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.

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Background: Cervical Cancer (CC) is the fourth most common cancer in women worldwide. Potential biomarkers in cancer can be identified by considering the changes in tumoral glycolysis. In this work, we investigated whether the expression of some glycolytic enzymes is associated with the overall and disease-free survival of patients with CC. Methods: We analyzed the expression of 14 genes related with glycolysis (SLC2A1, ADPGK, ALDOA, EDARADD, ENO1, GAPDH, GPI, HK2, LDHA, PFKP, PGK1, PKM, TPI1P1, SLC9A1) in 67 CC, 10 high-grade cervical intraepithelial neoplasia (HG-CIN) and 17 healthy cervical epitheliums (HCE), as controls, with the Human Gene 1.0 ST Microarray (HG 1.0 ST). Validation of gene expression of LDHA and PFKP was performed by qRT-PCR and immunohistochemistry. The expression of LDHA and PFKP was correlated with 5-year survival of CC patients by the Kaplan-Meier method, and FIGO staging and the gene expression were included as covariates in a Cox proportional hazard model. Results: The amount of the mRNA transcribed from the 14 glycolytic genes was higher in CC tumors than in HG-CIN and HCE. Overexpression of genes TPI1P1, LDHA, PFKP, GAPDH, GPI, PGK1 was associated with poor survival, but only the overexpression of LDHA and PFKP genes was independent of the FIGO stage. The qRT-PCR assays confirmed that the overexpression of LDHA and PFKP were associated with poor overall survival (LDHA p= 0.004, PFKP p ¼ 0.0043, Long-rang test) and diseasefree survival (LDHA p ¼ 0.001, PFKP p = 0.013, Long-rang test) in an independent fashion of the FIGO stage (LDHA p ¼ 0.050, PFKP p ¼ 0.029, Cox proportionalhazards regression). Interestingly, only the protein encoded by LDHA gene, analyzed by immunohistochemistry, showed a significant higher expression in recurrent than in non-recurrent tumors. Conclusions: Our results indicate that the expression of LDHA and PFKP at the mRNA and protein levels may be good biomarkers for overall and disease-free survival, independent of FIGO clinical stage, and could be potential therapeutic target for CC. Legal entity responsible for the study: Conacyt, Mexico. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest.

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