Single-Cell RNA Sequencing with Spatial Transcriptomics of Cancer Tissues

Abstract

Single-cell RNA sequencing (RNA-seq) techniques can perform analysis of transcriptome at the single-cell level and possess an unprecedented potential for exploring signatures involved in tumor development and progression. These techniques can perform sequence analysis of transcripts with a better resolution that could increase understanding of the cellular diversity found in the tumor microenvironment and how the cells interact with each other in complex heterogeneous cancerous tissues. Identifying the changes occurring in the genome and transcriptome in the spatial context is considered to increase knowledge of molecular factors fueling cancers. It may help develop better monitoring strategies and innovative approaches for cancer treatment. Recently, there has been a growing trend in the integration of RNA-seq techniques with contemporary omics technologies to study the tumor microenvironment. There has been a realization that this area of research has a huge scope of application in translational research. This review article presents an overview of various types of single-cell RNA-seq techniques used currently for analysis of cancer tissues, their pros and cons in bulk profiling of transcriptome, and recent advances in the techniques in exploring heterogeneity of various types of cancer tissues. Furthermore, we have highlighted the integration of single-cell RNA-seq techniques with other omics technologies for analysis of transcriptome in their spatial context, which is considered to revolutionize the understanding of tumor microenvironment.

Keywords: intratumor heterogeneity; single-cell RNA sequencing techniques; spatial transcriptomics.

Figure 1

Presents a timeline of the discovery of RNA sequencing techniques and their improvements in efficiency and sensitivity with innovations in techniques [9].

Figure 2

A schematic of various steps used for the analysis of biopsy tissue samples by RNA-seq techniques such as isolation and sequencing of single cells, preparation of RNA library, and single-cell level transcriptome analysis.

Figure 3

Shows different types of RNA-seq techniques used for the analysis of RNA from cancer tissues. (A) depicts cell expression by linear amplification and sequencing method; (B) displays single-cell RNA barcoding and sequencing (SCRB-seq) approach; (C) displays steps involved in switching mechanism at the end of the 5′-end of the RNA transcript sequencing (Smart-seq2), (D) represents various steps used for the analysis of transcripts by Drop-sequencing (Drop-seq), and (E) shows various steps involved in the Massively Parallel RNA Single-Cell Sequencing Framework (MARS-seq).

Figure 4

Single-cell RNA-seq (scRNA-seq) helps in dealing with solid and circulating tumor tissues in cancer research. The figure shows an analysis of tissue samples taken from cancer patients by mounting them on glass slides and then tissue permeabilization on glass slides. RNA is amplified using UMIs and imaged without losing the spatial localization of RNA analytes. In the above figure, the second route shows the isolation of cells from tissue samples up to single-cell level, then cell sorting by microfluid device, and then clustering of cells according to RNA sequences performed with NGS.