Cited by 4TGF-β signaling in diseasesGene Regulatory Network AnalysisDevelopmental Biology and Gene Regulation

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Transcriptional regulators ensuring specific gene expression and decision-making at high TGFβ doses

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Published version of a preprint

Abstract

TGFβ-signaling regulates cancer progression by controlling cell division, migration, and death. These outcomes are mediated by gene expression changes, but the mechanisms of decision-making toward specific fates remain unclear. Here, we combine SMAD transcription factor imaging, genome-wide RNA sequencing, and morphological assays to quantitatively link signaling, gene expression, and fate decisions in mammary epithelial cells. Fitting genome-wide kinetic models to our time-resolved data, we find that most of the TGFβ target genes can be explained as direct targets of SMAD transcription factors, whereas the remainder show signs of complex regulation, involving delayed regulation and strong amplification at high TGFβ doses. Knockdown experiments followed by global RNA sequencing revealed transcription factors interacting with SMADs in feedforward loops to control delayed and dose-discriminating target genes, thereby reinforcing the specific epithelial-to-mesenchymal transition at high TGFβ doses. We identified early repressors, preventing premature activation, and a late activator, boosting gene expression responses for a sufficiently strong TGFβ stimulus. Taken together, we present a global view of TGFβ-dependent gene regulation and describe specificity mechanisms reinforcing cellular decision-making.

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Research works printed but not linked: 91

  1. 10.1109/TAC.1974.1100705 · DOI · Paper page
  2. 10.1038/nrd3810 · DOI · Paper page
  3. 10.1038/nrg2102 · DOI · Paper page
  4. 10.1038/ng1987 · DOI
  5. 10.3390/cancers15020558 · DOI
  6. 10.1038/s41467-018-07455-9 · DOI
  7. 10.1016/j.gde.2010.09.007 · DOI
  8. 10.1073/pnas.2210891120 · DOI
  9. 10.1111/j.1742-4658.2008.06845.x · DOI · Paper page
  10. 10.3389/fgene.2021.651882 · DOI
  11. 10.1128/MCB.01443-08 · DOI
  12. 10.1080/21655979.2022.2053799 · DOI
  13. 10.1073/pnas.2102050118 · DOI
  14. 10.1242/jcs.139865 · DOI
  15. 10.1093/bioinformatics/bts635 · DOI · Paper page
  16. 10.1146/annurev.cellbio.21.022404.142018 · DOI · Paper page
  17. 10.1073/pnas.1611428114 · DOI
  18. 10.1186/s12976-017-0064-7 · DOI
  19. 10.1083/jcb.201109045 · DOI
  20. 10.18632/oncotarget.26574 · DOI
  21. 10.1074/jbc.274.44.31577 · DOI
  22. 10.1038/ni.1699 · DOI · Paper page
  23. 10.3892/mmr.2020.11649 · DOI
  24. 10.18632/oncotarget.8250 · DOI
  25. 10.1038/nrc2853 · DOI
  26. 10.1124/mol.62.1.65 · DOI
  27. 10.1038/s41598-023-48798-8 · DOI
  28. 10.1038/srep43567 · DOI
  29. 10.1016/S1097-2765(03)00109-6 · DOI
  30. 10.1038/nmeth.3317 · DOI · Paper page
  31. 10.1093/nar/gkad347 · DOI · Paper page
  32. 10.3389/fphy.2020.00070 · DOI
  33. 10.1016/j.cell.2018.01.029 · DOI · Paper page
  34. 10.1158/0008-5472.CAN-07-6793 · DOI
  35. 10.1093/bioinformatics/btt656 · DOI · Paper page
  36. 10.1016/j.ejso.2018.10.543 · DOI
  37. 10.1186/s13059-014-0550-8 · DOI · Paper page
  38. 10.1016/j.cels.2017.11.010 · DOI
  39. 10.1101/gad.13.17.2196 · DOI
  40. 10.1073/pnas.2133841100 · DOI · Paper page
  41. 10.1016/0092-8674(95)90401-8 · DOI · Paper page
  42. 10.18632/oncotarget.16432 · DOI
  43. 10.1046/j.1365-2443.2002.00599.x · DOI
  44. 10.1073/pnas.1312310110 · DOI
  45. 10.1038/onc.2012.191 · DOI
  46. 10.1016/j.cell.2011.08.050 · DOI
  47. 10.1038/sj.onc.1206420 · DOI
  48. 10.1074/jbc.M211304200 · DOI
  49. 10.1016/j.devcel.2015.10.010 · DOI
  50. 10.4161/19336918.2014.972740 · DOI
  51. 10.1074/jbc.M102382200 · DOI
  52. 10.1186/s12967-023-04303-3 · DOI
  53. 10.1016/j.cell.2013.02.005 · DOI
  54. 10.1126/science.1218351 · DOI · Paper page
  55. 10.1371/journal.pone.0074335 · DOI
  56. 10.1093/bioinformatics/btv405 · DOI
  57. 10.1073/pnas.2117323119 · DOI
  58. 10.1016/j.biocel.2007.09.006 · DOI
  59. 10.1038/onc.2016.504 · DOI
  60. 10.1016/S0092-8674(00)81600-1 · DOI
  61. 10.1038/nrc1208 · DOI
  62. 10.1016/j.devcel.2014.05.022 · DOI
  63. 10.15252/msb.20177733 · DOI
  64. 10.1126/science.286.5440.771 · DOI
  65. 10.1038/onc.2012.370 · DOI
  66. 10.1093/nar/gkx1190 · DOI
  67. 10.3892/ol.2021.12539 · DOI
  68. 10.1016/j.biopha.2017.03.017 · DOI
  69. 10.1038/s41392-018-0015-8 · DOI
  70. 10.1111/j.1600-0714.2005.00374.x · DOI
  71. 10.3892/etm.2023.11875 · DOI
  72. 10.1038/s41598-019-41870-2 · DOI
  73. 10.15252/msb.20177554 · DOI
  74. 10.1186/s13046-015-0141-x · DOI
  75. 10.1038/ncb1905 · DOI
  76. 10.3727/096504016X14755368915591 · DOI
  77. 10.3892/ijo.2018.4356 · DOI
  78. 10.1002/pmic.202000034 · DOI
  79. 10.2147/OTT.S243417 · DOI
  80. 10.1016/j.phymed.2022.154062 · DOI
  81. 10.1038/cr.2009.5 · DOI · Paper page
  82. 10.1073/pnas.1834070100 · DOI
  83. 10.3892/or.2015.3961 · DOI
  84. 10.1242/jcs.064915 · DOI
  85. 10.1126/scisignal.2005304 · DOI
  86. 10.1002/jcb.26270 · DOI
  87. 10.1038/s41419-019-1320-z · DOI
  88. 10.1038/srep11459 · DOI
  89. 10.21037/atm-21-1669 · DOI
  90. 10.1038/msb.2011.22 · DOI
  91. 10.1016/j.febslet.2012.03.063 · DOI

