Ultrasensitive amplification-free quantification of a methyl CpG-rich cancer biomarker by single-molecule kinetic fingerprinting.

The most well-studied epigenetic marker in humans is the 5-methyl modification of cytosine in DNA, which has great potential as a disease biomarker in liquid biopsies of cell-free DNA. Currently, quantification of DNA methylation relies heavily on bisulfite conversion followed by PCR amplification and NGS or microarray analysis. PCR is subject to potential bias in differential amplification of bisulfite-converted methylated versus unmethylated sequences. Here, we combine bisulfite conversion with single-molecule kinetic fingerprinting to develop an amplification-free assay for DNA methylation at the branched-chain amino acid transaminase 1 (BCAT1) promoter. Our assay selectively responds to methylated sequences with a limit of detection below 1 fM and a specificity of 99.9999%. Evaluating complex genomic DNA matrices, we reliably distinguish 2-5% DNA methylation at the BCAT1 promoter in whole blood DNA from completely unmethylated whole-genome amplified DNA. Taken together, these results demonstrate the feasibility and sensitivity of our amplification-free, single-molecule quantification approach to improve the early detection of methylated cancer DNA biomarkers.

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.

Feasibility of a dietary intervention to modify gut microbial metabolism in patients with hematopoietic stem cell transplantation.

Evaluation of the impact of dietary intervention on gastrointestinal microbiota and metabolites after allogeneic hematopoietic stem cell transplantation (HCT) is lacking. We conducted a feasibility study as the first of a two-phase trial. Ten adults received resistant potato starch (RPS) daily from day -7 to day 100. The primary objective was to test the feasibility of RPS and its effect on intestinal microbiome and metabolites, including the short-chain fatty acid butyrate. Feasibility met the preset goal of 60% or more, adhering to 70% or more doses; fecal butyrate levels were significantly higher when participants were on RPS than when they were not (P < 0.0001). An exploratory objective was to evaluate plasma metabolites. We observed longitudinal changes in plasma metabolites compared to baseline, which were independent of RPS (P < 0.0001). However, in recipients of RPS, the dominant plasma metabolites were more stable compared to historical controls with significant difference at engraftment (P < 0.05). These results indicate that RPS in recipients of allogeneic HCT is feasible; in this study, it was associated with significant alterations in intestinal and plasma metabolites. A phase 2 trial examining the effect of RPS on graft-versus-host disease in recipients of allogeneic HCT is underway. ClinicalTrials.gov registration: NCT02763033 .

Efficient assessment of real-world dynamics of circadian rhythms in heart rate and body temperature from wearable data.

Laboratory studies have made unprecedented progress in understanding circadian physiology. Quantifying circadian rhythms outside of laboratory settings is necessary to translate these findings into real-world clinical practice. Wearables have been considered promising way to measure these rhythms. However, their limited validation remains an open problem. One major barrier to implementing large-scale validation studies is the lack of reliable and efficient methods for circadian assessment from wearable data. Here, we propose an approximation-based least-squares method to extract underlying circadian rhythms from wearable measurements. Its computational cost is ∼ 300-fold lower than that of previous work, enabling its implementation in smartphones with low computing power. We test it on two large-scale real-world wearable datasets: [Formula: see text] of body temperature data from cancer patients and ∼ 184 000 days of heart rate and activity data collected from the 'Social Rhythms' mobile application. This shows successful extraction of real-world dynamics of circadian rhythms. We also identify a reasonable harmonic model to analyse wearable data. Lastly, we show our method has broad applicability in circadian studies by embedding it into a Kalman filter that infers the state space of the molecular clocks in tissues. Our approach facilitates the translation of scientific advances in circadian fields into actual improvements in health.

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.

A pilot intervention of using a mobile health app (ONC Roadmap) to enhance health-related quality of life in family caregivers of pediatric patients with cancer.

