The DOI matches its Crossref record.
Prognostic markers in triple‐negative breast cancer
Abstract
BACKGROUND.: Triple‐negative breast cancer (estrogen receptor‐negative, progesterone receptor‐negative, and HER2‐negative) is a high risk breast cancer that lacks the benefit of specific therapy that targets these proteins. METHODS.: In this study, the authors examined a large and well characterized series of invasive breast carcinoma (n = 1944) with a long‐term clinical follow‐up (median, 56 months) by using tissue microarray. The series were also stained with concurrent immunohistochemical prognostic panels (estrogen receptor, progesterone receptor, HER‐2, androgen receptor, epidermal growth factor receptor (EGFR), P‐cadherin, E‐cadherin, and basal (CK5/6, CK14), and p53), to characterize this specific subgroup of breast cancer and to identify prognostic markers that can identify tumors with more aggressive behavior. RESULTS.: Of informative cases, 16.3% were of the triple‐negative phenotype. The majority of these tumors were grade 3, ductal/no‐specific‐type carcinomas. There were positive associations with larger size, pushing margins, poorer Nottingham Prognostic Index, development of recurrence and distant metastasis, and poorer outcome. In addition, associations were found with loss of expression of androgen receptor and E‐cadherin, and positive expression of basal cytokeratins (basal phenotype), P‐cadherin, p53, and EGFR. In all tumors, tumor size, lymph node stage, and androgen receptor were the most useful prognostic markers. In the lymph node‐positive subgroup, both size and androgen receptor retained their prognostic significance. However, in the lymph node‐negative tumors, basal phenotype was the sole prognostic marker identified in this subgroup. Other parameters including age, histological grade, tumor size, vascular invasion or other biomarkers included in the current study were not significant. CONCLUSIONS.: The authors concluded that assessment of androgen receptor and basal phenotype, in addition to the established pathologic variables, mainly lymph node status and tumor size, can be used to select high‐risk and low‐risk patients at the time of primary surgery and can provide valuable information on treatment options in these triple‐negative tumors. Cancer 2007. © 2006 American Cancer Society
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
Cited by
ASCT2/SLC1A5 controls glutamine uptake and tumour growth in triple-negative basal-like breast cancer
van Geldermalsen, M., Wang, Q., Nagarajah, R., Marshall, A. D., Thoeng, A., Gao, D., Ritchie, W., Feng, Y., Bailey, C. G., Deng, N., et al. (2016) · Oncogene · doi:10.1038/onc.2015.381 · Cited by 580
The role of HER2, EGFR, and other receptor tyrosine kinases in breast cancer
Hsu, J. L., & Hung, M.-C. (2016) · Cancer and Metastasis Reviews · doi:10.1007/s10555-016-9649-6 · Cited by 445
Characteristics of triple-negative breast cancer
de Ruijter, T. C., Veeck, J., de Hoon, J. P. J., van Engeland, M., & Tjan-Heijnen, V. C. (2011) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-010-0957-x · Cited by 317
Triple‐negative breast cancer: Present challenges and new perspectives
Podo, F., Buydens, L. M. C., Degani, H., Hilhorst, R., Klipp, E., Gribbestad, I. S., Van Huffel, S., W.M. van Laarhoven, H., Luts, J., Monleon, D., et al. (2010) · Molecular Oncology · doi:10.1016/j.molonc.2010.04.006 · Cited by 299
Collins, L. C., Marotti, J. D., Gelber, S., Cole, K., Ruddy, K., Kereakoglow, S., Brachtel, E. F., Schapira, L., Come, S. E., Winer, E. P., et al. (2012) · Breast Cancer Research and Treatment · doi:10.1007/s10549-011-1872-9 · Cited by 271
Metadata
- Authors
- Rakha, E. A., El‐Sayed, M. E., Green, A. R., Lee, A. H. S., Robertson, J. F., & Ellis, I. O.
- Venue
- Cancer
- Publisher
- Wiley
- Published
- 2006-12-11
- Volume
- 109
- Issue
- 1
- Pages
- 25-32
- ISSN
- 0008-543X (ISSN-L)
- 1097-0142
- OpenAlex
- W1989663680
- Cited by
- 1,283
- References
- 0
- FWCI
- 20.14
- Type
- journal article
- Language
- en
- Open access
- closed
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: Prognostic markers in triple‐negative breast cancer. https://app.cochat.ai/papers/10.1002/cncr.22381
- The paper
- Rakha, E. A., El‐Sayed, M. E., Green, A. R., Lee, A. H. S., Robertson, J. F., & Ellis, I. O. (2007). Prognostic markers in triple‐negative breast cancer. Cancer. https://doi.org/10.1002/cncr.22381
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.