A systemic approach to screening high-throughput RT-qPCR data for a suitable set of reference circulating miRNAs

Evaluation of circulating miRNAs in mares approaching parturition

Circulating microRNAs (miRNAs) are stable in body fluids and can serve as biomarkers for various diseases and physiological states. Although pregnancy-related miRNAs have been identified in various mammals, studies on parturition-related circulating miRNAs in mares are limited. Therefore, this study aimed to identify parturition-related miRNAs and examine their potential applications in the prediction of parturition date. miRNAs were extracted from the plasma of Thoroughbred mares 30 days (295-326 days pregnant) and 5 (323-352 days pregnant) - 0 (328-357 days pregnant) days before parturition, followed by small RNA sequencing (small RNA-seq) and reverse transcription quantitative PCR (RT-qPCR). Additionally, we measured plasma progestin concentrations in mares using an enzyme-linked immunosorbent assay. Small RNA-seq data indicated that 18 miRNAs were affected by parturition proximity. Among the 18 miRNAs, two novel miRNAs and three known miRNAs (miR-361-3p, miR-483, and miR-99a) showed significant changes at 5-0 days before parturition compared with that at 30 days to parturition. Plasma progestin concentrations were higher at 5-3 days to parturition than at 30 days to parturition, and then decreased on the day of parturition. Conclusively, this study provides basic knowledge of parturition-related circulating miRNAs in mares, and identifies miRNAs that could potentially be used as biomarkers to predict parturition in mares.

Development of a robust and generalizable algorithm "gQuant" for accurate normalizer gene selection in qRT-PCR analysis

The emergent role of nucleic acid-based biomarkers-microRNAs(miRNAs), long non-coding RNAs(lncRNAs), and messenger RNAs(mRNAs), is becoming increasingly prominent in disease diagnostics and risk assessment. qRT-PCR is the primary analytical method for quantitative measurement of biomarkers. Yet, the relative infancy of non-coding RNAs recognition as biomarkers poses a challenge due to the absence of a consensus on a universally accepted normalizer gene, an absolute requirement for accurate quantification. Current tools normalizer selection are fraught with statistical limitations and suboptimal graphical user interface for data visualisation. These deficiencies underscore the necessity for a balanced tool tailored to handle qRT-PCR datasets. Addressing the identified challenges, we have developed 'gQuant' tool crafted to address these limitations. We employed voting classifiers that combine predictions from multiple statistical methods. Tool's efficacy was validated through different available and in house data derived from urinary exosomal miRNAs datasets. Comparative analysis with existing tools revealed that their integrated methodologies could skew the ranking of normalizer genes, whereas 'gQuant' consistently yielded rankings characterised by lower standard-deviation, reduced covariance, and enhanced kernel density estimation values. Given 'gQuant's' promising performance, normalizer gene identification will be greatly improved, improving precision of gene expression quantification in a variety of research scenarios. The gQuant tool developed for this study is available for public use and can be accessed at [ https://github.com/ABHAYHBB/gQuant-Tool ]."

Identifying the stability of housekeeping genes to be used for the quantitative real-time PCR normalization in retinal tissue of streptozotocin-induced diabetic rats

AIM

To investigate the stability of the seven housekeeping genes: beta-actin (ActB), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), 18s ribosomal unit 5 (18s), cyclophilin A (CycA), hypoxanthine-guanine phosphoribosyl transferase (HPRT), ribosomal protein large P0 (36B4) and terminal uridylyl transferase 1 (U6) in the diabetic retinal tissue of rat model.

METHODS

The expression of these seven genes in rat retinal tissues was determined using real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) in two groups; normal control rats and streptozotocin-induced diabetic rats. The stability analysis of gene expression was investigated using geNorm, NormFinder, BestKeeper, and comparative delta-Ct (ΔCt) algorithms.

