Genetic alterations and gene expression profiles of solid tumors

Genetic alterations and gene expression profiles of solid tumors

Prof. dr. M.J. van de Vijver, pathologist, P.I., department of Pathology, Academic Medical Center, University of Amsterdam

The research in our group is aimed at the use of genetic techniques to refine classification of solid tumors, with an emphasis on breast cancer, ovarian cancer and pancreatic cancer.
Breast cancer is presently classified based on tumor diameter, histologic type and grade, lymph node status and estrogen receptor, progesterone receptor and HER2 status. This classification has important implications for the treatment of breast cancer patients.

A more refined classification should be possible based on genetic alterations and gene expression profiles.
The genetic alterations identified in breast cancer are amplification of between 10 and 20 oncogenes and mutations in several tumor suppressor genes.
We have previously studied the genetic alterations (with a focus on HER2 gene amplification) in breast carcinomas in relation to clinical and pathological parameters.

Gene expression profiling has led to the identification of subsets of breast cancer revealed by unsupervised and supervised classification.
We have used supervised classification to identify a 70 gene prognosis profile and clinical studies are ongoing to investigate if and how this prognosis profile can be implemented in clinical practice.

The main projects on breast cancer are the identification of genetic alterations and gene expression profiles that are associated with pattern of metastasis and response to chemotherapy in patients with metastastatic breast cancer; and through participation in the EU funded BASIS project to identify genetic alterations in breast cancer in relation to histopathological features using whole genome sequence analysis and detailed histological analysis if breast carcinomas.

In ovarian cancer and pancreatic cancer we are studying heterogeneity of genetic alterations and gene expression profiles; and association with prognosis and response to therapy.