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Mobile application using Nottingham Prognostic Index (NPI) calculation

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Acknowledgement

I would take this opportunity to thank my research supervisor, family and friends for their support and guidance without which this research would not have been possible.

DECLARATION

I, [type your full first names and surname here], declare that the contents of this dissertation/thesis represent my own unaided work, and that the dissertation/thesis has not previously been submitted for academic examination towards any qualification. Furthermore, it represents my own opinions and not necessarily those of the University.

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Abstract

We report a novel approach to gene expression profiling using the Nottingham Prognostic Index (NPI) to stratify 26 patients with invasive breast carcinoma. As an aggregate index of parameters reflecting metastatic potential, growth rate, and genetic instability the NPI has distinct advantages over other clinicopathologic features used to segregate breast cancer patients. As a continuous variable it offers a responsive and sensitive means of modeling a continuum of clinical aggressiveness. Using RNA extracted from 26 tumors and cDNA microarrays with 23 343 unique genetic elements, 84 genes and expressed sequence tags were identified whose expression patterns correlated with NPI. Differential expression by immunohistochemistry (IHC) was also observed for two of three genes evaluated by this method. Correlation was determined by the Spearman rank correlation method with null distribution analysis. Among the 84 genetic elements were seven previously implicated in neoplastic progression (including the two demonstrating differential expression by IHC), 11 without specific cancer association but localized to chromosomal sites whose loss or gain has been identified in cytogenetic studies of breast carcinoma, and 73 not previously associated with breast carcinoma. Collectively, the expression patterns of these 84 elements have potential to distinguish high and low NPI patient samples. These data add support to the assertion that prognostic groups of breast carcinoma are reflected in distinguishable expression profiles of a limited set of genes.

Table of Contents

CHAPTER 1: INTRODUCTION7

CHAPTER TWO: LITERATURE REVIEW10

CHAPTER THREE: METHODOLOGY13

CHAPTER FOUR: DISCUSSION AND ANALYSIS18

CHAPTER FIVE: CONCLUSION44

REFERENCES50

Chapter 1: Introduction

The specific molecular events contributing to the spectrum of clinical aggressiveness and therapeutic responsiveness in breast carcinoma are poorly understood, but are thought to involve multifactorial, interactive, and stepwise alterations of gene expression. The current ability of grade and stage to assess prognosis and predict therapeutic response is less than ideal. Up to one-third of women with negative axillary lymph nodes will experience recurrence and approximately one-third of node-positive patients not receiving adjuvant therapy will be recurrence free after 10 years. Consideration of other factors such as special histologic type, hormone and growth factor receptor expression, and other individual parameters marginally improve this ability, but likely represent only a fraction of the molecular mechanisms ultimately determining the clinical behavior of tumors. (Anderson, 2000, 487)

Analyzing the variation in aggregate gene expression using gene array technology offers a powerful approach that has been employed in identifying molecular markers important in predicting outcome as well as response to targeted therapy. The ultimate aims of such endeavors may be to characterize conserved 'molecular signatures' that more accurately predict prognosis, or to characterize ...