Phospho-RNA-seq: a modified small RNA-seq method that reveals circulating mRNA and lncRNA fragments as potential biomarkers in human plasma.

Extracellular RNAs (exRNAs) in biofluids have attracted great interest as potential biomarkers. Although extracellular microRNAs in blood plasma are extensively characterized, extracellular messenger RNA (mRNA) and long non-coding RNA (lncRNA) studies are limited. We report that plasma contains fragmented mRNAs and lncRNAs that are missed by standard small RNA-seq protocols due to lack of 5' phosphate or presence of 3' phosphate. These fragments were revealed using a modified protocol ("phospho-RNA-seq") incorporating RNA treatment with T4-polynucleotide kinase, which we compared with standard small RNA-seq for sequencing synthetic RNAs with varied 5' and 3' ends, as well as human plasma exRNA Analyzing phospho-RNA-seq data using a custom, high-stringency bioinformatic pipeline, we identified mRNA/lncRNA transcriptome fingerprints in plasma, including tissue-specific gene sets. In a longitudinal study of hematopoietic stem cell transplant patients, bone marrow- and liver-enriched exRNA genes were tracked with bone marrow recovery and liver injury, respectively, providing proof-of-concept validation as a biomarker approach. By enabling access to an unexplored realm of mRNA and lncRNA fragments, phospho-RNA-seq opens up new possibilities for plasma transcriptomic biomarker development.

Men who inject opioids exhibit altered tRNA-Gly-GCC isoforms in semen.

In addition to their role in protein translation, tRNAs can be cleaved into shorter, biologically active fragments called tRNA fragments (tRFs). Specific tRFs from spermatocytes can propagate metabolic disorders in second generations of mice. Thus, tRFs in germline cells are a mechanism of epigenetic inheritance. It has also been shown that stress and toxins can cause alterations in tRF patterns. We were therefore interested in whether injecting illicit drugs, a major stressor, impacts tRFs in germline cells. We sequenced RNA from spermatocytes and from semen-derived exosomes from people who inject illicit drugs (PWID) and from non-drug using controls, both groups of unknown fertility status. All PWID injected opioids daily, but most also used other illicit drugs. The tRF cleavage products from Gly-GCC tRNA were markedly different between spermatocytes from PWID compared to controls. Over 90% of reads in controls mapped to shorter Gly-GCC tRFs, while in PWID only 45% did. In contrast, only 4.1% of reads in controls mapped to a longer tRFs versus 45.6% in PWID. The long/short tRF ratio was significantly higher in PWID than controls (0.23 versus 0.16, P = 0.0128). We also report differential expression of a group of small nucleolar RNAs (snoRNAs) in semen-derived exosomes, including, among others, ACA14a, U19, and U3-3. Thus, PWID exhibited an altered cleavage pattern of tRNA-Gly-GCC in spermatocytes and an altered cargo of snoRNAs in semen-derived exosomes. Participants were not exclusively using opioids and were not matched with controls in terms of diet, chronic disease, or other stressors, so our finding are not conclusively linked to opioid use. However, all individuals in the PWID group did inject heroin daily. Our study indicates a potential for opioid injection and/or its associated multi-drug use habits and lifestyle changes to influence epigenetic inheritance.

Rapid single-molecule digital detection of protein biomarkers for continuous monitoring of systemic immune disorders.

Digital protein assays have great potential to advance immunodiagnostics because of their single-molecule sensitivity, high precision, and robust measurements. However, translating digital protein assays to acute clinical care has been challenging because it requires deployment of these assays with a rapid turnaround. Herein, we present a technology platform for ultrafast digital protein biomarker detection by using single-molecule counting of immune-complex formation events at an early, pre-equilibrium state. This method, which we term "pre-equilibrium digital enzyme-linked immunosorbent assay" (PEdELISA), can quantify a multiplexed panel of protein biomarkers in 10 µL of serum within an unprecedented assay incubation time of 15 to 300 seconds over a 104 dynamic range. PEdELISA allowed us to perform rapid monitoring of protein biomarkers in patients manifesting post-chimeric antigen receptor T-cell therapy cytokine release syndrome, with ∼30-minute sample-to-answer time and a sub-picograms per mL limit of detection. The rapid, sensitive, and low-input volume biomarker quantification enabled by PEdELISA is broadly applicable to timely monitoring of acute disease, potentially enabling more personalized treatment.

