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01.05.2008 | Poster presentation

Identification and definition of novel clinical phenotypes of breast cancer through consensus derived from automated clustering methods

verfasst von: AR Green, JM Garibaldi, D Soria, F Ambrogi, G Ball, PJG Lisboa, TA Etchells, P Boracchi, E Biganzoli, RD Macmillan, RW Blamey, DG Powe, EA Rakha, IO Ellis

Erschienen in: Breast Cancer Research | Sonderheft 2/2008

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Excerpt

Breast cancer is a heterogeneous disease for which several forms have recently been identified on the basis of their gene expression characteristics [1]. We have previously demonstrated that protein expression characteristics can be used to identify comparable classes [2]. In the present study we extend this approach using improved biostatistical methods to confirm the validity of such an approach and to further define the key criteria for class membership. …

Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, Eystein Lonning P, Borresen-Dale AL: Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA. 2001, 98: 10869-10874. 10.1073/pnas.191367098.CrossRefPubMedPubMedCentral

Abd El-Rehim DM, Ball G, Pinder SE, Rakha E, Paish C, Robertson JF, Macmillan D, Blamey RW, Ellis IO: 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: 340-350. 10.1002/ijc.21004.CrossRefPubMed

Titel: Identification and definition of novel clinical phenotypes of breast cancer through consensus derived from automated clustering methods
verfasst von: AR Green
JM Garibaldi
D Soria
F Ambrogi
G Ball
PJG Lisboa
TA Etchells
P Boracchi
E Biganzoli
RD Macmillan
RW Blamey
DG Powe
EA Rakha
IO Ellis
Publikationsdatum: 01.05.2008
Verlag: BioMed Central
Erschienen in: Breast Cancer Research / Ausgabe Sonderheft 2/2008
Elektronische ISSN: 1465-542X
DOI: https://doi.org/10.1186/bcr1953

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Springer Medizin

Identification and definition of novel clinical phenotypes of breast cancer through consensus derived from automated clustering methods

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