The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
How Industry Is Approaching the Search for New Diagnostic Markers and Biomarkers
Open accessAbstract
In the diagnostic and the pharmaceutical industry there is a constant need for new diagnostic markers and biomarkers with improved sensitivity and specificity. During the last 5 years, only a few novel diagnostic markers have been introduced into the market. Proteomics technologies are now offering unique chances to identify new candidate markers. Before a marker can be introduced into the market, three successive developmental phases have to be completed: the discovery phase, in which a variety of proteomics technologies are applied to identify marker candidates; the prototype developmental phase, in which immunological assays are established and validated in defined sample collectives; and finally the product development phase, with assay formats suitable for automated platforms. The hurdles that a potential candidate marker has to pass in each developmental phase before reaching the market are considerable. The costs are increasing from phase to phase, and in industry a number of questions concerning the medical need and the potential return on investment have to be answered before a proteomics discovery project is started. In this review, we will cover aspects of all three developmental phases including the repertoire of discovery tools for protein separation as well as giving an outline of modern principles of mass spectrometry for the identification of proteins.
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
Electrospray Ionization for Mass Spectrometry of Large Biomolecules
Fenn, J. B., Mann, M., Meng, C. K., Wong, S. F., & Whitehouse, C. M. (1989) · Science · doi:10.1126/science.2675315 · Cited by 7,634
Anderson, N. L., & Anderson, N. G. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r200007-mcp200 · Cited by 4,414
Use of proteomic patterns in serum to identify ovarian cancer
Petricoin, E. F., Ardekani, A. M., Hitt, B. A., Levine, P. J., Fusaro, V. A., Steinberg, S. M., Mills, G. B., Simone, C., Fishman, D. A., Kohn, E. C., et al. (2002) · The Lancet · doi:10.1016/s0140-6736(02)07746-2 · Cited by 3,236
Molecular Imaging of Biological Samples: Localization of Peptides and Proteins Using MALDI-TOF MS
Caprioli, R. M., Farmer, T. B., & Gile, J. (1997) · Analytical Chemistry · doi:10.1021/ac970888i · Cited by 2,234
Large-Scale Delineation of Secreted Protein Biomarkers Overexpressed in Cancer Tissue and Serum
Welsh, J. B., Sapinoso, L. M., Kern, S. G., Brown, D. A., Liu, T., Bauskin, A. R., Ward, R. L., Hawkins, N. J., Quinn, D. I., Russell, P. J., et al. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0530278100 · Cited by 503 · cited 2×
“Genchips—In several recent studies, cDNA microarray analysis has revealed significantly elevated expression of the prostasin and osteopontin genes in ovarian cancers, and correspondingly high levels of these proteins have subsequently been detected in the serum of ovarian cancer patients (35).”
Background
Cited by
Biomarkers of Cardiovascular Disease: Molecular Basis and Practical Considerations
Vasan, R. S. (2006) · Circulation · doi:10.1161/circulationaha.104.482570 · Cited by 1,212
Navigating Challenges and Opportunities in Multi-Omics Integration for Personalized Healthcare
Mohr, A. E., Ortega-Santos, C. P., Whisner, C. M., Klein-Seetharaman, J., & Jasbi, P. (2024) · Biomedicines · doi:10.3390/biomedicines12071496 · Cited by 311
Tammen, H., Schulte, I., Hess, R., Menzel, C., Kellmann, M., Mohring, T., & Schulz‐Knappe, P. (2005) · PROTEOMICS · doi:10.1002/pmic.200401219 · Cited by 260
Metadata
- Authors
- Zolg, J. W., & Langen, H.
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2004-04
- Volume
- 3
- Issue
- 4
- Pages
- 345-354
- ISSN
- 1535-9476 (ISSN-L)
- OpenAlex
- W2139090311
- Cited by
- 170
- References
- 5
- FWCI
- 9.79
- 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: How Industry Is Approaching the Search for New Diagnostic Markers and Biomarkers. https://app.cochat.ai/papers/10.1074/mcp.m400007-mcp200
- The paper
- Zolg, J. W., & Langen, H. (2004). How Industry Is Approaching the Search for New Diagnostic Markers and Biomarkers. Molecular & Cellular Proteomics. https://doi.org/10.1074/mcp.m400007-mcp200
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.