Direct kinetic fingerprinting and digital counting of single protein molecules.

The sensitive and accurate quantification of protein biomarkers plays important roles in clinical diagnostics and biomedical research. Sandwich ELISA and its variants accomplish the capture and detection of a target protein via two antibodies that tightly bind at least two distinct epitopes of the same antigen and have been the gold standard for sensitive protein quantitation for decades. However, existing antibody-based assays cannot distinguish between signal arising from specific binding to the protein of interest and nonspecific binding to assay surfaces or matrix components, resulting in significant background signal even in the absence of the analyte. As a result, they generally do not achieve single-molecule sensitivity, and they require two high-affinity antibodies as well as stringent washing to maximize sensitivity and reproducibility. Here, we show that surface capture with a high-affinity antibody combined with kinetic fingerprinting using a dynamically binding, low-affinity fluorescent antibody fragment differentiates between specific and nonspecific binding at the single-molecule level, permitting the direct, digital counting of single protein molecules with femtomolar-to-attomolar limits of detection (LODs). We apply this approach to four exemplary antigens spiked into serum, demonstrating LODs 55- to 383-fold lower than commercially available ELISA. As a real-world application, we establish that endogenous interleukin-6 (IL-6) can be quantified in 2-µL serum samples from chimeric antigen receptor T cell (CAR-T cell) therapy patients without washing away excess serum or detection probes, as is required in ELISA-based approaches. This kinetic fingerprinting thus exhibits great potential for the ultrasensitive, rapid, and streamlined detection of many clinically relevant proteins.

Direct Kinetic Fingerprinting for High-Accuracy Single-Molecule Counting of Diverse Disease Biomarkers.

Methods for detecting and quantifying disease biomarkers in biofluids with high specificity and sensitivity play a pivotal role in enabling clinical diagnostics, including point-of-care tests. The most widely used molecular biomarkers include proteins, nucleic acids, hormones, metabolites, and other small molecules. While numerous methods have been developed for analyzing biomarkers, most techniques are challenging to implement for clinical use due to insufficient analytical performance, high cost, and/or other practical shortcomings. For instance, the detection of cell-free nucleic acid (cfNA) biomarkers by digital PCR and next-generation sequencing (NGS) requires time-consuming nucleic acid extraction steps, often introduces enzymatic amplification bias, and can be costly when high specificity is required. While several amplification-free methods for detecting cfNAs have been reported, these techniques generally suffer from low specificity and sensitivity. Meanwhile, the quantification of protein biomarkers is generally performed using immunoassays such as enzyme-linked immunosorbent assay (ELISA); the analytical performance of these methods is often limited by the availability of antibodies with high affinity and specificity as well as the significant nonspecific binding of antibodies to assay surfaces. To address the drawbacks of existing biomarker detection methods and establish a universal diagnostics platform capable of detecting different types of analytes, we have developed an amplification-free approach, named single-molecule recognition through equilibrium Poisson sampling (SiMREPS), for the detection of diverse biomarkers with arbitrarily high specificity and single-molecule sensitivity. SiMREPS utilizes the transient, reversible binding of fluorescent detection probes to immobilized target molecules to generate kinetic fingerprints that are detected by single-molecule fluorescence microscopy. The analysis of these kinetic fingerprints enables nearly perfect discrimination between specific binding to target molecules and any nonspecific binding. Early proof-of-concept studies demonstrated the in vitro detection of miRNAs with a limit of detection (LOD) of approximately 1 fM and >500-fold selectivity for single-nucleotide polymorphisms. The SiMREPS approach was subsequently expanded to the detection of rare mutant DNA alleles from biofluids at mutant allele fractions of as low as 1 in 1 million, corresponding to a specificity of >99.99999%. Recently, SiMREPS was generalized to protein quantification using dynamically binding antibody probes, permitting LODs in the low-femtomolar to attomolar range. Finally, SiMREPS has been demonstrated to be suitable for the in situ detection of miRNAs in cultured cells, the quantification of small-molecule toxins and drugs, and the monitoring of telomerase activity at the single-molecule level. In this Account, we discuss the principles of SiMREPS for the highly specific and sensitive detection of molecular analytes, including considerations for assay design. We discuss the generality of SiMREPS for the detection of very disparate analytes and provide an overview of data processing methods, including the expansion of the dynamic range using super-resolution analysis and the improvement of performance using deep learning algorithms. Finally, we describe current challenges, opportunities, and future directions for the SiMREPS approach.

