One Biosciences, a company pioneering clinical-grade single-cell tumour profiling, has announced data establishing that single-cell RNA expression profiles can be generated from standard, formalin-fixed paraffin wax-embedded (FFPE) pathology specimens obtained in routine cancer care using its proprietary platform OneMap.
The study, conducted with collaborators at Centre Léon Bérard, Hôpital Bichat–Claude Bernard, Institut Curie, and Memorial Sloan Kettering Cancer Center, was released as a preprint on BiorXiv.
“Every tumour is a unique ecosystem of many different types of cell, some cancerous, some not. Single cell profiling enables us to understand what those cells are, what they’re doing and potentially how that may impact treatment outcomes,” said Helena Yu, MD, thoracic medical oncologist at Memorial Sloan Kettering Cancer Center. “Until now that type of analysis required different types of sample and workflows than we deploy in clinical care. This study shows we can do that analysis from the same samples we already collect, paving the way to more deeply explore how we can leverage this technology to guide treatment.”
The study included multiple institutions from multiple regions and varied sample and tumour types to reflect the diversity encountered in real-world clinical care. The data include findings from 88 single-nucleus experiments spanning bladder, breast, colon, lung, ovarian, and pancreatic cancers, including 36 core biopsies. The assay produced reproducible measurements of cellular composition and cell-type-resolved gene expression. Technical reproducibility was high (median correlation >0.92 in cell-type proportions across replicates), and automated estimates of immune infiltration closely matched pathologists' assessments of tumour-infiltrating lymphocytes. The workflow succeeded on archival blocks up to roughly a decade old and on ultra-low-input biopsies, and it quantified clinically relevant antibody-drug-conjugate targets.
The assay uses single-nucleus RNA sequencing to measure gene activity inside individual cells present in thin sections of tissue prepared for standard pathologic analyses. OneMap an AI-powered software engine, identifies which cells are present and measures what each type is doing. OneMap then produces a single standardised report for each sample, eliminating the batch processing that older single-cell methods required.
"Single-cell analysis is a valuable addition to current molecular profiling, revealing important information about a tumour that standard tests cannot. Previously, it required the wrong kind of samples, too much tissue and analysis that only worked in large batches, making it impractical for real-world patient care," said Vincent Miller, executive chairman of One Biosciences. "This study validates our approach, which runs on ordinary pathology slides every hospital already produces, needs only a fraction of the tissue, and returns a standardised report for one patient at a time, creating a true sample-to-report solution that can enable more targeted clinical trials and ultimately improve patient care."