The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
How basal are triple‐negative breast cancers?
Open accessAbstract
The basal molecular subtype of breast cancer (BC) is defined by the mRNA expression pattern of an intrinsic ∼500‐gene set. It is the most homogeneous subtype in transcriptional terms, and one of the most aggressive in prognostic terms. Clinical trials testing new systemic therapeutic strategies have been launched in basal BCs. Although no proof of evidence has yet been reported, basal tumors are currently assimilated to and selected as triple‐negative (TN) BCs in these trials because of their frequent immunohistochemical (IHC) negativity for hormone and ERBB2 receptors. Here, we have assessed the degrees of correlation and of homogeneity of the TN phenotype (IHC‐based definition) and the basal subtype (gene expression‐based definition). We analyzed 172 TN BCs defined by gene expression profile as basal (123 cases) and nonbasal (49 cases). Conversely, 160 tumors were defined as basal by their gene expression profile and included 123 TN and 37 non‐TN samples. Uni‐ and multivariate analyses revealed that TN BCs represent a more heterogeneous group than basal BCs, including basal and nonbasal tumors very different both at the histoclinical and molecular level, notably for mRNA expression of molecules targeted by specific therapies under evaluation in clinical trials. These results call for caution in the interpretation of ongoing trials and selection of patients in future trials. They also warrant the identification of molecular markers for basal BCs more clinically applicable than gene expression profiles. © 2008 Wiley‐Liss, Inc.
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Molecular 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
Lynch, T. J., Bell, D. W., Sordella, R., Gurubhagavatula, S., Okimoto, R. A., Brannigan, B. W., Harris, P. L., Haserlat, S. M., Supko, J. G., Haluska, F. G., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa040938 · Cited by 11,486
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
EGFR Mutations in Lung Cancer: Correlation with Clinical Response to Gefitinib Therapy
Paez, J. G., Jänne, P. A., Lee, J. C., Tracy, S., Greulich, H., Gabriel, S., Herman, P., Kaye, F. J., Lindeman, N., Boggon, T. J., et al. (2004) · Science · doi:10.1126/science.1099314 · Cited by 9,368
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
Race, Breast Cancer Subtypes, and Survival in the Carolina Breast Cancer Study
Carey, L. A., Perou, C. M., Livasy, C. A., Dressler, L. G., Cowan, D., Conway, K., Karaca, G., Troester, M. A., Tse, C. K., Edmiston, S., et al. (2006) · JAMA · doi:10.1001/jama.295.21.2492 · Cited by 3,819
Nielsen, T. O., Hsu, F. D., Jensen, K., Cheang, M., Karaca, G., Hu, Z., Hernandez-Boussard, T., Livasy, C., Cowan, D., Dressler, L., et al. (2004) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-04-0220 · Cited by 2,663
Sotiriou, C., Neo, S.-Y., McShane, L. M., Korn, E. L., Long, P. M., Jazaeri, A., Martiat, P., Fox, S. B., Harris, A. L., & Liu, E. T. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1732912100 · Cited by 1,993
Herbst, R. S., Giaccone, G., Schiller, J. H., Natale, R. B., Miller, V., Manegold, C., Scagliotti, G., Rosell, R., Oliff, I., Reeves, J. A., et al. (2004) · Journal of Clinical Oncology · doi:10.1200/jco.2004.07.215 · Cited by 1,707
The molecular portraits of breast tumors are conserved across microarray platforms
Hu, Z., Fan, C., Oh, D. S., Marron, J., He, X., Qaqish, B. F., Livasy, C., Carey, L. A., Reynolds, E., Dressler, L., et al. (2006) · BMC Genomics · doi:10.1186/1471-2164-7-96 · Cited by 1,491
Cited by
Lehmann, B. D., Bauer, J. A., Chen, X., Sanders, M. E., Chakravarthy, A. B., Shyr, Y., & Pietenpol, J. A. (2011) · Journal of Clinical Investigation · doi:10.1172/jci45014 · Cited by 5,592
Patient-Derived Xenograft Models: An Emerging Platform for Translational Cancer Research
Hidalgo, M., Amant, F., Biankin, A. V., Budinská, E., Byrne, A. T., Caldas, C., Clarke, R. B., de Jong, S., Jonkers, J., Mælandsmo, G. M., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-14-0001 · Cited by 1,742
An overview of triple-negative breast cancer
Kumar, P., & Aggarwal, R. (2016) · Archives of Gynecology and Obstetrics · doi:10.1007/s00404-015-3859-y · Cited by 771
Lin, N. U., Vanderplas, A., Hughes, M. E., Theriault, R. L., Edge, S. B., Wong, Y., Blayney, D. W., Niland, J. C., Winer, E. P., & Weeks, J. C. (2012) · Cancer · doi:10.1002/cncr.27581 · Cited by 695
Triple-negative breast cancer—current status and future directions
Gluz, O., Liedtke, C., Gottschalk, N., Pusztai, L., Nitz, U., & Harbeck, N. (2009) · Annals of Oncology · doi:10.1093/annonc/mdp492 · Cited by 687
Metadata
- Authors
- Bertucci, F., Finetti, P., Cervera, N., Esterni, B., Hermitte, F., Viens, P., & Birnbaum, D.
- Venue
- International Journal of Cancer
- Publisher
- Wiley
- Published
- 2008-04-24
- Volume
- 123
- Issue
- 1
- Pages
- 236-240
- ISSN
- 0020-7136 (ISSN-L)
- 1097-0215
- OpenAlex
- W2035077913
- Cited by
- 443
- References
- 29
- FWCI
- 10.81
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Bertucci, F., Finetti, P., Cervera, N., Esterni, B., Hermitte, F., Viens, P., & Birnbaum, D. (2008). How basal are triple‐negative breast cancers? International Journal of Cancer. https://doi.org/10.1002/ijc.23518
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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.
