Computational identification of new potential transcriptional partners of ERRα in breast cancer cells: specific partners for specific targets
Abstract Estrogen related receptors are orphan members of the nuclear receptor superfamily acting as transcription factors (TFs). In contrast to classical nuclear receptors, the activities of the ERRs are not controlled by a natural ligand. Regulation of their activities thus relies on availability...
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Nature Portfolio
2022-03-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-07744-w |
| _version_ | 1819236733666983936 |
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| author | Catherine Cerutti Ling Zhang Violaine Tribollet Jing-Ru Shi Riwan Brillet Benjamin Gillet Sandrine Hughes Christelle Forcet Tie-Liu Shi Jean-Marc Vanacker |
| author_facet | Catherine Cerutti Ling Zhang Violaine Tribollet Jing-Ru Shi Riwan Brillet Benjamin Gillet Sandrine Hughes Christelle Forcet Tie-Liu Shi Jean-Marc Vanacker |
| author_sort | Catherine Cerutti |
| collection | DOAJ |
| description | Abstract Estrogen related receptors are orphan members of the nuclear receptor superfamily acting as transcription factors (TFs). In contrast to classical nuclear receptors, the activities of the ERRs are not controlled by a natural ligand. Regulation of their activities thus relies on availability of transcriptional co-regulators. In this paper, we focus on ERRα, whose involvement in cancer progression has been broadly demonstrated. We propose a new approach to identify potential co-activators, starting from previously identified ERRα-activated genes in a breast cancer (BC) cell line. Considering mRNA gene expression from two sets of human BC cells as major endpoint, we used sparse partial least squares modeling to uncover new transcriptional regulators associated with ERRα. Among them, DDX21, MYBBP1A, NFKB1, and SETD7 are functionally relevant in MDA-MB-231 cells, specifically activating the expression of subsets of ERRα-activated genes. We studied SET7 in more details and showed its co-localization with ERRα and its ERRα-dependent transcriptional and phenotypic effects. Our results thus demonstrate the ability of a modeling approach to identify new transcriptional partners from gene expression. Finally, experimental results show that ERRα cooperates with distinct co-regulators to control the expression of distinct sets of target genes, thus reinforcing the combinatorial specificity of transcription. |
| first_indexed | 2024-12-23T13:09:08Z |
| format | Article |
| id | doaj.art-ab50ff1f34e74eb59182eba683a88fbf |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-23T13:09:08Z |
| publishDate | 2022-03-01 |
| publisher | Nature Portfolio |
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| spelling | doaj.art-ab50ff1f34e74eb59182eba683a88fbf2022-12-21T17:45:48ZengNature PortfolioScientific Reports2045-23222022-03-0112111510.1038/s41598-022-07744-wComputational identification of new potential transcriptional partners of ERRα in breast cancer cells: specific partners for specific targetsCatherine Cerutti0Ling Zhang1Violaine Tribollet2Jing-Ru Shi3Riwan Brillet4Benjamin Gillet5Sandrine Hughes6Christelle Forcet7Tie-Liu Shi8Jean-Marc Vanacker9Institut de Génomique Fonctionnelle de Lyon, Université de Lyon, Université Lyon 1, CNRS UMR5242, Ecole Normale Supérieure de LyonInstitut de Génomique Fonctionnelle de Lyon, Université de Lyon, Université Lyon 1, CNRS UMR5242, Ecole Normale Supérieure de LyonInstitut de Génomique Fonctionnelle de Lyon, Université de Lyon, Université Lyon 1, CNRS UMR5242, Ecole Normale Supérieure de LyonInstitut de Génomique Fonctionnelle de Lyon, Université de Lyon, Université Lyon 1, CNRS UMR5242, Ecole Normale Supérieure de LyonInstitut de Génomique Fonctionnelle de Lyon, Université de Lyon, Université Lyon 1, CNRS UMR5242, Ecole Normale Supérieure de LyonInstitut de Génomique Fonctionnelle de Lyon, Université de Lyon, Université Lyon 1, CNRS UMR5242, Ecole Normale Supérieure de LyonInstitut de Génomique Fonctionnelle de Lyon, Université de Lyon, Université Lyon 1, CNRS UMR5242, Ecole Normale Supérieure de LyonInstitut de Génomique Fonctionnelle de Lyon, Université de Lyon, Université Lyon 1, CNRS UMR5242, Ecole Normale Supérieure de LyonThe Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal UniversityInstitut de Génomique Fonctionnelle de Lyon, Université de Lyon, Université Lyon 1, CNRS UMR5242, Ecole Normale Supérieure de LyonAbstract Estrogen related receptors are orphan members of the nuclear receptor superfamily acting as transcription factors (TFs). In contrast to classical nuclear receptors, the activities of the ERRs are not controlled by a natural ligand. Regulation of their activities thus relies on availability of transcriptional co-regulators. In this paper, we focus on ERRα, whose involvement in cancer progression has been broadly demonstrated. We propose a new approach to identify potential co-activators, starting from previously identified ERRα-activated genes in a breast cancer (BC) cell line. Considering mRNA gene expression from two sets of human BC cells as major endpoint, we used sparse partial least squares modeling to uncover new transcriptional regulators associated with ERRα. Among them, DDX21, MYBBP1A, NFKB1, and SETD7 are functionally relevant in MDA-MB-231 cells, specifically activating the expression of subsets of ERRα-activated genes. We studied SET7 in more details and showed its co-localization with ERRα and its ERRα-dependent transcriptional and phenotypic effects. Our results thus demonstrate the ability of a modeling approach to identify new transcriptional partners from gene expression. Finally, experimental results show that ERRα cooperates with distinct co-regulators to control the expression of distinct sets of target genes, thus reinforcing the combinatorial specificity of transcription.https://doi.org/10.1038/s41598-022-07744-w |
| spellingShingle | Catherine Cerutti Ling Zhang Violaine Tribollet Jing-Ru Shi Riwan Brillet Benjamin Gillet Sandrine Hughes Christelle Forcet Tie-Liu Shi Jean-Marc Vanacker Computational identification of new potential transcriptional partners of ERRα in breast cancer cells: specific partners for specific targets Scientific Reports |
| title | Computational identification of new potential transcriptional partners of ERRα in breast cancer cells: specific partners for specific targets |
| title_full | Computational identification of new potential transcriptional partners of ERRα in breast cancer cells: specific partners for specific targets |
| title_fullStr | Computational identification of new potential transcriptional partners of ERRα in breast cancer cells: specific partners for specific targets |
| title_full_unstemmed | Computational identification of new potential transcriptional partners of ERRα in breast cancer cells: specific partners for specific targets |
| title_short | Computational identification of new potential transcriptional partners of ERRα in breast cancer cells: specific partners for specific targets |
| title_sort | computational identification of new potential transcriptional partners of errα in breast cancer cells specific partners for specific targets |
| url | https://doi.org/10.1038/s41598-022-07744-w |
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