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

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 datas...

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Detalles Bibliográficos
Autores principales: Baba, Shahnawaz A., Labhsetwar, Shreyas, Klemke, Richard, Desgrosellier, Jay S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568552/
https://www.ncbi.nlm.nih.gov/pubmed/37840990
http://dx.doi.org/10.1016/j.dib.2023.109647
Descripción
Sumario: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.