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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.
Abd El-Rehim DM, Ball G, Pinder SE, Rakha E, Paish C, Robertson JF, Macmillan D, Blamey RW, Ellis IO. Abd El-Rehim DM, et al. Among authors: rakha e. Int J Cancer. 2005 Sep 1;116(3):340-50. doi: 10.1002/ijc.21004. Int J Cancer. 2005. PMID: 15818618
Global histone modifications in breast cancer correlate with tumor phenotypes, prognostic factors, and patient outcome.
Elsheikh SE, Green AR, Rakha EA, Powe DG, Ahmed RA, Collins HM, Soria D, Garibaldi JM, Paish CE, Ammar AA, Grainge MJ, Ball GR, Abdelghany MK, Martinez-Pomares L, Heery DM, Ellis IO. Elsheikh SE, et al. Among authors: rakha ea. Cancer Res. 2009 May 1;69(9):3802-9. doi: 10.1158/0008-5472.CAN-08-3907. Epub 2009 Apr 14. Cancer Res. 2009. PMID: 19366799 Free article.
A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients.
Soria D, Garibaldi JM, Ambrogi F, Green AR, Powe D, Rakha E, Macmillan RD, Blamey RW, Ball G, Lisboa PJ, Etchells TA, Boracchi P, Biganzoli E, Ellis IO. Soria D, et al. Among authors: rakha e. Comput Biol Med. 2010 Mar;40(3):318-30. doi: 10.1016/j.compbiomed.2010.01.003. Epub 2010 Jan 27. Comput Biol Med. 2010. PMID: 20106472 Free article.
543 results