Background: The Roadmap mobile health (mHealth) app was developed to provide health-related quality of life (HRQOL) support for family caregivers of patients with cancer. Methods: Eligibility included: family caregivers (age ≥18 years) who self-reported as the primary caregiver of their pediatric patient with cancer; patients (age ≥5 years) who were receiving cancer care at the University of Michigan. Feasibility was calculated as the percentage of caregivers who logged into ONC Roadmap and engaged with it at least twice weekly for at least 50% of the 120-day study duration. Feasibility and acceptability was also assessed through a Feasibility and Acceptability questionnaire and the Mobile App Rating Scale to specifically assess app-quality. Exploratory analyses were also conducted to assess HRQOL self- or parent proxy assessments and physiological data capture. Results: Between September 2020-September 2021, 100 participants (or 50 caregiver-patient dyads) consented and enrolled in the ONC Roadmap study for 120-days. Feasibility of the study was met, wherein the majority of caregivers (N=32; 65%) logged into ONC Roadmap and engaged with it at least twice weekly for at least 50% of the study duration (defined a priori in the Protocol). The Feasibility and Acceptability questionnaire responses indicated that the study was feasible and acceptable with the majority (>50%) reporting Agree or Strongly Agree with positive Net Favorability [(Agree + Strongly Agree) - (Disagree + Totally Disagree)] in each of the domains (e.g., Fitbit use, ONC Roadmap use, completing longitudinal assessments, engaging in similar future study, study expectations). Improvements were seen across the majority of the mental HRQOL domains across all groups; even though underpowered, there were significant improvements in caregiver-specific aspects of HRQOL and anxiety and in depression and fatigue for children (ages 8-17 years), and a trend toward improvement in depression for children ages 8-17 years and in fatigue for adult patients. Conclusions: This study supports that mHealth technology may be a promising platform to provide HRQOL support for caregivers of pediatric patients with cancer. Importantly, the findings suggest that the study protocol was feasible, and participants were favorable to participate in future studies of this intervention alongside routine cancer care delivery.

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.

Trans-Renal Cell-Free Tumor DNA for Urine-Based Liquid Biopsy of Cancer.

Cancer biomarkers are a promising tool for cancer detection, personalization of therapy, and monitoring of treatment response or recurrence. "Liquid biopsy" commonly refers to minimally invasive or non-invasive sampling of a bodily fluid (i.e., blood, urine, saliva) for detection of cancer biomarkers such as circulating tumor cells or cell-free tumor DNA (ctDNA). These methods offer a means to collect frequent tumor assessments without needing surgical biopsies. Despite much progress with blood-based liquid biopsy approaches, there are limitations-including the limited amount of blood that can be drawn from a person and challenges with collecting blood samples at frequent intervals to capture ctDNA biomarker kinetics. These limitations are important because ctDNA is present at extremely low levels in plasma and there is evidence that measuring ctDNA biomarker kinetics over time can be useful for clinical prediction. Additionally, blood-based assays require access to trained phlebotomists and often a trip to a healthcare facility. In contrast, urine is a body fluid that can be self-collected from a patient's home, at frequent intervals, and mailed to a laboratory for analysis. Multiple reports indicate that fragments of ctDNA pass from the bloodstream through the kidney's glomerular filtration system into the urine, where they are known as trans-renal ctDNA (TR-ctDNA). Accumulating studies indicate that the limitations of blood based ctDNA approaches for cancer can be overcome by measuring TR-ctDNA. Here, we review current knowledge about TR-ctDNA in urine as a cancer biomarker approach, and discuss its clinical potential and open questions in this research field.

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.

Consumer-grade wearables identify changes in multiple physiological systems during COVID-19 disease progression.

Consumer-grade wearables are needed to track disease, especially in the ongoing pandemic, as they can monitor patients in real time. We show that decomposing heart rate from low-cost wearable technologies into signals from different systems can give a multidimensional description of physiological changes due to COVID-19 infection. We find that the separate physiological features of basal heart rate, heart rate response to physical activity, circadian variation in heart rate, and autocorrelation of heart rate are significantly altered and can classify symptomatic versus healthy periods. Increased heart rate and autocorrelation begin at symptom onset, while the heart rate response to activity increases soon after symptom onset and increases more in individuals exhibiting cough. Symptom onset is associated with a blunting of circadian variation in heart rate, as measured by the uncertainty in the phase estimate. This work establishes an innovative data analytic approach to monitor disease progression remotely using consumer-grade wearables.

Risk Factors for COVID-19 in College Students Identified by Physical, Mental, and Social Health Reported During the Fall 2020 Semester: Observational Study Using the Roadmap App and Fitbit Wearable Sensors.

