The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Integrated Profiling of Basal and Luminal Breast Cancers
Abstract
Basal and luminal are two molecular subtypes of breast cancer with opposite histoclinical features. We report a combined, high-resolution analysis of genome copy number and gene expression in primary basal and luminal breast cancers. First, we identified and compared genomic alterations in 45 basal and 48 luminal tumors by using 244K oligonucleotide array comparative genomic hybridization (aCGH). We found various genome gains and losses and rare high-level gene amplifications that may provide therapeutic targets. We show that gain of 10p is a new alteration in basal breast cancer and that a subregion of the 8p12 amplification is specific of luminal tumors. Rare high-level amplifications contained BCL2L2, CCNE, EGFR, FGFR2, IGF1R, NOTCH2, and PIK3CA. Potential gene breaks involved ETV6 and FLT3. Second, we analyzed both aCGH and gene expression profiles for 42 basal and 32 luminal breast cancers. The results support the existence of specific oncogenic pathways in basal and luminal breast cancers, involving several potential oncogenes and tumor suppressor genes (TSG). In basal tumors, 73 candidate oncogenes were identified in chromosome regions 1q21-23, 10p14, and 12p13 and 28 candidate TSG in regions 4q32-34 and 5q11-23. In luminal breast cancers, 33 potential oncogenes were identified in 1q21-23, 8p12-q21, 11q13, and 16p12-13 and 61 candidate TSG in 16q12-13, 16q22-24, and 17p13. HORMAD1 (P = 6.5 × 10−5) and ZNF703 (P = 7 × 10−4) were the most significant basal and luminal potential oncogenes, respectively. Finally, among 10p candidate oncogenes associated with basal subtype, we validated CDC123/C10orf7 protein as a basal marker. [Cancer Res 2007;67(24):11565–75]
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Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
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
Cluster analysis and display of genome-wide expression patterns
Eisen, M. B., Spellman, P. T., Brown, P. O., & Botstein, D. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.25.14863 · Cited by 16,184
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
Exploration, normalization, and summaries of high density oligonucleotide array probe level data
Irizarry, R. A. (2003) · Biostatistics · doi:10.1093/biostatistics/4.2.249 · Cited by 10,603
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
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
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
Global variation in copy number in the human genome
Redon, R., Ishikawa, S., Fitch, K. R., Feuk, L., Perry, G. H., Andrews, T. D., Fiegler, H., Shapero, M. H., Carson, A. R., Chen, W., et al. (2006) · Nature · doi:10.1038/nature05329 · Cited by 4,288
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
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Triple-negative breast cancer: disease entity or title of convenience?
Carey, L., Winer, E., Viale, G., Cameron, D., & Gianni, L. (2010) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2010.154 · Cited by 783
FGFR1 Amplification Drives Endocrine Therapy Resistance and Is a Therapeutic Target in Breast Cancer
Turner, N., Pearson, A., Sharpe, R., Lambros, M., Geyer, F., Lopez-Garcia, M. A., Natrajan, R., Marchio, C., Iorns, E., Mackay, A., et al. (2010) · Cancer Research · doi:10.1158/0008-5472.can-09-3746 · Cited by 732
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
Prognostic and predictive value of PDL1 expression in breast cancer
Sabatier, R., Finetti, P., Mamessier, E., Adelaide, J., Chaffanet, M., Ali, H. R., Viens, P., Caldas, C., Birnbaum, D., & Bertucci, F. (2015) · Oncotarget · doi:10.18632/oncotarget.3216 · Cited by 508
Self-citationA gene expression signature identifies two prognostic subgroups of basal breast cancer
Sabatier, R., Finetti, P., Cervera, N., Lambaudie, E., Esterni, B., Mamessier, E., Tallet, A., Chabannon, C., Extra, J.-M., Jacquemier, J., et al. (2011) · Breast Cancer Research and Treatment · doi:10.1007/s10549-010-0897-9 · Cited by 290
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Metadata
- Authors
- Adélaïde, J., Finetti, P., Bekhouche, I., Repellini, L., Geneix, J., Sircoulomb, F., Charafe-Jauffret, E., Cervera, N., Desplans, J., Parzy, D., Schoenmakers, E., Viens, P., Jacquemier, J., Birnbaum, D., Bertucci, F., & Chaffanet, M.
- Venue
- Cancer Research
- Published
- 2007-12-15
- Volume
- 67
- Issue
- 24
- Pages
- 11565-11575
- ISSN
- 0008-5472 (ISSN-L)
- 1538-7445
- OpenAlex
- W1968154499
- Cited by
- 297
- References
- 48
- FWCI
- 9.11
- Type
- journal article
- Language
- en
- Open access
- closed
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- Adélaïde, J., Finetti, P., Bekhouche, I., Repellini, L., Geneix, J., Sircoulomb, F., Charafe-Jauffret, E., Cervera, N., Desplans, J., Parzy, D., Schoenmakers, E., Viens, P., Jacquemier, J., Birnbaum, D., Bertucci, F., & Chaffanet, M. (2007). Integrated Profiling of Basal and Luminal Breast Cancers. Cancer Research. https://doi.org/10.1158/0008-5472.can-07-2536
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