TY - JOUR A1 - Staiger, Christine A1 - Cadot, Sidney A1 - Kooter, Raul A1 - Dittrich, Marcus A1 - Müller, Tobias A1 - Klau, Gunnar W. A1 - Wessels, Lodewyk F. A. T1 - A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer JF - PLoS One N2 - Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single genes classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single genes classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single genes classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single genes sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single genes classifiers for predicting outcome in breast cancer. KW - modules KW - protein-interaction networks KW - expression signature KW - classification KW - set KW - metastasis KW - stability KW - survival KW - database KW - markers Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-131323 VL - 7 IS - 4 ER - TY - JOUR A1 - Wang, Huiqiang A1 - Chen, Nanhai G. A1 - Minev, Boris R. A1 - Szalay, Aladar A. T1 - Oncolytic vaccinia virus GLV-1h68 strain shows enhanced replication in human breast cancer stem-like cells in comparison to breast cancer cells JF - Journal of Translational Medicine N2 - Background: Recent data suggest that cancer stem cells (CSCs) play an important role in cancer, as these cells possess enhanced tumor-forming capabilities and are responsible for relapses after apparently curative therapies have been undertaken. Hence, novel cancer therapies will be needed to test for both tumor regression and CSC targeting. The use of oncolytic vaccinia virus (VACV) represents an attractive anti-tumor approach and is currently under evaluation in clinical trials. The purpose of this study was to demonstrate whether VACV does kill CSCs that are resistant to irradiation and chemotherapy. Methods: Cancer stem-like cells were identified and separated from the human breast cancer cell line GI-101A by virtue of increased aldehyde dehydrogenase 1 (ALDH1) activity as assessed by the ALDEFLUOR assay and cancer stem cell-like features such as chemo-resistance, irradiation-resistance and tumor-initiating were confirmed in cell culture and in animal models. VACV treatments were applied to both ALDEFLUOR-positive cells in cell culture and in xenograft tumors derived from these cells. Moreover, we identified and isolated CD44\(^+\)CD24\(^+\)ESA\(^+\) cells from GI-101A upon an epithelial-mesenchymal transition (EMT). These cells were similarly characterized both in cell culture and in animal models. Results: We demonstrated for the first time that the oncolytic VACV GLV-1h68 strain replicated more efficiently in cells with higher ALDH1 activity that possessed stem cell-like features than in cells with lower ALDH1 activity. GLV-1h68 selectively colonized and eventually eradicated xenograft tumors originating from cells with higher ALDH1 activity. Furthermore, GLV-1h68 also showed preferential replication in CD44\(^+\)CD24\(^+\)ESA\(^+\) cells derived from GI-101A upon an EMT induction as well as in xenograft tumors originating from these cells that were more tumorigenic than CD44\(^+\)CD24\(^-\)ESA\(^+\) cells. Conclusions: Taken together, our findings indicate that GLV-1h68 efficiently replicates and kills cancer stem-like cells. Thus, GLV-1h68 may become a promising agent for eradicating both primary and metastatic tumors, especially tumors harboring cancer stem-like cells that are resistant to chemo and/or radiotherapy and may be responsible for recurrence of tumors. KW - tumors KW - therapy KW - metastasis KW - identification KW - lines KW - gene expression KW - in-vitro propagation KW - acute myeloid leukemia KW - epithelial-mesenchymal transition KW - subpopulation Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-130019 VL - 10 IS - 167 ER -