Automatic Annotation of Spatial Expression Patterns via Sparse Bayesian Factor Models

Advances in reporters for gene expression have made it possible to document and quantify expression patterns in 2D–4D. In contrast to microarrays, which provide data for many genes but averaged and/or at low resolution, images reveal the high spatial dynamics of gene expression. Developing computational methods to compare, annotate, and model gene expression based on images is imperative, considering that available data are rapidly increasing. We have developed a sparse Bayesian factor analysis model in which the observed expression diversity of among a large set of high-dimensional images is modeled by a small number of hidden common factors. We apply this approach on embryonic expression patterns from a Drosophila RNA in situ image database, and show that the automatically inferred factors provide for a meaningful decomposition and represent common co-regulation or biological functions. The low-dimensional set of factor mixing weights is further used as features by a classifier to annotate expression patterns with functional categories. On human-curated annotations, our sparse approach reaches similar or better classification of expression patterns at different developmental stages, when compared to other automatic image annotation methods using thousands of hard-to-interpret features. Our study therefore outlines a general framework for large microscopy data sets, in which both the generative model itself, as well as its application for analysis tasks such as automated annotation, can provide insight into biological questions

Regional differences in HIV prevalence among drug users in China: potential for future spread of HIV?

Kretzschmar M, Zhang W, Mikolajczyk RT, et al. Regional differences in HIV prevalence among drug users in China: potential for future spread of HIV? BMC Infectious Diseases. 2008;8(1):108.Background: Drug use and in particular injecting drug use has been at the forefront of the explosive spread of HIV in general populations in many countries in Asia. There is concern that also in China increased HIV incidence in drug users might spark off a generalized epidemic in the wider population. Close monitoring of HIV incidence and risk factors in drug users is therefore important to be able to target interventions effectively. Second generation surveillance was launched to assess HIV prevalence and risk behaviours jointly with the purpose of describing trends and predicting future developments. To assess whether these goals were fulfilled among drug users in China we provide an analysis of risk factors for HIV infection and of regional differences in HIV prevalence. Methods: We analysed data collected in 2005 in 21 drug user second generation surveillance sentinel sites from 14 provinces in China. We used random effects logistic regression to test for risk factors for HIV infection and regional differences. Results: The overall HIV-1 antibody prevalence was 5.4% (279/5128); 4.9% among injecting drug users (IDU) not sharing needles and 3.7% among non-injecting drug users. We found substantial heterogeneity among the surveillance sites with prevalence rates ranging between 0% and 54%. HIV status was strongly affected by the regional prevalence of HIV. Risk behaviours were highly prevalent in regions where HIV prevalence is still low. The distribution of duration of drug use in different sites indicated different stages of the drug use epidemics. Conclusion: ]Regional differences in HIV prevalence in China reflect different stages of the drug use and HIV epidemics rather than differences in risk behaviours. Therefore, outbreaks of HIV among drug users in regions where prevalence is still low can be expected in the future. However, methodological limitations of surveillance embedded into routine systems limit the usability of existing data. More standardized approaches to data collection in secondary generation HIV surveillance are necessary to better understand regional differences in risk behaviour and prevalence and to design targeted intervention for those regions at risk of experiencing outbreaks

Triptolide Inhibits the Proliferation of Prostate Cancer Cells and Down-Regulates SUMO-Specific Protease 1 Expression

Recently, traditional Chinese medicine and medicinal herbs have attracted more attentions worldwide for its anti-tumor efficacy. Celastrol and Triptolide, two active components extracted from the Chinese herb Tripterygium wilfordii Hook F (known as Lei Gong Teng or Thunder of God Vine), have shown anti-tumor effects. Celastrol was identified as a natural 26 s proteasome inhibitor which promotes cell apoptosis and inhibits tumor growth. The effect and mechanism of Triptolide on prostate cancer (PCa) is not well studied. Here we demonstrated that Triptolide, more potent than Celastrol, inhibited cell growth and induced cell death in LNCaP and PC-3 cell lines. Triptolide also significantly inhibited the xenografted PC-3 tumor growth in nude mice. Moreover, Triptolide induced PCa cell apoptosis through caspases activation and PARP cleavage. Unbalance between SUMOylation and deSUMOylation was reported to play an important role in PCa progression. SUMO-specific protease 1 (SENP1) was thought to be a potential marker and therapeutical target of PCa. Importantly, we observed that Triptolide down-regulated SENP1 expression in both mRNA and protein levels in dose-dependent and time-dependent manners, resulting in an enhanced cellular SUMOylation in PCa cells. Meanwhile, Triptolide decreased AR and c-Jun expression at similar manners, and suppressed AR and c-Jun transcription activity. Furthermore, knockdown or ectopic SENP1, c-Jun and AR expression in PCa cells inhibited the Triptolide anti-PCa effects. Taken together, our data suggest that Triptolide is a natural compound with potential therapeutic value for PCa. Its anti-tumor activity may be attributed to mechanisms involving down-regulation of SENP1 that restores SUMOylation and deSUMOyaltion balance and negative regulation of AR and c-Jun expression that inhibits the AR and c-Jun mediated transcription in PCa