RESULTS

The 36B4 gene was stably expressed in the retinal tissues of normal control animals; however, it was less stable in diabetic retinas. The 18s gene was expressed consistently in both normal control and diabetic rats' retinal tissue. That this gene was the best reference for data normalisation in RT-qPCR studies that used the retinal tissue of streptozotocin-induced diabetic rats. Furthermore, there was no ideal gene stably expressed for use in all experimental settings.

CONCLUSION

Identifying relevant genes is a need for achieving RT-qPCR validity and reliability and must be appropriately achieved based on a specific experimental setting.

Optimized RT-qPCR and a novel normalization method for validating circulating miRNA biomarkers in ageing-related diseases

Circulating miRNAs have potential as minimally invasive biomarkers for diagnosing various diseases, including ageing-related disorders such as Alzheimer's disease (AD). However, the lack of standardization in the common analysis method, RT-qPCR, and specifically in the normalization step, has resulted in inconsistent data across studies, hindering miRNA clinical implementation as well as basic research. To address this issue, this study proposes an optimized protocol for key steps in miRNA profiling, which incorporates absorbance-based haemolysis detection for assessing sample quality, double spike-in controls for miRNA isolation and reverse transcription, and the use of 7 stable normalizers verified in an aging population, including healthy subjects and individuals at different stages of Alzheimer's disease (140 subjects). The stability of these 7 normalizers was demonstrated using our novel method called BestmiRNorm for identifying optimal normalizers. BestmiRNorm, developed utilizing the Python programming language, enables the assessment of up to 11 potential normalizers. The standardized application of this optimized RT-qPCR protocol and the recommended normalizers are crucial for the development of miRNAs as biomarkers for AD and other ageing-related diseases in clinical diagnostics and basic research.

Identification of Potential miRNA Biomarkers to Detect Hydrocortisone Administration in Horses

Circulating microRNAs (miRNAs) are stable in bodily fluids and are potential biomarkers of various diseases and physiological states. Although several studies have been conducted on humans to detect drug doping by miRNAs, research on drugs and miRNAs in horses is limited. In this study, circulating miRNAs in horses after hydrocortisone administration were profiled and variations in miRNAs affected by hydrocortisone administration during endogenous hydrocortisone elevation were examined. The miRNAs were extracted from thoroughbred horse plasma before and after hydrocortisone administration and subjected to small RNA sequencing and reverse transcription quantitative PCR (RT-qPCR). RT-qPCR validation was performed for the 20 miRNAs that were most affected by hydrocortisone administration. The effects of elevated endogenous hydrocortisone levels due to exercise and adrenocorticotropic hormone administration were also confirmed. The validation results showed that approximately half of the miRNAs showed the same significant differences as those obtained using small RNA sequencing. Among the twenty miRNAs, two novel miRNAs and miR-133a were found to vary differently between exogenous hydrocortisone administration and endogenous hydrocortisone elevation. This study provides basic knowledge regarding the circulating miRNA profile of horses after hydrocortisone administration and identifies three miRNAs that could potentially be used as biomarkers to detect hydrocortisone administration.

miR-26a/30d/152 are reliable reference genes for miRNA quantification in skin wound age estimation

MicroRNAs (miRNAs) are a class of small non-coding RNAs that exert their biological functions as negative regulators of gene expression. They are involved in the skin wound healing process with a dynamic expression pattern and can therefore potentially serve as biomarkers for skin wound age estimation. However, no reports have described any miRNAs as suitable reference genes (RGs) for miRNA quantification in wounded skin or samples with post-mortem changes. Here, we aimed to identify specific miRNAs as RGs for miRNA quantification to support further studies of skin wound age estimation. Overall, nine miRNAs stably expressed in mouse skin at certain posttraumatic intervals (PTIs) were preselected by next-generation sequencing as candidate RGs. These nine miRNAs and the commonly used reference genes (comRGs: U6, GAPDH, ACTB, 18S, 5S, LC-Ogdh) were quantitatively examined using quantitative real-time reverse-transcription polymerase chain reaction at different PTIs during skin wound healing in mice. The stabilities of these genes were evaluated using four independent algorithms: GeNorm, NormFinder, BestKeeper, and comparative Delta Ct. Stability was further evaluated in mice with different post-mortem intervals (PMIs). Overall, mmu-miR-26a-5p, mmu-miR-30d-5p, and mmu-miR-152-3p were identified as the most stable genes at both different PTIs and PMIs. These three miRNA RGs were additionally validated and compared with the comRGs in human samples. After assessing using one, two, or three miRNAs in combination for stability at different PTIs, PMIs, or in human samples, the set of miR-26a/30d/152 was approved as the best normalizer. In conclusion, our data suggest that the combination of miR-26a/30d/152 is recommended as the normalization strategy for miRNA qRT-PCR quantification in skin wound age estimation.

