Gene Expression Analysis in Cancer Cells Using RNA-Seq Technologies: A Comprehensive Review

Abstract

Cancer is a dynamic and heterogeneous disease arising from complex molecular alterations at multiple levels of regulation. To understand these changes, there is a need for high-resolution transcriptome methods that are able to capture global gene expression variations and their functional effects. RNA sequencing (RNA-Seq) is a game changing next generation sequencing technology for unbiased transcriptome profiling of cancer. This review describes the applications of RNA-Seq technology in cancer gene expression research and covers the basic principles of this methodology, the analysis process, and the biological and clinical implications. RNA-Seq yields information on differentially expressed genes, alternative splicing, gene fusion and non-coding RNA transcripts that promote tumor growth. Single-cell RNA sequencing has allowed for better characterization of tumor heterogeneity and microenvironment at the cellular level. Functional enrichment and pathway analyses provide a systems biology interpretation of transcriptome alterations, and identify deregulated signaling pathways and molecular networks associated with oncogenesis. RNA-Seq enables precision oncology through biomarker discovery, subtyping of cancers and therapy response prediction. Integration of RNA-Seq and multi-omics data has also contributed to better patient classification and molecular signature identification. However, the complexity of data, technological variability and the consistency of the analytical pipeline hinder its wide clinical deployment. RNA-Seq is a cornerstone of cancer research, providing deep insights into tumor biology and enabling personalized treatment. Advances in sequencing, computational and integrative multi-omics techniques are expected to bring about improved cancer diagnosis, prognosis and therapy.