Authors
Nhu-An Pham; Nikolina Radulovich; Emin Ibrahimov; Sebastiao N. Martins-Filho; Quan Li; Melania Pintilie; Jessica Weiss; Vibha Raghavan; Michael Cabanero; Robert E. Denroche; Julie M. Wilson; Cristiane Metran-Nascente; Ayelet Borgida; Shawn Hutchinson; Anna Dodd; Michael Begora; Dianne Chadwick; Stefano Serra; Jennifer J. Knox; Steven Gallinger; David W. Hedley; Lakshmi Muthuswamy; Ming-Sound Tsao
Abstract
Patient-derived xenograft (PDX) and their xenograft-derived organoid (XDO) models that recapitulate the genotypic and phenotypic landscape of patient cancers could help to advance research and lead to improved clinical management. PDX models were established from 276 pancreato-duodenal and biliary cancer resections. Initial, passage 0 (P0) engraftment rates were 59% (118/199) for pancreatic, 86% (25/29) for duodenal, and 35% (17/48) for biliary ductal tumors. Pancreatic ductal adenocarcinoma (PDAC), had a P0 engraftment rate of 62% (105/169). KRAS mutant and wild-type PDAC models were molecularly profiled, and XDO models were generated to perform initial drug response evaluations. Subsets of PDAC PDX models showed global copy number variants and gene expression profiles that were retained with serial passaging, and they showed a spectrum of somatic mutations represented in patient tumors. PDAC XDO models were established, with a success rate of 71% (10/14). Pathway activation of KRAS-MAPK in PDXs was independent of KRAS mutational status. Four wild-type KRAS models were characterized by one with EGFR (L747-P753 del), two with BRAF alterations (N486_P490del or V600E), and one with triple negative KRAS/EGFR/BRAF. Model OCIP256, characterized by BRAF (N486-P490 del), had activated phospho-ERK. A combination treatment of a pan-RAF inhibitor (LY3009120) and a MEK inhibitor (trametinib) effectively suppressed phospho-ERK and inhibited growth of OCIP256 XDO and PDX models. PDAC/duodenal adenocarcinoma have high success rates forming PDX/organoid and retaining their phenotypic and genotypic features. These models may be effective tools to evaluate novel drug combination therapies.
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