The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Glycoproteomic Analysis of Prostate Cancer Tissues by SWATH Mass Spectrometry Discovers N-acylethanolamine Acid Amidase and Protein Tyrosine Kinase 7 as Signatures for Tumor Aggressiveness
Open accessAbstract
The identification of biomarkers indicating the level of aggressiveness of prostate cancer (PCa) will address the urgent clinical need to minimize the general overtreatment of patients with non-aggressive PCa, who account for the majority of PCa cases. Here, we isolated formerly N-linked glycopeptides from normal prostate (n = 10) and from non-aggressive (n = 24), aggressive (n = 16), and metastatic (n = 25) PCa tumor tissues and analyzed the samples using SWATH mass spectrometry, an emerging data-independent acquisition method that generates a single file containing fragment ion spectra of all ionized species of a sample. The resulting datasets were searched using a targeted data analysis strategy in which an a priori spectral reference library representing known N-glycosites of the human proteome was used to identify groups of signals in the SWATH mass spectrometry data. On average we identified 1430 N-glycosites from each sample. Out of those, 220 glycoproteins showed significant quantitative changes associated with diverse biological processes involved in PCa aggressiveness and metastasis and indicated functional relationships. Two glycoproteins, N-acylethanolamine acid amidase and protein tyrosine kinase 7, that were significantly associated with aggressive PCa in the initial sample cohort were further validated in an independent set of patient tissues using tissue microarray analysis. The results suggest that N-acylethanolamine acid amidase and protein tyrosine kinase 7 may be used as potential tissue biomarkers to avoid overtreatment of non-aggressive PCa.
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.
Integrity signals
Registry
Cites
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.
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
SignalP 4.0: discriminating signal peptides from transmembrane regions
Petersen, T. N., Brunak, S., von Heijne, G., & Nielsen, H. (2011) · Nature Methods · doi:10.1038/nmeth.1701 · Cited by 8,847
Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925
Gillet, L. C., Navarro, P., Tate, S., Röst, H., Selevsek, N., Reiter, L., Bonner, R., & Aebersold, R. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o111.016717 · Cited by 2,877
Self-citationThe mutational landscape of lethal castration-resistant prostate cancer
Grasso, C. S., Wu, Y.-M., Robinson, D. R., Cao, X., Dhanasekaran, S. M., Khan, A. P., Quist, M. J., Jing, X., Lonigro, R. J., Brenner, J. C., et al. (2012) · Nature · doi:10.1038/nature11125 · Cited by 2,517
ProteoWizard: open source software for rapid proteomics tools development
Kessner, D., Chambers, M., Burke, R., Agus, D., & Mallick, P. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn323 · Cited by 2,024
Microarray data normalization and transformation
Quackenbush, J. (2002) · Nature Genetics · doi:10.1038/ng1032 · Cited by 1,975
mProphet: automated data processing and statistical validation for large-scale SRM experiments
Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Brusniak, M.-Y., Hengartner, M. O., & Aebersold, R. (2011) · Nature Methods · doi:10.1038/nmeth.1584 · Cited by 532
Self-citationLambert, J.-P., Ivosev, G., Couzens, A. L., Larsen, B., Taipale, M., Lin, Z.-Y., Zhong, Q., Lindquist, S., Vidal, M., Aebersold, R., et al. (2013) · Nature Methods · doi:10.1038/nmeth.2702 · Cited by 318
Self-citationCollins, B. C., Gillet, L. C., Rosenberger, G., Röst, H. L., Vichalkovski, A., Gstaiger, M., & Aebersold, R. (2013) · Nature Methods · doi:10.1038/nmeth.2703 · Cited by 314
Self-citationOn the uniform generation of random graphs with prescribed degree sequences
Milo, R., Kashtan, N., Itzkovitz, S., Newman, M. E. J., & Alon, U. (2003) · arXiv · doi:10.48550/arxiv.cond-mat/0312028 · Cited by 281
Cited by
Quantitative variability of 342 plasma proteins in a human twin population
Liu, Y., Buil, A., Collins, B. C., Gillet, L. C., Blum, L. C., Cheng, L., Vitek, O., Mouritsen, J., Lachance, G., Spector, T. D., et al. (2015) · Molecular Systems Biology · doi:10.15252/msb.20145728 · Cited by 328
Self-citationDual targeting of p53 and c-MYC selectively eliminates leukaemic stem cells
Abraham, S. A., Hopcroft, L. E. M., Carrick, E., Drotar, M. E., Dunn, K., Williamson, A. J. K., Korfi, K., Baquero, P., Park, L. E., Scott, M. T., et al. (2016) · Nature · doi:10.1038/nature18288 · Cited by 225
Applications of targeted proteomics in systems biology and translational medicine
Ebhardt, H. A., Root, A., Sander, C., & Aebersold, R. (2015) · PROTEOMICS · doi:10.1002/pmic.201500004 · Cited by 184
Self-citationMeyer, J. G., & Schilling, B. (2017) · Expert Review of Proteomics · doi:10.1080/14789450.2017.1322904 · Cited by 151
Metadata
- Authors
- Liu, Y., Chen, J., Sethi, A., Li, Q. K., Chen, L., Collins, B., Gillet, L. C. J., Wollscheid, B., Zhang, H., & Aebersold, R.
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2014-07
- Volume
- 13
- Issue
- 7
- Pages
- 1753-1768
- ISSN
- 1535-9476 (ISSN-L)
- OpenAlex
- W2098364431
- Cited by
- 190
- References
- 11
- FWCI
- 10.95
- Type
- journal article
- Language
- en
- Open access
- hybrid
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Glycoproteomic Analysis of Prostate Cancer Tissues by SWATH Mass Spectrometry Discovers N-acylethanolamine Acid Amidase and Protein Tyrosine Kinase 7 as Signatures for Tumor Aggressiveness. https://app.cochat.ai/papers/10.1074/mcp.m114.038273
- The paper
- Liu, Y., Chen, J., Sethi, A., Li, Q. K., Chen, L., Collins, B., Gillet, L. C. J., Wollscheid, B., Zhang, H., & Aebersold, R. (2014). Glycoproteomic Analysis of Prostate Cancer Tissues by SWATH Mass Spectrometry Discovers N-acylethanolamine Acid Amidase and Protein Tyrosine Kinase 7 as Signatures for Tumor Aggressiveness. Molecular & Cellular Proteomics. https://doi.org/10.1074/mcp.m114.038273
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.