ctDNA transiting into urine is ultrashort and facilitates noninvasive liquid biopsy of HPV+ oropharyngeal cancer.

BACKGROUNDTransrenal cell-free tumor DNA (TR-ctDNA), which transits from the bloodstream into urine, has the potential to enable noninvasive cancer detection for a wide variety of nonurologic cancer types.MethodsUsing whole-genome sequencing, we discovered that urine TR-ctDNA fragments across multiple cancer types are predominantly ultrashort (<50 bp) and, therefore, likely to be missed by conventional ctDNA assays. We developed an ultrashort droplet digital PCR assay to detect TR-ctDNA originating from HPV-associated oropharyngeal squamous cell carcinoma (HPV+ OPSCC) and confirmed that assaying ultrashort DNA is critical for sensitive cancer detection from urine samples.ResultsTR-ctDNA was concordant with plasma ctDNA for cancer detection in patients with HPV+ OPSCC. As proof of concept for using urine TR-ctDNA for posttreatment surveillance, in a small longitudinal case series, TR-ctDNA showed promise for noninvasive detection of recurrence of HPV+ OPSCC.ConclusionOur data indicate that focusing on ultrashort fragments of TR-ctDNA will be important for realizing the full potential of urine-based cancer diagnostics. This has implications for urine-based detection of a wide variety of cancer types and for facilitating access to care through at-home specimen collections.FundingNIH grants R33 CA229023, R21 CA225493; NIH/National Cancer Institute grants U01 CA183848, R01 CA184153, and P30CA046592; American Cancer Society RSG-18-062-01-TBG; American Cancer Society Mission Boost grant MBGI-22-056-01-MBG; and the A. Alfred Taubman Medical Research Institute.

Development of a high-performance multi-probe droplet digital PCR assay for high-sensitivity detection of human papillomavirus circulating tumor DNA from plasma.

OBJECTIVES: To develop a high-performance droplet digital PCR (ddPCR) assay capable of enhancing the detection of human papillomavirus (HPV) circulating tumor DNA (ctDNA) in plasma from patients with HPV-associated oropharyngeal squamous cell carcinoma (HPV+ OPSCC). MATERIALS AND METHODS: Plasma samples from subjects with HPV+ OPSCC were collected. We developed a high-performance ddPCR assay designed to simultaneously target nine regions of the HPV16 genome. RESULTS: The new assay termed 'ctDNA HPV16 Assessment using Multiple Probes' (CHAMP- 16) yielded significantly higher HPV16 counts compared to our previously validated 'Single-Probe' (SP) assay and a commercially available NavDx® assay. Analytical validation demonstrated that the CHAMP-16 assay had a limit of detection (LoD) of 4.1 copies per reaction, corresponding to < 1 genome equivalent (GE) of HPV16. When tested on plasma ctDNA from 21 patients with early-stage HPV+ OPSCC and known HPV16 ctDNA using the SP assay, all patients were positive for HPV16 ctDNA in both assays and the CHAMP-16 assay displayed 6.6-fold higher HPV16 signal on average. Finally, in a longitudinal analysis of samples from a patient with recurrent disease, the CHAMP-16 assay detected HPV16 ctDNA signal âˆ¼ 20 months prior to the conventional SP assay. CONCLUSION: Increased HPV16 signal detection using the CHAMP-16 assay suggests the potential for detection of recurrences significantly earlier than with conventional ddPCR assays in patients with HPV16+ OPSCC. Critically, this multi-probe approach maintains the cost-benefit advantage of ddPCR over next generation sequencing (NGS) approaches, supporting the cost-effectiveness of this assay for both large population screening and routine post-treatment surveillance.

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.

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.

Improved prediction of radiation pneumonitis by combining biological and radiobiological parameters using a data-driven Bayesian network analysis.

