Abstract
Unlike population-level approaches, single-cell RNA sequencing enables transcriptomic analysis of an individual cell. Through the combination of high-throughput sequencing and bioinformatic tools, single-cell RNA-seq can detect more than 10,000 transcripts in one cell to distinguish cell subsets and dynamic cellular changes. After several years’ development, single-cell RNA-seq can now achieve massively parallel, full-length mRNA sequencing as well as in situ sequencing and even has potential for multi-omic detection. One appealing area of single-cell RNA-seq is cancer research, and it is regarded as a promising way to enhance prognosis and provide more precise target therapy by identifying druggable subclones. Indeed, progresses have been made regarding solid tumor analysis to reveal intratumoral heterogeneity, correlations between signaling pathways, stemness, drug resistance, and tumor architecture shaping the microenvironment. Furthermore, through investigation into circulating tumor cells, many genes have been shown to promote a propensity toward stemness and the epithelial-mesenchymal transition, to enhance anchoring and adhesion, and to be involved in mechanisms of anoikis resistance and drug resistance. This review focuses on advances and progresses of single-cell RNA-seq with regard to the following aspects:1. Methodologies of single-cell RNA-seq2. Single-cell isolation techniques3. Single-cell RNA-seq in solid tumor research4. Single-cell RNA-seq in circulating tumor cell research5. Perspectives
Highlights
RNA sequencing (RNA-seq) has recently been developed as a powerful tool for investigating the intracellular transcriptome based on next-generation sequencing (NGS) [1]
The results showed that the WNT5A gene was highly related to chemotherapeutic resistance because when WNT5A was knocked down by shRNA, the tumor became drug sensitive; overall, the findings suggest that pathogenesis of castration-resistant prostate cancer (CRPC) is strongly related to the nonclassical WNT pathway [96]
After several years of development, singlecell RNA-seq has allowed for breakthroughs in both technologies and applications in oncology research
Summary
RNA sequencing (RNA-seq) has recently been developed as a powerful tool for investigating the intracellular transcriptome based on next-generation sequencing (NGS) [1]. CircRNA-seq, small RNA-seq, scMT-Seq, scTrio-Seq and G&T-Seq have all been reported in this research field This approach is widely adopted to define new cell and tissue types through unsorted single-cell RNAseq and unsupervised digital transcriptome clustering. Dramatic improvements are needed for multi-marker-based cell sorting to reduce false positive/negative and doublets in downstream sequencing [16, 59] This multi-channel, fluorescent antibody dyebased cell sorting approach has been broadly applied in many single-cell transcriptome studies [24, 60,61,62]. The first application of LCM-based single-cell RNA-seq was performed and named LCMSeq, showing a high gene detection rate, reproducibility and advantages in mouse and human neuron in situ heterogeneity analyses [47].
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