Adhesion molecule protein signature in ovarian cancer effusions is prognostic of patient outcome

作者:Kim Geoffrey; Davidson Ben; Henning Ryan; Wang Junbai; Yu Minshu; Annunziata Christina; Hetland Thea; Kohn Elise C*
来源:Cancer, 2012, 118(6): 1543-1553.
DOI:10.1002/cncr.26449

摘要

BACKGROUND: Ovarian cancer cells in malignant effusions lack attachment to solid-phase matrix substrata and receive survival stimuli through cellcell and cellsoluble matrix molecule interactions. We hypothesized that adhesion-related survival and proliferation pathway signals can inform clinical outcomes and guide targeted therapeutics. METHODS: Lysed cell pellets from a blinded set of benign (n 20) and malignant (n 51) peritoneal and pleural ovarian cancer patient effusions were applied to reverse-phase protein arrays and examined using validated antibodies to adhesion-associated protein endpoints. Results were subjected to hierarchical clustering for signature development. Association between specimen type, protein expression, and clinicopathologic associations were analyzed using the Mann-Whitney U test. Survival outcomes were estimated using the Kaplan-Meier method with log-rank comparison. RESULTS: A cell adhesion protein signature obtained from unsupervised clustering distinguished malignant from benign effusions (P 6.18E-06). Protein subset analyses from malignant cases defined 3 cell adhesion protein clusters driven by E-cadherin, epithelial cell adhesion molecule, and N-cadherin, respectively. The components of the E-and N-cadherin clusters correlated with clinical outcome by Kaplan-Meier statistics. Univariate analysis indicated that FAK and phosphorylated AKT were associated with higher overall and progression-free survival (PFS) (P.03), and Akt, phosphorylated paxillin, and E-and N-cadherin were associated with improved PFS (P .05). If 4 or 5 of the index adhesion proteins were high, PFS was improved by multivariate analysis (P .01). CONCLUSIONS: This hypothesis-testing examination of tumor cell adhesion molecules and pathways yielded potential predictive biomarkers with which to triage patients to selected molecular therapeutics and may serve as a platform for biomarker-based stratification for clinical application. Cancer 2012; 118: 1543-53. Published 2011 by the American Cancer Society*.

  • 出版日期2012-3-15