CoChat
Sign Up
Cited by 1,230Genomics and Chromatin DynamicsChromatin Remodeling and CancerEpigenetics and DNA Methylation

The chromatin accessibility landscape of primary human cancers

Open access
Corces, M. Ryan, Granja, Jeffrey M., Shams, Shadi, Louie, Bryan H., Seoane, Jose A., Zhou, Wanding, Silva, Tiago C., Groeneveld, Clarice +54 more·2018·Science
DOI 10.1126/science.aav1898PMC PMC6408149
Open this paper in CoChat — free account

Abstract

Cancer chromatin accessibility landscape: The Cancer Genome Atlas (TCGA) provides a high-quality resource of molecular data on a large variety of human cancers. Corces et al. used a recently modified assay to profile chromatin accessibility to determine the accessible chromatin landscape in 410 TCGA samples from 23 cancer types (see the Perspective by Taipale). When the data were integrated with other omics data available for the same tumor samples, inherited risk loci for cancer predisposition were revealed, transcription factors and enhancers driving molecular subtypes of cancer with patient survival differences were identified, and noncoding mutations associated with clinical prognosis were discovered. Science , this issue p. eaav1898 ; see also p. 401

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 · 10.1126/science.aav1898

Cites

19 of 19 references verified0 citation errors · 0 not checkable

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?

  • Open chromatin regions are not limited to active enhancers, and also harbour active gene promoters, regulatory elements in a poised chromatin configuration, and some structural regions such as tissue-invariant binding sites for CTCF.

    “However, open chromatin regions are not limited to active enhancers, and also harbour other regions including active gene promoters, regulatory elements in a ‘poised’ chromatin configuration (discussed below), as well as some structural regions such as tissue-invariant binding sites for the architectural protein CCCTC-binding factor (CTCF) [129–132].”

    From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [129]

    The Results section on DNA regulatory elements reports that accessible chromatin sites are strongly enriched in promoter and enhancer regions. The Discussion suggests that some sites of differential accessibility may reflect poised promoters or enhancers, but does not establish this directly. The Results mention accessibility at CTCF motif sites, but do not identify tissue-invariant CTCF binding sites as open structural regions. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • A majority of TCs (90%) were supported by FANTOM5 CAGE peaks and/or open chromatin regions from ENCODE and TCGA.

    “A majority of TCs (90%) were supported by FANTOM5 CAGE peaks17 and/or open chromatin regions from ENCODE22 and TCGA7”

    From Alternative promoters in CpG depleted regions are prevalently associated with epigenetic misregulation of liver cancer transcriptomes (2023) · cites this paper as [7]

