Clinical application of single-cell RNA sequencing in disease and therapy

The emergence of single-cell RNA sequencing (scRNA-seq) technology has revolutionized our capacity to study cell functions in complex tissue microenvironments. Traditional transcriptomic approaches, such as microarrays and bulk RNA sequencing, lacked the resolution to distinguish signals from heterogeneous cell populations or rare cell types, limiting their clinical utility. Since 2009, scRNA-seq has evolved as a new and powerful tool for revisiting somatic evolution and functions under physiological or pathological conditions.

This review focus on elaborating on the clinical applications of scRNA-seq technology, with a particular emphasis on the application of scRNA-seq methods in revisiting the somatic cell evolution in human diseases. We further provide a snapshot of the scRNA-seq applications in biomarker discovery and drug development, current challenges associated with the technology, and future directions.

With the recent progresses in single cell and spatial transcriptome technologies, scRNA-seq enables a deeper understanding of the complexity of human diseases. The integration of AI and machine learning algorithms into big data analysis offers hope for overcoming these hurdles, potentially allowing scRNA-seq and multi-omics approaches to bridge the gap in our understanding of complex biological systems and advances the development of precision medicine.

This review provides a systematic overview of the application of scRNA-seq technology in understanding of disease mechanisms. We cover applications in respiratory diseases, metabolic disorders, cardiovascular diseases, cancers, autoimmune and auto-inflammatory diseases, neurodegenerative diseases, and infectious diseases. This review also explores promises and challenges for the emerging application of scRNA-seq in drug discovery.