Biology subjects

Sandford, E.

Publications and source records attributed to Sandford, E..

4 recordsLinked to original sources

bioRxiv2025

Chromato-kinetic fingerprinting enables multiomic digital counting of single disease biomarker molecules

Early and personalized intervention in complex diseases requires robust molecular diagnostics, yet the simultaneous detection of diverse biomarkers--microRNAs (miRNAs), mutant DNAs, and proteins--remains challenging due to low abundance and preprocessing incompatibilities. We present Biomarker Single-molecule Chromato-kinetic multi-Omics Profiling and Enumeration (Bio-SCOPE), a next-generation, triple-modality, multiplexed detection platform that integrates both chromatic and kinetic fingerprinting for molecular profiling through digital encoding. Bio-SCOPE achieves femtomolar sensitivity, single-base mismatch specificity, and minimal matrix interference, enabling precise, parallel quantification of up to six biomarkers in a single sample with single-molecule resolution. We demonstrate its versatility in accurately detecting low-abundance miRNA signatures from human tissues, identifying upregulated miRNAs in the plasma of prostate cancer patients, and measuring elevated interleukin-6 (IL-6) and hsa-miR-21 levels in cytokine release syndrome patients. By seamlessly integrating multiomic biomarker panels on a unified, high-precision platform, Bio-SCOPE provides a transformative tool for molecular diagnostics and precision medicine.

biophysics↗

bioRxiv2024

Study Design and Interim Analysis of the Cancer Lifetime Assessment Screening Study in Canines (CLASSiC): The First Prospective Cancer Screening Study in Dogs Using Next-Generation Sequencing-Based Liquid Biopsy

ObjectiveThe Cancer Lifetime Assessment Screening Study in Canines (CLASSiC) is a prospective, longitudinal cancer screening study, in which enrolled dogs are screened for cancer with physical exams and next-generation sequencing-based liquid biopsy testing on a serial basis. The goals of the first interim analysis, presented here, are to assess the benefits of using the OncoK9(R) liquid biopsy test as a cancer screening tool in a prospective clinical setting, and to demonstrate test performance for cancer detection, including preclinical detection. Subjects726 presumably cancer-free client-owned dogs were prospectively enrolled in the study across 24 clinical sites in the US and Canada. Most subjects were at high risk of cancer at the time of enrollment based on age and/or breed. 419 dogs that were enrolled for at least one year and had at least two cancer screening study visits, or that had received a definitive or presumptive diagnosis of cancer up to the time of the interim analysis, were included in the analysis. MethodsClinical data and a blood sample were collected at each study visit (once or twice per year and when cancer was clinically suspected). Cell-free DNA extracted from plasma was tested by OncoK9(R) using next-generation sequencing (NGS) technology. Results417 dogs were eligible for inclusion in the interim analysis and had classifiable outcomes, with a mean on-study duration of 422 days. Of these, 51 dogs were newly diagnosed with cancer (37 definitive, 14 presumptive), translating to a 12% (51/417) observed incidence over the study period; the liver, skin, bone, heart, spleen, lung, and lymph node(s) were the most common anatomic locations for disease. The prospectively observed sensitivity (detection rate) of the test was 56.9% (95% CI: 42.3-70.4%) with a specificity of 98.9% (95% CI: 97.0-99.6%). The prospectively observed positive predictive value was 87.9% (95% CI: 70.9-96.0%) and the negative predictive value was 94.3% (95% CI: 91.3-96.3%). NGS-based liquid biopsy doubled the overall number of cancer cases detected in this study population (from 25 to 51); remarkably, the detection rate for preclinical cancer was increased 4.6-fold from 12% (6/51) by routine care alone to 55% (28/51) by combining routine care with OncoK9(R) testing. Clinical RelevanceCLASSiC is the [fi]rst study to prospectively document the incidence of cancer in a predominantly high-risk canine population, and to prospectively demonstrate that the addition of NGS-based cancer screening to regularly scheduled wellness visits has the potential to substantially increase preclinical cancer detection in this population.

genomics↗

bioRxiv2020

Machine Learning-Based Protein Microarray Digital Assay 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, we developed a rapid, accurate, and highly multiplexed microfluidic digital immunoassay by incorporating machine learning-based autonomous image analysis. The assay achieved 14-plexed biomarker detection at concentrations < 10pg/mL with a sample volume < 10 L, including all processes from sampling to analyzed data delivery within 30 min, while only requiring a 5-min assay incubation. The assay procedure applied 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 reduced errors facing the high-capacity multiplexing of digital immunoassay at low protein concentrations. Longitudinal data obtained for a panel of 14 serum cytokines in human patients receiving chimeric antigen receptor-T (CAR-T) cell therapy manifested the powerful biomarker profiling capability and great potential of the assay for its translation to near-real-time bedside immune status monitoring.

bioengineering↗

bioRxiv2019

A Pipeline for Fecal 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.

molecular biology↗