Abstract 1052: Identification of signal transduction pathway activity in patient-derived xenograft models in comparison with their originating clinical samples of a variety of human cancer types

• Published in: Cancer research (Chicago, Ill.) Vol. 78; no. 13_Supplement; p. 1052
• Main Authors: Verhaegh, Wim, Stolpe, Anja van de, Caushaj, Nevisa, Landesfeind, Manuel, Zaremba, Angelika
• Format: Journal Article
• Language: English
• Published: 01.07.2018
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/1538-7445.AM2018-1052

Abstract Background. Targeted drugs are directed against cellular signal transduction pathways, such as the PI3K pathway, and efficacy depends on the active pathway in the tumor. Development and clinical application of targeted drugs for personalized cancer treatment require tests which identify pathway activity in cancer cells/tissue. Patient-derived xenograft (PDX) models are becoming the cornerstone of preclinical drug development. Characterization of PDX models and clinical samples for pathway activity is needed for successful preclinical drug testing and patient drug response prediction. Inference of signal transduction pathway activity from cancer genomics information is often unreliable. A novel analysis method has been developed which enables identification and quantification of activity of signal transduction pathways, based on Bayesian reasoning models which infer an activity score from mRNA levels of pathway target genes (Verhaegh et al, Cancer Res 2014:2936-45). For the AR, ER, PI3K, Hedgehog, TGFbeta, Wnt, and NFkB pathways, models have been biologically validated on a number of different cell/tissue types. Methods. For a number of different cancer types (among which colon, breast, lung, ovarian, bladder, osteosarcoma, melanoma, esophagus), AR, ER, PI3K, Hedgehog, TGFbeta, Wnt, and NFkB pathway activity was inferred from Affymetrix HG-U133Plus2.0 microarray data, available from clinical studies (GEO database) and from PDX models (Charles River). Clinical and xenograft pathway activity scores were compared and where possible correlated to genomic datato identify associated pathway driving alterations. Results. Different cancer types were analyzed and compared. Pathway activity patterns for different cancer types in PDX models resemble pathway activity in clinical patient cohorts. Furthermore, known associated cancer mutations are reproduced in PDX models, such as APC mutations in colon PDX and ovary PDX, and an activating beta-catenin mutation in breast PDX, that show an activated Wnt pathway. Conclusion. Signal transduction pathway activity in PDX models resembles pathway activity in patient cohorts with corresponding cancer types and corresponds with known driving mutations. Functional pathway activity testing in PDX models is expected to increase xenograft model utility for (1) further validation of pathway tests for clinical diagnostic use and for (2) preclinical testing of targeted drug efficacy. Citation Format: Wim Verhaegh, Anja van de Stolpe, Nevisa Caushaj, Manuel Landesfeind, Angelika Zaremba. Identification of signal transduction pathway activity in patient-derived xenograft models in comparison with their originating clinical samples of a variety of human cancer types [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1052.