Profound effect of profiling platform and normalization strategy on detection of differentially expressed microRNAs

Adequate normalization minimizes the effects of systematic technical variations and is a prerequisite for getting meaningful biological changes. However, there is inconsistency about miRNA normalization performances and recommendations. Thus, we investigated the impact of seven different normalization methods (reference gene index, global geometric mean, quantile, invariant selection, loess, loessM, and generalized procrustes analysis) on intra- and inter-platform performance of two distinct and commonly used miRNA profiling platforms. We included data from miRNA profiling analyses derived from a hybridization-based platform (Agilent Technologies) and an RT-qPCR platform (Applied Biosystems). Furthermore, we validated a subset of miRNAs by individual RT-qPCR assays. Our analyses incorporated data from the effect of differentiation and tumor necrosis factor alpha treatment on primary human skeletal muscle cells and a murine skeletal muscle cell line. Distinct normalization methods differed in their impact on (i) standard deviations, (ii) the area under the receiver operating characteristic (ROC) curve, (iii) the similarity of differential expression. Loess, loessM, and quantile analysis were most effective in minimizing standard deviations on the Agilent and TLDA platform. Moreover, loess, loessM, invariant selection and generalized procrustes analysis increased the area under the ROC curve, a measure for the statistical performance of a test. The Jaccard index revealed that inter-platform concordance of differential expression tended to be increased by loess, loessM, quantile, and GPA normalization of AGL and TLDA data as well as RGI normalization of TLDA data. We recommend the application of loess, or loessM, and GPA normalization for miRNA Agilent arrays and qPCR cards as these normalization approaches showed to (i) effectively reduce standard deviations, (ii) increase sensitivity and accuracy of differential miRNA expression detection as well as (iii) increase inter-platform concordance. Results showed the successful adoption of loessM and generalized procrustes analysis to one-color miRNA profiling experiments

Identification of common blood gene signatures for the diagnosis of renal and cardiac acute allograft rejection.

To test, whether 10 genes, diagnostic of renal allograft rejection in blood, are able to diagnose and predict cardiac allograft rejection, we analyzed 250 blood samples from heart transplant recipients with and without acute rejection (AR) and with cytomegalovirus (CMV) infection by QPCR. A QPCR-based logistic regression model was built on 5 of these 10 genes (AR threshold composite score >37%  = AR) and tested for AR prediction in an independent set of 109 samples, where it correctly diagnosed AR with 89% accuracy, with no misclassifications for AR ISHLT grade 1b. CMV infection did not confound the AR score. The genes correctly diagnosed AR in a blood sample within 6 months prior to biopsy diagnosis with 80% sensitivity and untreated grade 1b AR episodes had persistently elevated scores until 6 months after biopsy diagnosis. The gene score was also correlated with presence or absence of cardiac allograft vasculopathy (CAV) irrespective of rejection grade. In conclusion, there is a common transcriptional axis of immunological trafficking in peripheral blood in both renal and cardiac organ transplant rejection, across a diverse recipient age range. A common gene signature, initially identified in the setting of renal transplant rejection, can be utilized serially after cardiac transplantation, to diagnose and predict biopsy confirmed acute heart transplant rejection

MicroRNAs-Proteomic Networks Characterizing Human Medulloblastoma-SLCs

Medulloblastoma (MB) is the most common malignant brain tumor of pediatric age and is characterized by cells expressing stem, astroglial, and neuronal markers. Among them, stem-like cells (hMB-SLCs) represent a fraction of the tumor cell population with the potential of self-renewal and proliferation and have been associated with tumor poor prognosis. In this context, microRNAs have been described as playing a pivotal role in stem cells differentiation. In our paper, we analyze microRNAs profile and genes expression of hMB-SLCs before and after Retinoic Acid- (RA-) induced differentiation. We aimed to identify pivotal players of specific pathways sustaining stemness and/or tumor development and progression and integrate the results of our recent proteomic study. Our results uncovered 22 differentially expressed microRNAs that were used as input together with deregulated genes and proteins in the Genomatix Pathway System (GePS) analysis revealing 3 subnetworks that could be interestingly involved in the maintenance of hMB-SLCs proliferation. Taken together, our findings highlight microRNAs, genes, and proteins that are significantly modulated in hMB-SLCs with respect to their RA-differentiated counterparts and could open new perspectives for prognostic and therapeutic intervention on MB

Two-phase wash to solve the ubiquitous contaminant-carryover problem in commercial nucleic-acid extraction kits

The success of fundamental and applied nucleic acid (NA) research depends on NA purity, but obtaining pure NAs from raw, unprocessed samples is challenging. Purification using solid-phase NA extractions utilizes sequential additions of lysis and wash buffers followed by elution. The resulting eluent contains NAs and carryover of extraction buffers. Typically, these inhibitory buffers are heavily diluted by the reaction mix (e.g., 10x dilution is 1 µL eluent in 9 µL reaction mix), but in applications requiring high sensitivity (e.g., single-cell sequencing, pathogen diagnostics) it is desirable to use low dilutions (e.g., 2x) to maximize NA concentration. Here, we demonstrate pervasive carryover of inhibitory buffers into eluent when several commercial sample-preparation kits are used following manufacturer protocols. At low eluent dilution (2–2.5x) we observed significant reaction inhibition of polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), and reverse transcription (RT). We developed a two-phase wash (TPW) method by adding a wash buffer with low water solubility prior to the elution step. The TPW reduces carryover of extraction buffers, phase-separates from the eluent, and does not reduce NA yield (measured by digital PCR). We validated the TPW for silica columns and magnetic beads by demonstrating significant improvements in performance and reproducibility of qPCR, LAMP, and RT reactions