Grade 2 and higher radiation pneumonitis (RP2) is a potentially fatal toxicity that limits efficacy of radiation therapy (RT). We wished to identify a combined biomarker signature of circulating miRNAs and cytokines which, along with radiobiological and clinical parameters, may better predict a targetable RP2 pathway. In a prospective clinical trial of response-adapted RT for patients (n = 39) with locally advanced non-small cell lung cancer, we analyzed patients' plasma, collected pre- and during RT, for microRNAs (miRNAs) and cytokines using array and multiplex enzyme linked immunosorbent assay (ELISA), respectively. Interactions between candidate biomarkers, radiobiological, and clinical parameters were analyzed using data-driven Bayesian network (DD-BN) analysis. We identified alterations in specific miRNAs (miR-532, -99b and -495, let-7c, -451 and -139-3p) correlating with lung toxicity. High levels of soluble tumor necrosis factor alpha receptor 1 (sTNFR1) were detected in a majority of lung cancer patients. However, among RP patients, within 2 weeks of RT initiation, we noted a trend of temporary decline in sTNFR1 (a physiological scavenger of TNFα) and ADAM17 (a shedding protease that cleaves both membrane-bound TNFα and TNFR1) levels. Cytokine signature identified activation of inflammatory pathway. Using DD-BN we combined miRNA and cytokine data along with generalized equivalent uniform dose (gEUD) to identify pathways with better accuracy of predicting RP2 as compared to either miRNA or cytokines alone. This signature suggests that activation of the TNFα-NFκB inflammatory pathway plays a key role in RP which could be specifically ameliorated by etanercept rather than current therapy of non-specific leukotoxic corticosteroids.

Attomolar Sensitivity in Single Biomarker Counting upon Aqueous Two-Phase Surface Enrichment.

From longstanding techniques like enzyme-linked immunosorbent assay (ELISA) to modern next-generation sequencing, many of the most sensitive and specific biomarker detection assays require capture of the analyte at a surface. While surface-based assays provide advantages, including the ability to reduce background by washing away excess reagents and/or increase specificity through analyte-specific capture probes, the limited efficiency of capture from dilute solution often restricts assay sensitivity to the femtomolar-to-nanomolar range. Although assays for many nucleic acid analytes can decrease limits of detection (LODs) to the subfemtomolar range using polymerase chain reaction, such amplification may introduce biases, errors, and an increased risk of sample cross-contamination. Furthermore, many analytes cannot be amplified easily, including short nucleic acid fragments, epigenetic modifications, and proteins. To address the challenge of achieving subfemtomolar LODs in surface-based assays without amplification, we exploit an aqueous two-phase system (ATPS) to concentrate target molecules in a smaller-volume phase near the assay surface, thus increasing capture efficiency compared to passive diffusion from the original solution. We demonstrate the utility of ATPS-enhanced capture via single molecule recognition through equilibrium Poisson sampling (SiMREPS), a microscopy technique previously shown to possess >99.9999% detection specificity for DNA mutations but an LOD of only ∼1-5 fM. By combining ATPS-enhanced capture with a Förster resonance energy transfer (FRET)-based probe design for rapid data acquisition over many fields of view, we improve the LOD ∼ 300-fold to <10 aM for an EGFR exon 19 deletion mutation. We further validate this ATPS-assisted FRET-SiMREPS assay by detecting endogenous exon 19 deletion molecules in cancer patient blood plasma.

Human papilloma virus circulating tumor DNA assay predicts treatment response in recurrent/metastatic head and neck squamous cell carcinoma.

