Circulating microRNAs as Non-Invasive Biomarkers in Endometriosis Diagnosis-A Systematic Review.

The aim of this systematic review is to assess the power of circulating miRNAs as biomarkers as a diagnostic tool in endometriosis. In endometriosis-suspected women with uncertain imaging, the only way to confirm or exclude endometriosis with certainty is currently laparoscopy. This creates a need for non-invasive diagnostics. We searched the literature through the PubMed database using the Mesh terms 'endometriosis' and 'miRNAs'. Some, but limited, overlap was found between the 32 articles included, with a total of 20 miRNAs reported as dysregulated in endometriosis in two or more studies. MiR-17-5p was reported as dysregulated in six studies, followed by miR-451a and let-7b-5p in four studies and miR-20a-5p, miR-143-3p, miR-199a-5p and miR-3613-5p in three studies. Furthermore, a possible impact of the menstrual phase on miRNA expression was noted in five studies, while no influence of hormonal intake was observed in any included study. The modest reproducibility between studies may be attributable to biological variability as well as to the lack of universal protocols, resulting in pre- and analytical variability. Despite the identification of several suitable candidate biomarkers among the miRNAs, the need for high-quality studies with larger and well-defined population cohorts and the use of standardized protocols lingers.

Identification and validation of extracellular vesicle reference genes for the normalization of RT-qPCR data.

Extracellular vesicles (EVs) contain a plethora of biomolecules, including nucleic acids, with diverse diagnostic and therapeutic application potential. Although reverse transcription-quantitative PCR (RT-qPCR) is the most widely applied laboratory technique to evaluate gene expression, its applicability in EV research is challenged by the lack of universal and stably present reference genes (RGs). In this study, we identify, validate and establish SNRPG, OST4, TOMM7 and NOP10 as RGs for the normalization of EV-associated genes by RT-qPCR. We show the stable presence of SNRPG, OST4, TOMM7 and NOP10 in multiple cell lines and their secreted EVs (n = 12) under different (patho)physiological conditions as well as in human-derived biofluids (n = 3). Enzymatic treatments confirm the presence of SNRPG, OST4, TOMM7 and NOP10 inside EVs. In addition, the four EV-associated RGs are stably detected in a size-range of EV subpopulations. RefFinder analysis reveals that SNRPG, OST4, TOMM7 and NOP10 are more stable compared to RGs established specifically for cultured cells or tissues such as HMBS, YWHAZ, SDHA and GAPDH. In summary, we present four universal and stably present EV-associated RGs to enable normalization and thus steer the implementation of RT-qPCR for the analysis of EV-associated RNA cargo for research or clinical applications.

Selective Replacement of Cholesterol with Cationic Amphiphilic Drugs Enables the Design of Lipid Nanoparticles with Improved RNA Delivery.

The delivery of RNA across biological barriers can be achieved by encapsulation in lipid nanoparticles (LNPs). Cationic amphiphilic drugs (CADs) are pharmacologically diverse compounds with ionizable lipid-like features. In this work, we applied CADs as a fifth component of state-of-the-art LNPs via microfluidic mixing. Improved cytosolic delivery of both siRNA and mRNA was achieved by partly replacing the cholesterol fraction of LNPs with CADs. The LNPs could cross the mucus layer in a mucus-producing air-liquid interface model of human primary bronchial epithelial cells following nebulization. Moreover, CAD-LNPs demonstrated improved epithelial and endothelial targeting following intranasal administration in mice, without a marked pro-inflammatory signature. Importantly, quantification of the CAD-LNP molar composition, as demonstrated for nortriptyline, revealed a gradual leakage of the CAD from the formulation during LNP dialysis. Altogether, these data suggest that the addition of a CAD prior to the rapid mixing process might have an impact on the composition, structure, and performance of LNPs.

Effective methods for bulk RNA-seq deconvolution using scnRNA-seq transcriptomes.

