The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
Significance of immunohistochemistry in breast cancer
Open accessAbstract
The biological characteristics of the tumour are used to estimate prognosis and select appropriate systemic therapy for patients with (breast) cancer. The advent of molecular technology has incorporated new biomarkers along with immunohistochemical and serum biomarkers. Immunohistochemical markers are often used to guide treatment decisions, to classify breast cancer into subtypes that are biologically distinct and behave differently, and both as prognostic and predictive factors. Steroid hormone receptors, markers of tumour proliferation, and factors involved in angiogenesis and apoptosis are of scientific interest. In this review we will provide information on the immunohistochemical markers used in the management of breast cancer patients using available data from the literature. We consider the utility of established immunohistochemical markers, and discuss the challenges involved in integrating novel molecular markers into clinical practice.
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
The biology of VEGF and its receptors
Ferrara, N., Gerber, H.-P., & LeCouter, J. (2003) · Nature Medicine · doi:10.1038/nm0603-669 · Cited by 9,591
Wolff, A. C., Hammond, M. E. H., Schwartz, J. N., Hagerty, K. L., Allred, D. C., Cote, R. J., Dowsett, M., Fitzgibbons, P. L., Hanna, W. M., Langer, A., et al. (2007) · Journal of Clinical Oncology · doi:10.1200/jco.2006.09.2775 · Cited by 4,434
Harris, L., Fritsche, H., Mennel, R., Norton, L., Ravdin, P., Taube, S., Somerfield, M. R., Hayes, D. F., & Bast, R. C. (2007) · Journal of Clinical Oncology · doi:10.1200/jco.2007.14.2364 · Cited by 2,217
Prognostic and predictive factors in breast cancer by immunohistochemical analysis.
Allred, D. C., Harvey, J. M., Berardo, M. D., & Gm, C. (1998) · PubMed · Cited by 2,143
Tsujimoto, Y., Finger, L. R., Yunis, J., Nowell, P. C., & Croce, C. M. (1984) · Science · doi:10.1126/science.6093263 · Cited by 1,769
Wolff, A. C., Hammond, M. E. H., Hicks, D. G., Dowsett, M., McShane, L. M., Allison, K. H., Allred, D. C., Bartlett, J. M. S., Bilous, M., Fitzgibbons, P., et al. (2014) · Archives of Pathology and Laboratory Medicine · doi:10.5858/arpa.2013-0953-sa · Cited by 1,762
p53 Status and the Efficacy of Cancer Therapy in Vivo
Lowe, S. W., Bodis, S., McClatchey, A., Remington, L., Ruley, H. E., Fisher, D. E., Housman, D. E., & Jacks, T. (1994) · Science · doi:10.1126/science.7973635 · Cited by 1,469
Ki67 in breast cancer: prognostic and predictive potential
Yerushalmi, R., Woods, R., Ravdin, P. M., Hayes, M. M., & Gelmon, K. A. (2010) · The Lancet Oncology · doi:10.1016/s1470-2045(09)70262-1 · Cited by 1,207
Goldhirsch, A., Glick, J. H., Gelber, R. D., Coates, A. S., Thürlimann, B., & Senn, H.-J. (2005) · Annals of Oncology · doi:10.1093/annonc/mdi326 · Cited by 1,127
Fisher, B., Dignam, J., Wolmark, N., Wickerham, D. L., Fisher, E. R., Mamounas, E., Smith, R., Begovic, M., Dimitrov, N. V., Margolese, R. G., et al. (1999) · The Lancet · doi:10.1016/s0140-6736(99)05036-9 · Cited by 1,040
Cited by
Digital pathology and artificial intelligence
Niazi, M. K. K., Parwani, A. V., & Gurcan, M. N. (2019) · The Lancet Oncology · doi:10.1016/s1470-2045(19)30154-8 · Cited by 1,232
Tumor biomarkers for diagnosis, prognosis and targeted therapy
Zhou, Y., Tao, L., Qiu, J., Xu, J., Yang, X., Zhang, Y., Tian, X., Guan, X., Cen, X., & Zhao, Y. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01823-2 · Cited by 720
Zhang, J., Mu, N., Liu, L., Xie, J., Feng, H., Yao, J., Chen, T., & Zhu, W. (2021) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2021.113241 · Cited by 325
Metadata
- Authors
- Zaha, D. C.
- Venue
- World Journal of Clinical Oncology
- Publisher
- Baishideng Publishing Group Inc.
- Published
- 2014
- Volume
- 5
- Issue
- 3
- Pages
- 382
- ISSN
- 2218-4333 (ISSN-L)
- OpenAlex
- W2049420719
- Cited by
- 277
- References
- 58
- FWCI
- 2.24
- 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: Significance of immunohistochemistry in breast cancer. https://app.cochat.ai/papers/10.5306/wjco.v5.i3.382
- The paper
- Zaha, D. C. (2014). Significance of immunohistochemistry in breast cancer. World Journal of Clinical Oncology. https://doi.org/10.5306/wjco.v5.i3.382
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.