MicroRNAs are regulators of gene expression. A wide-spread, yet not validated, assumption is that the targetome of miRNAs is non-randomly distributed across the transcriptome and that targets share functional pathways. We developed a computational and experimental strategy termed high-throughput miRNA interaction reporter assay (HiTmIR) to facilitate the validation of target pathways. First, targets and target pathways are predicted and prioritized by computational means to increase the specificity and positive predictive value. Second, the novel webtool miRTaH facilitates guided designs of reporter assay constructs at scale. Third, automated and standardized reporter assays are performed. We evaluated HiTmIR using miR-34a-5p, for which TNF- and TGFB-signaling, and Parkinson's Disease (PD)-related categories were identified and repeated the pipeline for miR-7-5p. HiTmIR validated 58.9% of the target genes for miR-34a-5p and 46.7% for miR-7-5p. We confirmed the targeting by measuring the endogenous protein levels of targets in a neuronal cell model. The standardized positive and negative targets are collected in the new miRATBase database, representing a resource for training, or benchmarking new target predictors. Applied to 88 target predictors with different confidence scores, TargetScan 7.2 and miRanda outperformed other tools. Our experiments demonstrate the efficiency of HiTmIR and provide evidence for an orchestrated miRNA-gene targeting.

NF-κB functions as modulator of T cell receptor-mediated signaling and transcriptional regulator of miR-34a. Our in silico analysis revealed that miR-34a impacts the NF-κB signalosome with miR-34a binding sites in 14 key members of the NF-κB signaling pathway. Functional analysis identified five target genes of miR-34a including PLCG1, CD3E, PIK3CB, TAB2, and NFΚBIA. Overexpression of miR-34a in CD4+ and CD8+ T cells led to a significant decrease of NFΚBIA as the most downstream cytoplasmic NF-κB member, a reduced cell surface abundance of TCRA and CD3E, and to a reduction of T cell killing capacity. Inhibition of miR-34a caused an increase of NFΚBIA, TCRA, and CD3E. Notably, activation of CD4+ and CD8+ T cells entrails a gradual increase of miR-34a. Our results lend further support to a model with miR-34a as a central NF-κB regulator in T cells.

Seroreactivity profiling emerges as valuable technique for minimal invasive cancer detection. Recently, we provided first evidence for the applicability of serum profiling of glioma using a limited number of immunogenic antigens. Here, we screened 57 glioma and 60 healthy sera for autoantibodies against 1827 Escherichia coli expressed clones, including 509 in-frame peptide sequences. By a linear support vector machine approach, we calculated mean specificity, sensitivity, and accuracy of 100 repetitive classifications. We were able to differentiate glioma sera from sera of the healthy controls with a specificity of 90.28%, a sensitivity of 87.31% and an accuracy of 88.84%. We were also able to differentiate World Health Organization grade IV glioma sera from healthy sera with a specificity of 98.45%, a sensitivity of 80.93%, and an accuracy of 92.88%. To rank the antigens according to their information content, we computed the area under the receiver operator characteristic curve value for each clone. Altogether, we found 46 immunogenic clones including 16 in-frame clones that were informative for the classification of glioma sera versus healthy sera. For the separation of glioblastoma versus healthy sera, we found 91 informative clones including 26 in-frame clones. The best-suited in-frame clone for the classification glioma sera versus healthy sera corresponded to the vimentin gene (VIM) that was previously associated with glioma. In the future, autoantibody signatures in glioma not only may prove useful for diagnosis but also offer the prospect for a personalized immune-based therapy.

Background: Chronic obstructive pulmonary disease (COPD) is a respiratory inflammatory condition with autoimmune features including IgG autoantibodies. In this study we analyze the complexity of the autoantibody response and reveal the nature of the antigens that are recognized by autoantibodies in COPD patients.

Since the benefit of prostate-specific antigen (PSA) screening remains controversial, new non-invasive biomarkers for prostate carcinoma (PCa) are still required. There is evidence that microRNAs (miRNAs) in whole peripheral blood can separate patients with localized prostate cancer from healthy individuals. However, the potential of blood-based miRNAs for the differential diagnosis of PCa and benign prostatic hyperplasia (BPH) has not been tested. We compared the miRNome from blood of PCa and BPH patients and further investigated the influence of the tumor volume, tumor-node-metastasis (TNM) classification, Gleason score, pretreatment risk status, and the pretreatment PSA value on the miRNA pattern. By microarray approach, we identified seven miRNAs that were significantly deregulated in PCa patients compared to BPH patients. Using quantitative real time PCR (qRT-PCR), we confirmed downregulation of hsa-miR-221* (now hsa-miR-221-5p) and hsa-miR-708* (now hsa-miR-708-3p) in PCa compared to BPH. Clinical parameters like PSA level, Gleason score, or TNM status seem to have only limited impact on the overall abundance of miRNAs in patients' blood, suggesting a no influence of these factors on the expression of deregulated miRNAs.