Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform.
Standard
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, Jahrgang 6, Nr. 2, 2, 2011, S. 16833.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
Harvard
APA
Vancouver
Bibtex
}
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 -