Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks
Open accessAbstract
Cell cycle (CC) and TP53 regulatory networks are frequently deregulated in cancer. While numerous genome-wide studies of TP53 and CC-regulated genes have been performed, significant variation between studies has made it difficult to assess regulation of any given gene of interest. To overcome the limitation of individual studies, we developed a meta-analysis approach to identify high confidence target genes that reflect their frequency of identification in independent datasets. Gene regulatory networks were generated by comparing differential expression of TP53 and CC-regulated genes with chromatin immunoprecipitation studies for TP53, RB1, E2F, DREAM, B-MYB, FOXM1 and MuvB. RNA-seq data from p21-null cells revealed that gene downregulation by TP53 generally requires p21 (CDKN1A). Genes downregulated by TP53 were also identified as CC genes bound by the DREAM complex. The transcription factors RB, E2F1 and E2F7 bind to a subset of DREAM target genes that function in G1/S of the CC while B-MYB, FOXM1 and MuvB control G2/M gene expression. Our approach yields high confidence ranked target gene maps for TP53, DREAM, MMB-FOXM1 and RB-E2F and enables prediction and distinction of CC regulation. A web-based atlas at www.targetgenereg.org enables assessing the regulation of any human gene of interest.
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Results from a recent meta-analysis of 20 genome-wide p53 gene expression profiles and 15 p53 binding profiles document that many p53 target genes are regulated across cell types as well as treatments.
“Results from a recent meta-analysis of 20 genome-wide p53 gene expression profiles, and 15 p53 binding profiles, document that many p53 target genes are regulated across cell types as well as treatments.18”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
Gene downregulation through distal enhancer interference by p53 binding is not supported by data from humans.
“but is not supported by data from humans.18, 19”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
Distal p53 binding also correlates with target gene activation, although to a lesser degree.
“the meta-analysis data provides evidence that distal p53 binding also correlates with target gene activation, although to a lesser degree.18”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
The number of data sets that agree on a gene being a p53 target represents a ranking of confidence, which is supported by recent meta-analysis results.
“Thus, the number of data sets that agree on a gene being a p53 target represents a ranking of confidence, which is supported by recent meta-analysis results.18”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
Proximal p53 binding, within 2.5 kb from the TSS, strongly correlates with transactivation of p53 target genes.
“A recent genome-wide meta-analysis also found that proximal p53 binding, within 2.5 kb from the TSS, strongly correlates with transactivation of p53 target genes.18”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
Recent approaches to predict functional sites that lead to target gene activation rely on ranking p53 binding sites based on multiple genome-wide data sets.
“To predict functional sites that lead to target gene activation, recent approaches now rely on ranking p53 binding sites based on multiple genome-wide data sets.18, 19, 56”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
The current model describes p53 solely as a transcriptional activator and not as a repressor.
“The current model describes p53 solely as a transcriptional activator and not as repressor,53 and is supported by multiple genome-wide analyses.18, 19, 23, 24, 89”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
Most genes downregulated by p53 are targets of the DREAM complex.
“and targets of the DREAM complex.18”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
In general, p21 is required for p53-dependent gene downregulation.
“Recent results from p21-knockout cells show that, in general, p21 is required for p53-dependent gene downregulation.18, 116”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
PMS2 and MLH1 were believed to be p53-activated targets, but meta-analysis data show this unlikely.
“The DNA repair genes PMS2 and MLH1 were also believed to be p53-activated targets,175 but meta-analysis data show this unlikely to be the case18 (Supplementary Table S2).”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
Some cell cycle genes, including PCNA, POLH and AEN, are targeted by both DREAM and p53; in these cases, the transcriptional activator p53 opposes the repressive DREAM complex, leading to target gene activation.
“Interestingly, some cell cycle genes, including PCNA, POLH and AEN, are targeted by both DREAM and p53: in these cases, the transcriptional activator p53 opposes the repressive DREAM complex, leading to target gene activation.18”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
Stabilization of the DREAM complex and its recruitment to target gene promoters leads to indirect p53-mediated downregulation of cell cycle genes such as CDK1, Cyclin A and B, CDC25C, MYBL2 (B-MYB), PLK1 and hundreds more, all of which are required for cell cycle progression.
“Stabilization of the DREAM complex and its recruitment to target gene promoters leads to indirect p53-mediated downregulation of cell cycle genes such as CDK1, Cyclin A and B, CDC25C, MYBL2 (B-MYB), PLK1 and hundreds more, all of which are required for cell cycle progression.18, 108, 114”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
MSH2, RAD51 and RECQL4 were thought to be direct p53 targets, but are indirectly repressed through the DREAM complex.
“Although several DNA repair genes, including MSH2,172 RAD51173 and RECQL4,87 were thought to be direct p53 targets, it has become evident that they are indirectly repressed through the DREAM complex.18, 108, 114”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
BCL2 and BID are reported as p53 targets but are not directly regulated by p53 according to meta-analysis data.
“Additional BCL-2 family members reported as p53 targets include BCL2190, 191 and BID192—but these are not directly regulated by p53 according to meta-analysis data18 (Supplementary Table S2).”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
SCO2, PARK2, LPIN1, CPT1C, SLC2A3, SLC2A4, ME1, ME2 and ME3 are involved in metabolism and are believed to be directly regulated by p53, but according to meta-analysis data these genes are not regulated by p53 in humans.
“Several additional genes, including SCO2,203 PARK2 (Parkin),133 LPIN1,204 CPT1C,205 SLC2A3 (GLUT3),206 SLC2A4 (GLUT4)207 and ME1, ME2 and ME3,80 are involved in metabolism and are believed to be directly regulated by p53. However, according to meta-analysis data these genes are not regulated by p53 in humans18 (Supplementary Table S2).”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
ULK1 and ULK2, which encode autophagy-activating kinases, were thought to be regulated by p53, but their regulation by p53 is not supported by meta-analysis data.
