The DOI matches its Crossref record; 131 of the 131 references it cites were found in a registry or an index.
Histological types of breast cancer: How special are they?
Open accessAbstract
Breast cancer is a heterogeneous disease, comprising multiple entities associated with distinctive histological and biological features, clinical presentations and behaviours and responses to therapy. Microarray‐based technologies have unravelled the molecular underpinning of several characteristics of breast cancer, including metastatic propensity and histological grade, and have led to the identification of prognostic and predictive gene expression signatures. Furthermore, a molecular taxonomy of breast cancer based on transcriptomic analysis has been proposed. However, microarray studies have primarily focused on invasive ductal carcinomas of no special type. Owing to the relative rarity of special types of breast cancer, information about the biology and clinical behaviour of breast cancers conveyed by histological type has not been taken into account. Histological special types of breast cancer account for up to 25% of all invasive breast cancers. Recent studies have provided direct evidence of the existence of genotypic–phenotypic correlations. For instance, secretory carcinomas of the breast consistently harbour the t(12;15) translocation that leads to the formation of the ETV6–NTRK3 fusion gene, adenoid cystic carcinomas consistently display the t(6;9) MYB–NFIB translocation and lobular carcinomas consistently show inactivation of the CDH1 gene through multiple molecular mechanisms. Furthermore, histopathological and molecular analysis of tumours from conditional mouse models has provided direct evidence for the causative role of specific genes in the genesis of specific histological special types of breast cancer. Here we review the associations between the molecular taxonomy of breast cancer and histological special types, discuss the possible origins of the heterogeneity of breast cancer and propose an approach for the identification of novel therapeutic targets based on the study of histological special types of breast cancer.
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
1 retracted
Genomic signatures to guide the use of chemotherapeutics
Potti, A., Dressman, H. K., Bild, A., Riedel, R. F., Chan, G., Sayer, R., Cragun, J., Cottrill, H., Kelley, M. J., Petersen, R., et al. (2006) · Nature Medicine · doi:10.1038/nm1491 · Cited by 593
RetractedMolecular portraits of human breast tumours
Perou, C. M., Sørlie, T., Eisen, M. B., van de Rijn, M., Jeffrey, S. S., Rees, C. A., Pollack, J. R., Ross, D. T., Johnsen, H., Akslen, L. A., et al. (2000) · Nature · doi:10.1038/35021093 · Cited by 16,261
Nishimura, R., Osako, T., Nishiyama, Y., Tashima, R., Nakano, M., Fujisue, M., Toyozumi, Y., & Arima, N. (2013) · Oncology · doi:10.1159/000353099 · Cited by 13,166
Sørlie, T., Perou, C. M., Tibshirani, R., Aas, T., Geisler, S., Johnsen, H., Hastie, T., Eisen, M. B., van de Rijn, M., Jeffrey, S. S., et al. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.191367098 · Cited by 10,938
Prospective identification of tumorigenic breast cancer cells
Al-Hajj, M., Wicha, M. S., Benito-Hernandez, A., Morrison, S. J., & Clarke, M. F. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0530291100 · Cited by 10,370
Gene expression profiling predicts clinical outcome of breast cancer
van 't Veer, L. J., Dai, H., van de Vijver, M. J., He, Y. D., Hart, A. A. M., Mao, M., Peterse, H. L., van der Kooy, K., Marton, M. J., Witteveen, A. T., et al. (2002) · Nature · doi:10.1038/415530a · Cited by 9,536
Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy
Farmer, H., McCabe, N., Lord, C. J., Tutt, A. N. J., Johnson, D. A., Richardson, T. B., Santarosa, M., Dillon, K. J., Hickson, I., Knights, C., et al. (2005) · Nature · doi:10.1038/nature03445 · Cited by 6,683
A Gene-Expression Signature as a Predictor of Survival in Breast Cancer
van de Vijver, M. J., He, Y. D., van 't Veer, L. J., Dai, H., Hart, A. A. M., Voskuil, D. W., Schreiber, G. J., Peterse, J. L., Roberts, C., Marton, M. J., et al. (2002) · New England Journal of Medicine · doi:10.1056/nejmoa021967 · Cited by 6,488
ELSTON, C. W., & ELLIS, I. O. (1991) · Histopathology · doi:10.1111/j.1365-2559.1991.tb00229.x · Cited by 6,175
Repeated observation of breast tumor subtypes in independent gene expression data sets
Sørlie, T., Tibshirani, R., Parker, J., Hastie, T., Marron, J. S., Nobel, A., Deng, S., Johnsen, H., Pesich, R., Geisler, S., et al. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0932692100 · Cited by 5,429
Cited by
Tumor Heterogeneity in Breast Cancer
Turashvili, G., & Brogi, E. (2017) · Frontiers in Medicine · doi:10.3389/fmed.2017.00227 · Cited by 561
Genetic susceptibility to breast cancer
Mavaddat, N., Antoniou, A. C., Easton, D. F., & Garcia-Closas, M. (2010) · Molecular Oncology · doi:10.1016/j.molonc.2010.04.011 · Cited by 375
Breast Cancer Histopathology Image Classification Using an Ensemble of Deep Learning Models
Hameed, Z., Zahia, S., Garcia-Zapirain, B., Javier Aguirre, J., & María Vanegas, A. (2020) · Sensors · doi:10.3390/s20164373 · Cited by 277
Optimization of liquid overlay technique to formulate heterogenic 3D co-cultures models
Costa, E. C., Gaspar, V. M., Coutinho, P., & Correia, I. J. (2014) · Biotechnology and Bioengineering · doi:10.1002/bit.25210 · Cited by 156
Mageau, E., Derbowka, R., Dickinson, N., Lefort, N., Kovala, A. T., Boreham, D. R., Tai, T. C., Thome, C., & Tharmalingam, S. (2025) · Current Issues in Molecular Biology · doi:10.3390/cimb47080589 · Cited by 12
Metadata
- Authors
- Weigelt, B., Geyer, F. C., & Reis-Filho, J. S.
- Venue
- Molecular Oncology
- Publisher
- Wiley
- Published
- 2010-04-18
- Volume
- 4
- Issue
- 3
- Pages
- 192-208
- ISSN
- 1574-7891 (ISSN-L)
- 1878-0261
- OpenAlex
- W2122197597
- Cited by
- 572
- References
- 131
- FWCI
- 6.59
- Type
- journal article
- Language
- en
- Open access
- green
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: Histological types of breast cancer: How special are they? https://app.cochat.ai/papers/10.1016/j.molonc.2010.04.004
- The paper
- Weigelt, B., Geyer, F. C., & Reis-Filho, J. S. (2010). Histological types of breast cancer: How special are they? Molecular Oncology. https://doi.org/10.1016/j.molonc.2010.04.004
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.