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Gene expression profiling of human ovarian tumours
S Biade1, M Marinucci, J Schick
1Department of Pharmacology, University of Pennsylvania Cancer Center, BRB II/III- Room 1020, 421 Curie Building, Philadelphia, PA, USA.
British Journal of Cancer
|September 14, 2006
Summary
Researchers identified gene expression profiles to distinguish ovarian tumor types. This could lead to better diagnostic and prognostic markers for ovarian cancer, aiding in clinical course prediction.
Area of Science:
- Oncology
- Genomics
- Biomarker Discovery
Background:
- Ovarian cancer lacks reliable diagnostic and prognostic markers.
- Gene expression profiling offers potential for improved classification.
Purpose of the Study:
- To identify gene expression profiles for ovarian tumors.
- To determine markers for histologic subtype, grade, and malignancy.
- To validate findings using quantitative RT-PCR and immunohistochemistry.
Main Methods:
- Gene expression profiling of 120 human ovarian tumors.
- Unsupervised and supervised cluster analysis.
- Quantitative RT-PCR and immunohistochemical analysis for validation.
Main Results:
- Three major tumor groups identified: benign, malignant, and mixed borderline/malignant.
- A set of genes distinguished benign, borderline, and malignant phenotypes.
- Borderline tumors interspersed between benign and malignant groups upon validation.
- Increased CD24 antigen expression in malignant versus benign tissue.
Conclusions:
- Gene expression profiles can classify ovarian tumors by malignancy.
- This classifier may predict the clinical course of borderline ovarian tumors.
- CD24 antigen expression is a potential marker for distinguishing tumor types.