“And, although ULK1 and ULK2, which encode autophagy-activating kinases, were thought to be regulated by p53,137 their regulation by p53 is not supported by meta-analysis data18 (Supplementary Table S2).”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
Most functional p53 binding sites are found in proximal promoters.
“Most functional p53 binding sites are found in proximal promoters 18 (Figure 1e).”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
The number of true p53 target genes is limited, and likely does not exceed a few hundred.
“The number of true p53 target genes is limited, and likely does not exceed a few hundred 18 (Figure 2a and Supplementary Tables S2 and S3).”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
SIAH1, RCHY1 (Pirh2) and RFWD2 (COP1) are believed to be involved in feedback loops as p53 targets, but these are not regulated by p53 according to meta-analysis data.
“Additional genes believed to be involved in feedback loops as p53 targets include SIAH1,228 RCHY1 (Pirh2)229 and RFWD2 (COP1),230 but these are not regulated by p53 according to meta-analysis data18 (Supplementary Table S2).”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
Gene downregulation by p53 is indirect and requires p21.
“Gene downregulation by p53 is indirect and requires p21. 18, 116”
From Census and evaluation of p53 target genes (2017) · cites this paper as [18]
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Expanding the p53 regulatory network: LncRNAs take up the challenge
Grossi, E., Sánchez, Y., & Huarte, M. (2016) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2015.07.011 · Cited by 78 · see citing works
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A Comprehensive and High-Resolution Genome-wide Response of p53 to Stress
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Fischer, M., Grundke, I., Sohr, S., Quaas, M., Hoffmann, S., Knörck, A., Gumhold, C., & Rother, K. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063187 · Cited by 64 · see citing works
Self-citationFischer, M., Quaas, M., Wintsche, A., Müller, G. A., & Engeland, K. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt849 · Cited by 62 · see citing works
Self-citationFischer, M., Quaas, M., Nickel, A., & Engeland, K. (2015) · Oncotarget · doi:10.18632/oncotarget.6356 · Cited by 59 · see citing works
Self-citationp53-directed translational control can shape and expand the universe of p53 target genes
Zaccara, S., Tebaldi, T., Pederiva, C., Ciribilli, Y., Bisio, A., & Inga, A. (2014) · Cell Death and Differentiation · doi:10.1038/cdd.2014.79 · Cited by 56 · see citing works
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E2F2 and CREB cooperatively regulate transcriptional activity of cell cycle genes
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p53, a novel regulator of lipid metabolism pathways
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Mechanisms of Cellular Senescence: Cell Cycle Arrest and Senescence Associated Secretory Phenotype
Kumari, R., & Jat, P. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.645593 · Cited by 1,622 · see citing works
The multiple mechanisms that regulate p53 activity and cell fate
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Census and evaluation of p53 target genes
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Self-citationKi-67: more than a proliferation marker
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Dual proteome-scale networks reveal cell-specific remodeling of the human interactome
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FoxM1 repression during human aging leads to mitotic decline and aneuploidy-driven full senescence
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Fujihara, K. M., Corrales Benitez, M., Cabalag, C. S., Zhang, B. Z., Ko, H. S., Liu, D. S., Simpson, K. J., Haupt, Y., Lipton, L., Haupt, S., et al. (2021) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-21-0067 · Cited by 48 · see citing works
MDM2 inhibition in the treatment of glioblastoma: From concept to clinical investigation
Pellot Ortiz, K. I., Rechberger, J. S., Nonnenbroich, L. F., Daniels, D. J., & Sarkaria, J. N. (2023) · Biomedicines · doi:10.3390/biomedicines11071879 · Cited by 30 · see citing works
p21 governs p53's repressive side
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Self-citation
- Authors
- Fischer, M., Grossmann, P., Padi, M., & DeCaprio, J. A.
- Affiliations
- Harvard University (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Fischer, Martin
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-06-08
- Volume
- 44
- Issue
- 13
- Pages
- 6070-6086
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC4994865
- OpenAlex
- W2416423710
- Cited by
- 330
- References
- 77
- Citations by year
- 2026: 18 · 2025: 31 · 2024: 38 · 2023: 44 · 2022: 42 · 2021: 44 · 2020: 32 · 2019: 34 · 2018: 25 · 2017: 20 · 2016: 2
- FWCI
- 2.72
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- HighWire Press Open Archive (submittedVersion)
- Qucosa (Saxon State and University Library Dresden) (submittedVersion, other-oa)
- Funders
- Joachim Herz Stiftung
- Deutsche Forschungsgemeinschaft
- Fritz Thyssen Stiftung
- Deutsche Akademie der Naturforscher Leopoldina - Nationale Akademie der Wissenschaften
- National Institutes of Health
- National Human Genome Research Institute (K25HG006031)
- National Cancer Institute (R01CA173023, R01CA063113, R35CA232128)
- Topics
- Health Sciences › Medicine › Oncology › Cancer-related Molecular Pathways
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- DREAM complex, FOXM1, gene regulatory networks, RB1, E2F1, E2F7, B-Myb, CDKN1A/p21, chromatin immunoprecipitation
- MeSH terms
- Forkhead Box Protein M1, Cell Cycle, Humans, Neoplasms, Promoter Regions, Genetic, Repressor Proteins, Gene Expression Regulation, Neoplastic, Tumor Suppressor Protein p53, Ubiquitin-Protein Ligases, E2F Transcription Factors, Cyclin-Dependent Kinase Inhibitor p21, Kv Channel-Interacting Proteins, Gene Regulatory Networks, Retinoblastoma Binding Proteins
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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