Cited by 195Cancer, Hypoxia, and MetabolismGenomics and Chromatin DynamicsChromatin Remodeling and Cancer

Inherent DNA‐binding specificities of the HIF‐1α and HIF‐2α transcription factors in chromatin

Open access
Smythies, James A, Sun, Min, Masson, Norma, Salama, Rafik, Simpson, Peter D, Murray, Elizabeth, Neumann, Viviana, Cockman, Matthew E +3 more·2019·The EMBO Reports

Abstract

Hypoxia‐inducible factor (HIF) is the major transcriptional regulator of cellular responses to hypoxia. The two principal HIF‐α isoforms, HIF‐1α and HIF‐2α, are progressively stabilized in response to hypoxia and form heterodimers with HIF‐1β to activate a broad range of transcriptional responses. Here, we report on the pan‐genomic distribution of isoform‐specific HIF binding in response to hypoxia of varying severity and duration, and in response to genetic ablation of each HIF‐α isoform. Our findings reveal that, despite an identical consensus recognition sequence in DNA, each HIF heterodimer loads progressively at a distinct repertoire of cell‐type‐specific sites across the genome, with little evidence of redistribution under any of the conditions examined. Marked biases towards promoter‐proximal binding of HIF‐1 and promoter‐distant binding of HIF‐2 were observed under all conditions and were consistent in multiple cell type. The findings imply that each HIF isoform has an inherent property that determines its binding distribution across the genome, which might be exploited to therapeutically target the specific transcriptional output of each isoform independently.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.15252/embr.201846401

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Promoter-proximal HIF-1 binding correlates with a higher transcript abundance.

    “Promoter-proximal HIF-1 binding correlates with a higher transcript abundance [68,71,79,82]”

    From HIF inhibition: Current strategies and clinical challenges (2026) · cites this paper as [71]

    The Results (Figure 6; page unavailable) show that HIF-1 binding sites are more promoter-proximal than HIF-2 sites. The Results section on the epigenetic landscape also reports an association between HIF-1 sites and transcriptional machinery, but the passages found do not establish that promoter-proximal HIF-1 binding correlates with higher transcript abundance. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 53 · Cited by 195