Phagocytosis of Staphylococcus aureus by Macrophages Exerts Cytoprotective Effects Manifested by the Upregulation of Antiapoptotic Factors

It is becoming increasingly apparent that Staphylococcus aureus are able to survive engulfment by macrophages, and that the intracellular environment of these host cells, which is essential to innate host defenses against invading microorganisms, may in fact provide a refuge for staphylococcal survival and dissemination. Based on this, we postulated that S. aureus might induce cytoprotective mechanisms by changing gene expression profiles inside macrophages similar to obligate intracellular pathogens, such as Mycobacterium tuberculosis. To validate our hypothesis we first ascertained whether S. aureus infection could affect programmed cell death in human (hMDMs) and mouse (RAW 264.7) macrophages and, specifically, protect these cells against apoptosis. Our findings indicate that S. aureus-infected macrophages are more resistant to staurosporine-induced cell death than control cells, an effect partly mediated via the inhibition of cytochrome c release from mitochondria. Furthermore, transcriptome analysis of human monocyte-derived macrophages during S. aureus infection revealed a significant increase in the expression of antiapoptotic genes. This was confirmed by quantitative RT-PCR analysis of selected genes involved in mitochondria-dependent cell death, clearly showing overexpression of BCL2 and MCL1. Cumulatively, the results of our experiments argue that S. aureus is able to induce a cytoprotective effect in macrophages derived from different mammal species, which can prevent host cell elimination, and thus allow intracellular bacterial survival. Ultimately, it is our contention that this process may contribute to the systemic dissemination of S. aureus infection

P1-07-13: Efficiency of a Laboratory Developed HER2 FISH Test on Circulating Tumor Cells.

Abstract INTRODUCTION: Most circulating tumor cell (CTC) platforms rely on EpCAM for capture and cytokeratin (CK) for detection. However, an important population of cells that are CK-negative (i.e. cells with epithelial-mesenchymal transition (EMT) phenotype) will be missed. We report a new strategy to efficiently isolate a more heterogeneous population of CTCs using an antibody cocktail. METHODS: In the first prospective study, blood (20 mL) was collected from 89 patients diagnosed with various late stage metastatic/recurrent cancers (breast, CRC, lung, prostate) following IRB approval. PBMCs were incubated with either EpCAM alone or a mixture of 10 capture antibodies to target both epithelial and mesenchymal cells. CTCs were subsequently captured in the OncoCEE™ channels and detected with cytokeratin (CK) and CD45. A second prospective IRB approved study involving 54 patients diagnosed with late stage metastatic/recurrent breast cancer was performed using similar detection strategies (CK cocktail mixture and anti-CD45) with the addition of HER2 FISH to determine amplification status among captured CK+/CD45- and CK-/CD45-cells. RESULTS: In the first study, overall detection of CK+ cells was 83% with EpCAM alone and 93% with antibody cocktail. In addition, a median of 0.4 CK+ cells/mL and 1.0 CK+ cells/mL was observed using EpCAM and antibody cocktail, respectively. In the second study, CK+/CD45- cells were detected in 43 of 54 cases (80%). Among the 43 cases in which CK+/CD45- cells were detected, high concordance (93%) in HER2 status between primary tumor and CTCs was observed with HER2 amplification noted in both CK+/CD45- (50%) and CK-/CD45- (50%) cells. CONCLUSIONS: We have developed a novel and robust method for CTC enumeration that utilizes a cocktail of antibodies for the detection of a heterogeneous (CK+ and CK-) population of CTCs. Our findings suggest an important population of CK- cells is being missed by current stain criteria in breast cancer patients. Data also demonstrate that recovery of CTCs from peripheral blood using the OncoCEE™ platform is efficient and suitable for FISH-based laboratory testing. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P1-07-13.</jats:p