BACKGROUND: RNA profiling technologies at single-cell resolutions, including single-cell and single-nuclei RNA sequencing (scRNA-seq and snRNA-seq, scnRNA-seq for short), can help characterize the composition of tissues and reveal cells that influence key functions in both healthy and disease tissues. However, the use of these technologies is operationally challenging because of high costs and stringent sample-collection requirements. Computational deconvolution methods that infer the composition of bulk-profiled samples using scnRNA-seq-characterized cell types can broaden scnRNA-seq applications, but their effectiveness remains controversial. RESULTS: We produced the first systematic evaluation of deconvolution methods on datasets with either known or scnRNA-seq-estimated compositions. Our analyses revealed biases that are common to scnRNA-seq 10X Genomics assays and illustrated the importance of accurate and properly controlled data preprocessing and method selection and optimization. Moreover, our results suggested that concurrent RNA-seq and scnRNA-seq profiles can help improve the accuracy of both scnRNA-seq preprocessing and the deconvolution methods that employ them. Indeed, our proposed method, Single-cell RNA Quantity Informed Deconvolution (SQUID), which combines RNA-seq transformation and dampened weighted least-squares deconvolution approaches, consistently outperformed other methods in predicting the composition of cell mixtures and tissue samples. CONCLUSIONS: We showed that analysis of concurrent RNA-seq and scnRNA-seq profiles with SQUID can produce accurate cell-type abundance estimates and that this accuracy improvement was necessary for identifying outcomes-predictive cancer cell subclones in pediatric acute myeloid leukemia and neuroblastoma datasets. These results suggest that deconvolution accuracy improvements are vital to enabling its applications in the life sciences.

mTOR Inhibition Enhances Delivery and Activity of Antisense Oligonucleotides in Uveal Melanoma Cells.

Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Owing to a lack of effective treatments, patients with metastatic disease have a median survival time of 6-12 months. We recently demonstrated that the Survival Associated Mitochondrial Melanoma Specific Oncogenic Non-coding RNA (SAMMSON) is essential for UM cell survival and that antisense oligonucleotide (ASO)-mediated silencing of SAMMSON impaired cell viability and tumor growth in vitro and in vivo. By screening a library of 2911 clinical stage compounds, we identified the mammalian target of rapamycin (mTOR) inhibitor GDC-0349 to synergize with SAMMSON inhibition in UM. Mechanistic studies revealed that mTOR inhibition enhanced uptake and reduced lysosomal accumulation of lipid complexed SAMMSON ASOs, improving SAMMSON knockdown and further decreasing UM cell viability. We found mTOR inhibition to also enhance target knockdown in other cancer cell lines as well as normal cells when combined with lipid nanoparticle complexed or encapsulated ASOs or small interfering RNAs (siRNAs). Our results are relevant to nucleic acid treatment in general and highlight the potential of mTOR inhibition to enhance ASO and siRNA-mediated target knockdown.

Benchmarking blood collection tubes and processing intervals for extracellular vesicle performance metrics.

The analysis of extracellular vesicles (EV) in blood samples is under intense investigation and holds the potential to deliver clinically meaningful biomarkers for health and disease. Technical variation must be minimized to confidently assess EV-associated biomarkers, but the impact of pre-analytics on EV characteristics in blood samples remains minimally explored. We present the results from the first large-scale EV Blood Benchmarking (EVBB) study in which we systematically compared 11 blood collection tubes (BCT; six preservation and five non-preservation) and three blood processing intervals (BPI; 1, 8 and 72 h) on defined performance metrics (n = 9). The EVBB study identifies a significant impact of multiple BCT and BPI on a diverse set of metrics reflecting blood sample quality, ex-vivo generation of blood-cell derived EV, EV recovery and EV-associated molecular signatures. The results assist the informed selection of the optimal BCT and BPI for EV analysis. The proposed metrics serve as a framework to guide future research on pre-analytics and further support methodological standardization of EV studies.

Blocking Abundant RNA Transcripts by High-Affinity Oligonucleotides during Transcriptome Library Preparation.

BACKGROUND: RNA sequencing has become the gold standard for transcriptome analysis but has an inherent limitation of challenging quantification of low-abundant transcripts. In contrast to microarray technology, RNA sequencing reads are proportionally divided in function of transcript abundance. Therefore, low-abundant RNAs compete against highly abundant - and sometimes non-informative - RNA species. RESULTS: We developed an easy-to-use strategy based on high-affinity RNA-binding oligonucleotides to block reverse transcription and PCR amplification of specific RNA transcripts, thereby substantially reducing their abundance in the final sequencing library. To demonstrate the broad application potential of our method, we applied it to different transcripts and library preparation strategies, including YRNAs in small RNA sequencing of human blood plasma, mitochondrial rRNAs in both 3' end sequencing and long-read sequencing, and MALAT1 in single-cell 3' end sequencing. We demonstrate that the blocking strategy is highly efficient, reproducible, specific, and generally results in better transcriptome coverage and complexity. CONCLUSION: Our method does not require modifications of the library preparation procedure apart from simply adding blocking oligonucleotides to the RT reaction and can thus be easily integrated into virtually any RNA sequencing library preparation protocol.

Artifacts and biases of the reverse transcription reaction in RNA sequencing.

