Pluto Bioinformatics

GSE115307: Race-specific transcriptome and Long non-coding RNA of ADT-resistant African-American prostate cancer cell models.

Bulk RNA sequencing

Purpose: The goals of this study are to compare NGS-derived Androgen Deprivation Therapy (ADT) resistant transcriptome to profiling (RNA-seq) to Androgen Deprivation Therapy (ADT) sensitive transcriptome in African American prostate cancer cells and validate by reverse transcription polymerase chain reaction (qRTPCR) methods.; Method: Total RNA was extracted from different CaP cell who were ADT sensitive and ADT resistance. Total RNA was subjected to whole transcriptome sequencing analysis. Sequence reads; Results: We performed whole transcriptome RNA-Seq analysis through paired-end deep sequencing to systematically investigate the molecular features of different CaP cell models- RCC7/N, RCC7T/E, RCC7T/E-ADT, RCC7T/E-CD133, E006AA-hT and E006AA-hT-ADT We obtained an average of 23.85 million reads per sample, ranging from 22.86 to 24.93 million reads, with an average mapping rate of 98.29% to the reference human genome (UCSC version hg20). Next we performed Kals Z-test and generated Fold-Change (FC) values, p values and False Discovery Rate (FDR) values for measuring comparative gene expression profile. By applying stringent statistical threshold of greater than or equal to 2 FC, p value < 0.05 and FDR value < 1, we identified genes that were significantly differentially expressed in three different comparative groups.; Conclusions: "Our study represents the first detailed analysis of African American ADT resistant transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. " SOURCE: Mohammad SaleemMolecular Therapeutics and Cancer Health Disparity University of Minnesota

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