High-frequency temperature monitoring at home using a wearable device: A case series of early fever detection and antibiotic administration for febrile neutropenia with bacteremia.

We present a case series of three febrile episodes in neutropenic pediatric cancer patients who wore a Food and Drug Administration approved high-frequency temperature monitoring (HFTM) wearable device (WD) at home. The WD detected fever events when temperature monitoring by thermometer did not detect fever or was not feasible to perform. Two of the episodes were associated with bloodstream infections and the WD detected fevers 5 and 12 h prior to fevers detected by thermometer, triggering earlier medical evaluation and more prompt administration of antibiotics. These observations provide a basis for future investigation of home-based HFTM to improve infection-related outcomes in pediatric oncology.

Severe Acute Respiratory Syndrome Coronavirus 2 Total and Subgenomic RNA Viral Load in Hospitalized Patients.

BACKGROUND: Previous studies demonstrated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA can be detected for weeks after infection. The significance of this finding is unclear and, in most patients, does not represent active infection. Detection of subgenomic RNA has been proposed to represent productive infection and may be a useful marker for monitoring infectivity. METHODS: We used quantitative reverse-transcription polymerase chain reaction (RT-qPCR) to quantify total and subgenomic nucleocapsid (sgN) and envelope (sgE) transcripts in 185 SARS-CoV-2-positive nasopharyngeal swab samples collected on hospital admission and to relate to symptom duration. RESULTS: We find that all transcripts decline at the same rate; however, sgE becomes undetectable before other transcripts. The median duration of symptoms to a negative test is 14 days for sgE and 25 days for sgN. There is a linear decline in subgenomic compared to total RNA, suggesting that subgenomic transcript copy number is dependent on copy number of total transcripts. The mean difference between total and sgN is 16-fold and the mean difference between total and sgE is 137-fold. This relationship is constant over duration of symptoms, allowing prediction of subgenomic copy number from total copy number. CONCLUSIONS: Subgenomic RNA may be no more useful in determining infectivity than a copy number threshold determined for total RNA.

Surveillance and Monitoring Techniques for HPV-Related Head and Neck Squamous Cell Carcinoma: Circulating Tumor DNA.

OPINION STATEMENT: Human papilloma virus (HPV) related head and neck cancer is rising in prevalence, preferentially affecting young patients and imparting long term toxicities. Despite this, there are no screening tests or clinical biomarkers for treatment monitoring. HPV circulating tumor DNA (HPV ctDNA) represents a novel circulating biomarker which may provide real-time assessment of tumor response to therapy and recurrence. Early work suggests the promise of this assay as a predictive biomarker in numerous clinical settings, namely risk of recurrence after chemoradiation in locally advanced disease. Advancement of these findings to the clinic will require a collaborative effort in the field, including technical harmonization of assay testing characteristics, understanding of the normal kinetics in patients being treated with standard of care therapies, and appropriately designed phase III trials prior to implementation in the clinic. If successful, HPV ctDNA has the potential to revolutionize clinical trial treatment paradigms and transform patient care.

Ultraspecific analyte detection by direct kinetic fingerprinting of single molecules.

