Utilization and prospects of single-cell RNA sequencing—Aiming to elucidate heterogeneity of cancer cells—

Abstract

Although the heterogeneity of tissues in cancer has been classically reported since the 1970s, the developments in various techniques, including next-generation sequencing, have revealed the heterogeneity of tissues and cell populations in more detail. Single-cell RNA sequencing, a method of analyzing gene expression at the single-cell level, is a powerful tool to accurately capture heterogeneity. The main methods of single-cell RNA sequencing analysis are dimensionality reduction and differentiation trajectory analysis including pseudotime analysis. The dimensionality reduction method allows us to classify different clones of cancer and accurately capture not only the differences between clones at the initial onset and at recurrence but also the changes in immune cells during different treatment phases. This is also important for elucidating the characteristics of cancer stem cells. Identification of clonal populations that directly affect the outcome of patients has also been reported. Differentiation trajectory analysis can also provide insight into the clonal origin of each heterogeneous cell population. In the future, the integration of single-cell RNA sequencing and recently developed methods for analyzing chromatin dynamics in single cells has the potential to accurately elucidate the pathogenesis of cancers with heterogeneity of tissues and cell populations and realize tailor-made therapies for patients.