An Analysis of Gene Array Data Related to Cell Adhesion and Prostate Cancer

Abstract

We embarked on the investigation presented in this report with three goals in mind. First, to discover a gene, or a group of genes, related to the attachment of prostate cells to their neighboring environment. The process of cell attachment is a very important process in cancer in general, and in prostate cancer in particular. Changes in cell attachment allow cells to move around the body, or metastasize, thereby causing the spread of cancer through the body, causing death. Second, we wanted to examine “statistical variability” of gene expression in a single cell line, with time as the only factor possibly related to cell event of interest: cell adhesion. Understanding gene variability is important with regards to future studies, which seek to measure changes in gene expression in human subjects, and is a prerequisite for making certain predictions about “effect size”, when planning to affect gene activity at some future time. We were especially interested in whether and how standardization of numerical values (e.g. division by a specific measure of abundance) obtained from microarrays may affect statistical parameters such as coefficient of correlation or coefficient of variation in measurements of gene expression. Finally, we wanted to take into consideration the notion of false positives, an issue of interest to researchers working with microarray data; this matter is addressed in the final section.