RNA sequencing: new technologies and applications in cancer research

Abstract

Over the past few decades, RNA sequencing has significantly progressed, becoming a paramount approach for transcriptome profiling. The revolution from bulk RNA sequencing to single-molecular, single-cell and spatial transcriptome approaches has enabled increasingly accurate, individual cell resolution incorporated with spatial information. Cancer, a major malignant and heterogeneous lethal disease, remains an enormous challenge in medical research and clinical treatment. As a vital tool, RNA sequencing has been utilized in many aspects of cancer research and therapy, including biomarker discovery and characterization of cancer heterogeneity and evolution, drug resistance, cancer immune microenvironment and immunotherapy, cancer neoantigens and so on. In this review, the latest studies on RNA sequencing technology and their applications in cancer are summarized, and future challenges and opportunities for RNA sequencing technology in cancer applications are discussed.

Keywords: Application; Cancer; RNA sequencing.

Fig. 1

The development timeline of RNA sequencing technologies

Fig. 2

RNA extraction and template preparation before RNA-sequencing. RNA was extracted from tissues, and after fragmentation, fragmented DNA molecules were converted into cDNA by reverse transcription then amplified by emulsion PCR or bridge PCR to prepare sequencing library

Fig. 3

Three kinds of sequencing methods. These methods contain sequencing by synthesis, sequencing by reversible terminator and sequencing by ligation. And their different mechanisms are shown in detail

Fig. 4

Bioinformatics tools commonly used in RNA-seq data analysis. These tools are primarily used in the four main processes of RNA-seq data analysis, including quality control, read alignment and transcript assembly, expression quantification and differential expression analysis

Fig. 5

Applications of RNA-seq in differential expression analysis and cancer biomarkers, cancer heterogeneity and drug resistance, cancer immune microenvironment, immunotherapy and neoantigen. a Differential expression analysis by RNA sequencing can identify potential biomarkers, including fusion transcript, lncRNA, miRNA and circRNA. b The heterogeneity and drug resistance of cancer cells identified by RNA-seq. c Novel molecular signature, regulatory protein and unknown subtypes in cancer infiltrating immune cells and potential resistance effector in immunotherapy can be identified by RNA-seq; d Neoantigen profiling by RNA-seq and TCR modification targeted neoantigens