RNA sequencing has spurred a significant number of research areas in recent years. Most protocols rely on synthesizing a more stable complementary DNA (cDNA) copy of the RNA molecule during the reverse transcription reaction. The resulting cDNA pool is often wrongfully assumed to be quantitatively and molecularly similar to the original RNA input. Sadly, biases and artifacts confound the resulting cDNA mixture. These issues are often overlooked or ignored in the literature by those that rely on the reverse transcription process. In this review, we confront the reader with intra- and intersample biases and artifacts caused by the reverse transcription reaction during RNA sequencing experiments. To fight the reader's despair, we also provide solutions to most issues and inform on good RNA sequencing practices. We hope the reader can use this review to their advantage, thereby contributing to scientifically sound RNA studies.

Longitudinal evaluation of serum microRNAs as biomarkers for neuroblastoma burden and therapeutic p53 reactivation.

Accurate assessment of treatment response and residual disease is indispensable for the evaluation of cancer treatment efficacy. However, performing tissue biopsies for longitudinal follow-up poses a major challenge in the management of solid tumours like neuroblastoma. In the present study, we evaluated whether circulating miRNAs are suitable to monitor neuroblastoma tumour burden and whether treatment-induced changes of miRNA abundance in the tumour are detectable in serum. We performed small RNA sequencing on longitudinally collected serum samples from mice carrying orthotopic neuroblastoma xenografts that were exposed to treatment with idasanutlin or temsirolimus. We identified 57 serum miRNAs to be differentially expressed upon xenograft tumour manifestation, out of which 21 were also found specifically expressed in the serum of human high-risk neuroblastoma patients. The murine serum levels of these 57 miRNAs correlated with tumour tissue expression and tumour volume, suggesting potential utility for monitoring tumour burden. In addition, we describe serum miRNAs that dynamically respond to p53 activation following treatment of engrafted mice with idasanutlin. We identified idasanutlin-induced serum miRNA expression changes upon one day and 11 days of treatment. By limiting to miRNAs with a tumour-related induction, we put forward hsa-miR-34a-5p as a potential pharmacodynamic biomarker of p53 activation in serum.

Direct lysis of 3D cell cultures for RT-qPCR gene expression quantification.

In vitro cell culture experiments are widely used to study cellular behavior in most biological research fields. Except for suspension cells, most human cell types are cultured as adherent monolayers on a plastic surface. While technically convenient, monolayer cultures can suffer from limitations in terms of physiological relevance, as their resemblance to complex in vivo tissue structures is limited. To address these limitations, three-dimensional (3D) cell culture systems have gained increased interest as they mimic key structural and functional properties of their in vivo tissue counterparts. Nevertheless, protocols established on monolayer cell cultures may require adjustments if they are to be applied to 3D cell cultures. As gene expression quantification is an essential part of many in vitro experiments, we evaluated and optimized a direct cell lysis, reverse transcription and qPCR protocol applicable for 3D cell cultures. The newly developed protocol wherein gene expression is determined directly from crude cell lysates showed improved cell lysis compared to the standard protocol, accurate gene expression quantification, hereby avoiding time-consuming cell harvesting and RNA extraction.

IL-10 producing regulatory B cells are decreased in blood from smokers and COPD patients.

BACKGROUND: Two opposing B cell subsets have been defined based on their cytokine profile: IL-6 producing effector B cells (B-effs) versus IL-10 producing regulatory B cells (B-regs) that respectively positively or negatively regulate immune responses. B-regs are decreased and/or impaired in many autoimmune diseases and inflammatory conditions. Since there is increasing evidence that links B cells and B cell-rich lymphoid follicles to the pathogenesis of COPD, the aim of this study was to investigate the presence and function of B-regs in COPD. METHODS: First, presence of IL-10 producing regulatory B cells in human lung tissue was determined by immunohistochemistry. Secondly, quantification of IL-10 + B-regs and IL-6 + B-effs in peripheral blood mononuclear cells (PBMCs) from healthy controls, smokers without airflow limitation, and COPD patients (GOLD stage I-IV) was performed by flow cytometry. Thirdly, we exposed blood-derived B cells from COPD patients in vitro to cigarette smoke extract (CSE) and quantified IL-10 + B-regs and IL-6 + B-effs. Furthermore, we aimed at restoring the perturbed IL10 production by blocking BAFF. Fourthly, we determined mRNA expression of transcription factors involved in IL-10 production in FACS sorted memory- and naive B cells upon exposure to medium or CSE. RESULTS: The presence of IL-10 producing regulatory B cells in parenchyma and lymphoid follicles in lungs was confirmed by immunohistochemistry. The percentage of IL-10 + B-regs was significantly decreased in blood-derived memory B cell subsets from smokers without airflow limitation and patients with COPD, compared to never smokers. Furthermore, the capacity of B cells to produce IL-10 was reduced upon in vitro exposure to CSE and this could not be restored by BAFF-blockade. Finally, upon CSE exposure, mRNA levels of the transcription factors IRF4 and HIF-1α, were decreased in memory B cells. CONCLUSION: Decreased numbers and impaired function of B-regs in smokers and patients with COPD might contribute to the initiation and progression of the disease.

