Functional characterization of epithelial ovarian cancer histotypes by drug target based protein signaling activation mapping: Implications for personalized cancer therapy. Issue 2 (January 2015)
- Record Type:
- Journal Article
- Title:
- Functional characterization of epithelial ovarian cancer histotypes by drug target based protein signaling activation mapping: Implications for personalized cancer therapy. Issue 2 (January 2015)
- Main Title:
- Functional characterization of epithelial ovarian cancer histotypes by drug target based protein signaling activation mapping: Implications for personalized cancer therapy
- Authors:
- Sereni, Maria Isabella
Baldelli, Elisa
Gambara, Guido
Deng, Jianghong
Zanotti, Laura
Bandiera, Elisabetta
Bignotti, Eliana
Ragnoli, Monica
Tognon, Germana
Ravaggi, Antonella
Meani, Francesco
Memo, Maurizio
Angioli, Roberto
Liotta, Lance A.
Pecorelli, Sergio L.
Petricoin, Emanuel
Pierobon, Mariaelena
Pandey, Akhilesh
Moran, Michael F. - Abstract:
- <abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>Epithelial ovarian carcinoma (EOC) is a deadly disease, with a 5‐year survival of 30%. The aim of the study was to perform broad‐scale protein signaling activation mapping to evaluate if EOC can be redefined based on activated protein signaling network architecture rather than histology. Tumor cells were isolated using laser capture microdissection (LCM) from 72 EOCs. Tumors were classified as serous (<italic>n</italic> = 38), endometrioid (<italic>n</italic> = 13), mixed (<italic>n</italic> = 8), clear cell (CCC; <italic>n</italic> = 7), and others (<italic>n</italic> = 6). LCM tumor cells were lysed and subjected to reverse‐phase protein microarray to measure the expression/activation level of 117 protein drug targets. Unsupervised hierarchical clustering analysis was utilized to explore the overall signaling network. ANOVA was used to detect significant differences among the groups (<italic>p</italic> &lt; 0.05). Regardless of histology, unsupervised analysis revealed five pathway‐driven clusters. When the EOC histotypes were compared by ANOVA, only CCC showed a distinct signaling network, with activation of EGFR, Syk, HER2/ErbB2, and SHP2 (<italic>p</italic> = 0.0007, <italic>p</italic> = 0.0021, <italic>p</italic> &lt; 0.0001, and <italic>p</italic> = 0.0410, respectively). The histological classification of EOC fails to adequately describe the underpinning protein signaling<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>Epithelial ovarian carcinoma (EOC) is a deadly disease, with a 5‐year survival of 30%. The aim of the study was to perform broad‐scale protein signaling activation mapping to evaluate if EOC can be redefined based on activated protein signaling network architecture rather than histology. Tumor cells were isolated using laser capture microdissection (LCM) from 72 EOCs. Tumors were classified as serous (<italic>n</italic> = 38), endometrioid (<italic>n</italic> = 13), mixed (<italic>n</italic> = 8), clear cell (CCC; <italic>n</italic> = 7), and others (<italic>n</italic> = 6). LCM tumor cells were lysed and subjected to reverse‐phase protein microarray to measure the expression/activation level of 117 protein drug targets. Unsupervised hierarchical clustering analysis was utilized to explore the overall signaling network. ANOVA was used to detect significant differences among the groups (<italic>p</italic> &lt; 0.05). Regardless of histology, unsupervised analysis revealed five pathway‐driven clusters. When the EOC histotypes were compared by ANOVA, only CCC showed a distinct signaling network, with activation of EGFR, Syk, HER2/ErbB2, and SHP2 (<italic>p</italic> = 0.0007, <italic>p</italic> = 0.0021, <italic>p</italic> &lt; 0.0001, and <italic>p</italic> = 0.0410, respectively). The histological classification of EOC fails to adequately describe the underpinning protein signaling network. Nevertheless, CCC presents unique signaling characteristics compared to the other histotypes. EOC may need to be characterized by functional signaling activation mapping rather than pure histology.</p> </abstract> … (more)
- Is Part Of:
- Proteomics. Volume 15:Issue 2/3(2015)
- Journal:
- Proteomics
- Issue:
- Volume 15:Issue 2/3(2015)
- Issue Display:
- Volume 15, Issue 2/3 (2015)
- Year:
- 2015
- Volume:
- 15
- Issue:
- 2/3
- Issue Sort Value:
- 2015-0015-NaN-0000
- Page Start:
- 365
- Page End:
- 373
- Publication Date:
- 2015-01
- Subjects:
- Proteins -- Separation -- Periodicals
Bioinformatics -- Periodicals
Proteomics -- Periodicals
Genomes -- Periodicals
Molecular genetics -- Periodicals
572.605 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1615-9861 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/pmic.201400214 ↗
- Languages:
- English
- ISSNs:
- 1615-9853
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6936.178000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 4029.xml