Key points

The small size of miRNAs makes them less susceptible to post-mortem autolysis or putrefaction, leading to their potential use in wound age estimation.Studying miRNAs as biological indicators of skin wound age estimation requires the selection and validation of stable reference genes because commonly used reference genes, such as U6, ACTB, GAPDH, 5S, 18S, and LC-Ogdh, are not stable.miR-26a/30d/152 are stable and reliable as reference genes and their use in combination is a recommended normalization strategy for miRNA quantitative analysis in wounded skin.

Identification of extremely GC-rich micro RNAs for RT-qPCR data normalization in human plasma

We aimed at extending the repertoire of high-quality miRNA normalizers for reverse transcription-quantitative PCR (RT-qPCR) of human plasma with special emphasis on the extremely guanine-cytosine-rich portion of the miRNome. For high-throughput selection of stable candidates, microarray technology was preferred over small-RNA sequencing (sRNA-seq) since the latter underrepresented miRNAs with a guanine-cytosine (GC) content of at least 75% (p = 0.0002, n = 2). miRNA abundances measured on the microarray were ranked for consistency and uniformity using nine normalization approaches. The eleven most stable sequences included miRNAs of moderate, but also extreme GC content (45%-65%: miR-320d, miR-425-5p, miR-185-5p, miR-486-5p; 80%-95%: miR-1915-3p, miR-3656-5p, miR-3665-5p, miR-3960-5p, miR-4488-5p, miR-4497 and miR-4787-5p). In contrast, the seven extremely GC-rich miRNAs were not found in the two plasma miRNomes screened by sRNA-seq. Stem-loop RT-qPCR was employed for stability verification in 32 plasma samples of healthy male Caucasians (age range: 18-55 years). In general, inter-individual variance of miRNA abundance was low or very low as indicated by coefficient of variation (CV) values of 0.6%-8.2%. miR-3665 and miR-1915-3p outperformed in this analysis (CVs: 0.6 and 2.4%, respectively). The eight most stable sequences included four extremely GC-rich miRNAs (miR-1915-3p, miR-3665, miR-4787-5p and miR-4497). The best-performing duo normalization factor (NF) for the condition of human plasma, miR-320d and miR-4787-5p, also included a GC-extreme miRNA. In summary, the identification of extremely guanine-cytosine-rich plasma normalizers will help to increase accuracy of PCR-based miRNA quantification, thus raise the potential that miRNAs become markers for psychological stress reactions or early and precise diagnosis of clinical phenotypes. The novel miRNAs might also be useful for orthologous contexts considering their conservation in related animal genomes.

Exosome-Derived microRNAs from Mouthrinse Have the Potential to Be Novel Biomarkers for Sjögren Syndrome

