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Prediction of recurrence of non muscle-invasive bladder cancer by means of a protein signature identified by antibody microarray analyses
Article first published online: 29 APR 2014
© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Volume 14, Issue 11, pages 1333–1342, June 2014
How to Cite
Srinivasan, H., Allory, Y., Sill, M., Vordos, D., Alhamdani, M. S. S., Radvanyi, F., Hoheisel, J. D. and Schröder, C. (2014), Prediction of recurrence of non muscle-invasive bladder cancer by means of a protein signature identified by antibody microarray analyses. Proteomics, 14: 1333–1342. doi: 10.1002/pmic.201300320
- Issue published online: 5 JUN 2014
- Article first published online: 29 APR 2014
- Accepted manuscript online: 9 MAR 2014 10:59PM EST
- Manuscript Accepted: 28 FEB 2014
- Manuscript Revised: 5 FEB 2014
- Manuscript Received: 2 AUG 2013
- European Commission as part of the DropTop, ProteinBinders, AffinityProteome, and Affinomics projects
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Figure S1. Hierarchical cluster analysis of the sample set. The Euclidean distance and the average linkage method were used. For each sample, the identifier and the incubation batch are given. The incubation batches do not cluster. Repeated samples, however, are located next or very close to each other. Samples whose names start with the letter V represent healthy bladder and cluster next to each other. Below, the two labels and five array batches are indicated by a colour-code.
Figure S2. Volcano plot summarising expression differences between samples from cancer and healthy patients. The Log2-fold change and respective FDR are given. The black dots above the red line indicate proteins with significantly different expression (FDR < 0.05).
Figure S3. Distribution of protein expression in all patient samples. Data are shown for all differential proteins.
Figure S4. Expression variations in the TGF-beta signalling pathways. Proteins with significantly differential expression in samples with and without recurrence are coloured in the KEGG pathway of TGF-beta signalling. Red stands for higher and green for lower protein expression in recurrent samples. Clearly, the TGF-beta pathway is less active in recurrent samples as compared to non-recurrent tumours.
Figure S5. Expression variations in the apoptosis pathway. Proteins with significantly differential expression in samples with and without recurrence are coloured in the KEGG pathway for apoptosis. Red stands for higher and green for lower protein expression in recurrent samples.
Figure S6. Expression variations in cancer pathways. Proteins with significantly differential expression in samples with and without recurrence are coloured in the KEGG cancer pathways. Red stands for higher and green for lower protein expression in recurrent samples.
Figure S7. Protein interactions of strongly regulated proteins. Analysis of the protein expression data with the pathway analysis software STRING 9.1 revealed several protein interactions. Proteins coloured in red were higher expressed in recurrent than non-recurrent tumours; green-coloured proteins exhibited lower expression.
Table S1. List of the proteins targeted by the 813 antibodies used in the analysis.
Table S2. Proteins with differential expression in samples from patients with recurrent and non-recurrent tumours.
Table S3. Proteins with differential expression in non muscle-invasive tumors and normal bladder tissue samples.
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