首页 > 期刊杂志 > 正文

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

Kim G,Davidson B,Henning R,Wang J,Yu M,Annunziata C,Hetland T,Kohn EC

Abstract

Ovarian cancer cells in malignant effusions lack attachment to solid-phase matrix substrata and receive survival stimuli through cell-cell and cell-soluble matrix molecule interactions. We hypothesized that adhesion-related survival and proliferation pathway signals can inform clinical outcomes and guide targeted therapeutics.
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.
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).
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.

摘要

full text

我要评论

0条评论