CoChat
Sign Up
Cited by 1,479

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Integrated genomic and molecular characterization of cervical cancer

The Cancer Genome Atlas Research Network·2017·Nature
DOI 10.1038/nature21386PMC PMC5354998
Open this paper in CoChat — free account

Overview

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 · 10.1038/nature21386

Cites

11 of 11 references verified0 citation errors · 0 not checkable

Statistics

Verification

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?

Self-check

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

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

Citations

Cites

Show all 11 references

Research works printed but not linked: 55

  1. Ferlay, J. et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int. J. Cancer 136, E359–E386 (2015) · DOI · Paper page
  2. Schiffman, M. et al. Human papillomavirus testing in the prevention of cervical cancer. J. Natl. Cancer Inst. 103, 368–383 (2011) · DOI
  3. Uyar, D. & Rader, J. Genomics of cervical cancer and the role of human papillomavirus pathobiology. Clin. Chem. 60, 144–146 (2014) · DOI
  4. Moody, C. A. & Laimins, L. A. Human papillomavirus oncoproteins: pathways to transformation. Nat. Rev. Cancer 10, 550–560 (2010) · DOI
  5. Chung, T. K. H. et al. Genomic aberrations in cervical adenocarcinomas in Hong Kong Chinese women. Int. J. Cancer 137, 776–783 (2015) · DOI
  6. Ojesina, A. I. et al. Landscape of genomic alterations in cervical carcinomas. Nature 506, 371–375 (2014) · DOI
  7. Cancer Genome Atlas Network. Comprehensive molecular characterization of urothelial bladder carcinoma. Nature 507, 315–322 (2014) · DOI
  8. Cancer Genome Atlas Network. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 517, 576–582 (2015) · DOI · Paper page
  9. Burns, M. B., Temiz, N. A. & Harris, R. S. Evidence for APOBEC3B mutagenesis in multiple human cancers. Nat. Genet. 45, 977–983 (2013) · DOI
  10. Henderson, S., Chakravarthy, A., Su, X., Boshoff, C. & Fenton, T. R. APOBEC-mediated cytosine deamination links PIK3CA helical domain mutations to human papillomavirus-driven tumor development. Cell Reports 7, 1833–1841 (2014) · DOI
  11. Roberts, S. A. et al. An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers. Nat. Genet. 45, 970–976 (2013) · DOI
  12. Cancer Genome Atlas Research Network. Integrated genomic analyses of ovarian carcinoma. Nature 474, 609–615 (2011) · DOI · Paper page
  13. The Cancer Genome Atlas Research Network. Integrated genomic characterization of endometrial carcinoma. Nature 497, 67–73 (2013) · DOI · Paper page
  14. Godinho, M. F. E. et al. BCAR4 induces antioestrogen resistance but sensitises breast cancer to lapatinib. Br. J. Cancer 107, 947–955 (2012) · DOI
  15. Shen, R., Olshen, A. B. & Ladanyi, M. Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis. Bioinformatics 25, 2906–2912 (2009) · DOI · Paper page
  16. Byers, L. A. et al. An epithelial–mesenchymal transition gene signature predicts resistance to EGFR and PI3K inhibitors and identifies Axl as a therapeutic target for overcoming EGFR inhibitor resistance. Clin. Cancer Res. 19, 279–290 (2013) · DOI · Paper page
  17. Hsu, S.-D. et al. miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions. Nucleic Acids Res. 42, D78–D85 (2014) · DOI
  18. Akbani, R. et al. A pan-cancer proteomic perspective on The Cancer Genome Atlas. Nat. Commun. 5, 3887 (2014) · DOI
  19. Seton-Rogers, S. Oncogenes: all eyes on YAP1. Nat. Rev. Cancer 14, 514–515 (2014) · DOI
  20. Vandewalle, C., Van Roy, F. & Berx, G. The role of the ZEB family of transcription factors in development and disease. Cell. Mol. Life Sci. 66, 773–787 (2009) · DOI
  21. Ciriello, G., Cerami, E., Sander, C. & Schultz, N. Mutual exclusivity analysis identifies oncogenic network modules. Genome Res. 22, 398–406 (2012) · DOI
  22. Gregory, P. A. et al. The miR-200 family and miR-205 regulate epithelial to mesenchymal transition by targeting ZEB1 and SIP1. Nat. Cell Biol. 10, 593–601 (2008) · DOI
  23. Massagué, J. TGFβ signalling in context. Nat. Rev. Mol. Cell Biol. 13, 616–630 (2012) · DOI
  24. Haslehurst, A. M. et al. EMT transcription factors snail and slug directly contribute to cisplatin resistance in ovarian cancer. BMC Cancer 12, 91 (2012) · DOI
  25. Taube, J. H. et al. Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes. Proc. Natl Acad. Sci. USA 107, 15449–15454 (2010) · DOI
  26. Jaiswal, B. S. et al. Oncogenic ERBB3 mutations in human cancers. Cancer Cell 23, 603–617 (2013) · DOI · Paper page
  27. Sedgewick, A. J., Benz, S. C., Rabizadeh, S., Soon-Shiong, P. & Vaske, C. J. Learning subgroup-specific regulatory interactions and regulator independence with PARADIGM. Bioinformatics 29, i62–i70 (2013) · DOI
