Establishment and Thorough Characterization of Xenograft (PDX) Models Derived from Patients with Pancreatic Cancer for Molecular Analyses and Chemosensitivity Testing

Simple Summary Patients with pancreatic cancer (PC) still have a poor prognosis as therapeutic options are quite limited for both resectable and inoperable as well as metastasized late-stage tumors. The aim of our study was to generate a PC-PDX in vivo platform of well-characterized models. For this, patient tissues were implanted into immunocompromised mice and established PDXs were examined for morphology, and analyzed regarding their response to standard of care (SoC) drugs, HLA status and molecular characteristics. Our established 45 PC-PDX models closely resemble patient tumor morphology, mutational status, gene expression profile and sensitivity toward gemcitabine, abraxane and 5-FU. Moreover, we show replacement of human tissue by murine stroma, and that stroma components collagen I, alpha-SMA, FAP and SPARC remain unaffected by the implantation route (s.c. vs. orthotopic) as well as by SoC drug treatment. The comprehensive data set of our PDX models allows testing for new therapeutic targets and novel therapies for PC.Abstract Patient-derived xenograft (PDX) tumor models are essential for identifying new biomarkers, signaling pathways and novel targets, to better define key factors of therapy response and resistance mechanisms. Therefore, this study aimed at establishing pancreas carcinoma (PC) PDX models with thorough molecular characterization, and the identification of signatures defining responsiveness toward drug treatment. In total, 45 PC-PDXs were generated from 120 patient tumor specimens and the identity of PDX and corresponding patient tumors was validated. The majority of engrafted PDX models represent ductal adenocarcinomas (PDAC). The PDX growth characteristics were assessed, with great variations in doubling times (4 to 32 days). The mutational analyses revealed an individual mutational profile of the PDXs, predominantly showing alterations in the genes encoding KRAS, TP53, FAT1, KMT2D, MUC4, RNF213, ATR, MUC16, GNAS, RANBP2 and CDKN2A. Sensitivity of PDX toward standard of care (SoC) drugs gemcitabine, 5-fluorouracil, oxaliplatin and abraxane, and combinations thereof, revealed PDX models with sensitivity and resistance toward these treatments. We performed correlation analyses of drug sensitivity of these PDX models and their molecular profile to identify signatures for response and resistance. This study strongly supports the importance and value of PDX models for improvement in therapies of PC.