagnosis of patients with myelodysplastic syndromes (MDS) is largely dependent on morphologic examination of bone marrow aspirates. Several criteria that form the basis of the classifications and scoring systems most commonly used in clinical practice are affected by operator-dependent variation. To identify standardized molecular markers that would allow prediction of prognosis, we have used gene expression profiling (GEP) data on CD34+ cells from patients with MDS to determine the relationship between gene expression levels and prognosis.

Gene expression and epigenetic discovery screen reveal methylation of SFRP2 in prostate cancer

Aberrant activation of Wnts is common in human cancers, including prostate. Hypermethylation associated transcriptional silencing of Wnt antagonist genes SFRPs (Secreted Frizzled-Related Proteins) is a frequent oncogenic event. The significance of this is not known in prostate cancer. The objectives of our study were to (i) profile Wnt signaling related gene expression and (ii) investigate methylation of Wnt antagonist genes in prostate cancer. Using TaqMan Low Density Arrays, we identified 15 Wnt signaling related genes with significantly altered expression in prostate cancer; the majority of which were upregulated in tumors. Notably, histologically benign tissue from men with prostate cancer appeared more similar to tumor (r = 0.76) than to benign prostatic hyperplasia (BPH; r = 0.57, p < 0.001). Overall, the expression profile was highly similar between tumors of high (≥ 7) and low (≤ 6) Gleason scores. Pharmacological demethylation of PC-3 cells with 5-Aza-CdR reactivated 39 genes (≥ 2-fold); 40% of which inhibit Wnt signaling. Methylation frequencies in prostate cancer were 10% (2/20) (SFRP1), 64.86% (48/74) (SFRP2), 0% (0/20) (SFRP4) and 60% (12/20) (SFRP5). SFRP2 methylation was detected at significantly lower frequencies in high-grade prostatic intraepithelial neoplasia (HGPIN; 30%, (6/20), p = 0.0096), tumor adjacent benign areas (8.82%, (7/69), p < 0.0001) and BPH (11.43% (4/35), p < 0.0001). The quantitative level of SFRP2 methylation (normalized index of methylation) was also significantly higher in tumors (116) than in the other samples (HGPIN = 7.45, HB = 0.47, and BPH = 0.12). We show that SFRP2 hypermethylation is a common event in prostate cancer. SFRP2 methylation in combination with other epigenetic markers may be a useful biomarker of prostate cancer.

Characterization of a reference material for BCR-ABL (M-BCR) mRNA quantitation by real-time amplification assays:towards new standards for gene expression measurements

Monitoring of BCR-ABL transcripts has become established practice in the management of chronic myeloid leukemia. However, nucleic acid amplification techniques are prone to variations which limit the reliability of real-time quantitative PCR (RQ-PCR) for clinical decision making, highlighting the need for standardization of assays and reporting of minimal residual disease (MRD) data. We evaluated a lyophilized preparation of a leukemic cell line (K562) as a potential quality control reagent. This was found to be relatively stable, yielding comparable respective levels of ABL, GUS and BCR-ABL transcripts as determined by RQ-PCR before and after accelerated degradation experiments as well as following 5 years storage at -20 degrees C. Vials of freeze-dried cells were sent at ambient temperature to 22 laboratories on four continents, with RQ-PCR analyses detecting BCR-ABL transcripts at levels comparable to those observed in primary patient samples. Our results suggest that freeze-dried cells can be used as quality control reagents with a range of analytical instrumentations and could enable the development of urgently needed international standards simulating clinically relevant levels of MRD.

An atlas of human gene expression from massively parallel signature sequencing (MPSS).

We have used massively parallel signature sequencing (MPSS) to sample the transcriptomes of 32 normal human tissues to an unprecedented depth, thus documenting the patterns of expression of almost 20,000 genes with high sensitivity and specificity. The data confirm the widely held belief that differences in gene expression between cell and tissue types are largely determined by transcripts derived from a limited number of tissue-specific genes, rather than by combinations of more promiscuously expressed genes. Expression of a little more than half of all known human genes seems to account for both the common requirements and the specific functions of the tissues sampled. A classification of tissues based on patterns of gene expression largely reproduces classifications based on anatomical and biochemical properties. The unbiased sampling of the human transcriptome achieved by MPSS supports the idea that most human genes have been mapped, if not functionally characterized. This data set should prove useful for the identification of tissue-specific genes, for the study of global changes induced by pathological conditions, and for the definition of a minimal set of genes necessary for basic cell maintenance. The data are available on the Web at http://mpss.licr.org and http://sgb.lynxgen.com.