Metadata

Authors
Hartmann, L., Kristofori, P., Li, C., Becker, K., Hexemer, L., Bohn, S., Lenhardt, S., Weiss, S., Voss, B., Loewer, A., & Legewie, S.
Affiliations
  • University of Stuttgart (DE)
  • Technische Universität Darmstadt (DE)
Corresponding author
  • Loewer, Alexander
  • Legewie, Stefan
Venue
Life Science Alliance
Published
2024-11-14
Volume
8
Issue
1
Pages
e202402859
ISSN
2575-1077 (ISSN-L)
OpenAlex
W4404348144
Cited by
4
References
3
Citations by year
2026: 1 · 2025: 3
FWCI
0.54
Type
journal article
Language
en
Open access
Locations
  • Life Science Alliance (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • TUbilio (Technical University of Darmstadt) (acceptedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
Deutsche Forschungsgemeinschaft (LE 3473/4-1, 468927954, LO 1634/7-1)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › TGF-β signaling in diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
Keywords
TGF-beta signaling, Smad transcription factors, gene expression regulation, cellular decision-making, mammary epithelial cells, epithelial-mesenchymal transition, feed-forward loop, transcriptional amplification, tumor progression
MeSH terms
Animals, Epithelial Cells, Female, Gene Expression Regulation, Humans, Transcription Factors, Signal Transduction, Transforming Growth Factor beta, Smad Proteins, Epithelial-Mesenchymal Transition

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