Accès gratuit
Numéro
Med Sci (Paris)
Volume 23, Numéro 6-7, Juin-Juillet 2007
Page(s) 626 - 632
Section M/S revues
DOI https://doi.org/10.1051/medsci/20072367626
Publié en ligne 15 juin 2007
  1. Asselin-Labat ML, Sutherland KD, Barker H, et al. Gata-3 is an essential regulator of mammary-gland morphogenesis and luminal-cell differentiation. Nat Cell Biol 2006; 9 : 201–9.
  2. Asselin-Labat ML, Shackleton M, Stingl J, et al. Steroid hormone receptor status of mouse mammary stem cells. J Natl Cancer Inst 2006; 98 : 1011–4.
  3. Kouros-Mehr H, Slorach EM, Sternlicht MD, Werb Z. GATA-3 maintains the differentiation of the luminal cell fate in the mammary gland. Cell 2006; 127 : 1041–55.
  4. Bertucci F, Houlgatte R, Benziane A, et al. Gene expression profiling of primary breast carcinomas using arrays of candidate genes. Hum Mol Genet 2000; 9 : 2981–991.
  5. Jenssen TK, Kuo WP, Stokke T, Hovig E. Associations between gene expressions in breast cancer and patient survival. Hum Genet 2002; 111 : 411–20.
  6. Sorlie T, Tibshirani R, Parker J, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 2003; 100 : 8418–23.
  7. Birnbaum D, Bertucci F, Ginestier C, Tagett R, et al. Basal and luminal breast cancers : basic or luminous ? Int J Oncol 2004; 25 : 249–58.
  8. Charafe-Jauffret E, Ginestier C, Monville F, et al. How to best classify breast cancer : conventional and novel classifications. Int J Oncol 2005; 27 : 1307–13.
  9. Neve RM, Chin K, Fridlyand J, et al. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell 2006; 10 : 515–27.
  10. Charafe-Jauffret E, Ginestier C, Monville F, et al. Gene expression profiling of breast cell lines identifies potential new basal markers. Oncogene 2006; 25 : 2273–84.
  11. Bertucci F, Borie N, Ginestier C, et al. Identification and validation of an ERBB2 gene expression signature in breast cancers. Oncogene 2004; 23 : 2564–75.
  12. Konecny GE, Pegram MD, Venkatesan N, et al. Activity of the dual kinase inhibitor lapatinib (GW572016) against HER-2-overexpressing and trastuzumab-treated breast cancer cells. Cancer Res 2006; 66 : 1630–9.
  13. Abd El-Rehim DM, Ball G, Pinder SE, et al. High-throughput protein expression analysis using tissue microarray technology of a large well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses. Int J Cancer 2005; 116 : 340–50.
  14. Dolled-Filhart M, Ryden L, Cregger M, et al. Classification of breast cancer using genetic algorithms and tissue microarrays. Clin Cancer Res 2006; 12 : 6459–68.
  15. Jacquemier J, Ginestier C, Rougemont J, et al. Protein expression profiling identifies subclasses of breast cancer and predicts prognosis. Cancer Res 2005; 65 : 767–79.
  16. Nielsen TO, Hsu FD, Jensen K, et al. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin Cancer Res 2004; 10 : 5367–74.
  17. Bertucci F, Finetti P, Rougemont J, et al. Gene expression profiling identifies molecular subtypes of inflammatory breast cancer. Cancer Res 2005; 65 : 2170–8.
  18. Van Laere SJ, Van den Eynden GG, Van der Auwera I, et al. Identification of cell-of-origin breast tumor subtypes in inflammatory breast cancer by gene expression profiling. Breast Cancer Res Treat 2006; 95 : 243–55.
  19. Bertucci F, Finetti P, Cervera N, et al. Gene expression profiling shows medullary breast cancer is a subgroup of basal breast cancers. Cancer Res 2006; 66 : 4636–44.
  20. Turner NC, Reis-Filho JS. Basal-like breast cancer and the BRCA1 phenotype. Oncogene 2006; 25 : 5846–53.
  21. Korkola JE, DeVries S, Fridlyand J, et al. Differentiation of lobular versus ductal breast carcinomas by expression microarray analysis. Cancer Res 2003; 63 : 7167–75.
  22. Zhao H, Langerod A, Ji Y, et al. Different gene expression patterns in invasive lobular and ductal carcinomas of the breast. Mol Biol Cell 2004; 15 : 2523–36.
  23. Buttitta F, Felicioni L, Barassi F, et al. PIK3CA mutation and histological type in breast carcinoma : high frequency of mutations in lobular carcinoma. J Pathol 2006; 208 : 350–5.
