Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics

Background: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. Methodology/Principal Findings: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer. Conclusions/Significance: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy

Elevated levels of Dickkopf-related protein 3 in seminal plasma of prostate cancer patients

<p>Abstract</p> <p>Background</p> <p>Expression of Dkk-3, a secreted putative tumor suppressor, is altered in age-related proliferative disorders of the human prostate. We now investigated the suitability of Dkk-3 as a diagnostic biomarker for prostate cancer (PCa) in seminal plasma (SP).</p> <p>Methods</p> <p>SP samples were obtained from 81 patients prior to TRUS-guided prostate biopsies on the basis of elevated serum prostate-specific antigen (PSA; > 4 ng/mL) levels and/or abnormal digital rectal examination. A sensitive indirect immunoenzymometric assay for Dkk-3 was developed and characterized in detail. SP Dkk-3 and PSA levels were determined and normalized to total SP protein. The diagnostic accuracies of single markers including serum PSA and multivariate models to discriminate patients with positive (N = 40) and negative (N = 41) biopsy findings were investigated.</p> <p>Results</p> <p>Biopsy-confirmed PCa showed significantly higher SP Dkk-3 levels (100.9 ± 12.3 vs. 69.2 ± 9.4 fmol/mg; <it>p </it>= 0.026). Diagnostic accuracy (AUC) of SP Dkk-3 levels (0.633) was enhanced in multivariate models by including serum PSA (model A; AUC 0.658) or both, serum and SP PSA levels (model B; AUC 0.710). In a subpopulation with clinical follow-up > 3 years post-biopsy to ensure veracity of negative biopsy status (positive biopsy N = 21; negative biopsy N = 25) AUCs for SP Dkk-3, model A and B increased to 0.667, 0.724 and 0.777, respectively.</p> <p>Conclusions</p> <p>In multivariate models to detect PCa, inclusion of SP Dkk-3 levels, which were significantly elevated in biopsy-confirmed PCa patients, improved the diagnostic performance compared with serum PSA only.</p

Identification of claudin-4 as a marker highly overexpressed in both primary and metastatic prostate cancer

In the quest for markers of expression and progression for prostate cancer (PCa), the majority of studies have focussed on molecular data exclusively from primary tumours. Although expression in metastases is inferred, a lack of correlation with secondary tumours potentially limits their applicability diagnostically and therapeutically. Molecular targets were identified by examining expression profiles of prostate cell lines using cDNA microarrays. Those genes identified were verified on PCa cell lines and tumour samples from both primary and secondary tumours using real-time RT–PCR, western blotting and immunohistochemistry. Claudin-4, coding for an integral membrane cell-junction protein, was the most significantly (P<0.00001) upregulated marker in both primary and metastatic tumour specimens compared with benign prostatic hyperplasia at both RNA and protein levels. In primary tumours, claudin-4 was more highly expressed in lower grade (Gleason 6) lesions than in higher grade (Gleason ⩾7) cancers. Expression was prominent throughout metastases from a variety of secondary sites in fresh-frozen and formalin-fixed specimens from both androgen-intact and androgen-suppressed patients. As a result of its prominent expression in both primary and secondary PCas, together with its established role as a receptor for Clostridium perfringens enterotoxin, claudin-4 may be useful as a potential marker and therapeutic target for PCa metastases

Quantitative real-time RT-PCR of CD24 mRNA in the detection of prostate cancer

BACKGROUND: Gene expression profiling has recently shown that the mRNA for CD24 is overexpressed in prostate carcinomas (Pca) compared to benign or normal prostate epithelial tissues. Immunohistochemical studies have reported the usefulness of anti-CD24 for detecting prostate cancer over the full range of prostate specimens encountered in surgical pathology, e.g. needle biopsies, transurethral resection of prostate chips, or prostatectomies. It is a small mucin-like cell surface protein and thus promises to become at least a standard adjunctive stain for atypical prostate biopsies. We tested the usefulness of real-time RT-PCR for specific and sensitive detection of CD24 transcripts as a supplementary measure for discriminating between malignant and benign lesions in prostatic tissues. METHODS: Total RNA was isolated from snap-frozen chips in 55 cases of benign prostatic hyperplasia (BPH) and from frozen sections in 59 prostatectomy cases. The latter contain at least 50% malignant epithelia. Relative quantification of CD24 transcripts was performed on the LightCycler instrument using hybridization probes for detection and porphobilinogen deaminase transcripts (PBGD) for normalization. RESULTS: Normalized CD24 transcript levels showed an average 2.69-fold increase in 59 Pca-cases (mean 0.21) when compared to 55 cases of BPH (mean 0.08). This difference was highly significant (p < 0.0001). The method has a moderate specificity (47.3%) but a high sensitivity (86.4%) if the cutoff is set at 0.0498. CD24 expression levels among Pca cases were not statistically associated with the tumor and lymph-node stage, the grading (WHO), the surgical margins, or the Gleason score. CONCLUSION: The present study demonstrates the feasibility of quantitative CD24 RNA transcript detection in prostatic tissues even without previous laser microdissection

TL1A Selectively Enhances IL-12/IL-18-Induced NK Cell Cytotoxicity against NK-Resistant Tumor Targets

# The Author(s) 2010. This article is published with open access at Springerlink.com Introduction TL1A (TNFSF15) augments IFN-γ production by IL-12/IL-18 responsive human T cells. Its ligand, death domain receptor 3 (DR3), is induced by activation on T and NK cells. Although IL-12/IL-18 induces DR3 expression on most NK cells, addition of TL1A minimally increases IFN-

An Unexpected Function of the Prader-Willi Syndrome Imprinting Center in Maternal Imprinting in Mice

