Screening for Breast Cancer Using Molecular Signatures
Currently there are no molecular screening tools available that can identify the patients at high risk for breast cancer development or local recurrence. Numerous studies have suggested the existence of genetic alterations in histologically non-malignant breast tissue, identical to those found in the adjacent tumor. Examples of such changes are Loss of Heterozygosity (LOH), chromosomal abnormalities, altered epigenetic patterns and specific gene mutations. These genetic changes can accumulate over time and are likely to contribute to the initiation of cancer prior to the histological development of tumors.
In order to identify such early changes in vivo and investigate their functional meaning, distribution, frequency and identity, we analyze DNA and RNA samples from patients by various molecular tools including 40K cDNA microarrays, Affymetrix gene chips, and real time PCR. Currently, samples from tumor specimens as well as several distinct zones of the surrounding non-malignant tissue from approximately 100 breast cancer patients are being investigated and characterized by generation of gene expression profiles and comparative genomic hybridization (CGH) data, followed by data analysis.
Advanced statistical and functional tools for array data analysis are necessary for identification of the significant but sometimes subtle genetic variations in these large and heterogeneous data sets. In order to extract biological meaning and find relevant patterns, an in-house and publicly available software package for statistical and functional analysis of array data is being used (http://www.tm4.org/; Saeed AI et al. TM4: a free, open-source system for microarray data management and analysis. Biotechniques. 2003 Feb;34(2):374-8). New algorithms for analysis and integration of different types of data are continuously being added to this software.
By this approach we hope to gain a better understanding of early molecular events leading to cancer and to develop tools that can be used for disease detection even before clinical or pathological signs of breast cancer occur.
This project started in 2004 and is a close collaboration with Dr.Timothy Yeatman of The H. Lee Moffitt Cancer Center, Tampa, Florida. (http://www.moffitt.usf.edu/)