Self-check

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

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

Cites

Flagged first, then by citations

Research works printed but not linked: 58

  1. [1]Hutter C, Zenklusen JC, The Cancer Genome Atlas: Creating Lasting Value beyond Its Data. Cell. 173, 283– 285 (2018). 29625045
  2. [4]Egeblad M, Nakasone ES, Werb Z, Tumors as organs: Complex tissues that interface with the entire organism. Dev. Cell. 18, 884– 901 (2010). 20627072 PMC2905377
  3. [6]Almamun M, Integrated methylome and transcriptome analysis reveals novel regulatory elements in pediatric acute lymphoblastic leukemia. Epigenetics. 10, 882– 890 (2015). 26308964 PMC4622668
  4. [7]He Y, Improved regulatory element prediction based on tissue-specific local epigenomic signatures. Proc. Natl. Acad. Sci. 114, E1633– E1640 (2017). 28193886 PMC5338528
  5. [8]Yao L, Shen H, Laird PW, Farnham PJ, Berman BP, Inferring regulatory element landscapes and transcription factor networks from cancer methylomes. Genome Biol. 16, 1– 21 (2015). 25994056 PMC4460959
  6. [9]Ceccarelli M, Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma. Cell. 164, 550– 563 (2016). 26824661 PMC4754110
  7. [10]Noushmehr H, Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of Glioma. Cancer Cell. 17, 510– 522 (2010). 20399149 PMC2872684
  8. [11]Hinoue T, Genome-scale analysis of aberrant DNA methylation in colorectal cancer. Cancer Res. 71, 271– 282 (2011). PMC3266034 21659424
  9. [14]Akhtar-zaidi B, Epigenomic Enhancer Profiling Defines a Signature of Colon Cancer. Science. 336, 736– 740 (2012). 22499810 PMC3711120
  10. [15]Chen H, A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples. Cell. 173, 386– 399. e12 (2018). 29625054 PMC5890960
  11. [16]Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ, Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods. 10, 1213– 1218 (2013). 24097267 PMC3959825
  12. [17]Corces MR, An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods. 14, 959– 962 (2017). 28846090 PMC5623106
  13. [19]Schuijers J, Transcriptional Dysregulation of MYC Reveals Common Enhancer-Docking Mechanism. Cell Rep. 23, 349– 360 (2018). 29641996 PMC5929158
  14. [20]Audrey G, A Switch Between Topological Domains Underlies HoxD Genes Collinearity in Mouse Limbs. Science. 340, 1195 (2012). 23744951
  15. [21]Yeager M, Genome-wide association study of prostate cancer identifies a second risk locus at 8q24. Nat. Genet. 39, 645– 649 (2007). 17401363
  16. [22]Tomlinson IPM, A genome-wide association study identifies colorectal cancer susceptibility loci on chromosomes 10p14 and 8q23.3. Nat. Genet. 40, 623– 630 (2008). 18372905
  17. [23]Sur IK, Mice lacking a Myc enhancer that includes human SNP rs6983267 are resistant to intestinal tumors. Science. 338, 1360– 1363 (2012). 23118011
  18. [24]Thurman RE, The accessible chromatin landscape of the human genome. Nature. 489, 75– 82 (2012). 22955617 PMC3721348
  19. [25]Corces MR, Lineage-specific and single cell chromatin accessibility charts human hematopoiesis and leukemia evolution. Nat. Genet. 48, 1193– 1203 (2016). 27526324 PMC5042844
  20. [27]Rodriguez A, Laio A, Clustering By Fast Search and Find of Desity Peaks. Science. 344, 1492– 1496 (2014). 24970081
  21. [29]Kulis M, Whole-genome fingerprint of the DNA methylome during human B cell differentiation. Nat. Genet. 47, 746– 756 (2015). 26053498 PMC5444519
  22. [30]Kim HS, Pluripotency factors functionally premark cell-type-restricted enhancers in ES cells. Nature. 556, 510– 514 (2018). 29670286 PMC6021123
  23. [31]Shen H, Integrated Molecular Characterization of Testicular Germ Cell Tumors. Cell Rep. 23, 3392– 3406 (2018). 29898407 PMC6075738
  24. [32]Werner S, Dual roles of the transcription factor grainyhead-like 2 (GRHL2) in breast cancer. J. Biol. Chem. 288, 22993– 23008 (2013). 23814079 PMC3743475
  25. [33]Denny SK, Nfib Promotes Metastasis through a Widespread Increase in Chromatin Accessibility. Cell. 166, 328– 342 (2016). 27374332 PMC5004630
  26. [34]Baek S, Goldstein I, Hager GL, Bivariate Genomic Footprinting Detects Changes in Transcription Factor Activity. Cell Rep. 19, 1710– 1722 (2017). 28538187 PMC5530758
  27. [37]Ellis T, The transcriptional repressor CDP (Cutl1) is essential for epithelial cell differentiation of the lung and the hair follicle. Genes Dev. 15, 2307– 2319 (2001). 11544187 PMC312776
  28. [41]Eom YH, Kim HS, Lee A, Song BJ, Chae BJ, Breast Cancer BCL2 as a Subtype-Specific Prognostic Marker for Breast Cancer. 19, 252– 260 (2016). PMC5053309 27721874
