Please note that we have stopped the regular imports of Gene Expression Omnibus (GEO) data into ArrayExpress. This may not be the latest version of this experiment.
E-GEOD-4922 - Transcription profiling of human breast cancer tumor samples from Uppsala and Singapore cohorts
Released on 15 June 2008, last updated on 27 March 2012
Histological grading of breast cancer defines morphological subtypes informative of metastatic potential, although not without considerable inter-observer disagreement and clinical heterogeneity particularly among the moderately differentiated grade II (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade I (G1) and grade III (G3) histology might provide a more objective measure of grade with prognostic benefit for patients with moderately differentiated disease. To this end, we studied the expression profiles of 347 primary invasive breast tumors analyzed on Affymetrix microarrays. Using class prediction algorithms, we identified 264 robust grade-associated markers, six of which could accurately classify G1 and G3 tumors, and separate G2 tumors into two highly discriminant classes (termed G2a and G2b genetic grades) with patient survival outcomes highly similar to those with G1 and G3 histology, respectively. Statistical analysis of conventional clinical variables further distinguished G2a and G2b subtypes from each other, but also from histologic G1 and G3 tumors. In multivariate analyses, genetic grade was consistently found to be an independent prognostic indicator of disease recurrence comparable to that of lymph node status and tumor size. When incorporated into the Nottingham Prognostic Index, genetic grade enhanced detection of patients with less harmful tumors, likely to benefit little from adjuvant therapy. Our findings show that a genetic grade signature can improve prognosis and therapeutic planning for breast cancer patients, and support the view that low and high grade disease, as defined genetically, reflect independent pathobiological entities rather than a continuum of cancer progression. Three separate breast cancer cohorts were analyzed: 1) Uppsala (n=249), 2) Stockholm (n=58), 3) Singapore (n=40). The Uppsala and Singapore data can be accessed here. The Stockholm cohort data can be accessed at GEO Series GSE1456. Experiment Overall Design: All tumor specimens were assessed on U133 A and B arrays.
transcription profiling by array, co-expression, disease state
Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer. Anna V Ivshina, Joshy George, Oleg Senko, Benjamin Mow, Thomas C Putti, Johanna Smeds, Thomas Lindahl, Yudi Pawitan, Per Hall, Hans Nordgren, John E L Wong, Edison T Liu, Jonas Bergh, Vladimir A Kuznetsov, Lance D Miller.