The detection and quantification of biomarkers have numerous applications in biological research and medicine. The most widely used methods to detect nucleic acids require amplification via the polymerase chain reaction (PCR). However, errors arising from the imperfect copying fidelity of DNA polymerases, limited specificity of primers, and heat-induced damage reduce the specificity of PCR-based methods, particularly for single-nucleotide variants. Furthermore, not all analytes can be amplified efficiently. While amplification-free methods avoid these pitfalls, the specificity of most such methods is strictly constrained by probe binding thermodynamics, which for example hampers detection of rare somatic mutations. In contrast, single-molecule recognition through equilibrium Poisson sampling (SiMREPS) provides ultraspecific detection with single-molecule and single-nucleotide sensitivity by monitoring the repetitive interactions of a fluorescent probe with surface-immobilized targets. In this review, we discuss SiMREPS in comparison with other analytical approaches, and describe its utility in quantifying a range of nucleic acids and other analytes.

A guide to nucleic acid detection by single-molecule kinetic fingerprinting.

Conventional methods for detecting small quantities of nucleic acids require amplification by the polymerase chain reaction (PCR), which necessitates prior purification and introduces copying errors. While amplification-free methods do not have these shortcomings, they are generally orders of magnitude less sensitive and specific than PCR-based methods. In this review, we provide a practical guide to a novel amplification-free method, single-molecule recognition through equilibrium Poisson sampling (SiMREPS), that provides both single-molecule sensitivity and single-base selectivity by monitoring the repetitive interactions of fluorescent probes to immobilized targets. We demonstrate how this kinetic fingerprinting filters out background arising from the inevitable nonspecific binding of probes, yielding virtually zero background signal. As practical applications of this digital detection methodology, we present the quantification of microRNA miR-16 and the detection of the mutation EGFR L858R with an apparent single-base discrimination factor of over 3 million.

A Systematic Review of Machine Learning Techniques in Hematopoietic Stem Cell Transplantation (HSCT).

Machine learning techniques are widely used nowadays in the healthcare domain for the diagnosis, prognosis, and treatment of diseases. These techniques have applications in the field of hematopoietic cell transplantation (HCT), which is a potentially curative therapy for hematological malignancies. Herein, a systematic review of the application of machine learning (ML) techniques in the HCT setting was conducted. We examined the type of data streams included, specific ML techniques used, and type of clinical outcomes measured. A systematic review of English articles using PubMed, Scopus, Web of Science, and IEEE Xplore databases was performed. Search terms included "hematopoietic cell transplantation (HCT)," "autologous HCT," "allogeneic HCT," "machine learning," and "artificial intelligence." Only full-text studies reported between January 2015 and July 2020 were included. Data were extracted by two authors using predefined data fields. Following PRISMA guidelines, a total of 242 studies were identified, of which 27 studies met the inclusion criteria. These studies were sub-categorized into three broad topics and the type of ML techniques used included ensemble learning (63%), regression (44%), Bayesian learning (30%), and support vector machine (30%). The majority of studies examined models to predict HCT outcomes (e.g., survival, relapse, graft-versus-host disease). Clinical and genetic data were the most commonly used predictors in the modeling process. Overall, this review provided a systematic review of ML techniques applied in the context of HCT. The evidence is not sufficiently robust to determine the optimal ML technique to use in the HCT setting and/or what minimal data variables are required.

Ultraspecific and Amplification-Free Quantification of Mutant DNA by Single-Molecule Kinetic Fingerprinting.

Conventional techniques for detecting rare DNA sequences require many cycles of PCR amplification for high sensitivity and specificity, potentially introducing significant biases and errors. While amplification-free methods exist, they rarely achieve the ability to detect single molecules, and their ability to discriminate between single-nucleotide variants is often dictated by the specificity limits of hybridization thermodynamics. Here we show that a direct detection approach using single-molecule kinetic fingerprinting can surpass the thermodynamic discrimination limit by 3 orders of magnitude, with a dynamic range of up to 5 orders of magnitude with optional super-resolution analysis. This approach detects mutations as subtle as the drug-resistance-conferring cancer mutation EGFR T790M (a single C → T substitution) with an estimated specificity of 99.99999%, surpassing even the leading PCR-based methods and enabling detection of 1 mutant molecule in a background of at least 1 million wild-type molecules. This level of specificity revealed rare, heat-induced cytosine deamination events that introduce false positives in PCR-based detection, but which can be overcome in our approach through milder thermal denaturation and enzymatic removal of damaged nucleobases.

