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Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform.

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Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform. / Ummanni, Ramesh; Mundt, Frederike; Pospisil, Heike; Venz, Simone; Scharf, Christian; Barett, Christine; Fälth, Maria; Köllermann, Jens; Walther, Reinhard; Schlomm, Thorsten; Sauter, Guido; Bokemeyer, Carsten; Sültmann, Holger; Schuppert, A; Brümmendorf, Tim; Balabanov, Stefan.

In: PLOS ONE, Vol. 6, No. 2, 2, 2011, p. 16833.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Ummanni, R, Mundt, F, Pospisil, H, Venz, S, Scharf, C, Barett, C, Fälth, M, Köllermann, J, Walther, R, Schlomm, T, Sauter, G, Bokemeyer, C, Sültmann, H, Schuppert, A, Brümmendorf, T & Balabanov, S 2011, 'Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform.', PLOS ONE, vol. 6, no. 2, 2, pp. 16833. https://doi.org/10.1371/journal.pone.0016833

APA

Ummanni, R., Mundt, F., Pospisil, H., Venz, S., Scharf, C., Barett, C., Fälth, M., Köllermann, J., Walther, R., Schlomm, T., Sauter, G., Bokemeyer, C., Sültmann, H., Schuppert, A., Brümmendorf, T., & Balabanov, S. (2011). Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform. PLOS ONE, 6(2), 16833. [2]. https://doi.org/10.1371/journal.pone.0016833

Vancouver

Ummanni R, Mundt F, Pospisil H, Venz S, Scharf C, Barett C et al. Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform. PLOS ONE. 2011;6(2):16833. 2. https://doi.org/10.1371/journal.pone.0016833

Bibtex

@article{667593f8c9d642e6892a102a068ed39e,
title = "Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform.",
abstract = "Prostate cancer (PCa) is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE) coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24) compared to benign (n = 21) prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies.",
author = "Ramesh Ummanni and Frederike Mundt and Heike Pospisil and Simone Venz and Christian Scharf and Christine Barett and Maria F{\"a}lth and Jens K{\"o}llermann and Reinhard Walther and Thorsten Schlomm and Guido Sauter and Carsten Bokemeyer and Holger S{\"u}ltmann and A Schuppert and Tim Br{\"u}mmendorf and Stefan Balabanov",
year = "2011",
doi = "10.1371/journal.pone.0016833",
language = "Deutsch",
volume = "6",
pages = "16833",
journal = "PLOS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "2",

}

RIS

TY - JOUR

T1 - Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform.

AU - Ummanni, Ramesh

AU - Mundt, Frederike

AU - Pospisil, Heike

AU - Venz, Simone

AU - Scharf, Christian

AU - Barett, Christine

AU - Fälth, Maria

AU - Köllermann, Jens

AU - Walther, Reinhard

AU - Schlomm, Thorsten

AU - Sauter, Guido

AU - Bokemeyer, Carsten

AU - Sültmann, Holger

AU - Schuppert, A

AU - Brümmendorf, Tim

AU - Balabanov, Stefan

PY - 2011

Y1 - 2011

N2 - Prostate cancer (PCa) is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE) coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24) compared to benign (n = 21) prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies.

AB - Prostate cancer (PCa) is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE) coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24) compared to benign (n = 21) prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies.

U2 - 10.1371/journal.pone.0016833

DO - 10.1371/journal.pone.0016833

M3 - SCORING: Zeitschriftenaufsatz

VL - 6

SP - 16833

JO - PLOS ONE

JF - PLOS ONE

SN - 1932-6203

IS - 2

M1 - 2

ER -