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.

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.

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.