Circulating microRNAs and treatment response in the Phase II SWOG S0925 study for patients with new metastatic hormone-sensitive prostate cancer.

BACKGROUND: Previous studies suggest circulating, blood-based microRNAs (miRNAs) may serve as minimally invasive prostate cancer biomarkers, however there is limited data from prospective clinical trials. Here, we explore the role of candidate plasma miRNAs as potential biomarkers in the SWOG 0925 randomized phase II study of androgen deprivation combined with cixutumumab versus androgen deprivation alone in patients with new metastatic hormone-sensitive prostate cancer. METHODS: Correlative biospecimens, including circulating tumor cells (CTCs) and plasma for miRNA analysis, were collected at baseline and after 12 weeks on treatment from 50 patients enrolled on SWOG 0925. Circulating microRNAs were quantified using real-time RT-PCR microRNA array that allowed specific analysis of previously identified candidate miRNAs (miR-141, miR-200a, miR-200b, miR-210, and miR-375) as well as discovery analysis to identify new candidate miRNAs. MiRNA levels were correlated to previously reported CTC counts using CellSearch® (Veridex) and with the primary study outcome of 28-week PSA response (≤0.2, 0.2 to ≤4.0, or >4.0 ng/mL), previously shown to correlate with overall survival. RESULTS: We observed a correlation between baseline circulating miR-141, miR-200a, and miR-375 levels with baseline CTCs. Baseline miR-375 levels were associated with 28-week PSA response (≤0.2, 0.2 to ≤4.0, or >4.0 ng/mL, P = 0.007). Using ROC curve analysis, there was no significant difference between baseline miR-375 and baseline CTC in predicting 28-week PSA response (≤0.2 vs >0.2 ng/mL). To discover novel candidate miRNAs, we analyzed 365 miRNAs for association with the 28-week PSA response endpoint and identified new candidate miRNAs along with the existing candidates miR-375 and miR-200b (P = 0.0012, P = 0.0046, respectively. CONCLUSIONS: Baseline plasma miR-141, miR-200a, and miR-375 levels are associated with baseline CTC count. Baseline miR-375 was also associated with the trial endpoint of 28-week PSA response. Our results provide evidence that circulating miRNA biomarkers may have value as prognostic biomarkers and warrant further study in larger prospective clinical trials.

MicroRNA profiling: approaches and considerations.

MicroRNAs (miRNAs) are small RNAs that post-transcriptionally regulate the expression of thousands of genes in a broad range of organisms in both normal physiological contexts and in disease contexts. miRNA expression profiling is gaining popularity because miRNAs, as key regulators in gene expression networks, can influence many biological processes and also show promise as biomarkers for disease. Technological advances have spawned a multitude of platforms for miRNA profiling, and an understanding of the strengths and pitfalls of different approaches can aid in their effective use. Here, we review the major considerations for carrying out and interpreting results of miRNA-profiling studies.

The accessible chromatin landscape of the human genome.

DNase I hypersensitive sites (DHSs) are markers of regulatory DNA and have underpinned the discovery of all classes of cis-regulatory elements including enhancers, promoters, insulators, silencers and locus control regions. Here we present the first extensive map of human DHSs identified through genome-wide profiling in 125 diverse cell and tissue types. We identify ∼2.9 million DHSs that encompass virtually all known experimentally validated cis-regulatory sequences and expose a vast trove of novel elements, most with highly cell-selective regulation. Annotating these elements using ENCODE data reveals novel relationships between chromatin accessibility, transcription, DNA methylation and regulatory factor occupancy patterns. We connect ∼580,000 distal DHSs with their target promoters, revealing systematic pairing of different classes of distal DHSs and specific promoter types. Patterning of chromatin accessibility at many regulatory regions is organized with dozens to hundreds of co-activated elements, and the transcellular DNase I sensitivity pattern at a given region can predict cell-type-specific functional behaviours. The DHS landscape shows signatures of recent functional evolutionary constraint. However, the DHS compartment in pluripotent and immortalized cells exhibits higher mutation rates than that in highly differentiated cells, exposing an unexpected link between chromatin accessibility, proliferative potential and patterns of human variation.

