Although global gene microarray studies have demonstrated the molecular heterogeneity of breast cancer (BC) and provided potential for clinical applications, the molecular subclassification of luminal/ER-positive tumours, which is the largest class of BC, remains unclear. Characterisation of luminal/ER-positive subtypes could have important implications in clinical decision-making and patient management. The patient study cohort is derived from a consecutive series of approximately 1902 cases of primary operable invasive breast carcinoma obtained from the Nottingham Tenovus Primary Breast Carcinoma Series, with patients presenting between 1986 and 1998. This is a well-characterized series of primary breast carcinoma that has been treated in a uniform way and previously used to study a wide range of proteins. Using gene microarray experiments in 128 frozen invasive BC derived from this series , 47,2 93 gene transcripts were analysed using a number of different bio-statistical models to identify a transcript signature for luminal/ER-positive BC, from which candidate genes were selected and that can be used to characterise ER-positive breast cancer. In addition, other biomarkers with strong relevance in ER-positive breast cancer were studied because the evidence strongly suggests an important role in the biology and molecular classification of ER-positive breast cancer. The selection criteria was based on published literature concentrating mainly on ER related pathways including ER coregulators (CARMI, PELPI), cellular proliferation (p27. TK1, cyclin B1), apoptosis (Bc12), Akt/PIK3 pathway (FOX03a), gene expression profiling (FOXA1, XBP1, TFF1) and endocrine resistance (CD71). Immunohistochemistry and high throughput tissue micro array technology were used to study the protein expression of 16 biomarkers with strong relevance to ER pathways in a well characterised consecutive series of invasive BC (n=1902) in addition to anther 9 markers that were available from the database of the breast cancer research group, University of Nottingham. The data were analysed using different clustering methods including K-means and Partitioning around Medoids. Kaplan Meier plots with Log-rank test (LR) were used to model clinical outcome. A transcript signature for ER positive BC was identified including RERG, GATA3 and other genes by a supervised classification analysis using 10-fold external cross-validation of the gene microarray data. Immunohistochemical validation studies confirmed their association with ER positive BC. Through a consensus approach using different clustering techniques applied to protein expression data 25 markers, three biological clusters (patient subclasses) in ER positive breast cancer showing significant difference in clinical outcome (LR= 28.185 & p<0.001) have been identified. Importantly, the poor prognosis cluster was significantly characterised by high tumour grade and frequent development of distant metastasis. In conclusion, our results emphasised the heterogeneity of luminal/ER-positive BC. Molecular profiling of breast cancer using protein biomarkers on TMAs can sub-classify ER-positive tumours into clinically and biologically relevant subgroups.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:575458 |
| Date | January 2011 |
| Creators | Habashy, Hany Onsy Fouad Ibrahim |
| Publisher | University of Nottingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.nottingham.ac.uk/29131/ |
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