Computational pathology aids derivation of microRNA biomarker signals from Cytosponge samples.

BACKGROUND: Non-endoscopic cell collection devices combined with biomarkers can detect Barrett's intestinal metaplasia and early oesophageal cancer. However, assays performed on multi-cellular samples lose information about the cell source of the biomarker signal. This cross-sectional study examines whether a bespoke artificial intelligence-based computational pathology tool could ascertain the cellular origin of microRNA biomarkers, to inform interpretation of the disease pathology, and confirm biomarker validity. METHODS: The microRNA expression profiles of 110 targets were assessed with a custom multiplexed panel in a cohort of 117 individuals with reflux that took a Cytosponge test. A computational pathology tool quantified the amount of columnar epithelium present in pathology slides, and results were correlated with microRNA signals. An independent cohort of 139 Cytosponges, each from an individual patient, was used to validate the findings via qPCR. FINDINGS: Seventeen microRNAs are upregulated in BE compared to healthy squamous epithelia, of which 13 remain upregulated in dysplasia. A pathway enrichment analysis confirmed association to neoplastic and cell cycle regulation processes. Ten microRNAs positively correlated with columnar epithelium content, with miRNA-192-5p and -194-5p accurately detecting the presence of gastric cells (AUC 0.97 and 0.95). In contrast, miR-196a-5p is confirmed as a specific BE marker. INTERPRETATION: Computational pathology tools aid accurate cellular attribution of molecular signals. This innovative design with multiplex microRNA coupled with artificial intelligence has led to discovery of a quality control metric suitable for large scale application of the Cytosponge. Similar approaches could aid optimal interpretation of biomarkers for clinical use. FUNDING: Funded by the NIHR Cambridge Biomedical Research Centre, the Medical Research Council, the Rosetrees and Stoneygate Trusts, and CRUK core grants.

Methodological considerations for measuring biofluid-based microRNA biomarkers.

MicroRNAs (miRNAs) are small non-coding RNA that regulate the expression of messenger RNA and are implicated in almost all cellular processes. Importantly, miRNAs can be released extracellularly and are stable in these matrices where they may serve as indicators of organ or cell-specific toxicity, disease, and biological status. There has thus been great enthusiasm for developing miRNAs as biomarkers of adverse outcomes for scientific, regulatory, and clinical purposes. Despite advances in measurement capabilities for miRNAs, miRNAs are still not routinely employed as noninvasive biomarkers. This is in part due to the lack of standard approaches for sample preparation and miRNA measurement and uncertainty in their biological interpretation. Members of the microRNA Biomarkers Workgroup within the Health and Environmental Sciences Institute's (HESI) Committee on Emerging Systems Toxicology for the Assessment of Risk (eSTAR) are a consortium of private- and public-sector scientists dedicated to developing miRNAs as applied biomarkers. Here, we explore major impediments to routine acceptance and use of miRNA biomarkers and case examples of successes and deficiencies in development. Finally, we provide insight on miRNA measurement, collection, and analysis tools to provide solid footing for addressing knowledge gaps toward routine biomarker use.