Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation

Han Jin, Cheng Zhang, Martin Zwahlen, Kalle Feilitzen, Max Karlsson, Mengnan Shi, Meng Yuan, Xiya Song, Xiangyu Li, Hong Yang, Hasan Turkez, Linn Fagerberg, Mathias Uhlén () and Adil Mardinoglu ()
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Han Jin: KTH Royal Institute of Technology
Cheng Zhang: KTH Royal Institute of Technology
Martin Zwahlen: KTH Royal Institute of Technology
Kalle Feilitzen: KTH Royal Institute of Technology
Max Karlsson: KTH Royal Institute of Technology
Mengnan Shi: KTH Royal Institute of Technology
Meng Yuan: KTH Royal Institute of Technology
Xiya Song: KTH Royal Institute of Technology
Xiangyu Li: KTH Royal Institute of Technology
Hong Yang: KTH Royal Institute of Technology
Hasan Turkez: Atatürk University
Linn Fagerberg: KTH Royal Institute of Technology
Mathias Uhlén: KTH Royal Institute of Technology
Adil Mardinoglu: KTH Royal Institute of Technology

Nature Communications, 2023, vol. 14, issue 1, 1-15

Abstract: Abstract Cell lines are valuable resources as model for human biology and translational medicine. It is thus important to explore the concordance between the expression in various cell lines vis-à-vis human native and disease tissues. In this study, we investigate the expression of all human protein-coding genes in more than 1,000 human cell lines representing 27 cancer types by a genome-wide transcriptomics analysis. The cell line gene expression is compared with the corresponding profiles in various tissues, organs, single-cell types and cancers. Here, we present the expression for each cell line and give guidance for the most appropriate cell line for a given experimental study. In addition, we explore the cancer-related pathway and cytokine activity of the cell lines to aid human biology studies and drug development projects. All data are presented in an open access cell line section of the Human Protein Atlas to facilitate the exploration of all human protein-coding genes across these cell lines.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41132-w

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DOI: 10.1038/s41467-023-41132-w

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