Research works printed but not linked: 39

  1. [1]Ortiz‐Barahona A, Villar D, Pescador N, Amigo J, del Peso L (2010) Genome‐wide identification of hypoxia‐inducible factor binding sites and target genes by a probabilistic model integrating transcription‐profiling data and in silico binding site prediction. Nucleic Acids Res 38: 2332– 2345 20061373 PMC2853119
  2. [2]Semenza GL (2012) Hypoxia‐inducible factors in physiology and medicine. Cell 148: 399– 408 22304911 PMC3437543
  3. [3]Holmquist‐Mengelbier L, Fredlund E, Lofstedt T, Noguera R, Navarro S, Nilsson H, Pietras A, Vallon‐Christersson J, Borg A, Gradin K et al (2006) Recruitment of HIF‐1alpha and HIF‐2alpha to common target genes is differentially regulated in neuroblastoma: HIF‐2alpha promotes an aggressive phenotype. Cancer Cell 10: 413– 423 17097563
  4. [5]Wenger RH, Stiehl DP, Camenisch G (2005) Integration of oxygen signaling at the consensus HRE. Sci STKE 2005: re12 16234508
  5. [6]Maxwell PH, Eckardt KU (2016) HIF prolyl hydroxylase inhibitors for the treatment of renal anaemia and beyond. Nat Rev Nephrol 12: 157– 168 26656456
  6. [7]Chan MC, Holt‐Martyn JP, Schofield CJ, Ratcliffe PJ (2016) Pharmacological targeting of the HIF hydroxylases – a new field in medicine development. Mol Aspects Med 47–48: 54– 75 26791432
  7. [8]Courtney KD, Infante JR, Lam ET, Figlin RA, Rini BI, Brugarolas J, Zojwalla NJ, Lowe AM, Wang K, Wallace EM et al (2018) Phase I dose‐escalation trial of PT2385, a first‐in‐class hypoxia‐inducible factor‐2alpha antagonist in patients with previously treated advanced clear cell renal cell carcinoma. J Clin Oncol 36: 867– 874 29257710 PMC5946714
  8. [9]Eltzschig HK, Bratton DL, Colgan SP (2014) Targeting hypoxia signalling for the treatment of ischaemic and inflammatory diseases. Nat Rev Drug Discov 13: 852– 869 25359381 PMC4259899
  9. [10]Wu D, Rastinejad F (2017) Structural characterization of mammalian bHLH‐PAS transcription factors. Curr Opin Struct Biol 43: 1– 9 27721191 PMC5382129
  10. [11]Semenza GL (2001) HIF‐1 and mechanisms of hypoxia sensing. Curr Opin Cell Biol 13: 167– 171 11248550
  11. [13]Gordan JD, Thompson CB, Simon MC (2007) HIF and c‐Myc: sibling rivals for control of cancer cell metabolism and proliferation. Cancer Cell 12: 108– 113 17692803 PMC3215289
  12. [14]Takeda N, O'Dea EL, Doedens A, Kim JW, Weidemann A, Stockmann C, Asagiri M, Simon MC, Hoffmann A, Johnson RS (2010) Differential activation and antagonistic function of HIF‐{alpha} isoforms in macrophages are essential for NO homeostasis. Genes Dev 24: 491– 501 20194441 PMC2827844
  13. [15]Raval RR, Lau KW, Tran MG, Sowter HM, Mandriota SJ, Li JL, Pugh CW, Maxwell PH, Harris AL, Ratcliffe PJ (2005) Contrasting properties of hypoxia‐inducible factor 1 (HIF‐1) and HIF‐2 in von Hippel‐Lindau‐Associated renal cell carcinoma. Mol Cell Biol 25: 5675– 5686 15964822 PMC1157001
  14. [16]Salama R, Masson N, Simpson P, Sciesielski LK, Sun M, Tian YM, Ratcliffe PJ, Mole DR (2015) Heterogeneous effects of direct hypoxia pathway activation in kidney cancer. PLoS One 10: e0134645 26262842 PMC4532367
  15. [17]Shen C, Beroukhim R, Schumacher SE, Zhou J, Chang M, Signoretti S, Kaelin WG Jr (2011) Genetic and functional studies implicate HIF1alpha as a 14q kidney cancer suppressor gene. Cancer Discov 1: 222– 235 22037472 PMC3202343
  16. [18]Tian H, McKnight SL, Russell DW (1997) Endothelial PAS domain protein 1 (EPAS1), a transcription factor selectively expressed in endothelial cells. Genes Dev 11: 72– 82 9000051
  17. [19]Wiesener MS, Jurgensen JS, Rosenberger C, Scholze CK, Horstrup JH, Warnecke C, Mandriota S, Bechmann I, Frei UA, Pugh CW et al (2003) Widespread hypoxia‐inducible expression of HIF‐2alpha in distinct cell populations of different organs. FASEB J 17: 271– 273 12490539
  18. [20]Stiehl DP, Bordoli MR, Abreu‐Rodriguez I, Wollenick K, Schraml P, Gradin K, Poellinger L, Kristiansen G, Wenger RH (2012) Non‐canonical HIF‐2alpha function drives autonomous breast cancer cell growth via an AREG‐EGFR/ErbB4 autocrine loop. Oncogene 31: 2283– 2297 21927022
  19. [21]Fuady JH, Gutsche K, Santambrogio S, Varga Z, Hoogewijs D, Wenger RH (2016) Estrogen‐dependent downregulation of hypoxia‐inducible factor (HIF)‐2alpha in invasive breast cancer cells. Oncotarget 7: 31153– 31165 27105516 PMC5058746
  20. [22]Toschi A, Lee E, Gadir N, Ohh M, Foster DA (2008) Differential dependence of hypoxia‐inducible factors 1 alpha and 2 alpha on mTORC1 and mTORC2. J Biol Chem 283: 34495– 34499 18945681 PMC2596400
  21. [23]Maranchie JK, Zhan Y (2005) Nox4 is critical for hypoxia‐inducible factor 2‐alpha transcriptional activity in von Hippel‐Lindau‐deficient renal cell carcinoma. Cancer Res 65: 9190– 9193 16230378 PMC1459967
  22. [25]Choudhry H, Schödel J, Oikonomopoulos S, Camps C, Grampp S, Harris AL, Ratcliffe PJ, Ragoussis J, Mole DR (2014) Extensive regulation of the non‐coding transcriptome by hypoxia: role of HIF in releasing paused RNApol2. EMBO Rep 15: 70– 76 24363272 PMC3983684
  23. [27]Gordan JD, Bertout JA, Hu CJ, Diehl JA, Simon MC (2007) HIF‐2alpha promotes hypoxic cell proliferation by enhancing c‐myc transcriptional activity. Cancer Cell 11: 335– 347 17418410 PMC3145406
  24. [29]Sahlgren C, Gustafsson MV, Jin S, Poellinger L, Lendahl U (2008) Notch signaling mediates hypoxia‐induced tumor cell migration and invasion. Proc Natl Acad Sci USA 105: 6392– 6397 18427106 PMC2359811
  25. [30]Chen W, Hill H, Christie A, Kim MS, Holloman E, Pavia‐Jimenez A, Homayoun F, Ma Y, Patel N, Yell P et al (2016) Targeting renal cell carcinoma with a HIF‐2 antagonist. Nature 539: 112– 117 27595394 PMC5340502
  26. [31]Cho H, Du X, Rizzi JP, Liberzon E, Chakraborty AA, Gao W, Carvo I, Signoretti S, Bruick RK, Josey JA et al (2016) On‐target efficacy of a HIF‐2alpha antagonist in preclinical kidney cancer models. Nature 539: 107– 111 27595393 PMC5499381
  27. [34]Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W et al (2008) Model‐based analysis of ChIP‐Seq (MACS). Genome Biol 9: R137 18798982 PMC2592715
  28. [35]Hower V, Evans SN, Pachter L (2011) Shape‐based peak identification for ChIP‐Seq. BMC Bioinformatics 12: 15 21226895 PMC3032669
  29. [37]Myers RM, Stamatoyannopoulos J, Snyder M, Dunham I, Hardison RC, Bernstein BE, Gingeras TR, Kent WJ, Birney E, Wold B et al (2011) A user's guide to the encyclopedia of DNA elements (ENCODE). PLoS Biol 9: e1001046 21526222 PMC3079585
  30. [38]Lee MG, Villa R, Trojer P, Norman J, Yan KP, Reinberg D, Di Croce L, Shiekhattar R (2007) Demethylation of H3K27 regulates polycomb recruitment and H2A ubiquitination. Science 318: 447– 450 17761849
  31. [39]Jiang BH, Semenza GL, Bauer C, Marti HH (1996) Hypoxia‐inducible factor 1 levels vary exponentially over a physiologically relevant range of O2 tension. Am J Physiol 271: C1172– C1180 8897823
  32. [40]Platt JL, Salama R, Smythies J, Choudhry H, Davies JO, Hughes JR, Ratcliffe PJ, Mole DR (2016) Capture‐C reveals preformed chromatin interactions between HIF‐binding sites and distant promoters. EMBO Rep 17: 1410– 1421 27506891 PMC5048371
  33. [41]Racusen LC, Monteil C, Sgrignoli A, Lucskay M, Marouillat S, Rhim JG, Morin JP (1997) Cell lines with extended in vitro growth potential from human renal proximal tubule: characterization, response to inducers, and comparison with established cell lines. J Lab Clin Med 129: 318– 329 9042817
  34. [44]Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, 1000 Genome Project Data Processing Subgroup (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics 25: 2078– 2079 19505943 PMC2723002
  35. [45]Dale RK, Pedersen BS, Quinlan AR (2011) Pybedtools: a flexible Python library for manipulating genomic datasets and annotations. Bioinformatics 27: 3423– 3424 21949271 PMC3232365
  36. [47]Shen L, Shao N, Liu X, Nestler E (2014) ngs.plot: quick mining and visualization of next‐generation sequencing data by integrating genomic databases. BMC Genom 15: 284 PMC4028082 24735413
  37. [48]Anders S, Pyl PT, Huber W (2015) HTSeq‐a Python framework to work with high‐throughput sequencing data. Bioinformatics 31: 166– 169 25260700 PMC4287950
  38. [49]Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA‐seq data with DESeq2. Genome Biol 15: 550 25516281 PMC4302049
  39. [51]Xiao Y, Hsiao TH, Suresh U, Chen HI, Wu X, Wolf SE, Chen Y (2014) A novel significance score for gene selection and ranking. Bioinformatics 30: 801– 807 22321699 PMC3957066

