The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
A Mouse to Human Search for Plasma Proteome Changes Associated with Pancreatic Tumor Development
Open accessAbstract
BACKGROUND: The complexity and heterogeneity of the human plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. Refined genetically engineered mouse (GEM) models of human cancer have been shown to faithfully recapitulate the molecular, biological, and clinical features of human disease. Here, we sought to exploit the merits of a well-characterized GEM model of pancreatic cancer to determine whether proteomics technologies allow identification of protein changes associated with tumor development and whether such changes are relevant to human pancreatic cancer. METHODS AND FINDINGS: Plasma was sampled from mice at early and advanced stages of tumor development and from matched controls. Using a proteomic approach based on extensive protein fractionation, we confidently identified 1,442 proteins that were distributed across seven orders of magnitude of abundance in plasma. Analysis of proteins chosen on the basis of increased levels in plasma from tumor-bearing mice and corroborating protein or RNA expression in tissue documented concordance in the blood from 30 newly diagnosed patients with pancreatic cancer relative to 30 control specimens. A panel of five proteins selected on the basis of their increased level at an early stage of tumor development in the mouse was tested in a blinded study in 26 humans from the CARET (Carotene and Retinol Efficacy Trial) cohort. The panel discriminated pancreatic cancer cases from matched controls in blood specimens obtained between 7 and 13 mo prior to the development of symptoms and clinical diagnosis of pancreatic cancer. CONCLUSIONS: Our findings indicate that GEM models of cancer, in combination with in-depth proteomic analysis, provide a useful strategy to identify candidate markers applicable to human cancer with potential utility for early detection.
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DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988) · Biometrics · doi:10.2307/2531595 · Cited by 22,649
Keller, A., Nesvizhskii, A. I., Kolker, E., & Aebersold, R. (2002) · Analytical Chemistry · doi:10.1021/ac025747h · Cited by 4,830
A Statistical Model for Identifying Proteins by Tandem Mass Spectrometry
Nesvizhskii, A. I., Keller, A., Kolker, E., & Aebersold, R. (2003) · Analytical Chemistry · doi:10.1021/ac0341261 · Cited by 4,809
A gene atlas of the mouse and human protein-encoding transcriptomes
Su, A. I., Wiltshire, T., Batalov, S., Lapp, H., Ching, K. A., Block, D., Zhang, J., Soden, R., Hayakawa, M., Kreiman, G., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400782101 · Cited by 3,475
Hingorani, S. R., Wang, L., Multani, A. S., Combs, C., Deramaudt, T. B., Hruban, R. H., Rustgi, A. K., Chang, S., & Tuveson, D. A. (2005) · Cancer Cell · doi:10.1016/j.ccr.2005.04.023 · Cited by 2,609
Preinvasive and invasive ductal pancreatic cancer and its early detection in the mouse
Hingorani, S. R., Petricoin, E. F., Maitra, A., Rajapakse, V., King, C., Jacobetz, M. A., Ross, S., Conrads, T. P., Veenstra, T. D., Hitt, B. A., et al. (2003) · Cancer Cell · doi:10.1016/s1535-6108(03)00309-x · Cited by 2,471
Genetics and biology of pancreatic ductal adenocarcinoma
Hezel, A. F., Kimmelman, A. C., Stanger, B. Z., Bardeesy, N., & DePinho, R. A. (2006) · Genes & Development · doi:10.1101/gad.1415606 · Cited by 1,577
Self-citationComparison of Label-free Methods for Quantifying Human Proteins by Shotgun Proteomics
Old, W. M., Meyer-Arendt, K., Aveline-Wolf, L., Pierce, K. G., Mendoza, A., Sevinsky, J. R., Resing, K. A., & Ahn, N. G. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500084-mcp200 · Cited by 1,206
Pancreatic cancer biology and genetics
Bardeesy, N., & DePinho, R. A. (2002) · Nature Reviews Cancer · doi:10.1038/nrc949 · Cited by 1,142
Self-citationIdentification and validation of oncogenes in liver cancer using an integrative oncogenomic approach
Zender, L., Spector, M. S., Xue, W., Flemming, P., Cordon-Cardo, C., Silke, J., Fan, S.-T., Luk, J. M., Wigler, M., Hannon, G. J., et al. (2006) · Cell · doi:10.1016/j.cell.2006.05.030 · Cited by 1,065
Cited by
Hidalgo, M. (2010) · New England Journal of Medicine · doi:10.1056/nejmra0901557 · Cited by 2,570
Kleeff, J., Korc, M., Apte, M., La Vecchia, C., Johnson, C. D., Biankin, A. V., Neale, R. E., Tempero, M., Tuveson, D. A., Hruban, R. H., et al. (2016) · Nature Reviews Disease Primers · doi:10.1038/nrdp.2016.22 · Cited by 1,982
Preclinical Mouse Cancer Models: A Maze of Opportunities and Challenges
Day, C.-P., Merlino, G., & Van Dyke, T. (2015) · Cell · doi:10.1016/j.cell.2015.08.068 · Cited by 676
Genetics and biology of pancreatic ductal adenocarcinoma
Ying, H., Dey, P., Yao, W., Kimmelman, A. C., Draetta, G. F., Maitra, A., & DePinho, R. A. (2016) · Genes & Development · doi:10.1101/gad.275776.115 · Cited by 527
Mass spectrometry in high-throughput proteomics: ready for the big time
Nilsson, T., Mann, M., Aebersold, R., Yates, J. R., Bairoch, A., & Bergeron, J. J. M. (2010) · Nature Methods · doi:10.1038/nmeth0910-681 · Cited by 470
Metadata
- Authors
- Faca, V. M., Song, K. S., Wang, H., Zhang, Q., Krasnoselsky, A. L., Newcomb, L. F., Plentz, R. R., Gurumurthy, S., Redston, M. S., Pitteri, S. J., Pereira-Faca, S. R., Ireton, R. C., Katayama, H., Glukhova, V., Phanstiel, D., Brenner, D. E., Anderson, M. A., Misek, D., Scholler, N., Urban, N. D., Barnett, M. J., Edelstein, C., Goodman, G. E., Thornquist, M. D., McIntosh, M. W., DePinho, R. A., Bardeesy, N., & Hanash, S. M.
- Venue
- PLoS Medicine
- Publisher
- Public Library of Science (PLoS)
- Published
- 2008-06-10
- Volume
- 5
- Issue
- 6
- Pages
- e123
- ISSN
- 1549-1277 (ISSN-L)
- 1549-1676
- OpenAlex
- W2156250197
- Cited by
- 257
- References
- 58
- FWCI
- 16.17
- Type
- journal article
- Language
- en
- Open access
- gold
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- Faca, V. M., Song, K. S., Wang, H., Zhang, Q., Krasnoselsky, A. L., Newcomb, L. F., Plentz, R. R., Gurumurthy, S., Redston, M. S., Pitteri, S. J., Pereira-Faca, S. R., Ireton, R. C., Katayama, H., Glukhova, V., Phanstiel, D., Brenner, D. E., Anderson, M. A., Misek, D., Scholler, N., . . . Hanash, S. M. (2008). A Mouse to Human Search for Plasma Proteome Changes Associated with Pancreatic Tumor Development. PLoS Medicine. https://doi.org/10.1371/journal.pmed.0050123
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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