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Title: A dataset of chromosomal instability gene signature scores in normal and cancer cells from the human breast
Creator: Desgrosellier, Jay S
Contributor: Baba, Shahnawaz A.
Desgrosellier, Jay S.
Klemke, Richard
Labhsetwar, Shreyas
Date Created and/or Issued: 2018 to 2023
Contributing Institution: UC San Diego, Research Data Curation Program
Collection: A dataset of chromosomal instability gene signature scores in normal and cancer cells from the human breast
Rights Information: Under copyright
Constraint(s) on Use: This work is protected by the U.S. Copyright Law (Title 17, U.S.C.). Use of this work beyond that allowed by "fair use" or any license applied to this work requires written permission of the copyright holder(s). Responsibility for obtaining permissions and any use and distribution of this work rests exclusively with the user and not the UC San Diego Library. Inquiries can be made to the UC San Diego Library program having custody of the work.
Use: This work is available from the UC San Diego Library. This digital copy of the work is intended to support research, teaching, and private study.
Rights Holder and Contact: UC Regents
Description: 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, providing a CIN enrichment score for each cell. 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.
Tobacco-Related Disease Research Program [Grant #T32IR4741 (to J.S.D.)]; and the California Breast Cancer Research Program [Grant #B28IB5479 (to J.S.D.)].
Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp)
Shahnawaz A. Baba was responsible for conceptualization of the study. Shahnawaz A. Baba, Labhsetwar, Shreyas, Richard Klemke, and Jay S. Desgrosellier were responsible for developing the methodology. Shreyas Labhsetwar and Richard Klemke were responsible for formal analysis and software development. Jay S. Desgrosellier was Principal Investigator.
Baba, Shahnawaz A.; Labhsetwar, Shreyas; Klemke, Richard; Desgrosellier, Jay S. (2023). A dataset of chromosomal instability gene signature scores in normal and cancer cells from the human breast. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0R78FDG
Type: dataset
Identifier: ark:/20775/bb12054874
Language: English
Subject: Stress tolerance
Breast cancer subtype
Cancer stem cell
Chromosomal missegregation
Tumor initiation
Signaling state

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