Doctoral Degrees (Anatomical Pathology)

Permanent URI for this collection

https://scholar.sun.ac.za/handle/10019.1/3629

Browse

Browsing Doctoral Degrees (Anatomical Pathology) by Subject "Breast -- Cancer -- Diagnosis"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Analysis of the clinical utility of gene expression profiling in relation to conventional prognostic markers in South African patients with breast carcinoma
    (Stellenbosch : Stellenbosch University, 2014-12) Grant, Kathleen Ann; Kotze, Maritha J.; Wright, Colleen A.; Apffelstaedt, Justus P.; Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Pathology. Anatomical Pathology.
    ENGLISH ABSTRACT: Breast cancer is a heterogeneous disease characterised by marked inter-individual variability in presentation, prognosis and clinical outcome. The recognition that morphological assessment has limited utility in stratifying patients into prognostic subgroups led to clinico-pathological classification of tumour biology, based on receptor expression using immunohistochemical (IHC) techniques. This standard is currently complemented by the development of gene expression profiling methodology that led to the identification of intrinsic molecular subtypes, reflecting tumour genetics as the true driver of biological activity in breast cancer. The study was based on the hypothesis that molecular classification of breast carcinomas integrated with established clinico-pathological risk factors will improve current diagnostic and risk management algorithms used in clinical decision-making. A pathology-supported genetic testing strategy was used to evaluate microarray-based gene profiling against diagnostic pathology techniques as the current standard. Clinico-pathological factors including age, number of positive axillary nodes, tumour size, grade, proliferation index and hormone receptor status was documented for 141 breast cancer patients (143 tumours) referred for microarray-based gene expression profiling between 2007 and 2014. Subsets of patients were selected from the database based on the inclusion criteria defined for three phases in which the study was performed, in order to determine 1) the percentage of patients stratified as having a low as opposed to high risk of distant recurrence using the 70-gene MammaPrint profile within the inclusion criteria, 2) correlation of HER2 status as determined by IHC and fluorescence in situ hybridisation (FISH) with microarray-based mRNA readout (TargetPrint), and 3) the relationship between hormone receptor determination as reported by standard IHC and molecular subtyping using the 80-gene BluePrint profile. Similar distribution patterns for MammaPrint low- and high-risk profiles were obtained irrespective of whether fresh tumour biopsies or formalin-fixed paraffin embedded (FFPE) tissue was used. During the first phase of the study, 60% of the 106 tumour specimens analysed with MammaPrint were classified as low-risk and 40% as high-risk using a newly-developed MammaPrint pre-screen algorithm (MPA) aimed at cost-saving. In the second phase of the study, performed in 102 breast tumours, discordant or equivocal HER2 results were found in four cases. Reflex testing confirmed the TargetPrint results in discordant cases, achieving 100% concordance regardless of whether fresh tumour or FFPE tissue was used for microarray analysis. For the third phase of the study 74 HER2-negative tumour samples were selected for comparative analysis. Statistically significant positive correlations were found between protein expression (IHC score) and mRNA (TargetPrint) levels for estrogen receptor (ER) (R=0.53, p<0.0001) as well as progesterone receptor (PR) (R=0.62, p<0.0001), while combined ER/PR tumour status was reported concordantly in 82.4% of these tumours. BluePrint was essential for interpretation of these results used in treatment decision-making. The MPA developed in South Africa in 2009 was validated in this study as an appropriate strategy to prevent chemotherapy overtreatment in patients with early-stage breast cancer. The use of microarray-based analysis proved to be a reliable ancillary method of assessing HER2 status in breast cancer patients. Risk reclassification based on the TargetPrint results helped to avoid unnecessary high treatment costs in false-positive cases, in addition to providing potentially life-saving treatment to those for whom it was indicated. While neither IHC nor TargetPrint estimation of intrinsic subtype correlated independently with the molecular subtype as indicated by BluePrint profiling, the ability to distinguish between basal-like and luminal tumours was enhanced when the combined protein and mRNA values was considered. Genomic profiling provided information over and above that obtained from routine clinico-pathological assessments. This finding supports the relevance of a pathology-supported genetic testing approach to breast cancer management, whereby advanced genomic testing is combined with existing clinico-pathological risk stratification methods for improved patient management.