Despite the rising incidence of human papillomavirus related (HPV+) oropharyngeal squamous cell carcinoma (OPSCC), treatment of metastatic disease remains palliative. Even with new treatments such as immunotherapy, response rates are low and can be delayed, while even mild tumor progression in the face of an ineffective therapy can lead to rapid death. Real-time biomarkers of response to therapy could improve outcomes by guiding early change of therapy in the metastatic setting. Herein, we developed and analytically validated a new droplet digital PCR (ddPCR)-based assay for HPV16 circulating tumor DNA (ctDNA) and evaluated plasma HPV16 ctDNA for predicting treatment response in metastatic HPV+ OPSCC. We found that longitudinal changes HPV16 ctDNA correlate with treatment response and that ctDNA responses are observed earlier than conventional imaging (average 70 days, range: 35-166). With additional validation in multi-site studies, this assay may enable early identification of treatment failure, allowing patients to be directed promptly toward clinical trials or alternative therapies.

Monitoring beliefs and physiological measures in students at risk for COVID-19 using wearable sensors and smartphone technology: Protocol for a mobile health study.

BACKGROUND: The COVID-19 pandemic has impacted lives significantly and greatly affected an already vulnerable population, college students, in relation to mental health and public safety. Social distancing and isolation have brought about challenges to student's mental health. Mobile health apps and wearable sensors may help to monitor students at risk for COVID-19 and support their mental well-being. OBJECTIVE: Through the use of a wearable sensor and smartphone-based survey completion, this study aimed to monitor students at risk for COVID-19. METHODS: We conducted a prospective study of students, undergraduate and graduate, at a public university in the Midwest. Students were instructed to download the Fitbit, Social Rhythms, and Roadmap 2.0 apps onto their personal mobile devices (Android or iOS). Subjects consented to provide up to 10 saliva samples during the study period. Surveys were administered through the Roadmap 2.0 app at five timepoints - at baseline, 1-month later, 2-months later, 3-months later, and at study completion. The surveys gathered information regarding demographics, COVID-19 diagnoses and symptoms, and mental health resilience, with the aim of documenting the impact of COVID-19 on the college student population. RESULTS: This study enrolled 2,158 college students between September 2020 and January 2021. Subjects are currently being followed on-study for one academic year. Data collection and analysis are ongoing. CONCLUSIONS: This study examined student health and well-being during the COVID-19 pandemic. It also assessed the feasibility of wearable sensor use and survey completion in a college student population, which may inform the role of our mobile health tools on student health and well-being. Finally, using wearable sensor data, biospecimen collection, and self-reported COVID-19 diagnosis, our results may provide key data towards the development of a model for the early prediction and detection of COVID-19. CLINICALTRIAL: ClinicalTrials.gov NCT04766788.

Monitoring Health Care Workers at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology: Protocol for an Observational mHealth Study.

BACKGROUND: Health care workers (HCWs) have been working on the front lines of the COVID-19 pandemic with high risks of viral exposure, infection, and transmission. Standard COVID-19 testing is insufficient to protect HCWs from these risks and prevent the spread of disease. Continuous monitoring of physiological data with wearable sensors, self-monitoring of symptoms, and asymptomatic COVID-19 testing may aid in the early detection of COVID-19 in HCWs and may help reduce further transmission among HCWs, patients, and families. OBJECTIVE: By using wearable sensors, smartphone-based symptom logging, and biospecimens, this project aims to assist HCWs in self-monitoring COVID-19. METHODS: We conducted a prospective, longitudinal study of HCWs at a single institution. The study duration was 1 year, wherein participants were instructed on the continuous use of two wearable sensors (Fitbit Charge 3 smartwatch and TempTraq temperature patches) for up to 30 days. Participants consented to provide biospecimens (ie, nasal swabs, saliva swabs, and blood) for up to 1 year from study entry. Using a smartphone app called Roadmap 2.0, participants entered a daily mood score, submitted daily COVID-19 symptoms, and completed demographic and health-related quality of life surveys at study entry and 30 days later. Semistructured qualitative interviews were also conducted at the end of the 30-day period, following completion of daily mood and symptoms reporting as well as continuous wearable sensor use. RESULTS: A total of 226 HCWs were enrolled between April 28 and December 7, 2020. The last participant completed the 30-day study procedures on January 16, 2021. Data collection will continue through January 2023, and data analyses are ongoing. CONCLUSIONS: Using wearable sensors, smartphone-based symptom logging and survey completion, and biospecimen collections, this study will potentially provide data on the prevalence of COVID-19 infection among HCWs at a single institution. The study will also assess the feasibility of leveraging wearable sensors and self-monitoring of symptoms in an HCW population. TRIAL REGISTRATION: ClinicalTrials.gov NCT04756869; https://clinicaltrials.gov/ct2/show/NCT04756869. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29562.

