Abstract 1472: Building comprehensive and fully annotated patient tumor derived xenogragft (PDX) library mirroring cancer patient population
Authors: Cai Jie , Chen Dawei , Kumari Rajendra , Guo Sheng , Yang Jie , Yang Mengmeng , McKenzie Andrew , Wang Zhun , Huang Xuesong , An Xiaoyu , Liu Jinping , Wery Jean-Pierre , Li Henry 
Published: August 2015

Abstract
Patient derived xenografts (PDXs) mirrors patients’ pathology and genetic profiles, thus valued as predictive experimental models for studying oncogenesis and personalized treatments. Cancer is not a single disease but diseases of complex genetic components and oncogenic processes. Limited number of PDX models with minimal genetic characterization is insufficient to meet current research needs. For this, we have built the largest and most comprehensive PDX library with full genetic profiles. By far, our PDX library contains over 1,100 models derived from patients of both Asian and Western origins, covering over 20 major cancer types, including large panels (over 100 models each) of NSLCL(1), CRC(2), gastric(3), HCC(4), and pancreatic, and smaller panels (&lt;100) of esophageal, H&N, ovarian, cholangiocarcinoma, breast, brain, etc. Our PDX models come with original patient and pathology diagnosis information, and verified at the level of histopathology and genetic fingerprints. These models have tumor growth and standard of care (SOC) treatment information. They are fully profiled using GeneChip based technology (U219, SNP6.0, miRNA), NGS (RNAseq and WES), and hotspot mutation, etc (HuPrime® 1.0), with HLA typing readily available to enable immuno-oncology research. Comparing our PDXs’ genomic profiles with published patient genomic profiles in literature (4) and TCGA data source (Guo et al., 2015 AACR Annual) revealed high degree of similarity. Subsets of models have been comprehensively characterized for special relevance to specific clinical characteristics and specific drug targeting mechanisms (HuPrime® 2.0). These subsets include all clinically observed EGFR mutated NSCLC(1, 5, 6); c-MET activation diseases(7); FGFR driven diseases; RET-fusion driven CRC(8); FLT3-LTD driven AML (9), IDH mutated AML(9) and CRC; RSPO-fusion driven CRC; BCL-ABL fusion disease, HER driven gastric and breast cancers, and ALK fusion NSCLC, etc. We have also established numeric drug resistant models to various SOCs of both chemotherapy and target therapies. The resistance could be de novo (1) or induced (10). These resistant models can be great tools to investigate drug resistant mechanisms and approaches to overcome them. Many PDXs can also been tested orthotopically, including liver, brain, colon, pancreatic, ovarian, and breast etc. Models have great metastatic potential have also been identified, enabling study metastatic mechanism and identifying agents to block the metastasis. A number of PDXs can grow in humanized mice (HuPrime® 3.0), where human immunity has been reconstituted in the immune-compromised mouse background (11) to facilitate immune-oncology research.
Our large library of different disease panels are particularly useful in conducting mouse clinical trial (MCT of HuTrialTM) (2, 5, 12), which can be used to discover predictive biomarker (2, 5, 13) and guide clinical study design.
Citation Format: Jie Cai, Dawei Chen, Rajendra Kumari, Sheng Guo, Jie Yang, Mengmeng Yang, Andrew McKenzie, Zhun Wang, Xuesong Huang, Xiaoyu An, Jinping Liu, Jean-Pierre Wery, Henry Li. Building comprehensive and fully annotated patient tumor derived xenogragft (PDX) library mirroring cancer patient population. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1472. doi:10.1158/1538-7445.AM2015-1472