Urothelial cell carcinoma (UCC) is the ninth most common cancer that accounts for 4.7\% of all the new cancer cases globally. UCC development and progression are due to complex and stochastic genetic programmes. To study the cascades  molecular events underlying the poor prognosis that are due to limited treatment options for advance disease and resistance to conventional therapies in UCC, transcriptomics technology (RNA-Seq), a method of analysing the RNA content of a sample using the modern high-throughput sequencing platforms has been employed to address these limitations . Here we review the principles of RNA-Seq technology and summarize the recent studies on human bladder cancer that employed this technique to unravel the pathogenesis of the disease, identify biomarkers, discover pathways and classify the disease state. We list the commonly used computational platforms and software that are publicly available for RNA-Seq analysis. Moreover, we discussed the future perspective for RNA-Seq studies on bladder cancer and recommend the application of new technology called single cell sequencing (scRNA-Seq) to further understand bladder cancer . Keywords: Transcriptome profiling, RNA-sequencing, genomics, bioinformatics, bladder cancer
Urothelial cell carcinoma (UCC) is the ninth most common cancer that accounts for 4.7\% of all the new cancer cases globally. UCC development and progression are due to complex and stochastic genetic programmes. To study the cascades of molecular events underlying the poor prognosis that may lead to limited treatment options for advanced disease and resistance to conventional therapies in UCC, transcriptomics technology (RNA-Seq), a method of analysing the RNA content of a sample using modern high-throughput sequencing platforms has been employed . Here we review the principles of RNA-Seq technology and summarize recent studies on human bladder cancer that employed this technique to unravel the pathogenesis of the disease, identify biomarkers, discover pathways and classify the disease state. We list the commonly used computational platforms and software that are publicly available for RNA-Seq analysis. Moreover, we discussed the future perspectives for RNA-Seq studies on bladder cancer and recommend the application of new technology called single cell sequencing (scRNA-Seq) to further understand the disease . Keywords: Transcriptome profiling, RNA-sequencing, genomics, bioinformatics, bladder cancer
A
of
R
are due
may lead
R
advance
advanced
D
the
D
to address these limitations
D
the
R
perspective
perspectives
R
bladder cancer
the disease