Machine learning-based cytokine microarray digital immunoassay analysis.

Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short assay turnaround poses a formidable technological challenge. Here, the authors develop a rapid, accurate, and highly multiplexed microfluidic digital immunoassay by incorporating machine learning-based autonomous image analysis. The assay has achieved 12-plexed biomarker detection in sample volume <15 µL at concentrations < 5 pg/mL while only requiring a 5-min assay incubation, allowing for all processes from sampling to result to be completed within 40 min. The assay procedure applies both a spatial-spectral microfluidic encoding scheme and an image data analysis algorithm based on machine learning with a convolutional neural network (CNN) for pre-equilibrated single-molecule protein digital counting. This unique approach remarkably reduces errors facing the high-capacity multiplexing of digital immunoassay at low protein concentrations. Longitudinal data obtained for a panel of 12 serum cytokines in human patients receiving chimeric antigen receptor-T (CAR-T) cell therapy reveals the powerful biomarker profiling capability. The assay could also be deployed for near-real-time immune status monitoring of critically ill COVID-19 patients developing cytokine storm syndrome.

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.

A Pipeline for Faecal Host DNA Analysis by Absolute Quantification of LINE-1 and Mitochondrial Genomic Elements Using ddPCR.

Stool contains DNA shed from cells of the gastrointestinal (GI) tract and has great potential as a bio-specimen for non-invasive, nucleic acid-based detection of GI diseases. Whereas methods for studying faecal microbiome DNA are plentiful, there is a lack of well-characterised procedures for stabilisation, isolation, and quantitative analysis of faecal host DNA. We report an optimised pipeline for faecal host DNA analysis from the point-of-collection to droplet digital PCR (ddPCR) absolute quantification of host-specific gene targets. We evaluated multiple methods for preservation and isolation of host DNA from stool to identify the highest performing methods. To quantify host DNA even if present in partially degraded form, we developed sensitive, human-specific short-amplicon ddPCR assays targeting repetitive nuclear genomic elements (LINE-1) and mitochondrial genes. We validated the ability of these optimised methods to perform absolute quantification of host DNA in 200 stool DNA extracts from samples that were serially collected from three healthy individuals and three hospitalised patients. These specimens allowed assessment of host DNA day-to-day variability in stool specimens with widely varying physical characteristics (i.e., Bristol scores). We further extended this approach to mouse stool analysis, to enable faecal host DNA studies in animal disease models as well.

BaiHui: cross-species brain-specific network built with hundreds of hand-curated datasets.

MOTIVATION: Functional gene networks, representing how likely two genes work in the same biological process, are important models for studying gene interactions in complex tissues. However, a limitation of the current network-building scheme is the lack of leveraging evidence from multiple model organisms as well as the lack of expert curation and quality control of the input genomic data. RESULTS: Here, we present BaiHui, a brain-specific functional gene network built by probabilistically integrating expertly-hand-curated (by reading original publications) heterogeneous and multi-species genomic data in human, mouse and rat brains. To facilitate the use of this network, we deployed a web server through which users can query their genes of interest, visualize the network, gain functional insight from enrichment analysis and download network data. We also illustrated how this network could be used to generate testable hypotheses on disease gene prioritization of brain disorders. AVAILABILITY AND IMPLEMENTATION: BaiHui is freely available at: http://guanlab.ccmb.med.umich.edu/BaiHui/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Targeted exome analysis identifies the genetic basis of disease in over 50% of patients with a wide range of ataxia-related phenotypes.