  29. [42]Cho SW, Promoter of lncRNA Gene PVT1 Is a Tumor-Suppressor DNA Boundary Element. Cell. 173, 1398– 1412. e22 (2018). 29731168 PMC5984165
  30. [43]Silva TC, Enhancer Linking by Methylation/Expression Relationships with the R package ELMER version 2. bioRxiv (2017) (available at http://biorxiv.org/content/early/2017/06/11/148726. abstract).
  31. [44]Robertson AG, Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer. Cell. 171, 540– 556 (2017). 28988769 PMC5687509
  32. [45]Castro MAA, Regulators of genetic risk of breast cancer identified by integrative network analysis. Nat. Genet. 48, 12– 21 (2015). 26618344 PMC4697365
  33. [46]Thorsson V, The Immune Landscape of Cancer. Immunity. 48, 812– 830. e14 (2018). 29628290 PMC5982584
  34. [47]Yoshihara K, Inferring tumour purity and stromal and immune cell admixture from expression data. Nat. Commun. 4, 1– 11 (2013). PMC3826632 24113773
  35. [48]Carter SL, Absolute quantification of somatic DNA alterations in human cancer. Nat. Biotechnol. 30, 413 (2012). 22544022 PMC4383288
  36. [50]Makowski MM, An interaction proteomics survey of transcription factor binding at recurrent TERT promoter mutations. Proteomics. 16, 417– 426 (2016). 26553150
  37. [51]Katainen R, CTCF/cohesin-binding sites are frequently mutated in cancer. Nat. Genet. 47, 818– 821 (2015). 26053496
  38. [53]Hawkins RD, Distinct epigenomic landscapes of pluripotent and lineage-committed human cells. Cell Stem Cell. 6, 479– 491 (2010). 20452322 PMC2867844
  39. [54]Kelly TK, Genome-wide mapping of nucleosome positioning and DNA methylation within individual DNA molecules. Genome Res, 2497– 2506 (2012). 22960375 PMC3514679
  40. [55]Mo A, Epigenomic Signatures of Neuronal Diversity in the Mammalian Brain. Neuron. 86, 1369– 1384 (2015). 26087164 PMC4499463
  41. [56]Picelli S, Tn5 transposase and tagmentation procedures for massively scaled sequencing projects. Genome Res. 24, 2033– 2040 (2014). 25079858 PMC4248319
  42. [57]Buenrostro JD, Wu B, Chang HY, Greenleaf WJ, ATAC-seq: A Method for Assaying Chromatin Accessibility Genome-Wide. Curr. Protoc. Mol. Biol. 109, 1– 9 (2015). PMC4374986 25559105
  43. [59]Perez AR, GuideScan software for improved single and paired CRISPR guide RNA design. Nat. Biotechnol. 35, 347– 349 (2017). 28263296 PMC5607865
  44. [60]Jiang H, Lei R, Ding SW, Zhu S, Skewer: A fast and accurate adapter trimmer for next-generation sequencing paired-end reads. BMC Bioinformatics. 15, 1– 12 (2014). 24925680 PMC4074385
  45. [61]Langmead B, Salzberg SL, Fast gapped-read alignment with Bowtie 2. Nat. Methods. 9, 357– 359 (2012). 22388286 PMC3322381
  46. [63]Korn JM, Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs. Nat. Genet. 40, 1253– 1260 (2008). 18776909 PMC2756534
  47. [64]Newton Y, TumorMap: Exploring the molecular similarities of cancer samples in an interactive portal. Cancer Res. 77, e111– e114 (2017). 29092953 PMC5751940
  48. [65]Weirauch MT, Determination and Inference of Eukaryotic Transcription Factor Sequence Specificity. Cell. 158, 1431– 1443 (2014). 25215497 PMC4163041
  49. [66]Du P, Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics. 11, 1– 9 (2010). 21118553 PMC3012676
  50. [67]Gendoo DMA, Genefu: An R/Bioconductor package for computation of gene expression-based signatures in breast cancer. Bioinformatics. 32, 1097– 1099 (2016). 26607490 PMC6410906
  51. [68]Ali HR, Genome-driven integrated classification of breast cancer validated in over 7, 500 samples. Genome Biol. 15, 1– 14 (2014). PMC4166472 25164602
  52. [69]Wirapati P, Meta-analysis of gene expression profiles in breast cancer: Toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 10, 1– 11 (2008). PMC2575538 18662380
  53. [70]Bernard PS, Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. 27, 1160– 1167 (2009). 19204204 PMC2667820
  54. [71]Ciriello G, Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer. Cell. 163, 506– 519 (2015). 26451490 PMC4603750
  55. [74]Fletcher MNC, Master regulators of FGFR2 signalling and breast cancer risk. Nat. Commun. 4, 1– 12 (2013). PMC3778544 24043118
  56. [75]Liu J, An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell. 173, 400– 416. e11 (2018). 29625055 PMC6066282
  57. [76]Zhou W, Triche TJ, Laird PW, Shen H, SeSAMe: reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions. Nucleic Acids Res, 1– 15 (2018). 30085201 PMC6237738
  58. [78]Machiela MJ, Chanock SJ, LDlink: A web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. Bioinformatics. 31, 3555– 3557 (2015). 26139635 PMC4626747

