CoChat
Sign Up
Cited by 13

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Proteomics characterisation of central nervous system metastasis biomarkers in triple negative breast cancer

Rojas, Katerin L, Trilla-Fuertes, Lucía, Gámez-Pozo, Angelo, Chiva, Cristina, Sepúlveda, Juan, Manso, Luis, Prado-Vázquez, Guillermo, Zapater-Moros, Andrea, López-Vacas, Rocío, Ferrer-Gómez, María, Mendiola, César, Espinosa, Enrique, Sabidó, Eduard, Ciruelos, Eva, Fresno Vara, Juan Ángel·2019·ecancermedicalscience
DOI 10.3332/ecancer.2019.891PMC PMC6369972
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 · 10.3332/ecancer.2019.891

Cites

2 of 2 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

Flagged first, then by citations

Research works printed but not linked: 28

  1. [1]Lehmann BD Bauer JA Chen X Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies J Clin Invest 2011 121 7 2750 2767 10.1172/JCI45014 21633166 PMC3127435 · DOI · Paper page
  2. [2]Lachapelle J Foulkes WD Triple-negative and basal-like breast cancer: implications for oncologists Curr Oncol 2011 18 4 161 164 10.3747/co.v18i4.824 21874112 PMC3149541 · DOI
  3. [3]Heitz F Harter P Lueck HJ Triple-negative and HER2-overexpressing breast cancers exhibit an elevated risk and an earlier occurrence of cerebral metastases Eur J Cancer 2009 45 16 2792 2798 10.1016/j.ejca.2009.06.027 19643597 · DOI
  4. [4]Bos PD Zhang XH Nadal C Genes that mediate breast cancer metastasis to the brain Nature 2009 459 7249 1005 1009 10.1038/nature08021 19421193 PMC2698953 · DOI · Paper page
  5. [5]Laimito KR Gámez-Pozo A Sepúlveda J Characterisation of the triple negative breast cancer phenotype associated with the development of central nervous system metastases Ecancermedicalscience 2016 10 632 27170832 PMC4854224
  6. [6]Gámez-Pozo A Berges-Soria J Arevalillo JM Combined label-free quantitative proteomics and microRNA expression analysis of breast cancer unravel molecular differences with clinical implications Cancer Res 2015 75 11 2243 2253 10.1158/0008-5472.CAN-14-1937 25883093 · DOI
  7. [7]Gámez-Pozo A Trilla-Fuertes L Berges-Soria J Functional proteomics outlines the complexity of breast cancer molecular subtypes Scientific Reports 2017 7 1 10100 10.1038/s41598-017-10493-w 28855612 PMC5577137 · DOI
  8. [8]Gámez-Pozo A Trilla-Fuertes L Prado-Vázquez G Prediction of adjuvant chemotherapy response in triple negative breast cancer with discovery and targeted proteomics PLoS One 2017 12 6 e0178296 10.1371/journal.pone.0178296 28594844 PMC5464546 · DOI
  9. [9]Bernhardt S Bayerlová M Vetter M Proteomic profiling of breast cancer metabolism identifies SHMT2 and ASCT2 as prognostic factors Breast Cancer Res 2017 19 1 112 10.1186/s13058-017-0905-7 29020998 PMC5637318 · DOI
  10. [11]Gallien S Kim SY Domon B Large-Scale targeted proteomics using internal standard triggered-parallel reaction monitoring (IS-PRM) Mol Cell Proteomics 2015 14 6 1630 1644 10.1074/mcp.O114.043968 25755295 PMC4458725 · DOI
  11. [12]Gámez-Pozo A Ferrer NI Ciruelos E Shotgun proteomics of archival triple-negative breast cancer samples Proteomics Clin Appl 2013 7 3–4 283 291 10.1002/prca.201200048 23436753 · DOI
  12. [13]Gámez-Pozo A Sánchez-Navarro I Calvo E Protein phosphorylation analysis in archival clinical cancer samples by shotgun and targeted proteomics approaches Mol Biosyst 2011 7 8 2368 2374 10.1039/c1mb05113j 21617801 · DOI
  13. [14]Vitzthum F Behrens F Anderson NL Proteomics: from basic research to diagnostic application. A review of requirements and needs J Proteome Res 2005 4 4 1086 1097 10.1021/pr050080b 16083257 · DOI
