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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:
Dimitry Nuyten Division of of Experimental Therapy, The Netherlands Cancer Institute, Amsterdam, The Netherlands
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