Sjögren syndrome (SS) is diagnosed based on invasive tissue biopsies and blood sampling. Therefore, a novel non-invasive and simple inspection diagnostic marker of SS is required. Here, we identified exosome-derived microRNAs (miRNAs) as biomarkers for SS using non-invasive mouthrinse samples collected from patients with SS and healthy volunteers. We compared miRNAs derived from exosomes in mouthrinse samples from the two groups using microarrays and real-time polymerase chain reaction (PCR) and identified 12 miRNAs as biomarker candidates. The expression ratios of four miRNAs were significantly increased in the SS group compared to the control group. Logistic regression analysis revealed a more significant influence of miR-1290 and let-7b-5p in the SS group than that in the control group. We combined these miRNAs to create a diagnostic prediction formula using logistic regression analysis. The combination of miR-1290 and let-7b-5p distinguished SS from the control samples with an AUC, sensitivity, specificity, positive predictive value, and negative predictive value of 0.856, 91.7%, 83.3%, 84.6%, and 90.9%, respectively. These results indicated that an increased ratio of these miRNAs could serve as a novel and non-invasive diagnostic marker for SS. This is the first report of diagnosis and screening of SS by adopting a non-invasive method using mouthrinse.

A Translational Model to Improve Early Detection of Epithelial Ovarian Cancers

Neural network analyses of circulating miRNAs have shown potential as non-invasive screening tests for ovarian cancer. A clinically useful test would detect occult disease when complete cytoreduction is most feasible. Here we used murine xenografts to sensitize a neural network model to detect low volume disease and applied the model to sera from 75 early-stage ovarian cancer cases age-matched to 200 benign adnexal masses or healthy controls. The 14-miRNA model efficiently discriminated tumor bearing animals from controls with 100% sensitivity down to tumor inoculums of 50,000 cells. Among early-stage patient samples, the model performed well with 73% sensitivity at 91% specificity. Applied to a population with 1% disease prevalence, we hypothesize the model would detect most early-stage ovarian cancers while maintaining a negative predictive value of 99.97% (95% CI 99.95%-99.98%). Overall, this supports the concept that miRNAs may be useful as screening markers for early-stage disease.

Comparison of Data Normalization Strategies for Array-Based MicroRNA Profiling Experiments and Identification and Validation of Circulating MicroRNAs as Endogenous Controls in Hypertension

Introduction: MicroRNAs are small noncoding RNAs with potential regulatory roles in hypertension and drug response. The presence of many of these RNAs in biofluids has spurred investigation into their role as possible biomarkers for use in precision approaches to healthcare. One of the major challenges in clinical translation of circulating miRNA biomarkers is the limited replication across studies due to lack of standards for data normalization techniques for array-based approaches and a lack of consensus on an endogenous control normalizer for qPCR-based candidate miRNA profiling studies.

Methods: We conducted genome-wide profiling of 754 miRNAs in baseline plasma of 36 European American individuals with uncomplicated hypertension selected from the PEAR clinical trial, who had been untreated for hypertension for at least one month prior to sample collection. After appropriate quality control with amplification score and missingness filters, we tested different normalization strategies such as normalization with global mean of imputed and unimputed data, mean of restricted set of miRNAs, quantile normalization, and endogenous control miRNA normalization to identify the method that best reduces the technical/experimental variability in the data. We identified best endogenous control candidates with expression pattern closest to the mean miRNA expression in the sample, as well as by assessing their stability using a combination of NormFinder, geNorm, Best Keeper and Delta Ct algorithms under the Reffinder software. The suitability of the four best endogenous controls was validated in 50 hypertensive African Americans from the same trial with reverse-transcription–qPCR and by evaluating their stability ranking in that cohort.

Results: Among the compared normalization strategies, quantile normalization and global mean normalization performed better than others in terms of reducing the standard deviation of miRNAs across samples in the array-based data. Among the four strongest candidate miRNAs from our selection process (miR-223-3p, 19b, 106a, and 126-5p), miR-223-3p and miR-126-5p were consistently expressed with the best stability ranking in the validation cohort. Furthermore, the combination of miR-223-3p and 126-5p showed better stability ranking when compared to single miRNAs.

