Title: Expression profiling to predict the clinical behaviour of ovarian cancer fails independent evaluation
Authors: Gevaert, Olivier ×
De Smet, Frank
Van Gorp, Toon
Pochet, Nathalie
Engelen, Kristof
Amant, Frédéric
De Moor, Bart
Timmerman, Dirk
Vergote, Ignace #
Issue Date: 22-Jan-2008
Publisher: BioMed Central
Series Title: BMC Cancer vol:8 issue:1 pages:18-18
Abstract: ABSTRACT: BACKGROUND: In a previously published pilot study we explored the performance of microarrays in predicting clinical behaviour of ovarian tumours. For this purpose we performed microarray analysis on 20 patients and estimated that we could predict advanced stage disease with 100% accuracy and the response to platin-based chemotherapy with 76.92% accuracy using leave-one-out cross validation techniques in combination with Least Squares Support Vector Machines (LS-SVMs). METHODS: In the current study we evaluate whether tumour characteristics in an independent set of 49 patients can be predicted using the pilot data set with principal component analysis or LS-SVMs. RESULTS: The results of the principal component analysis suggest that the gene expression data from stage I, platin-sensitive advanced stage and platin-resistant advanced stage tumours in the independent data set did not correspond to their respective classes in the pilot study. Additionally, LS-SVM models built using the data from the pilot study - although they only misclassified one of four stage I tumours and correctly classified all 45 advanced stage tumours - were not able to predict resistance to platin-based chemotherapy. Furthermore, models based the pilot data and on previously published gene sets related to ovarian cancer outcomes, did not perform significantly better than our models. CONCLUSIONS: We discuss possible reasons for failure of the model for predicting response to platin-based chemotherapy and conclude that existing results based on gene expression patterns of ovarian tumours need to be thoroughly scrutinized before these results can be accepted to reflect the true performance of microarray technology.
Description: \emph{BMC Cancer}, vol. 8, no. 18, Jan. 2008
ISSN: 1471-2407
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Basic Research in Gynaecology Section (-)
Centre of Microbial and Plant Genetics
Gynaecological Imaging Section (-)
Gynaecological Oncology
ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
Section Woman - Miscellaneous (-)
Environment and Health - miscellaneous
× corresponding author
# (joint) last author

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