4.7 Article

Comparative proteome, transcriptome, and genome analysis of a gonadal and an extragonadal germ cell tumor cell

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 7, Issue 9, Pages 3890-3899

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/pr800173g

Keywords

extragonadal germ cell tumor; comparative proteome analysis; array-CGH; cisplatin resistance; cell lines

Funding

  1. Wilhelm Sander-Stiftung
  2. Werner Otto Stiftung

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Whereas clinical differences between testicular and extragonadal germ cell tumors (GCT), like reduced cisplatin sensitivity of extragonadal tumors, are well-established, little is known about underlying tumor biology. A combined approach using global proteome analysis and RT-PCR to assess mRNA levels of selected proteins on the one hand, and array comparative genomic hybridization (array-CGH), on the other hand, was used to compare two germ cell tumor (GCT) cell lines showing embryonal carcinoma histology, one of testicular, and one of extragonadal origin. Overall, the two cell lines show remarkably similar protein profiles. In total, 66 proteins were found to be differentially expressed in an at least 2-fold manner. Of these, 35 proteins (53%) could be positively identified by peptide mass fingerprinting and database search. mRNA levels of 27 differentially expressed proteins were analyzed by RT-PCR. In 17/27 genes (63%), differences in mRNA expression corresponded with differences detected on protein level, suggesting that these proteins are mainly regulated through transcription. Interestingly, no close correlation was found between proteomic and genomic analysis: 13/30 genes (43%) with higher protein levels in one cell line showed higher copy numbers of the respective gene loci in array-CGH analysis. Corresponding differences from proteome, transcriptome, and mRNA analyses were found in 9 of 27 proteins (33%). Several proteins potentially involved in cisplatin resistance were identified in the extragonadal cell line, suggesting that the cisplatin-resistant phenotype of this cell line is multifactorial. Furthermore, our data demonstrate that a combined approach of proteome, transcriptome, and genome analysis is a promising tool to gain information on gene regulation in human tumors.

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