  24. Holst F, Stahl PR, Ruiz C, et al. Estrogen receptor alpha (ESR1) gene amplification is frequent in breast cancer. Nat Genet 2007; 39 : 655–60.
  25. Chin K, DeVries S, Fridlyand J, et al. Genomic and transcriptional aberrations linked to breast cancer pathophysiologies. Cancer Cell 2006; 10 : 529–41.
  26. Gelsi-Boyer V, Orsetti B, Cervera N, et al. Comprehensive profiling of 8p11-12 amplification in breast cancer. Mol Cancer Res 2005; 3 : 655–67.
  27. Ray ME, Yang ZQ, Albertson D, et al. Genomic and expression analysis of the 8p11-12 amplicon in human breast cancer cell lines. Cancer Res 2004; 64 : 40–7.
  28. Reis-Filho JS, Simpson PT, Turner NC, et al. FGFR1 emerges as a potential therapeutic target for lobular breast carcinomas. Clin Cancer Res 2006; 12 : 6652–62.
  29. Letessier A, Sircoulomb F, Ginestier C, et al. Frequency, prognostic impact, and subtype association of 8p12, 8q24, 11q13, 12p13, 17q12, and 20q13 amplifications in breast cancers. BMC Cancer 2006; 6 : 245.
  30. Coe BP, Ylstra B, Carvalho B, et al. Resolving the resolution of array CGH. Genomics 2007; 89 : 647–53.
  31. Edgren H, Kallioniemi O. Integrated breast cancer genomics. Cancer Cell 2006; 10 : 453–4.
  32. Sorlie T. Molecular classification of breast tumors : toward improved diagnostics and treatments. Meth Mol Biol 2007; 360 : 91–114.
  33. Benvenuti S, Arena S, Bardelli A. Identification of cancer genes by mutational profiling of tumor genomes. FEBS Lett 2005; 579 : 1884–90.
  34. Chanock SM, Burdett LP, Yeager MP, et al. Somatic sequence alterations in twenty-one genes selected by expression profile analysis of breast carcinomas. Breast Cancer Res 2007; 9 : R5.
  35. Sjoblom T, Jones S, Wood LD, et al. The consensus coding sequences of human breast and colorectal cancers. Science 2006; 314 : 268–74.
  36. Moyano JV, Evans JR, Chen F, et al. AlphaB-crystallin is a novel oncoprotein that predicts poor clinical outcome in breast cancer. J Clin Invest 2006; 116 : 261–70.
  37. Kondo T, Setoguchi T, Taga T. Persistence of a small subpopulation of cancer stem-like cells in the C6 glioma cell line. Proc Natl Acad Sci USA 2004; 101 : 781–6.
  38. Dontu G, Abdallah WM, Foley JM, et al. In vitro propagation and transcriptional profiling of human mammary stem/progenitor cells. Genes Dev 2003; 17 : 1253–70.
  39. Ponti D, Costa A, Zaffaroni N, et al. Isolation and in vitro propagation of tumorigenic breast cancer cells with stem/progenitor cell properties. Cancer Res 2005; 65 : 5506–11.
  40. Al Hajj M, Wicha MS, Benito-Hernandez A, et al. Prospective identification of tumorigenic breast cancer cells. Proc Natl Acad Sci USA 2003; 100 : 3983–8.
  41. Liu R, Wang X, Chen GY, et al. The prognostic role of a gene signature from tumorigenic breast-cancer cells. N Engl J Med 2007; 356 : 217–26.
  42. Tognon C, Knezevich SR, Huntsman D, et al. Expression of the ETV6-NTRK3 gene fusion as a primary event in human secretory breast carcinoma. Cancer Cell 2002; 2 : 367–76.
  43. Wicha MS, Liu S, Dontu G. Cancer stem cells : an old idea : a paradigm shift. Cancer Res 2006; 66 : 1883–90.
  44. Carroll JS, Brown M. Estrogen receptor target gene : an evolving concept. Mol Endocrinol 2006; 20 : 1707–14.
  45. Bergamaschi A, Kim YH, Wang P, et al. Distinct patterns of DNA copy number alteration are associated with different clinicopathological features and gene-expression subtypes of breast cancer. Genes Chrom Cancer 2006; 45 : 1033–40.
  46. Yao J, Weremowicz S, Feng B, et al. Combined cDNA array comparative genomic hybridization and serial analysis of gene expression analysis of breast tumor progression. Cancer Res 2006; 66 : 4065–78.

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