CiLiQuant: Quantification of RNA Junction Reads Based on Their Circular or Linear Transcript Origin.

Distinguishing circular RNA reads from reads derived from the linear host transcript is a challenging task because of sequence overlap. We developed a computational approach, CiLiQuant, that determines the relative circular and linear abundance of transcripts and gene loci using back-splice and unambiguous forward-splice junction reads generated by existing mapping and circular RNA discovery tools.

A 3'-end capture sequencing method for high-throughput targeted gene expression profiling.

Molecular phenotyping through shallow 3'-end RNA-sequencing workflows is increasingly applied in the context of large-scale chemical or genetic perturbation screens to study disease biology or support drug discovery. While these workflows enable accurate quantification of the most abundant genes, they are less effective for applications that require expression profiling of low abundant transcripts, like long noncoding RNAs (lncRNAs), or selected gene panels. To tackle these issues, we describe a workflow combining 3'-end library preparation with 3'-end hybrid capture probes and shallow RNA-sequencing for cost-effective, targeted quantification of subsets of (low abundant) genes across hundreds to thousands of samples. To assess the performance of the method, we designed a capture probe set for more than 100 mRNA and lncRNA target genes and applied the workflow to a cohort of 360 samples. When compared to standard 3'-end RNA-sequencing, 3'-end capture sequencing resulted in a more than 200-fold enrichment of target gene abundance while conserving relative intergene and intersample abundances. 3'-end RNA capture sequencing enables accurate targeted gene expression profiling at extremely shallow sequencing depth.

Evaluation of efficiency and sensitivity of 1D and 2D sample pooling strategies for SARS-CoV-2 RT-qPCR screening purposes.

To increase the throughput, lower the cost, and save scarce test reagents, laboratories can pool patient samples before SARS-CoV-2 RT-qPCR testing. While different sample pooling methods have been proposed and effectively implemented in some laboratories, no systematic and large-scale evaluations exist using real-life quantitative data gathered throughout the different epidemiological stages. Here, we use anonymous data from 9673 positive cases to model, simulate and compare 1D and 2D pooling strategies. We show that the optimal choice of pooling method and pool size is an intricate decision with a testing population-dependent efficiency-sensitivity trade-off and present an online tool to provide the reader with custom real-time 1D pooling strategy recommendations.

Unlocking the secrets of long non-coding RNAs in asthma.

Asthma is a very heterozygous disease, divided in subtypes, such as eosinophilic and neutrophilic asthma. Phenotyping and endotyping of patients, especially patients with severe asthma who are refractory to standard treatment, are crucial in asthma management and are based on a combination of clinical and biological features. Nevertheless, the quest remains to find better biomarkers that distinguish asthma subtypes in a more clear and objective manner and to find new therapeutic targets to treat people with therapy-resistant asthma. In the past, research to identify asthma subtypes mainly focused on expression profiles of protein-coding genes. However, advances in RNA-sequencing technologies and the discovery of non-coding RNAs as important post-transcriptional regulators have provided an entire new field of research opportunities in asthma. This review focusses on long non-coding RNAs (lncRNAs) in asthma; these are non-coding RNAs with a length of more than 200 nucleotides. Many lncRNAs are differentially expressed in asthma, and several have been associated with asthma severity or inflammatory phenotype. Moreover, in vivo and in vitro functional studies have identified the mechanisms of action of specific lncRNAs. Although lncRNAs remain not widely studied in asthma, the current studies show the potential of lncRNAs as biomarkers and therapeutic targets as well as the need for further research.

Reliable and Scalable SARS-CoV-2 qPCR Testing at a High Sample Throughput: Lessons Learned from the Belgian Initiative.

