Abstract

Even within a single type of cancer, cells of various types exist and play interrelated roles. Each of the individual cells resides in a distinct microenvironment and behaves differently. Such heterogeneity is the most cumbersome nature of cancers, which is occasionally uncountable when effective prevention or total elimination of cancers is attempted. To understand the heterogeneous nature of each cell, the use of conventional methods for the analysis of “bulk” cells is insufficient. Although some methods are high-throughput and compressive regarding the genes being detected, the obtained data would be from the cell mass, and the average of a large number of the component cells would no longer be measured. Single-cell analysis, which has developed rapidly in recent years, is causing a drastic change. Genome, transcriptome, and epigenome analyses at single-cell resolution currently target cancer cells, cancer-associated fibroblasts, endothelial cells of vessels, and circulating and infiltrating immune cells. In fact, surprisingly diverse features of clonal evolution of cancer cells, during the development of cancer or acquisition of drug resistance, accompanied by corresponding gene expression changes in the circumstantial stromal cells, appeared in recent single-cell analyses. Based on the obtained novel insights, better optimal drug selection and new drug administration sequences were started. Even a remaining concern of the single cell analyses is being addressed. Until very recently, it was impossible to obtain positional information of cells in cancer via single-cell analysis because such information is lost during preparation of single-cell suspensions. A new method, collectively called spatial transcriptome (ST) analysis, has been developed and rapidly applied to various clinical specimens. In this review, we first outline the recent achievements of single-cell cancer analysis in analyzing the molecular basis underlying the acquisition of drug resistance, particularly focusing on the latest anti-epidermal growth factor receptor tyrosine kinase inhibitor, osimertinib. Further, we review the currently available ST analysis methods and introduce our recent attempts regarding the respective topics.

Highlights

  • Single-cell sequencing for intratumor heterogeneity of cancer cells Single-cell analysis for understanding intratumor heterogeneity and clonal evolution of cancer cells During cancer progression, tumor cells proliferate with an accumulation of genomic mutations

  • By irradiating the laser beam to any targeted cell, the transcriptome in vivo analysis (TIVA)-tag is activated inside the cell and hybridizes with the cellular mRNA

  • Thereafter, the TIVA-tag-mRNA hybrid was purified from the selected cells with streptavidin, and the captured mRNA was analyzed by RNA-seq

Read more

Summary

Background

A detailed understanding of cellular diversity and constituting ecosystems of cancers is expected to serve as a foundation for cancer eradication and control. The selection of the optimal drug and drug administration procedure is not always based on molecular evidence, considering the possible emergence of drugresistant cells To this end, conventional omics analysis approaches such as RNA-seq, chromatin immunoprecipitation sequencing (ChIP-seq), and whole-genome/exome sequencing (WGS/WES) have limited power, they may be comprehensive regarding the covered genes and genome. Conventional omics analysis approaches such as RNA-seq, chromatin immunoprecipitation sequencing (ChIP-seq), and whole-genome/exome sequencing (WGS/WES) have limited power, they may be comprehensive regarding the covered genes and genome These methods usually use the “bulk” for the material. They measure the average value of a large number of component cells; they cannot detect the behavior of minor cells or the presence of heterogeneous cellular populations therein. Perspectives on the integration of these two approaches are discussed

Main text
Method name
Conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call