BMT Roadmap: A User-Centered Design Health Information Technology Tool to Promote Patient-Centered Care in Pediatric Hematopoietic Cell Transplantation.

Health information technology (HIT) has great potential for increasing patient engagement. Pediatric hematopoietic cell transplantation (HCT) is a setting ripe for using HIT but in which little research exists. "BMT Roadmap" is a web-based application that integrates patient-specific information and includes several domains: laboratory results, medications, clinical trial details, photos of the healthcare team, trajectory of transplant process, and discharge checklist. BMT Roadmap was provided to 10 caregivers of patients undergoing first-time HCT. Research assistants performed weekly qualitative interviews throughout the patient's hospitalization and at discharge and day 100 to assess the impact of BMT Roadmap. Rigorous thematic analysis revealed 5 recurrent themes: emotional impact of the HCT process itself; critical importance of communication among patients, caregivers, and healthcare providers; ways in which BMT Roadmap was helpful during inpatient setting; suggestions for improving BMT Roadmap; and other strategies for organization and management of complex healthcare needs that could be incorporated into BMT Roadmap. Caregivers found the tool useful and easy to use, leading them to want even greater access to information. BMT Roadmap was feasible, with no disruption to inpatient care. Although this initial study is limited by the small sample size and single-institution experience, these initial findings are encouraging and support further investigation.

Release of Cell-free MicroRNA Tumor Biomarkers into the Blood Circulation with Pulsed Focused Ultrasound: A Noninvasive, Anatomically Localized, Molecular Liquid Biopsy.

Purpose To compare the abilities of three pulsed focused ultrasound regimes (that cause tissue liquefaction, permeabilization, or mild heating) to release tumor-derived microRNA into the circulation in vivo and to evaluate release dynamics. Materials and Methods All rat experiments were approved by the University of Washington Institutional Animal Care and Use Committee. Reverse-transcription quantitative polymerase chain reaction array profiling was used to identify candidate microRNA biomarkers in a rat solid tumor cell line. Rats subcutaneously grafted with these cells were randomly assigned among three pulsed focused ultrasound treatment groups: (a) local tissue liquefaction via boiling histotripsy, (b) tissue permeabilization via inertial cavitation, and (c) mild (<10°C) heating of tissue, as well as a sham-treated control group. Blood specimens were drawn immediately prior to treatment and serially over 24 hours afterward. Plasma microRNA was quantified with reverse-transcription quantitative polymerase chain reaction, and statistical significance was determined with one-way analysis of variance (Kruskal-Wallis and Friedman tests), followed by the Dunn multiple-comparisons test. Results After tissue liquefaction and cavitation treatments (but not mild heating), plasma quantities of candidate biomarkers increased significantly (P value range, <.0001 to .04) relative to sham-treated controls. A threefold to 32-fold increase occurred within 15 minutes after initiation of pulsed focused ultrasound tumor treatment, and these increases persisted for 3 hours. Histologic examination confirmed complete liquefaction of the targeted tumor area with boiling histotripsy, in addition to areas of petechial hemorrhage and tissue disruption by means of cavitation-based treatment. Conclusion Mechanical tumor tissue disruption with pulsed focused ultrasound-induced bubble activity significantly increases the plasma abundance of tumor-derived microRNA rapidly after treatment. © RSNA, 2016 Online supplemental material is available for this article.

High-throughput sequencing of two populations of extracellular vesicles provides an mRNA signature that can be detected in the circulation of breast cancer patients.

