Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare the epigenomes of different patient-derived models of colorectal cancer (PDO, PDX and PDOX) to the original patient tumor. Methods: The Omni-ATAC protocol was utilized for ATAC library preparations. The nulcei were extracted from samples (PT, PDO, PDX and PDOX). For each sample set, three biological replicates were included. The libraries were sequenced using Illumina HiSeq 4000 PE 150bp. Results: Using an optimized data analysis workflow, we achieved high quality ATAC-seq library. Data were mapped to hg19 with over 90% mapping rate, and relative low mitochondria fraction (<30%). We used Diffbind to assess the chromatin accessibility enrichment in each model with a strict threshold of p <0.05 and |logFC|>1. Conclusions: Our study represents the first detailed analysis of CRC PDMC epigenome. CRC cells from all three models share chromatin alterations when compared to PT cells, representing a PT-PDMC epigenetic axis. Chromatin alterations in CRC cells are more similar betweeen PDOX and PDX than between PDOX and PDO, indicating that the growth environment of the model exerts strong influence on chraomtin adaptation in tumor cells.
Project description:Mouse models have been developed to investigate colorectal cancer etiology and evaluate new anti-cancer therapies. While genetically engineered and carcinogen-induced mouse models have provided important information with regard to the mechanisms underlying the oncogenic process, xenograft models remain the standard for the evaluation of new chemotherapy and targeted drug treatments for clinical use. However, it remains unclear if drug efficacy data obtained from xenograft models translate into clinically-relevant treatment modalities. In this study, we have generated a panel of 28 patient-derived colorectal cancer explants (PDCCEs), an extension of our previous work, by direct transplantation of human colorectal cancer (CRC) tissues into NOD-SCID mice. A comprehensive histological and molecular evaluation of PDCCEs and their corresponding patient tumor demonstrates that PDCCEs maintain histological features and global biology through multiple passages. Furthermore, we demonstrate that in vivo sensitivity of PDCCEs to oxaliplatin can predict patient outcomes. Our findings suggest that PDCCEs maintain similarity to the patient tumor from which they are derived and can serve as a reliable preclinical model that can be incorporated into future strategies to optimize individual therapy for patients with CRC. 28 human primary colorectal and 37 mouse derived colorectal explant tumors
Project description:Mouse models have been developed to investigate colorectal cancer etiology and evaluate new anti-cancer therapies. While genetically engineered and carcinogen-induced mouse models have provided important information with regard to the mechanisms underlying the oncogenic process, xenograft models remain the standard for the evaluation of new chemotherapy and targeted drug treatments for clinical use. However, it remains unclear if drug efficacy data obtained from xenograft models translate into clinically-relevant treatment modalities. In this study, we have generated a panel of 28 patient-derived colorectal cancer explants (PDCCEs), an extension of our previous work, by direct transplantation of human colorectal cancer (CRC) tissues into NOD-SCID mice. A comprehensive histological and molecular evaluation of PDCCEs and their corresponding patient tumor demonstrates that PDCCEs maintain histological features and global biology through multiple passages. Furthermore, we demonstrate that in vivo sensitivity of PDCCEs to oxaliplatin can predict patient outcomes. Our findings suggest that PDCCEs maintain similarity to the patient tumor from which they are derived and can serve as a reliable preclinical model that can be incorporated into future strategies to optimize individual therapy for patients with CRC.
Project description:RNA-Seq and a species-specific mapping strategy were used to profile the human and mouse transcriptomes of tumour samples taken from 79 PDX models representing multiple cancer types (19 x breast, 37 x lung, 8 x colorectal, 7 x ovarian, 3 x endometrial, 2 x pancreatic, 2 x ampullary, 1 x leukaemia).