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来自人类乳腺正常细胞和癌细胞的染色体不稳定基因特征评分数据集。

A dataset of chromosomal instability gene signature scores in normal and cancer cells from the human breast.

作者信息

Baba Shahnawaz A, Labhsetwar Shreyas, Klemke Richard, Desgrosellier Jay S

机构信息

Department of Pathology, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.

出版信息

Data Brief. 2023 Oct 8;51:109647. doi: 10.1016/j.dib.2023.109647. eCollection 2023 Dec.

Abstract

These data show the relative amount of chromosomal instability (CIN) in a diverse array of human breast cell types, including non-transformed mammary epithelial cells as well as cancer cell lines. Additional data is also provided from human embryonic and mesenchymal stem cells. To produce this dataset, we compared a published chromosomal instability gene signature against publicly available datasets containing gene expression information for each cell. We then analyzed these data with the Python GSEAPY software package to provide a CIN enrichment score. These data are useful for comparing the relative amounts of CIN in different breast cell types. This includes cells representing the major clinical (ER/PR, HER2 & Triple-negative) as well as intrinsic breast cancer subtypes (Luminal B, HER2+, Basal-like and Claudin-low). Our dataset has a great potential for re-use given the recent surge in interest surrounding the role of CIN in breast cancer. The large size of the dataset, coupled with the diversity of the cell types represented, provides numerous possibilities for future comparisons.

摘要

这些数据显示了多种人类乳腺细胞类型中染色体不稳定性(CIN)的相对量,包括未转化的乳腺上皮细胞以及癌细胞系。还提供了来自人类胚胎干细胞和间充质干细胞的其他数据。为了生成这个数据集,我们将一个已发表的染色体不稳定性基因特征与包含每个细胞基因表达信息的公开可用数据集进行了比较。然后,我们使用Python GSEAPY软件包分析这些数据,以提供CIN富集分数。这些数据有助于比较不同乳腺细胞类型中CIN的相对量。这包括代表主要临床(雌激素受体/孕激素受体、人表皮生长因子受体2和三阴性)以及内在乳腺癌亚型(管腔B型、人表皮生长因子受体2阳性、基底样和Claudin低表达型)的细胞。鉴于最近人们对CIN在乳腺癌中的作用的兴趣激增,我们的数据集具有很大的重用潜力。数据集的规模庞大,再加上所代表的细胞类型的多样性,为未来的比较提供了众多可能性。

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