PURPOSE: To examine the impact of a targeted exome approach for the molecular diagnosis of patients nationwide with a wide range of ataxia-related phenotypes. METHODS: One hundred and seventy patients with ataxia of unknown etiology referred from clinics throughout the United States and Canada were studied using a targeted exome approach. Patients ranged in age from 2 to 88 years. Analysis was focused on 441 curated genes associated with ataxia and ataxia-like conditions. RESULTS: Pathogenic and suspected diagnostic variants were identified in 88 of the 170 patients, providing a positive molecular diagnostic rate of 52%. Forty-six different genes were implicated, with the six most commonly mutated genes being SPG7, SYNE1, ADCK3, CACNA1A, ATP1A3, and SPTBN2, which accounted for >40% of the positive cases. In many cases a diagnosis was provided for conditions that were not suspected and resulted in the broadening of the clinical spectrum of several conditions. CONCLUSION: Exome sequencing with targeted analysis provides a high-yield approach for the genetic diagnosis of ataxia-related conditions. This is the largest targeted exome study performed to date in patients with ataxia and ataxia-like conditions and represents patients with a wide range of ataxia phenotypes typically encountered in neurology and genetics clinics.

Mutations in VPS13D lead to a new recessive ataxia with spasticity and mitochondrial defects.

OBJECTIVE: To identify novel causes of recessive ataxias, including spinocerebellar ataxia with saccadic intrusions, spastic ataxias, and spastic paraplegia. METHODS: In an international collaboration, we independently performed exome sequencing in 7 families with recessive ataxia and/or spastic paraplegia. To evaluate the role of VPS13D mutations, we evaluated a Drosophila knockout model and investigated mitochondrial function in patient-derived fibroblast cultures. RESULTS: Exome sequencing identified compound heterozygous mutations in VPS13D on chromosome 1p36 in all 7 families. This included a large family with 5 affected siblings with spinocerebellar ataxia with saccadic intrusions (SCASI), or spinocerebellar ataxia, recessive, type 4 (SCAR4). Linkage to chromosome 1p36 was found in this family with a logarithm of odds score of 3.1. The phenotypic spectrum in our 12 patients was broad. Although most presented with ataxia, additional or predominant spasticity was present in 5 patients. Disease onset ranged from infancy to 39 years, and symptoms were slowly progressive and included loss of independent ambulation in 5. All but 2 patients carried a loss-of-function (nonsense or splice site) mutation on one and a missense mutation on the other allele. Knockdown or removal of Vps13D in Drosophila neurons led to changes in mitochondrial morphology and impairment in mitochondrial distribution along axons. Patient fibroblasts showed altered morphology and functionality including reduced energy production. INTERPRETATION: Our study demonstrates that compound heterozygous mutations in VPS13D cause movement disorders along the ataxia-spasticity spectrum, making VPS13D the fourth VPS13 paralog involved in neurological disorders. Ann Neurol 2018.

Mutation in ATG5 reduces autophagy and leads to ataxia with developmental delay.

Autophagy is required for the homeostasis of cellular material and is proposed to be involved in many aspects of health. Defects in the autophagy pathway have been observed in neurodegenerative disorders; however, no genetically-inherited pathogenic mutations in any of the core autophagy-related (ATG) genes have been reported in human patients to date. We identified a homozygous missense mutation, changing a conserved amino acid, in ATG5 in two siblings with congenital ataxia, mental retardation, and developmental delay. The subjects' cells display a decrease in autophagy flux and defects in conjugation of ATG12 to ATG5. The homologous mutation in yeast demonstrates a 30-50% reduction of induced autophagy. Flies in which Atg5 is substituted with the mutant human ATG5 exhibit severe movement disorder, in contrast to flies expressing the wild-type human protein. Our results demonstrate the critical role of autophagy in preventing neurological diseases and maintaining neuronal health.