  14. [15]Owhashi M Taoka Y Ishii K Identification of a ubiquitin family protein as a novel neutrophil chemotactic factor Biochem Biophys Res Commun 2003 309 3 533 539 10.1016/j.bbrc.2003.08.038 12963022 · DOI
  15. [16]Desai SD Haas AL Wood LM Elevated expression of ISG15 in tumor cells interferes with the ubiquitin/26S proteasome pathway Cancer Res 2006 66 2 921 928 10.1158/0008-5472.CAN-05-1123 16424026 · DOI
  16. [17]Desai SD ISG15: A double edged sword in cancer Oncoimmunology 2015 4 12 e1052935 10.1080/2162402X.2015.1052935 26587329 PMC4635879 · DOI
  17. [18]Bektas N Noetzel E Veeck J The ubiquitin-like molecule interferon-stimulated gene 15 (ISG15) is a potential prognostic marker in human breast cancer Breast Cancer Res 2008 10 4 R58 10.1186/bcr2117 18627608 PMC2575531 · DOI
  18. [19]Weichselbaum RR Ishwaran H Yoon T An interferon-related gene signature for DNA damage resistance is a predictive marker for chemotherapy and radiation for breast cancer Proc Natl Acad Sci USA 2008 105 47 18490 18495 10.1073/pnas.0809242105 19001271 PMC2587578 · DOI
  19. [20]Desai SD Reed RE Burks J ISG15 disrupts cytoskeletal architecture and promotes motility in human breast cancer cells Exp Biol Med (Maywood) 2012 237 1 38 49 10.1258/ebm.2011.011236 22185919 · DOI
  20. [21]Chen H Herndon ME Lawler J The cell biology of thrombospondin-1 Matrix Biol 2000 19 7 597 614 10.1016/S0945-053X(00)00107-4 11102749 · DOI
  21. [23]Suh EJ Kabir MH Kang UB Comparative profiling of plasma proteome from breast cancer patients reveals thrombospondin-1 and BRWD3 as serological biomarkers Exp Mol Med 2012 44 1 36 44 10.3858/emm.2012.44.1.003 22024541 PMC3277896 · DOI
  22. [24]Yee KO Connolly CM Duquette M The effect of thrombospondin-1 on breast cancer metastasis Breast Cancer Res Treat 2009 114 1 85 96 10.1007/s10549-008-9992-6 18409060 PMC2631620 · DOI
  23. [25]Campone M Valo I Jézéquel P Prediction of recurrence and survival for triple-negative breast cancer (TNBC) by a protein signature in tissue samples Mol Cell Proteomics 2015 14 11 2936 2946 10.1074/mcp.M115.048967 26209610 PMC4638037 · DOI
  24. [26]Hirst J Robinson MS Clathrin and adaptors Biochim Biophys Acta 1998 1404 1–2 173 193 10.1016/S0167-4889(98)00056-1 9714795 · DOI
  25. [27]Kulpa DA Del Cid N Peterson KA Adaptor protein 1 promotes cross-presentation through the same tyrosine signal in major histocompatibility complex class I as that targeted by HIV-1 J Virol 2013 87 14 8085 8098 10.1128/JVI.00701-13 23678182 PMC3700188 · DOI
  26. [28]Miliani de Marval P Lutfeali S Jin JY CYLD inhibits tumorigenesis and metastasis by blocking JNK/AP1 signaling at multiple levels Cancer Prev Res (Phila) 2011 4 6 851 859 10.1158/1940-6207.CAPR-10-0360 21478324 PMC3107906 · DOI
  27. [29]Tham YL Sexton K Kramer R Primary breast cancer phenotypes associated with propensity for central nervous system metastases Cancer 2006 107 696 704 16826579
  28. [30]Samaan NA Buzdar AU Aldinger KA Estrogen receptor: a prognostic factor in breast cancer Cancer 1981 47 554 560 7226005

Cited by

Sorted by citations

Metadata

Authors
Rojas, K. L., Trilla-Fuertes, L., Gámez-Pozo, A., Chiva, C., Sepúlveda, J., Manso, L., Prado-Vázquez, G., Zapater-Moros, A., López-Vacas, R., Ferrer-Gómez, M., Mendiola, C., Espinosa, E., Sabidó, E., Ciruelos, E., & Fresno Vara, J. Á.
Venue
ecancermedicalscience
Publisher
Ecancer Global Foundation
Published
2019-01-15
Volume
13
ISSN
1754-6605
DOI
10.3332/ecancer.2019.891
PMC
PMC6369972
Cited by
13
References
2

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