  28. Hoadley, K. A. et al. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell 158, 929–944 (2014) · DOI
  29. den Boon, J. A. et al. Molecular transitions from papillomavirus infection to cervical precancer and cancer: role of stromal estrogen receptor signaling. Proc. Natl Acad. Sci. USA 112, E3255–E3264 (2015) · DOI
  30. Roman, A. & Munger, K. The papillomavirus E7 proteins. Virology 445, 138–168 (2013) · DOI
  31. Vande Pol, S. B. & Klingelhutz, A. J. Papillomavirus E6 oncoproteins. Virology 445, 115–137 (2013) · DOI
  32. Dellambra, E. et al. Downregulation of 14-3-3σ prevents clonal evolution and leads to immortalization of primary human keratinocytes. J. Cell Biol. 149, 1117–1130 (2000) · DOI
  33. Moreira, J. M. A., Gromov, P. & Celis, J. E. Expression of the tumor suppressor protein 14-3-3σ is down-regulated in invasive transitional cell carcinomas of the urinary bladder undergoing epithelial-to-mesenchymal transition. Mol. Cell. Proteomics 3, 410–419 (2004) · DOI
  34. Hermeking, H. et al. 14-3-3σ is a p53-regulated inhibitor of G2/M progression. Mol. Cell 1, 3–11 (1997) · DOI · Paper page
  35. Chang, T.-C. et al. 14-3-3σ regulates β-catenin-mediated mouse embryonic stem cell proliferation by sequestering GSK-3β. PLoS One 7, e40193 (2012) · DOI
  36. Wentzensen, N., Vinokurova, S. & von Knebel Doeberitz, M. Systematic review of genomic integration sites of human papillomavirus genomes in epithelial dysplasia and invasive cancer of the female lower genital tract. Cancer Res. 64, 3878–3884 (2004) · DOI · Paper page
  37. Tang, A. L. et al. UM-SCC-104: a new human papillomavirus-16-positive cancer stem cell-containing head and neck squamous cell carcinoma cell line. Head Neck 34, 1480–1491 (2012) · DOI
  38. Chu, J. et al. BioBloom tools: fast, accurate and memory-efficient host species sequence screening using bloom filters. Bioinformatics 30, 3402–3404 (2014) · DOI
  39. Kostic, A. D. et al. PathSeq: software to identify or discover microbes by deep sequencing of human tissue. Nat. Biotechnol. 29, 393–396 (2011) · DOI
  40. Trapnell, C., Pachter, L. & Salzberg, S. L. TopHat: discovering splice junctions with RNA-seq. Bioinformatics 25, 1105–1111 (2009) · DOI
  41. Schiffman, M. et al. A population-based prospective study of carcinogenic human papillomavirus variant lineages, viral persistence, and cervical neoplasia. Cancer Res. 70, 3159–3169 (2010) · DOI
  42. McCarroll, S. A. et al. Integrated detection and population-genetic analysis of SNPs and copy number variation. Nat. Genet. 40, 1166–1174 (2008) · DOI · Paper page
  43. Korn, J. M. et al. Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs. Nat. Genet. 40, 1253–1260 (2008) · DOI · Paper page
  44. Olshen, A. B., Venkatraman, E. S., Lucito, R. & Wigler, M. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 5, 557–572 (2004) · DOI
  45. Mermel, C. H. et al. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biol. 12, R41 (2011) · DOI
  46. Carter, S. L. et al. Absolute quantification of somatic DNA alterations in human cancer. Nat. Biotechnol. 30, 413–421 (2012) · DOI
  47. Chen, K. et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat. Methods 6, 677–681 (2009) · DOI
  48. Yang, L. et al. Diverse mechanisms of somatic structural variations in human cancer genomes. Cell 153, 919–929 (2013) · DOI
  49. Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011) · DOI · Paper page
  50. Carstens, J. L., Lovisa, S. & Kalluri, R. Microenvironment-dependent cues trigger miRNA-regulated feedback loop to facilitate the EMT/MET switch. J. Clin. Invest. 124, 1458–1460 (2014) · DOI
  51. Ceppi, P. & Peter, M. E. MicroRNAs regulate both epithelial-to-mesenchymal transition and cancer stem cells. Oncogene 33, 269–278 (2014) · DOI
  52. Díaz-Martín, J. et al. A core microRNA signature associated with inducers of the epithelial-to-mesenchymal transition. J. Pathol. 232, 319–329 (2014) · DOI
  53. Kiesslich, T., Pichler, M. & Neureiter, D. Epigenetic control of epithelial–mesenchymal-transition in human cancer. Mol. Clin. Oncol. 1, 3–11 (2013) · DOI
  54. Tam, W. L. & Weinberg, R. A. The epigenetics of epithelial–mesenchymal plasticity in cancer. Nat. Med. 19, 1438–1449 (2013) · DOI
  55. Zwiener, I., Frisch, B. & Binder, H. Transforming RNA-seq data to improve the performance of prognostic gene signatures. PLoS One 9, e85150 (2014) · DOI

Cited by

Metadata

Authors
The Cancer Genome Atlas Research Network
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2017-01-23
Volume
543
Issue
7645
Pages
378-384
ISSN
  • 0028-0836
  • 1476-4687
DOI
10.1038/nature21386
PMC
PMC5354998
Cited by
1,479
References
11
Language
en
Licence
creativecommons.org/licenses/by/4.0 (tdm)

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