BACKGROUND: The COVID-19 pandemic triggered a seismic shift in education to web-based learning. With nearly 20 million students enrolled in colleges across the United States, the long-simmering mental health crisis in college students was likely further exacerbated by the pandemic. OBJECTIVE: This study leveraged mobile health (mHealth) technology and sought to (1) characterize self-reported outcomes of physical, mental, and social health by COVID-19 status; (2) assess physical activity through consumer-grade wearable sensors (Fitbit); and (3) identify risk factors associated with COVID-19 positivity in a population of college students prior to release of the vaccine. METHODS: After completing a baseline assessment (ie, at Time 0 [T0]) of demographics, mental, and social health constructs through the Roadmap 2.0 app, participants were instructed to use the app freely, wear the Fitbit, and complete subsequent assessments at T1, T2, and T3, followed by a COVID-19 assessment of history and timing of COVID-19 testing and diagnosis (T4: ~14 days after T3). Continuous measures were described using mean (SD) values, while categorical measures were summarized as n (%) values. Formal comparisons were made on the basis of COVID-19 status. The multivariate model was determined by entering all statistically significant variables (P<.05) in univariable associations at once and then removing one variable at a time through backward selection until the optimal model was obtained. RESULTS: During the fall 2020 semester, 1997 participants consented, enrolled, and met criteria for data analyses. There was a high prevalence of anxiety, as assessed by the State Trait Anxiety Index, with moderate and severe levels in 465 (24%) and 970 (49%) students, respectively. Approximately one-third of students reported having a mental health disorder (n=656, 33%). The average daily steps recorded in this student population was approximately 6500 (mean 6474, SD 3371). Neither reported mental health nor step count were significant based on COVID-19 status (P=.52). Our analyses revealed significant associations of COVID-19 positivity with the use of marijuana and alcohol (P=.02 and P=.046, respectively) and with lower belief in public health measures (P=.003). In addition, graduate students were less likely and those with ≥20 roommates were more likely to report a COVID-19 diagnosis (P=.009). CONCLUSIONS: Mental health problems were common in this student population. Several factors, including substance use, were associated with the risk of COVID-19. These data highlight important areas for further attention, such as prioritizing innovative strategies that address health and well-being, considering the potential long-term effects of COVID-19 on college students. TRIAL REGISTRATION: ClinicalTrials.gov NCT04766788; https://clinicaltrials.gov/ct2/show/NCT04766788. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/29561.

Early HPV ctDNA Kinetics and Imaging Biomarkers Predict Therapeutic Response in p16+ Oropharyngeal Squamous Cell Carcinoma.

PURPOSE: In locally advanced p16+ oropharyngeal squamous cell carcinoma (OPSCC), (i) to investigate kinetics of human papillomavirus (HPV) circulating tumor DNA (ctDNA) and association with tumor progression after chemoradiation, and (ii) to compare the predictive value of ctDNA to imaging biomarkers of MRI and FDG-PET. EXPERIMENTAL DESIGN: Serial blood samples were collected from patients with AJCC8 stage III OPSCC (n = 34) enrolled on a randomized trial: pretreatment; during chemoradiation at weeks 2, 4, and 7; and posttreatment. All patients also had dynamic-contrast-enhanced and diffusion-weighted MRI, as well as FDG-PET scans pre-chemoradiation and week 2 during chemoradiation. ctDNA values were analyzed for prediction of freedom from progression (FFP), and correlations with aggressive tumor subvolumes with low blood volume (TVLBV) and low apparent diffusion coefficient (TVLADC), and metabolic tumor volume (MTV) using Cox proportional hazards model and Spearman rank correlation. RESULTS: Low pretreatment ctDNA and an early increase in ctDNA at week 2 compared with baseline were significantly associated with superior FFP (P < 0.02 and P < 0.05, respectively). At week 4 or 7, neither ctDNA counts nor clearance were significantly predictive of progression (P = 0.8). Pretreatment ctDNA values were significantly correlated with nodal TVLBV, TVLADC, and MTV pre-chemoradiation (P < 0.03), while the ctDNA values at week 2 were correlated with these imaging metrics in primary tumor. Multivariate analysis showed that ctDNA and the imaging metrics performed comparably to predict FFP. CONCLUSIONS: Early ctDNA kinetics during definitive chemoradiation may predict therapy response in stage III OPSCC.

Highly sensitive and quantitative biodetection with lipid-polymer hybrid nanoparticles having organic room-temperature phosphorescence.

