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.

During preclinical drug development, the ability of cancer cell lines to faithfully model human disease is important for identifying potential therapeutic strategies. Here, using transcriptomic datasets of over 1000 cell lines, the authors evaluate how representative each line is of its cancer type and present their cell line selection tool.

Details

Title
Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation
Author
Jin, Han 1   VIAFID ORCID Logo  ; Zhang, Cheng 1   VIAFID ORCID Logo  ; Zwahlen, Martin 1   VIAFID ORCID Logo  ; von Feilitzen, Kalle 1   VIAFID ORCID Logo  ; Karlsson, Max 1   VIAFID ORCID Logo  ; Shi, Mengnan 1   VIAFID ORCID Logo  ; Yuan, Meng 1 ; Song, Xiya 1 ; Li, Xiangyu 1   VIAFID ORCID Logo  ; Yang, Hong 1   VIAFID ORCID Logo  ; Turkez, Hasan 2 ; Fagerberg, Linn 1   VIAFID ORCID Logo  ; Uhlén, Mathias 3   VIAFID ORCID Logo  ; Mardinoglu, Adil 4   VIAFID ORCID Logo 

 KTH Royal Institute of Technology, Science for Life Laboratory, Department of Protein Science, Stockholm, Sweden (GRID:grid.5037.1) (ISNI:0000000121581746) 
 Atatürk University, Department of Medical Biology, Faculty of Medicine, Erzurum, Turkey (GRID:grid.411445.1) (ISNI:0000 0001 0775 759X) 
 KTH Royal Institute of Technology, Science for Life Laboratory, Department of Protein Science, Stockholm, Sweden (GRID:grid.5037.1) (ISNI:0000000121581746); Karolinska Institute, Department of Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626) 
 KTH Royal Institute of Technology, Science for Life Laboratory, Department of Protein Science, Stockholm, Sweden (GRID:grid.5037.1) (ISNI:0000000121581746); King’s College London, Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, London, UK (GRID:grid.13097.3c) (ISNI:0000 0001 2322 6764) 
Pages
5417
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2861032324
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.