人类前列腺癌细胞系 VCaP 对雌激素和雄激素反应的大量 mRNA 序列数据

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Camille Lafront , Lucas Germain , Étienne Audet-Walsh
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引用次数: 0

摘要

前列腺癌是一种激素依赖性疾病,其生长和存活依赖于雄激素信号和雌激素信号。为了确定人类前列腺癌细胞系VCaP中受这些性类固醇激素调控的基因,这些细胞被雄激素和/或雌激素处理了24小时。然后,纯化每个样本的 RNA 进行测序,生成大量 mRNA-seq 数据。在验证原始质量后,将读数与人类参考转录组(Gencode v27)进行伪配对。对已对齐和量化的数据进行分析,以确定每种激素治疗后转录组的变化。本文介绍的这些数据可以用特定的基因表达折叠变化阈值或不同的配对组合进行重新分析,以比较激素对 VCaP 细胞转录的影响,更好地了解前列腺癌细胞生物学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bulk mRNA-sequencing data of the estrogen and androgen responses in the human prostate cancer cell line VCaP
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.
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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