We present our approach to rapidly establishing a standardized, multi-site, nation-wide COVID-19 screening program in Belgium. Under auspices of a federal government Task Force responsible for upscaling the country's testing capacity, we were able to set up a national testing initiative with readily available resources, putting in place a robust, validated, high-throughput, and decentralized qPCR molecular testing platform with embedded proficiency testing. We demonstrate how during an acute scarcity of equipment, kits, reagents, personnel, protective equipment, and sterile plastic supplies, we introduced an approach to rapidly build a reliable, validated, high-volume, high-confidence workflow based on heterogeneous instrumentation and diverse assays, assay components, and protocols. The workflow was set up with continuous quality control monitoring, tied together through a clinical-grade information management platform for automated data analysis, real-time result reporting across different participating sites, qc monitoring, and making result data available to the requesting physician and the patient. In this overview, we address challenges in optimizing high-throughput cross-laboratory workflows with minimal manual intervention through software, instrument and assay validation and standardization, and a process for harmonized result reporting and nation-level infection statistics monitoring across the disparate testing methodologies and workflows, necessitated by a rapid scale-up as a response to the pandemic.

Orthogonal proteomics methods to unravel the HOTAIR interactome.

Accumulating evidence highlights the role of long non-coding RNAs (lncRNAs) in cellular homeostasis, and their dysregulation in disease settings. Most lncRNAs function by interacting with proteins or protein complexes. While several orthogonal methods have been developed to identify these proteins, each method has its inherent strengths and limitations. Here, we combine two RNA-centric methods ChIRP-MS and RNA-BioID to obtain a comprehensive list of proteins that interact with the well-known lncRNA HOTAIR. Overexpression of HOTAIR has been associated with a metastasis-promoting phenotype in various cancers. Although HOTAIR is known to bind with PRC2 and LSD1 protein complexes, only very limited unbiased comprehensive approaches to map its interactome have been performed. Both ChIRP-MS and RNA-BioID data sets show an association of HOTAIR with mitoribosomes, suggesting that HOTAIR has functions independent of its (post-)transcriptional mode-of-action.

RNA biomarkers from proximal liquid biopsy for diagnosis of ovarian cancer.

BACKGROUND: Most ovarian cancer patients are diagnosed at an advanced stage and have a high mortality rate. Current screening strategies fail to improve prognosis because markers that are sensitive for early stage disease are lacking. This medical need justifies the search for novel approaches using utero-tubal lavage as a proximal liquid biopsy. METHODS: In this study, we explore the extracellular transcriptome of utero-tubal lavage fluid obtained from 26 ovarian cancer patients and 48 controls using messenger RNA (mRNA) capture and small RNA sequencing. RESULTS: We observed an enrichment of ovarian and fallopian tube specific messenger RNAs in utero-tubal lavage fluid compared to other human biofluids. Over 300 mRNAs and 41 miRNAs were upregulated in ovarian cancer samples compared with controls. Upregulated genes were enriched for genes involved in cell cycle activation and proliferation, hinting at a tumor-derived signal. CONCLUSION: This is a proof-of-principle that mRNA capture sequencing of utero-tubal lavage fluid is technically feasible, and that the extracellular transcriptome of utero-tubal lavage should be further explored in larger cohorts to assess the diagnostic value of the biomarkers identified in this study. IMPACT: Proximal liquid biopsy from the gynecologic tract is a promising source for mRNA and miRNA biomarkers for diagnosis of early-stage ovarian cancer.

miR-99b-5p, miR-380-3p, and miR-485-3p are novel chemosensitizing miRNAs in high-risk neuroblastoma.

Neuroblastoma is a deadly childhood cancer arising in the developing sympathetic nervous system. High-risk patients are currently treated with intensive chemotherapy, which is curative in only 50% of children and leaves some surviving patients with life-long side effects. microRNAs (miRNAs) are critical regulators of neural crest development and are deregulated during neuroblastoma tumorigenesis, making miRNA-based drugs an attractive therapeutic avenue. A functional screen of >1,200 miRNA mimics was conducted in neuroblastoma cell lines to discover miRNAs that sensitized cells to low doses (30% inhibitory concentration [IC30]) of doxorubicin and vincristine chemotherapy used in the treatment of the disease. Three miRNAs, miR-99b-5p, miR-380-3p, and miR-485-3p, had potent chemosensitizing activity with doxorubicin in multiple models of high-risk neuroblastoma. These miRNAs underwent genomic loss in a subset of neuroblastoma patients, and low expression predicted poor survival outcome. In vitro functional assays revealed each of these miRNAs enhanced the anti-proliferative and pro-apoptotic effects of doxorubicin. We used RNA sequencing (RNA-seq) to show that miR-99b-5p represses neuroblastoma dependency genes LIN28B and PHOX2B both in vitro and in patient-derived xenograft (PDX) tumors. Luciferase reporter assays demonstrate that PHOX2B is a direct target of miR-99b-5p. We anticipate that restoring the function of the tumor-suppressive miRNAs discovered here may be a valuable therapeutic strategy for the treatment of neuroblastoma patients.