Conclusion: We identified quantile normalization followed by global mean normalization to be the best methods in reducing the variance in the data. We identified the combination of miR-223-3p and 126-5p as potential endogenous control in studies of hypertension.

miRNA and lncRNA Expression Networks Modulate Cell Cycle and DNA Repair Inhibition in Senescent Prostate Cells

Cellular senescence is a state of permanent growth arrest that arises once cells reach the limit of their proliferative capacity. It creates an inflammatory microenvironment favouring the initiation and progression of various age-related diseases, including prostate cancer. Non-coding RNAs (ncRNAs) have emerged as important regulators of cellular gene expression. Nonetheless, very little is known about the interplay of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) and how deregulation of ncRNA networks promotes cellular senescence. To investigate this, human prostate epithelial cells were cultured through different passages until senescent, and their RNA was extracted and sequenced using RNA sequencing (RNAseq) and microRNA sequencing (miRNA-seq) miRNAseq. Differential expression (DE) gene analysis was performed to compare senescent and proliferating cells with Limma, miRNA-target interactions with multiMiR, lncRNA-target interactions using TCGA data and network evaluation with miRmapper. We found that miR-335-3p, miR-543 and the lncRNAs H19 and SMIM10L2A all play central roles in the regulation of cell cycle and DNA repair processes. Expression of most genes belonging to these pathways were down-regulated by senescence. Using the concept of network centrality, we determined the top 10 miRNAs and lncRNAs, with miR-335-3p and H19 identified as the biggest hubs for miRNAs and lncRNA respectively. These ncRNAs regulate key genes belonging to pathways involved in cell senescence and prostate cancer demonstrating their central role in these processes and opening the possibility for their use as biomarkers or therapeutic targets to mitigate against prostate ageing and carcinogenesis.

Circulating non-coding RNAs as a diagnostic and management biomarker for breast cancer: current insights

Cancer biomarkers can be used to determine the molecular status of a tumor or its metastases, which either release them directly into body fluids or indirectly through disruption of tumor/metastatic tissue. New minimally invasive and repeatable sample collection methods, such as liquid biopsy, have been developed in the last decade to apply cancer knowledge and track its progression. Circulating non-coding RNAs, which include microRNAs, long non-coding RNAs, and PIWI-interacting RNAs, are increasingly being recognized as potential cancer biomarkers. The growing understanding of cancer's molecular pathogenesis, combined with the rapid development of new molecular techniques, encourages the study of early molecular alterations associated with cancer development in body fluids. Specific genetic and epigenetic changes in circulating free RNA (cf-RNA) in plasma, serum, and urine could be used as diagnostic biomarkers for a variety of cancers. Only a subset of these cf-RNAs have been studied in breast cancer, with the most extensive research focusing on cf-miRNA in plasma. These findings pave the way for immediate use of selected cf-RNAs as biomarkers in breast cancer liquid biopsy, as well as additional research into other cf-RNAs to advance.

Liquid Biopsy for Cancer Cachexia: Focus on Muscle-Derived microRNAs

Cancer cachexia displays a complex nature in which systemic inflammation, impaired energy metabolism, loss of muscle and adipose tissues result in unintentional body weight loss. Cachectic patients have a poor prognosis and the presence of cachexia reduces the tolerability of chemo/radio-therapy treatments and it is frequently the primary cause of death in advanced cancer patients. Early detection of this condition could make treatments more effective. However, early diagnostic biomarkers of cachexia are currently lacking. In recent years, although solid biopsy still remains the "gold standard" for diagnosis of cancer, liquid biopsy is gaining increasing interest as a source of easily accessible potential biomarkers. Moreover, the growing interest in circulating microRNAs (miRNAs), has made these molecules attractive for the diagnosis of several diseases, including cancer. Some muscle-derived circulating miRNA might play a pivotal role in the onset/progression of cancer cachexia. This topic is of great interest since circulating miRNAs might be easily detectable by means of liquid biopsies and might allow an early diagnosis of this syndrome. We here summarize the current knowledge on circulating muscular miRNAs involved in muscle atrophy, since they might represent easily accessible and promising biomarkers of cachexia.

Serum MicroRNAs as Xerostomia Biomarkers in Patients With Oropharyngeal Cancer Undergoing Radiation Therapy

PURPOSE

Severe xerostomia is noted in the majority of patients irradiated for oropharyngeal cancer. Extracellular microRNAs (miRNAs) may serve as effective tools allowing prediction of radiation-related toxicity. The aim of this study was to create an efficient prognostic miRNA-based test for severe, patient-rated xerostomia 3 months after primary treatment.

