Gene expression profiling can identify individual patients at increased risk of developing a local recurrence after breast-conserving therapy


This study is the first one to describe a micro array based predictor for local recurrence after breast conserving therapy. Many groups have focussed on prognosis prediction (development of distant metastasis) and response to neo-adjuvant chemotherapy. Unfortunately, all the large publicly available micro array data sets for breast cancer lack detailed information on local recurrence. Therefore we have used our own data set for training and validation (the patients were randomly assigned to one of the two sets).

We have applied a combination of biological gene expression profiling (hypothesis driven gene expression analysis) and a supervised (data or outcome driven) analysis to optimize the predictive value of the previously established profiles towards local recurrence. Out these profiles, the Wound-response signature is the only one that shows a significant prediction of local recurrence risk in the validation series. A recent meta-analysis from the EBTCG on local treatment confirms the importance of local control in breast cancer. This classifier might be helpful in clinical decision making for breast cancer patients after validation in a larger patient series.  

 

Bibliographic reference:

Nuyten DS et al.: "Predicting a local recurrence after breast-conserving therapy by gene expression profiling", Breast Cancer Res. 2006 Oct 30;8(5):R62

 

Dimitry Nuyten

Division of of Experimental Therapy, The Netherlands Cancer Institute, Amsterdam, The Netherlands