Research Interests

My research interests are in functional genomics and breast cancer. We are using DNA microarrays to study patterns of gene expression in clinical breast cancer samples. Breast cancer is a very heterogeneous disease presenting a diverse range of biologically characteristics of the tumors as well as different responses to treatment and clinically outcomes for the patients. The DNA microarray technology allows us to study expression of many genes in concert and to explore complex interplays between genes that otherwise would be unrecognized by standard methods. By using this technology in combination with statistical and bioinformatical tools, we have been able to identify specific patterns of gene expression that provided distinctive molecular portraits of breast tumors. Different sets of co-expressed genes give us clues to specific pathways that may be involved in these cancers as well as the cellular composition of the tumors.

In collaboration with other groups in the department as well as outside our hospital, we are also using this technology to study genome-wide copy number changes and single nucleotide polymorphisms (SNPs) in the same patient samples. Integrating such knowledge from several levels of molecular screening is needed to identify genes and proteins involved in tumorigenesis and ascertain their potential as prognostic and predictive factors as well targets for intervention.


This work can be divided into four subprojects:

1. Validation of the molecular subtypes of breast cancer and their clinical correlation in several breast cancer cohorts, focusing particularly on patients with earlier disease stages. Identification of a minimal set of informative predictor genes for this classification, and carry out comparative analyses of microarray-based and more quantitative methods for these genes.
2. Identification of gene expression profiles that can predict presence of micro-metastases in early breast cancer, using tumors from a series of breast cancer patients, for which researchers at DNR have developed methods for detecting single tumor cells in bone marrow.
3. Identification and validation of genes predictive of chemotherapy response, based on gene expression and array-based copy number (aCGH) profiling of tumor samples from prospective cohorts available to us that are designed to focus on chemotherapy response prediction in breast cancer. The profiles found in vivo will be tested functionally using RNA interference in breast cancer cell lines.
4. Identification of gene targets undergoing somatic genetic mutations in breast cancer using a novel NMD-aCGH method. Combination of the NMD microarray data on mutated candidate genes with the aCGH data on deletions should enable us to identify classical “two-hit” tumor suppressor genes (TSG) in breast cancer. These analyses are complemented with methylation studies to further explore the TSG cadidates.