Authors
Smythies, J. A., Sun, M., Masson, N., Salama, R., Simpson, P. D., Murray, E., Neumann, V., Cockman, M. E., Choudhry, H., Ratcliffe, P. J., & Mole, D. R.
Affiliations
  • University of Oxford (GB)
  • The Francis Crick Institute (GB)
  • King Abdulaziz University (SA)
Corresponding author
  • Ratcliffe, Peter J
  • Mole, David R
Venue
The EMBO Reports
Published
2018-11-14
Volume
20
Issue
1
ISSN
  • 1469-221X (ISSN-L)
  • 1469-3178
OpenAlex
W2901273371
Cited by
195
References
53
Citations by year
2026: 14 · 2025: 26 · 2024: 19 · 2023: 26 · 2022: 38 · 2021: 24 · 2020: 31 · 2019: 17
FWCI
5.44
Type
journal article
Language
en
Open access
Locations
  • EMBO Reports (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Figshare (submittedVersion, cc-by)
  • The Francis Crick Institute (cc-by)
Funders
  • Cancer Research UK (A416016, FC001501)
  • DH | National Institute for Health Research (NIHR‐RP‐2016‐06‐004)
  • The Deanship of Scientific Research, KAU, Ministry of High Education for Saudi Arabia
  • Wellcome Trust (088182/Z/09/Z, 078333/Z/05/Z, WT091857MA, 203141/Z/16/Z, FC001501)
  • Ludwig Institute for Cancer Research
  • UK Medical Research Council (FC001501)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
Keywords
hypoxia-inducible factor, HIF-1α, HIF-2α, DNA binding specificity, transcription factor binding sites, hypoxia, cell type-specific binding, transcriptional regulation
MeSH terms
Endothelial PAS Domain-Containing Protein 1, Cell Line, Chromatin, DNA, DNA-Binding Proteins, Gene Expression Regulation, Humans, Promoter Regions, Genetic, Transcription, Genetic, Cell Hypoxia, Protein Isoforms, Basic Helix-Loop-Helix Proteins, Basic Helix-Loop-Helix Transcription Factors, Hypoxia-Inducible Factor 1, alpha Subunit, Epigenomics

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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review