Cited by

Sorted by citations

Authors
Corces, M. R., Granja, J. M., Shams, S., Louie, B. H., Seoane, J. A., Zhou, W., Silva, T. C., Groeneveld, C., Wong, C. K., Cho, S. W., Satpathy, A. T., Mumbach, M. R., Hoadley, K. A., Robertson, A. G., Sheffield, N. C., Felau, I., Castro, M. A. A., Berman, B. P., Staudt, L. M., Zenklusen, J. C., Laird, P. W., Curtis, C., The Cancer Genome Atlas Analysis Network, Greenleaf, W. J., Chang, H. Y., Akbani, R., Benz, C. C., Boyle, E. A., Broom, B. M., Cherniack, A. D., Craft, B., Demchok, J. A., Doane, A. S., Elemento, O., Ferguson, M. L., Goldman, M. J., Hayes, D. N., He, J., Hinoue, T., Imielinski, M., Jones, S. J. M., Kemal, A., Knijnenburg, T. A., Korkut, A., Lin, D.-C., Liu, Y., Mensah, M. K. A., Mills, G. B., Reuter, V. P., Schultz, A., Shen, H., Smith, J. P., Tarnuzzer, R., Trefflich, S., Wang, Z., Weinstein, J. N., Westlake, L. C., Xu, J., Yang, L., Yau, C., Zhao, Y., & Zhu, J.
Affiliations
  • Stanford University (US)
  • Stanford Medicine (US)
  • Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Van Andel Institute (US)
  • Cedars-Sinai Medical Center (US)
  • Universidade Federal do Paraná (BR)
  • University of California, Santa Cruz (US)
  • University of North Carolina at Chapel Hill (US)
  • BC Cancer Agency (CA)
  • University of Virginia (US)
  • National Institutes of Health (US)
  • Chan Zuckerberg Biohub San Francisco (US)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Corces, M. Ryan
  • Granja, Jeffrey M.
  • Greenleaf, William J.
  • Chang, Howard Y.
ORCID
Venue
Science
Publisher
American Association for the Advancement of Science (AAAS)
Published
2018-10-26
Volume
362
Issue
6413
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
DOI
10.1126/science.aav1898
PMC
PMC6408149
OpenAlex
W2898215009
Cited by
1,230
References
19
Citations by year
2026: 142 · 2025: 148 · 2024: 168 · 2023: 183 · 2022: 179 · 2021: 193 · 2020: 138 · 2019: 67 · 2018: 9
FWCI
37.71
Type
journal article
Language
en
Open access
Locations
  • Science (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
  • Scholarworks@UNIST (Ulsan National Institute of Science and Technology) (submittedVersion)
  • UNC Libraries
Funders
National Institutes of Health (R35-CA209919, P50-HG007735, K99-AG059918, 1U24CA210974-01, 1U24CA210949-01, 1U24CA210978-01, 1U24CA210952-01, 1U24CA210989-01, 1U24CA210990-01, 1U24CA210950-01, 1U24CA210988-01, 1U24CA210969-01)
Topics
  • 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
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
Keywords
chromatin accessibility, cancer, cis-regulatory elements, distal enhancers, transcription factors, long-range gene regulation, tumor molecular subtypes, tumor immune evasion, non-coding mutations, enhancer activation, patient survival, non-coding genome
MeSH terms
Chromatin, Enhancer Elements, Genetic, Humans, Immunity, Neoplasms, Regulatory Sequences, Nucleic Acid, Transcription Factors, Gene Expression Regulation, Neoplastic, DNA Footprinting, Transposases, Genetic Predisposition to Disease, Genetic Loci

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