Expression profiling to predict outcome in breast cancer: the influence of sample selection.
Gene expression profiling of tumors using DNA microarrays is a promising method for predicting prognosis and treatment response in cancer patients. It was recently reported that expression profiles of sporadic breast cancers could be used to predict disease recurrence better than currently available clinical and histopathological prognostic factors. Having observed an overlap in those data between the genes that predict outcome and those that predict estrogen receptor-alpha status, we examined their predictive power in an independent data set. We conclude that it may be important to define prognostic expression profiles separately for estrogen receptor-alpha-positive and estrogen receptor-alpha-negative tumors.
Gruvberger
Sofia K
SK
Department of Oncology, The Jubileum Institute, Lund University Hospital, Lund, Sweden.
Ringnér
Markus
M
Edén
Patrik
P
Borg
Ake
A
Fernö
Mårten
M
Peterson
Carsten
C
Meltzer
Paul S
PS
D001943:Breast Neoplasms / Q000235:genetics / Q000473:pathology*; D047628:Estrogen Receptor alpha; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D009364:Neoplasm Recurrence, Local; D020411:Oligonucleotide Array Sequence Analysis; D011237:Predictive Value of Tests; D011379:Prognosis; D011960:Receptors, Estrogen / Q000235:genetics*
D047628:Estrogen Receptor alpha; D011960:Receptors, Estrogen