Proteomic Analysis of Malignant Ovarian Cancer Effusions as a Tool for Biologic and Prognostic Profiling
Open Access
- 1 February 2006
- journal article
- research article
- Published by American Association for Cancer Research (AACR) in Clinical Cancer Research
- Vol. 12 (3) , 791-799
- https://doi.org/10.1158/1078-0432.ccr-05-2516
Abstract
Purpose: Malignant epithelial ovarian cancer effusions are important in disease dissemination and clinical outcome. The identification of biochemical events active in effusions may improve our identification and application of targeted therapeutics. Experimental Design: Archival effusion samples for which outcome information was known were studied. Clinical variables were comparable between these groups. Two cohorts of patients with malignant effusion were assessed: those with effusion at presentation (Tap1) or at first recurrence (Tap2). Expression and activated fraction of selected signaling proteins were quantitated on serial protein microarrays using validated antibodies. Proteomic results and clinical variables were analyzed by univariate analysis followed by Cox proportional hazards model analysis. Results: Malignant effusions (>80% malignant cells) were distinguished from benign effusions by higher expression of AKT, activated extracellular signal-regulated kinase, activated (P ≤ 0.001) and total cAMP-responsive element binding protein (P = 0.01), and JNK (P = 0.03). Malignant pleural effusions could not be differentiated from ascites by signaling profiles. Both had signal expression clusters for survival, proliferation and metastasis, and injury pathways. Cox proportional hazards model analysis revealed high p38 and pEGFR/EGFR ratio as jointly associated with poor survival in Tap1 cases (both P ≤ 0.002). Phospho-JNK quantity was associated with worse outcome in Tap2 patients (P = 0.004), when taking other factors into consideration. Conclusions: Proliferation, survival, and apoptosis signaling dysregulation can be identified in ovarian cancer effusion samples. Biochemical characterization of clinical effusions may provide either predictive and/or correlative information on patient outcome from which to further understand the mechanisms of effusion development and target clinical intervention.Keywords
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