METHODS AND MATERIALS

This prospective study enrolled patients with oropharyngeal cancer treated between 2016 and 2018 in 3 centers in Poland. The primary endpoint was severe (grade ≥3) xerostomia as assessed by the European Organisation for Research and Treatment of Cancer H&N-35 questionnaires. Initially, a group of 10 patients with severe xerostomia was randomly selected and matched with a comparative group of 10 patients without severe xerostomia. Samples were collected before radiation therapy, after receiving 20 Gy, and within 24 hours after treatment completion. Quantitative real-time polymerase chain reaction arrays (QIAGEN, Hilden, Germany) were used to quantify expression levels of 752 miRNAs in the serum at all timepoints. The resulting logistic-regression based model was validated in additional 60 patients: 30 with grade >3 xerostomia and 30 without.

RESULTS

Of 152 eligible patients, we successfully recruited 111 patients. Severe xerostomia 3 months after treatment was reported by 63 patients (56.8%). Mean dose delivered to parotid glands was higher in both the exploratory and validation cohort. The model based on miR-185-5p and miR-425-5p expression levels measured before the start of radiation therapy had an area under the curve of 0.96 (95% confidence interval, 0.88-1.00). The model based on the same miRNAs remained robust when parameters were measured after 20 Gy (area under the curve 0.90; 95% confidence interval, 0.75-1.00). These results were confirmed in the validation group. In the validation group, preradiation therapy model application yielded 73.3% sensitivity and 80.0% specificity. In the samples taken after 20 Gy, the same 2 miRNAs yielded 67.7% sensitivity and 72.4% specificity. The model including pretreatment miR-185-5p and miR-425-5p levels together with mean parotid dose yielded 90.0% sensitivity and 80.0% specificity. In the validation cohort, this model yielded 80.6% sensitivity and 55.2% specificity. The model based on miRNA levels measured after 20 Gy and mean parotid dose had 80.0% sensitivity and 100% specificity in the exploratory group. In the validation cohort its performance fell to 71.0% sensitivity and 58.6% specificity.

CONCLUSIONS

Serum expression levels of miR-425-5p and miR-185-5p measured before the start of radiation therapy or during therapy (after 20 Gy) had significant prognostic value for the occurrence of severe xerostomia 3 months after treatment completion. The variability explained by miRNAs appears to be, at least partially, independent from that related to the dosimetric data.

Identification of miR-4644 as a suitable endogenous normalizer for circulating miRNA quantification in hepatocellular carcinoma

Background: Circulating microRNAs (miRNAs) have proved to be promising biomarkers for early diagnosis and therapeutic monitoring in cancers. Particularly for hepatocellular carcinoma (HCC), detection of circulating miRNA biomarkers as a new diagnostic approach has been written into the latest Guidelines for Diagnosis and Treatment of Primary Liver Cancer in China (2019 edition). However, no general consensus on an ideal endogenous normalizer for circulating miRNAs quantification has been reached, so it will affect the accuracy of quantitative results. In this study, we aim to identify a stable endogenous normalizer for analyzing circulating miRNAs.

Methods: Candidate miRNAs were selected by screening dataset GSE104310, as well as data statistics and analysis. Five commonly reference genes were chosen for further comparison and verification. Then, the expression levels of these genes in serum were analyzed by quantitative reverse transcription PCR (RT-qPCR) among four groups, including patients diagnosed with HCC, chronic hepatitis B (CHB), liver cirrhosis, and healthy subjects. Furthermore, the stability of target genes was evaluated using geNorm, NormFinder, comparative ΔCq programs, and validated by database. We also explored the availability of the miRNA combination, and compared the performance difference between combination and individuals, as well as the selectivity of miRNA references in the combinations.

