MicroRNAs (miRNAs) constitute a class of small cellular RNAs (typically 21–23nt) that function as post-transcriptional regulators of gene expression. Current estimates indicate that more than one ...third of the cellular transcriptome is regulated by miRNAs, although they are relatively few in number (less than 2000 human miRNAs).
The high relative stability of miRNA in common clinical tissues and biofluids (e.g. plasma, serum, urine, saliva, etc.) and the ability of miRNA expression profiles to accurately classify discrete tissue types and disease states have positioned miRNA quantification as a promising new tool for a wide range of diagnostic applications. Furthermore miRNAs have been shown to be rapidly released from tissues into the circulation with the development of pathology.
To facilitate discovery and clinical development of miRNA-based biomarkers, we developed a genome-wide Locked Nucleic Acid (LNA™)-based miRNA qPCR platform with unparalleled sensitivity and robustness. The platform allows high-throughput profiling of miRNAs from important clinical sources without the need for pre-amplification.
Using this system, we have profiled thousands of biofluid samples including blood derived plasma and serum. An extensive quality control (QC) system has been implemented in order to secure technical excellence and reveal any unwanted bias coming from pre-analytical or analytical variables. We present our approaches to sample and RNA QC as well as data QC and normalization. Specifically we have developed normal reference ranges for circulating miRNAs in serum and plasma as well as a hemolysis indicator based on microRNA expression.
Identification of melanoma patients at high risk for recurrence and monitoring for recurrence are critical for informed management decisions. We hypothesized that serum microRNAs (miRNAs) could ...provide prognostic information at the time of diagnosis unaccounted for by the current staging system and could be useful in detecting recurrence after resection.
We screened 355 miRNAs in sera from 80 melanoma patients at primary diagnosis (discovery cohort) using a unique quantitative reverse transcription-PCR (qRT-PCR) panel. Cox proportional hazard models and Kaplan-Meier recurrence-free survival (RFS) curves were used to identify a miRNA signature with prognostic potential adjusting for stage. We then tested the miRNA signature in an independent cohort of 50 primary melanoma patients (validation cohort). Logistic regression analysis was performed to determine if the miRNA signature can determine risk of recurrence in both cohorts. Selected miRNAs were measured longitudinally in subsets of patients pre-/post-operatively and pre-/post-recurrence.
A signature of 5 miRNAs successfully classified melanoma patients into high and low recurrence risk groups with significant separation of RFS in both discovery and validation cohorts (p = 0.0036, p = 0.0093, respectively). Significant separation of RFS was maintained when a logistic model containing the same signature set was used to predict recurrence risk in both discovery and validation cohorts (p < 0.0001, p = 0.033, respectively). Longitudinal expression of 4 miRNAs in a subset of patients was dynamic, suggesting miRNAs can be associated with tumor burden.
Our data demonstrate that serum miRNAs can improve accuracy in identifying primary melanoma patients with high recurrence risk and in monitoring melanoma tumor burden over time.
The virus/host interplay mediates liver pathology in chronic HBV infection. MiRNAs play a pivotal role in virus/host interactions and are detected in both serum and HBsAg-particles, but studies of ...their dynamics during chronic infection and antiviral therapy are missing. We studied serum miRNAs during different phases of chronic HBV infection and antiviral treatment.
MiRNAs were profiled by miRCURY-LNA-Universal-RT-miRNA-PCR (Exiqon-A/S) and qPCR-panels-I/II-739-miRNA-assays and single-RT-q-PCRs. Two cohorts of well-characterized HBsAg-carriers were studied (median follow-up 34-52 months): a) training-panel (141 sera) and HBsAg-particles (32 samples) from 61 HBsAg-carriers and b) validation-panel (136 sera) from 84 carriers.
Thirty-one miRNAs were differentially expressed in inactive-carriers (IC) and chronic-hepatitis-B (CHB) with the largest difference for miR-122-5p, miR-99a-5p and miR-192-5p (liver-specific-miRNAs), over-expressed in both sera and HBsAg-particles of CHB (ANOVA/U-test p-values: <0.000001/0.000001; <0.000001/0.000003; <0.000001/0.000005, respectively) and significantly down-regulated during- and after-treatment in sustained-virological-responders (SVR). MiRNA-profiles of IC and SVR clustered in the heatmap. Liver-miRNAs were combined with miR-335, miR-126 and miR-320a (internal controls) to build a MiR-B-Index with 100% sensitivity, 83.3% and 92.5% specificity (-1.7 cut-off) in both training and validation cohorts to identify IC. MiR-B-Index (-5.72, -20.43/14.38) correlated with ALT (49, 10/2056 U/l, ρ = -0.497, p<0.001), HBV-DNA (4.58, undetectable/>8.3 Log10 IU/mL, ρ = -0.732, p<0.001) and HBsAg (3.40, 0.11/5.49 Log10 IU/mL, ρ = -0.883, p<0.001). At multivariate analysis HBV-DNA (p = 0.002), HBsAg (p<0.001) and infection-phase (p<0.001), but not ALT (p = 0.360) correlated with MiR-B-Index. In SVR to Peg-IFN/NUCs MiR-B-Index improved during-therapy and post-treatment reaching IC-like values (5.32, -1.65/10.91 vs 6.68, 0.54/9.53, p = 0.324) beckoning sustained HBV-immune-control earlier than HBsAg-decline.
Serum miRNA profile change dynamically during the different phases of chronic HBV infection. We identified a miRNA signature associated with both natural-occurring and therapy-induced immune control of HBV infection. The MiR-B-Index might be a useful biomarker for the early identification of the sustained switch from CHB to inactive HBV-infection in patients treated with antivirals.
microRNAs represent the best described class of small RNAs (21-23nt) and have been shown to function as post-transcriptional regulators of gene expression. The high relative stability of microRNA in ...common clinical source materials and the ability of microRNA expression profiles to accurately classify discrete tissue types and specific disease states have positioned microRNA quantification as a promising new biomarker for a wide range of diagnostic applications
We have developed a genome-wide LNA™-based microRNA qPCR platform with unparalleled sensitivity and robustness even in biofluids where microRNA levels are extremely low. Only a single cDNA synthesis reaction is required to conduct full miRNome profiling thereby facilitating high-throughput profiling in important clinical sources without the need for pre-amplification. Thousands of biofluid samples have been profiled including blood derived plasma/serum and urine to accurately determine normal reference ranges for circulating microRNAs. Procedures have been developed to control pre-analytical variables such as hemolysis in serum/plasma samples. In addition, a data QC system has been implemented to secure technical excellence and reveal any unwanted bias in the dataset.
We are currently screening for and validating microRNAs as biomarkers for stage II colorectal cancer (CRC). microRNA profiling has been performed on plasma samples from a clinical trial conducted in 7 different hospitals. We show that hemolysis in this sample set correlates with hospital ID, and with the utilization of specific blood sample collection vials. Using a microRNA-based hemolysis signature, we eliminated hemolyzed samples and demonstrated that this step leads to a major improvement of CRC detection (ROC AUC increase from 0.67 to 0.80). We conclude that pre-analytical variables such as hemolysis can be a source of bias in samples of different origin, and that sample and data QC procedures can overcome this challenge and lead to improved miRNA biomarker performance.
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