Circular RNAs in Clear Cell Renal Cell Carcinoma: Their Microarray-Based Identification, Analytical Validation, and Potential Use in a Clinico-Genomic Model to Improve Prognostic Accuracy

Circular RNAs (circRNAs) may act as novel cancer biomarkers. However, a genome-wide evaluation of circRNAs in clear cell renal cell carcinoma (ccRCC) has yet to be conducted. Therefore, the objective of this study was to identify and validate circRNAs in ccRCC tissue with a focus to evaluate their potential as prognostic biomarkers. A genome-wide identification of circRNAs in total RNA extracted from ccRCC tissue samples was performed using microarray analysis. Three relevant differentially expressed circRNAs were selected (circEGLN3, circNOX4, and circRHOBTB3), their circular nature was experimentally confirmed, and their expression-along with that of their linear counterparts-was measured in 99 malignant and 85 adjacent normal tissue samples using specifically established RT-qPCR assays. The capacity of circRNAs to discriminate between malignant and adjacent normal tissue samples and their prognostic potential (with the endpoints cancer-specific, recurrence-free, and overall survival) after surgery were estimated by C-statistics, Kaplan-Meier method, univariate and multivariate Cox regression analysis, decision curve analysis, and Akaike and Bayesian information criteria. CircEGLN3 discriminated malignant from normal tissue with 97% accuracy. We generated a prognostic for the three endpoints by multivariate Cox regression analysis that included circEGLN3, circRHOBT3 and linRHOBTB3. The predictive outcome accuracy of the clinical models based on clinicopathological factors was improved in combination with this circRNA-based signature. Bootstrapping as well as Akaike and Bayesian information criteria confirmed the statistical significance and robustness of the combined models. Limitations of this study include its retrospective nature and the lack of external validation. The study demonstrated the promising potential of circRNAs as diagnostic and particularly prognostic biomarkers in ccRCC patients

Differential expression of microRNA-206 and its target genes in pre-eclampsia

Objectives: Pre-eclampsia is a multi-system disease that significantly contributes to maternal and fetal morbidity and mortality. In this study, we used a non-biased microarray approach to identify novel circulating miRNAs in maternal plasma that may be associated with pre-eclampsia. Methods: Plasma samples were obtained at 16 and 28 weeks of gestation from 18 women who later developed pre-eclampsia (cases) and 18 matched women with normotensive pregnancies (controls). We studied miRNA expression profiles in plasma and subsequently confirmed miRNA and target gene expression in placenta samples. Placental samples were obtained from an independent cohort of 19 women with pre-eclampsia matched with 19 women with normotensive pregnancies. Results: From the microarray, we identified 1 miRNA that was significantly differentially expressed between cases and controls at 16 weeks of gestation and 6 miRNAs that were significantly differentially expressed at 28 weeks. Following qPCR validation only one, miR-206, was found to be significantly increased in 28 week samples in women who later developed pre-eclampsia (1.4 fold change ± 0.2). The trend for increase in miR-206 expression was mirrored within placental tissue from women with pre-eclampsia. In parallel, IGF-1, a target gene of miR-206, was also found to be down-regulated (0.41 ± 0.04) in placental tissue from women with pre-eclampsia. miR-206 expression was also detectable in myometrium tissue and trophoblast cell lines. Conclusions: Our pilot study has identified miRNA-206 as a novel factor up-regulated in pre-eclampsia within the maternal circulation and in placental tissue

Comparison of methods for in-house screening of HLA*B57:01 to prevent abacavir hypersensitivity in HIV-1 care

Abacavir is a nucleoside reverse transcriptase inhibitor used as part of combination antiretroviral therapy in HIV-1-infected patients. Because this drug can cause a hypersensitivity reaction that is correlated with the presence of the HLA-B*57:01 allotype, screening for the presence of HLA-B*57:01 is recommended before abacavir initiation. Different genetic assays have been developed for HLA-B*57:01 screening, each with specific sensitivity, turnaround time and assay costs. Here, a new real-time PCR (qPCR) based analysis is described and compared to sequence specific primer PCR with capillary electrophoresis (SSP PCR CE) on 149 patient-derived samples, using sequence specific oligonucleotide hybridization combined with high resolution SSP PCR as gold standard. In addition to these PCR based methods, a complementary approach was developed using flow cytometry with an HLA-B17 specific monoclonal antibody as a pre-screening assay to diminish the number of samples for genetic testing. All three assays had a maximum sensitivity of >99. However, differences in specificity were recorded, i.e. 84.3%, 97.2% and >99% for flow cytometry, qPCR and SSP PCR CE respectively. Our data indicate that the most specific and sensitive of the compared methods is the SSP PCR CE. Flow cytometry pre-screening can substantially decrease the number of genetic tests for HLA-B*57:01 typing in a clinical setting