Genomic imprinting is a phenomenon that some genes are expressed differentially according to the parent of origin. Prader-Willi syndrome (PWS) and Angelman syndrome (AS) are neurobehavioral disorders caused by deficiency of imprinted gene expression from paternal and maternal chromosome 15q11–q13, respectively. Imprinted genes at the PWS/AS domain are regulated through a bipartite imprinting center, the PWS-IC and AS-IC. The PWS-IC activates paternal-specific gene expression and is responsible for the paternal imprint, whereas the AS-IC functions in the maternal imprint by allele-specific repression of the PWS-IC to prevent the paternal imprinting program. Although mouse chromosome 7C has a conserved PWS/AS imprinted domain, the mouse equivalent of the human AS-IC element has not yet been identified. Here, we suggest another dimension that the PWS-IC also functions in maternal imprinting by negatively regulating the paternally expressed imprinted genes in mice, in contrast to its known function as a positive regulator for paternal-specific gene expression. Using a mouse model carrying a 4.8-kb deletion at the PWS-IC, we demonstrated that maternal transmission of the PWS-IC deletion resulted in a maternal imprinting defect with activation of the paternally expressed imprinted genes and decreased expression of the maternally expressed imprinted gene on the maternal chromosome, accompanied by alteration of the maternal epigenotype toward a paternal state spread over the PWS/AS domain. The functional significance of this acquired paternal pattern of gene expression was demonstrated by the ability to complement PWS phenotypes by maternal inheritance of the PWS-IC deletion, which is in stark contrast to paternal inheritance of the PWS-IC deletion that resulted in the PWS phenotypes. Importantly, low levels of expression of the paternally expressed imprinted genes are sufficient to rescue postnatal lethality and growth retardation in two PWS mouse models. These findings open the opportunity for a novel approach to the treatment of PWS

Serological Markers for Inflammatory Bowel Disease in AIDS Patients with Evidence of Microbial Translocation

Background: Breakdown of the gut mucosal barrier during chronic HIV infection allows translocation of bacterial products such as lipopolysaccharides (LPS) from the gut into the circulation. Microbial translocation also occurs in inflammatory bowel disease (IBD). IBD serological markers are useful in the diagnosis of IBD and to differentiate between Crohn's disease (CD) and ulcerative colitis (UC). Here, we evaluate detection of IBD serological markers in HIV-infected patients with advanced disease and their relationship to HIV disease markers.Methods IBD serological markers (ASCA, pANCA, anti-OmpC, and anti-CBir1) were measured by ELISA in plasma from AIDS patients (n = 26) with low CD4 counts (<300 cells/$\mu$l) and high plasma LPS levels, and results correlated with clinical data. For meta-analysis, relevant data were abstracted from 20 articles. Results: IBD serological markers were detected in approximately 65% of AIDS patients with evidence of microbial translocation. An antibody pattern consistent with IBD was detected in 46%; of these, 75% had a CD-like pattern. Meta-analysis of data from 20 published studies on IBD serological markers in CD, UC, and non-IBD control subjects indicated that IBD serological markers are detected more frequently in AIDS patients than in non-IBD disease controls and healthy controls, but less frequently than in CD patients. There was no association between IBD serological markers and HIV disease markers (plasma viral load and CD4 counts) in the study cohort. Conclusions: IBD serological markers may provide a non-invasive approach to monitor HIV-related inflammatory gut disease. Further studies to investigate their clinical significance in HIV-infected individuals are warranted

Accurate molecular classification of cancer using simple rules

<p>Abstract</p> <p>Background</p> <p>One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible.</p> <p>Methods</p> <p>We screened a small number of informative single genes and gene pairs on the basis of their depended degrees proposed in rough sets. Applying the decision rules induced by the selected genes or gene pairs, we constructed cancer classifiers. We tested the efficacy of the classifiers by leave-one-out cross-validation (LOOCV) of training sets and classification of independent test sets.</p> <p>Results</p> <p>We applied our methods to five cancerous gene expression datasets: leukemia (acute lymphoblastic leukemia [ALL] vs. acute myeloid leukemia [AML]), lung cancer, prostate cancer, breast cancer, and leukemia (ALL vs. mixed-lineage leukemia [MLL] vs. AML). Accurate classification outcomes were obtained by utilizing just one or two genes. Some genes that correlated closely with the pathogenesis of relevant cancers were identified. In terms of both classification performance and algorithm simplicity, our approach outperformed or at least matched existing methods.</p> <p>Conclusion</p> <p>In cancerous gene expression datasets, a small number of genes, even one or two if selected correctly, is capable of achieving an ideal cancer classification effect. This finding also means that very simple rules may perform well for cancerous class prediction.</p

Are all ‘research fields’ equal? Rethinking practice for the use of data from crowd-sourcing market places

New technologies like large-scale social media sides (e.g., Facebook and Twitter) and crowdsourcing services (e.g., Amazon Mechanical Turk, Crowdflower, Clickworker) impact social science research and provide many new and interesting avenues for research. The use of these new technologies for research has not been without challenges and a recently published psychological study on Facebook led to a widespread discussion on the ethics of conducting large-scale experiments online. Surprisingly little has been said about the ethics of conducting research using commercial crowdsourcing market places. In this paper, I want to focus on the question of which ethical questions are raised by data collection with crowdsourcing tools. I briefly draw on implications of internet research more generally and then focus on the specific challenges that research with crowdsourcing tools faces. I identify fair-pay and related issues of respect for autonomy as well as problems with power dynamics between researcher and participant, which has implications for ‘withdrawal-withoutprejudice’, as the major ethical challenges with crowdsourced data. Further, I will to draw attention on how we can develop a ‘best practice’ for researchers using crowdsourcing tools