Application of RNA-Seq Technology in Cancer Research

Over the past few decades, RNA sequencing has significantly progressed, becoming a paramount approach for transcriptome profiling. 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.

Computational Analysis of RNA Sequencing Data

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. 1 RNA sequencing data analysis process.

Applications of RNA-sequencing in Cancer Research

As an important part of next-generation sequencing, RNA sequencing has made great contributions in various fields, especially cancer research, including studies on differential gene expression analysis and cancer biomarkers, cancer heterogeneity and evolution, cancer drug resistance, the cancer microenvironment and immunotherapy, neoantigens, etc.

Fig. 2 Applications of RNA-seq in differential expression analysis and cancer biomarkers, cancer heterogeneity and drug resistance, cancer immune microenvironment, immunotherapy and neoantigen.

Differential gene expression analysis and cancer biomarkers

Samples from different backgrounds (different species, tissues and periods) can be used for RNA sequencing to identify differentially expressed genes, revealing their function and potential molecular mechanisms. More importantly, differential gene expression analysis facilitates the discovery of potential cancer biomarkers. RNA-seq could detect early mutations as well as high molecular risk mutations, thus can discover novel cancer biomarkers and potential therapeutic targets, monitoring of diseases and guiding targeted therapy during early treatment decisions.

Cancer heterogeneity and evolution

The continuous accumulation of heterogeneity may reflect the evolution of cancer. Early RNA sequencing detected all RNA transcripts in a given tissue or cell group, ignoring differences in individual cells. Transcriptome profiling of single-cell RNA sequencing solves this problem by providing single-cell resolution of the transcriptome. A recent single-cell RNA-seq study of 49 samples of metastatic lung cancer revealed changes in plasticity induced by non-small cell lung cancer treatment, providing new directions for clinical treatment.

Cancer drug resistance

RNA sequencing became a vital tool for revealing the mechanisms of cancer drug resistance. In breast cancer, single-cell RNA sequencing identified a tumor-infiltrating immunosuppressive immature myeloid cell that leads to drug resistance. Another study identified a new COX7B gene related to platinum resistance and a surrogate marker CD63 in cancer cells by single-cell RNA-seq.

The cancer microenvironment and immunotherapy

Transcriptomic profiling by RNA-seq, in particular scRNA-seq, provides comprehensive information on cellular activity and interactions among cells in the tumor microenvironment (TME). ScRNA-seq enables genomic and molecular profiling of high quantity and quality individual immune cells and assessment of cellular heterogeneity to depict the immune system spectrum in the cancer microenvironment.

Cancer neoantigens

An RNA-seq-based transcriptomic approach is an efficient tool for neoantigen profiling in many studies. A neoantigen prediction program, Neopepsee, based on RNA-seq data and somatic mutation, can be utilized to detect potential neoantigens for personal vaccine development with reduced false-positive rate compared to binding affinity prediction. Several neoantigens have been identified to be related to cancer prognosis and might be potential targets of immunotherapies, such as the TP53 neoantigen for HCC patients.

Perspectives

RNA-seq has been applied in an impressively wide range of cancer research. All applications in cancer research rely on the boost of advanced RNA-seq technologies, especially the combination of scRNA-seq and spatial transcriptomics as well as data from multi-omics, which will bring RNA-seq technologies into single-cell resolution and tissue-level transcriptomics, providing new insight into cancer diagnosis, treatment and prevention.

References:

Hong, M.; et al. RNA sequencing: new technologies and applications in cancer research. Journal of hematology & oncology. 2020, 13(1): 1-16.
Saeidian, A. H.; et al. Research techniques made simple: whole-transcriptome sequencing by RNA-Seq for diagnosis of monogenic disorders. Journal of Investigative Dermatology. 2020, 140(6): 1117-1126. e1.

* For research use only. Not intended for any clinical use.

Quick Inquiry

Application of RNA-Seq Technology in Cancer Research

Computational Analysis of RNA Sequencing Data

Applications of RNA-sequencing in Cancer Research

Perspectives

Related Products and Services at Creative Biogene