Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Abstract P2-09-12: Phosphoproteomic Pathway Profiling of Breast Cancers for Biomarker and Target Discovery for Personalized Therapy
Ist Teil von
Cancer research (Chicago, Ill.), 2010-12, Vol.70 (24_Supplement), p.P2-P2-09-12
Erscheinungsjahr
2010
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
Abstract
Introduction: The control and activation of signaling pathways has been shown to influence response to targeted therapy (PTEN and PI3K for trastuzumab, KRAS and MAPK for cetuximab). Single tissue biomarkers (eg HER2-receptor status) are often poor surrogates for the activation state of downstream pathways such as MAPK and PI3K. We have used phosphoproteomic profiling in order to reclassify breast tumors for therapeutic response prediction.
Methods: Eleven cell lines were profiled using phosphoproteome arrays (250 targets) and reclassified using unsupervised clustering. Sensitivity to therapy predicted by pathway activation status was correlated with sensitivity to therapies in vitro measured by the AlamarBlue cell viability assay. Target specificity was assayed using in-cell western blotting. Phosphoprotein clusters were validated in 107 breast tumors by reverse phase protein arrays (RPPA), and the expression of targets validated in independent cohorts of cancers by quantitative immunofluorescence (AQUA) on tissue microarrays.
Results: Phosphoproteomic profiling revealed 3 main clusters of breast tumors with overlap with existing molecular phenotypes (luminal, basal, and mixed) and different profiles of pathway activation (Cluster A: anti-apoptotic, Cluster B: growth factor-dependent, Cluster C: cell cycle-dependent). Good to excellent correlations between pathway activation and in vitro sensitivity to targeted therapies were shown for several pathways and individual molecules within pathways, including components of NFkB, STAT, and cell cycle. These biomarkers were shown to be present in clinical cohorts by RPPA and AQUA, and related to molecular phenotype. Conclusions: Phosphoproteomic profiling can be used to reclassify tumors in order to make a priori predictions about therapeutic targeting. These clusters exist in real clinical specimens and are therefore also promising biomarkers for targeted therapy.
Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P2-09-12.