A versatile organic room-temperature phosphorescence (RTP)-based "turn on" biosensor platform has been devised with high sensitivity by combining oxygen-sensitive lipid-polymer hybrid RTP nanoparticles with a signal-amplifying enzymatic oxygen scavenging reaction in aqueous solutions. When integrated with a sandwich-DNA hybridization assay on 96-well plates, our phosphorimetric sensor demonstrates sequence-specific detection of a cell-free cancer biomarker, a TP53 gene fragment, with a sub-picomolar (0.5 p.m.) detection limit. This assay is compatible with detecting cell-free nucleic acids in human urine samples. Simply by re-programming the detection probe, our unique methodology can be adapted to a broad range of biosensor applications for biomarkers of great clinical importance but difficult to detect due to their low abundance in vivo.

One-Step Multiplexed Droplet Digital Polymerase Chain Reaction for Quantification of p190 BCR-ABL1 Fusion Transcript in B-Lymphoblastic Leukemia.

CONTEXT.­: Quantification and detection of the t(9;22) (BCR-ABL1) translocation in chronic myelogenous leukemia and B-lymphoblastic leukemia are important for directing treatment protocols and monitoring disease relapse. However, quantification using traditional reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is dependent on a calibration curve and is prone to laboratory-to-laboratory variation. Droplet digital polymerase chain reaction (ddPCR) is a novel method that allows for highly sensitive absolute quantification of transcript copy number. As such, ddPCR is a good candidate for disease monitoring, an assay requiring reproducible measurements with high specificity and sensitivity. OBJECTIVE.­: To compare results of ddPCR and RT-qPCR BCR-ABL1 fusion transcript measurements of patient samples and determine if either method is superior. DESIGN.­: We optimized and standardized a 1-step multiplexed ddPCR assay to detect BCR-ABL1 p190 and ABL1 e10 transcripts. The ddPCR optimization included varying cycle number and primer concentration with standardization of droplet generation and droplet number and analyses to improve data sensitivity. Following optimization, ddPCR measurements were performed on clinical samples and compared with traditional RT-qPCR results. RESULTS.­: Droplet digital polymerase chain reaction was able to detect the BCR-ABL1 p190 transcript to 0.001% (1:10-5) with a calculated limit of detection and limit of quantitation of 4.1 and 5.3 transcripts, respectively. When tested on patient samples, ddPCR was able to identify 20% more positives than a laboratory-developed 2-step RT-qPCR assay. CONCLUSIONS.­: Droplet digital polymerase chain reaction demonstrated increased detection of BCR-ABL1 compared with RT-qPCR. Improved detection of BCR-ABL1 p190 and the potential for improved standardization across multiple laboratories makes ddPCR a suitable method for disease monitoring in patients with acute B-lymphoblastic leukemia.

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.

Rapid kinetic fingerprinting of single nucleic acid molecules by a FRET-based dynamic nanosensor.

Biofluid-derived cell-free nucleic acids such as microRNAs (miRNAs) and circulating tumor-derived DNAs (ctDNAs) have emerged as promising disease biomarkers. Conventional detection of these biomarkers by digital PCR and next generation sequencing, although highly sensitive, requires time-consuming extraction and amplification steps that also increase the risk of sample loss and cross-contamination. To achieve the direct, rapid, and amplification-free detection of miRNAs and ctDNAs with near-perfect specificity and single-molecule level sensitivity, we herein designed a single-molecule kinetic fingerprinting assay, termed intramolecular single-molecule recognition through equilibrium Poisson sampling (iSiMREPS). iSiMREPS exploits a dynamic DNA nanosensor comprising a surface anchor and a pair of fluorescent detection probes: one probe captures a target molecule onto the surface, while the other transiently interrogates the target to generate kinetic fingerprints by intramolecular single-molecule Förster resonance energy transfer (smFRET) that are recorded by single-molecule fluorescence microscopy and identify the target after kinetic filtering and data analysis. We optimize the sensor design, use formamide to further accelerate the fingerprinting kinetics, and maximize sensitivity by removing non-target-bound probes using toehold-mediated strand displacement to reduce background. We show that iSiMREPS can detect, in as little as 10 s, two distinct, promising cancer biomarkers-miR-141 and a common EGFR exon 19 deletion-reaching a limit of detection (LOD) of ~3 fM and a mutant allele fraction among excess wild-type as low as 1 in 1 million, or 0.0001%. We anticipate that iSiMREPS will find utility in research and clinical diagnostics based on its features of rapid detection, high specificity, sensitivity, and generalizability.