A clinical road map for single-cell omics

Abstract

In a matter of years, single-cell omics has matured from a pioneering technique employed by just a handful of specialized laboratories to become a ubiquitous feature of biological research and a key driver of scientific discovery. The widespread adoption and development of single-cell omic assays has sparked mounting enthusiasm that these technologies are poised to also enhance the precision of diagnosis, the monitoring of disease progression, and the personalization of therapeutic strategies. Despite initial forays into clinical settings, however, single-cell technologies are not yet routinely used to inform medical or surgical decision-making. Here, we identify and categorize key experimental, computational, and conceptual barriers that currently hinder the clinical deployment of single-cell omics. We focus on the potential for single-cell transcriptomics to guide clinical decision-making through the development of combinatorial biomarkers that simultaneously quantify multiple cell-type-specific pathophysiological processes. We articulate a framework to identify patient subpopulations that stand to benefit from such biomarkers, and we outline the experimental and computational requirements to derive reproducible and actionable clinical readouts from single-cell omics.