Abstract 1016: Transcriptomic analysis of bulk tissues of large PDX collection as a novel platform discovering new TME target/drug

Abstract

Abstract Cancers are collections of diverse diseases of genetic and immunological abnormalities. The heterogeneous tumor microenvironment (TME), including immune components, and their interactions with tumor cells play critical roles in tumor progression and response to pharmaceutics, particularly immuno-oncology (I/O) therapy. However, investigating TME-specific components is rather challenging for the difficulty to separate stroma from tumor cells, either physically via microdissection or in silico via bioinformatics. Patient derived xenograft (PDX) may be a new system to investigate TME1, where human and mouse content can readily be separated in silico2. We have transcriptome-sequenced ~1600 bulk tumor tissues from subcutaneous PDXs grown in athymic mice3. By aligning reads to human and mouse genomes, we found that the average mouse-to-human sequencing read ratio is around 11% (5~20%), consistent with the previous report2. After removal of the low-expressed and less-variable genes and by deconvolution analysis of gene expression data, we identified all types of TME components, including adaptive and innate immune cells. The corresponding fractions vary across cancer types and individual models. Co-regulation analysis identified a huge number of intra-species interactions and also, a smaller number of inter-species interactions that vary greatly among different cancer types. The cross-species interactions observed are likely implicated in the growth of these tumors, and their numbers may also reveal the degree of the dependence of tumor growth on TME, which should be reversely correlated to the transplantation take-rate of corresponding type of PDX. Indeed, we have demonstrated this reverse-correlations (# interactions: take-rate %) with statistical-significance (p-value = 0.034) across our PDX collections, including melanoma (406:27%), lung (146:50%), colorectal (CRC) (157:68%) and pancreatic cancer (32:80%). The cancer type with the highest take-rate and lowest # interactions is pancreatic cancer that also has highest KRAS mutation rate (>90%), hinting the role of KRAS mutation in tumor growth independency on TME. This is further confirmed in KRAS mutant CRC (1:96%) vs. wild-type (98:53%). Moreover, some putative cross-species co-regulations in specific cancers were also observed in human tumors (e.g. in TCGA dataset), indicating potential importance in TME-tumor interaction and tumor development in human. Further investigation of each of these interactions may reveal novel TME-related disease pathways and thus novel targeting strategy for cancer therapy. In conclusion, transcriptomic analysis of large number of bulk PDXs provides a novel and unique platform to study TME, likely to facilitate new discovery of disease pathways and strategy to treat cancers involving the TME mechanism, particularly I/O strategy. Citation Format: Jia Xue, Wubin Qian, Sheng Guo, Xiaoyu An, Xuesong Ouyang, Henry Q. Li. Transcriptomic analysis of bulk tissues of large PDX collection as a novel platform discovering new TME target/drug [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 1016.