Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation
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...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-09-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-41132-w |
| _version_ | 1797557957001478144 |
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| author | Han Jin Cheng Zhang Martin Zwahlen Kalle von Feilitzen Max Karlsson Mengnan Shi Meng Yuan Xiya Song Xiangyu Li Hong Yang Hasan Turkez Linn Fagerberg Mathias Uhlén Adil Mardinoglu |
| author_facet | Han Jin Cheng Zhang Martin Zwahlen Kalle von Feilitzen Max Karlsson Mengnan Shi Meng Yuan Xiya Song Xiangyu Li Hong Yang Hasan Turkez Linn Fagerberg Mathias Uhlén Adil Mardinoglu |
| author_sort | Han Jin |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T17:23:34Z |
| format | Article |
| id | doaj.art-981f4ee29ebc40c8b7248086e28ad99a |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-10T17:23:34Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-981f4ee29ebc40c8b7248086e28ad99a2023-11-20T10:15:26ZengNature PortfolioNature Communications2041-17232023-09-0114111510.1038/s41467-023-41132-wSystematic transcriptional analysis of human cell lines for gene expression landscape and tumor representationHan Jin0Cheng Zhang1Martin Zwahlen2Kalle von Feilitzen3Max Karlsson4Mengnan Shi5Meng Yuan6Xiya Song7Xiangyu Li8Hong Yang9Hasan Turkez10Linn Fagerberg11Mathias Uhlén12Adil Mardinoglu13Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyDepartment of Medical Biology, Faculty of Medicine, Atatürk UniversityScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyScience for Life Laboratory, Department of Protein Science, KTH Royal Institute of TechnologyAbstract 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.https://doi.org/10.1038/s41467-023-41132-w |
| spellingShingle | Han Jin Cheng Zhang Martin Zwahlen Kalle von Feilitzen Max Karlsson Mengnan Shi Meng Yuan Xiya Song Xiangyu Li Hong Yang Hasan Turkez Linn Fagerberg Mathias Uhlén Adil Mardinoglu Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation Nature Communications |
| title | Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation |
| title_full | Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation |
| title_fullStr | Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation |
| title_full_unstemmed | Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation |
| title_short | Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation |
| title_sort | systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation |
| url | https://doi.org/10.1038/s41467-023-41132-w |
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