Results: 11 candidate miRNAs were obtained, and miR-4644 stood out among these miRNAs, and proved to be much more stable than other endogenous miRNAs. Further study showed that miR-4644 exhibited higher stability and expression abundance than other commonly miRNA reference controls. Finally, we discovered the combination of miR-4644 and miR-16 revealed high performance in stability when compared to miRNA individuals. Furthermore, the combination consisted of references with closer nature could give rise to amplification effects in stability.

Conclusions: Our findings demonstrated that miR-4644 is an ideal endogenous normalizer for circulating microRNA quantification in hepatocellular carcinoma. Besides, combining miR-4644 with miR-16 into a whole as a reference control would greatly improve the accuracy of quantification.

NormiRazor: tool applying GPU-accelerated computing for determination of internal references in microRNA transcription studies

BACKGROUND

Multi-gene expression assays are an attractive tool in revealing complex regulatory mechanisms in living organisms. Normalization is an indispensable step of data analysis in all those studies, since it removes unwanted, non-biological variability from data. In targeted qPCR assays it is typically performed with respect to prespecified reference genes, but the lack of robust strategy of their selection is reported in literature, especially in studies concerning circulating microRNAs (miRNA). Unfortunately, this problem impedes translation of scientific discoveries on miRNA biomarkers into widely available laboratory assays. Previous studies concluded that averaged expressions of multi-miRNA combinations are more stable references than single genes. However, due to the number of such combinations the computational load is considerable and may be hindering for objective reference selection in large datasets. Existing implementations of normalization algorithms (geNorm, NormFinder and BestKeeper) have poor performance and may require days to compute stability values for all potential reference as the evaluation is performed sequentially.

RESULTS

We designed NormiRazor - an integrative tool which implements those methods in a parallel manner on a graphics processing unit (GPU) using CUDA platform. We tested our approach on publicly available miRNA expression datasets. As a result, the times of executions on 8 datasets containing from 50 to 400 miRNAs (subsets of GSE68314) decreased 18.7 ±0.6 (mean ±SD), 104.7 ±4.2 and 76.5 ±2.2 times for geNorm, BestKeeper and NormFinder with respect to previous Python implementation. To allow for easy access to normalization pipeline for biomedical researchers we implemented NormiRazor as an online platform where a user could normalize their datasets based on the automatically selected references. It is available at norm.btm.umed.pl, together with instruction manual and exemplary datasets.

CONCLUSIONS

NormiRazor allows for an easy, informed choice of reference genes for qPCR transcriptomic studies. As such it can improve comparability and repeatability of experiments and in longer perspective help translate newly discovered biomarkers into readily available assays.

The Value of Serum MicroRNA Expression Signature in Predicting Refractoriness to Bortezomib-Based Therapy in Multiple Myeloma Patients

Bortezomib is the first-in-class proteasome inhibitor, commonly used in the treatment of multiple myeloma (MM). The mechanisms underlying acquired bortezomib resistance in MM are poorly understood. Several cell-free miRNAs have been found to be aberrantly regulated in MM patients. The aim of this pilot study was to identify a blood-based miRNA signature that predicts bortezomib-based therapy efficacy in MM patients. Thirty MM patients treated with bortezomib-based regimens were studied, including 19 with refractory disease and 11 who were bortezomib sensitive. Serum miRNA expression patterns were identified with miRCURY LNA miRNA miRNome PCR Panels I+II (Exiqon/Qiagen). Univariate analysis found a total of 21 miRNAs to be differentially expressed in patients with MM according to bortezomib sensitivity. Multivariate logistic regression was created and allowed us to discriminate refractory from sensitive patients with a very high AUC of 0.95 (95%CI: 0.84-1.00); sensitivity, specificity and accuracy were estimated as 0.95, 0.91, and 0.93. The model used expression of 3 miRNAs: miR-215-5p, miR-181a-5p and miR-376c-3p. This study is the first to demonstrate that serum expression of several miRNAs differs between patients who are bortezomib refractory and those who are sensitive which may prove useful in studies aimed at overcoming drug resistance in MM treatment.