Bulk mRNA-sequencing data of the estrogen and androgen responses in the human prostate cancer cell line VCaPGEO)
Camille Lafront,
Lucas Germain,
Étienne Audet-Walsh
Affiliations
Camille Lafront
Department of Molecular Medicine, Faculty of Medicine, Université Laval, 1050 avenue de la Médecine, Québec City, Québec G1V 0A6, Canada; Endocrinology – Nephrology Division of Centre de recherche du CHU de Québec – Université Laval, Québec City, Québec, Canada; Centre de recherche sur le cancer de l'Université Laval, 9 rue McMahon, Québec City, Québec G1R 3S3, Canada
Lucas Germain
Department of Molecular Medicine, Faculty of Medicine, Université Laval, 1050 avenue de la Médecine, Québec City, Québec G1V 0A6, Canada; Endocrinology – Nephrology Division of Centre de recherche du CHU de Québec – Université Laval, Québec City, Québec, Canada; Centre de recherche sur le cancer de l'Université Laval, 9 rue McMahon, Québec City, Québec G1R 3S3, Canada
Étienne Audet-Walsh
Department of Molecular Medicine, Faculty of Medicine, Université Laval, 1050 avenue de la Médecine, Québec City, Québec G1V 0A6, Canada; Endocrinology – Nephrology Division of Centre de recherche du CHU de Québec – Université Laval, Québec City, Québec, Canada; Centre de recherche sur le cancer de l'Université Laval, 9 rue McMahon, Québec City, Québec G1R 3S3, Canada; Corresponding author at: Department of Molecular Medicine, Faculty of Medicine, Université Laval, 1050 avenue de la Médecine, Québec City, Québec G1V 0A6, Canada.
Prostate cancer is a hormone-dependent disease that relies on the androgen signaling, as well as on the estrogen signaling, for growth and survival. To identify the genes regulated by these sex-steroid hormones in the human prostate cancer cell line VCaP, these cells were treated for 24 h with either androgens and/or estrogens. Then, the RNA of each sample was purified for sequencing to generate bulk mRNA-seq data. After verifying raw quality, reads were pseudo-aligned on the human reference transcriptome (Gencode v27). Analysis was carried out on aligned and quantified data to determine the transcriptomic changes following each hormonal treatment. These data presented herein can be reanalyzed with specific fold-change thresholds for gene expression, or with different pair-wise combinations to compare the hormones’ transcriptional impacts on VCaP cells and better understand prostate cancer cell biology.