Extracellular vesicles (EVs) contain a wide range of RNA types with a reported prevalence of non-coding RNA. To date a comprehensive characterization of the protein coding transcripts in EVs is still lacking. We performed RNA-Sequencing (RNA-Seq) of 2 EV populations and identified a small fraction of transcripts that were expressed at significantly different levels in large oncosomes and exosomes, suggesting they may mediate specialized functions. However, these 2 EV populations exhibited a common mRNA signature that, in comparison to their donor cells, was significantly enriched in mRNAs encoding E2F transcriptional targets and histone proteins. These mRNAs are primarily expressed in the S-phase of the cell cycle, suggesting that they may be packaged into EVs during S-phase. In silico analysis using subcellular compartment transcriptome data from the ENCODE cell line compendium revealed that EV mRNAs originate from a cytoplasmic RNA pool. The EV signature was independently identified in plasma of patients with breast cancer by RNA-Seq. Furthermore, several transcripts differentially expressed in EVs from patients versus controls mirrored differential expression between normal and breast cancer tissues. Altogether, this largest high-throughput profiling of EV mRNA demonstrates that EVs carry tumor-specific alterations and can be interrogated as a source of cancer-derived cargo.

Quantitative and stoichiometric analysis of the microRNA content of exosomes.

Exosomes have been proposed as vehicles for microRNA (miRNA) -based intercellular communication and a source of miRNA biomarkers in bodily fluids. Although exosome preparations contain miRNAs, a quantitative analysis of their abundance and stoichiometry is lacking. In the course of studying cancer-associated extracellular miRNAs in patient blood samples, we found that exosome fractions contained a small minority of the miRNA content of plasma. This low yield prompted us to perform a more quantitative assessment of the relationship between miRNAs and exosomes using a stoichiometric approach. We quantified both the number of exosomes and the number of miRNA molecules in replicate samples that were isolated from five diverse sources (i.e., plasma, seminal fluid, dendritic cells, mast cells, and ovarian cancer cells). Regardless of the source, on average, there was far less than one molecule of a given miRNA per exosome, even for the most abundant miRNAs in exosome preparations (mean ± SD across six exosome sources: 0.00825 ± 0.02 miRNA molecules/exosome). Thus, if miRNAs were distributed homogenously across the exosome population, on average, over 100 exosomes would need to be examined to observe one copy of a given abundant miRNA. This stoichiometry of miRNAs and exosomes suggests that most individual exosomes in standard preparations do not carry biologically significant numbers of miRNAs and are, therefore, individually unlikely to be functional as vehicles for miRNA-based communication. We propose revised models to reconcile the exosome-mediated, miRNA-based intercellular communication hypothesis with the observed stoichiometry of miRNAs associated with exosomes.

User-Centered Design Groups to Engage Patients and Caregivers with a Personalized Health Information Technology Tool.

Health information technology (IT) has opened exciting avenues for capturing, delivering and sharing data, and offers the potential to develop cost-effective, patient-focused applications. In recent years, there has been a proliferation of health IT applications such as outpatient portals. Rigorous evaluation is fundamental to ensure effectiveness and sustainability, as resistance to more widespread adoption of outpatient portals may be due to lack of user friendliness. Health IT applications that integrate with the existing electronic health record and present information in a condensed, user-friendly format could improve coordination of care and communication. Importantly, these applications should be developed systematically with appropriate methodological design and testing to ensure usefulness, adoption, and sustainability. Based on our prior work that identified numerous information needs and challenges of HCT, we developed an experimental prototype of a health IT tool, the BMT Roadmap. Our goal was to develop a tool that could be used in the real-world, daily practice of HCT patients and caregivers (users) in the inpatient setting. Herein, we examined the views, needs, and wants of users in the design and development process of the BMT Roadmap through user-centered Design Groups. Three important themes emerged: 1) perception of core features as beneficial (views), 2) alerting the design team to potential issues with the user interface (needs); and 3) providing a deeper understanding of the user experience in terms of wider psychosocial requirements (wants). These findings resulted in changes that led to an improved, functional BMT Roadmap product, which will be tested as an intervention in the pediatric HCT population in the fall of 2015 (ClinicalTrials.govNCT02409121).