Project description:Pancreatic adenocarcinoma (PDAC) is one of the most lethal human malignancies and a major health problem. Patient-derived xenografts (PDX) are appearing as a prime approach for preclinical studies despite being insufficiently characterized as a model of the human disease and its diversity. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The extensive multiomics characterization of the xenografts demonstrated that PDX is a suitable model for preclinical studies, representing the diversity of the primary cancers. this dataset, describe the RNA sequencing data used in the multiomics study.
Project description:We generated novel patient derived xenograft (PDX) and cell line -derived xenograft models for pancreatic ductal adenocarcinoma (PDAC) which reflect different molecular subtypes. Pancreatic ductal adenocarcinoma is currently the tumor with the fourth highest mortality rate. Recently, subtypes of PDAC have been reported by Collisson et al (Nat. Med. 17(4) 2011. DOI: 10.1038/nm.2344). However current fetal calf serum (FCS) cultured cell lines do not accurately model these subtypes. We thus generated novel serum-free cell lines derived from primary patient xenografts. We here analyse the gene-expression profiles of the xenografts and the derived cell lines. We show that indeed three different subtypes can be separated in our models based on gene-expression data. Further, we identify upregulation of a drug-detoxification pathway specifically in xenografts and cell lines of one of the subtypes. These models and data will help to better understand inter-patient heterogeneity in PDAC and identify novel drug targets and diagnostic markers.
Project description:Pancreatic adenocarcinoma (PDAC) is one of the most lethal human malignancies and a major health problem. Patient-derived xenografts (PDX) are appearing as a prime approach for preclinical studies despite being insufficiently characterized as a model of the human disease and its diversity. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The extensive multiomics characterization of the xenografts demonstrated that PDX is a suitable model for preclinical studies, representing the diversity of the primary cancers. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The variable 'MultiOmicsClassification' indicates the resulting sample's group. 'CIMPclass' is the CpG island methylator phenotype as estimated from the methylation arrays analysis. In this dataset, Illumina Infinium HumanCode-24 BeadChips SNP arrays were used to analyze the DNA xenografts samples from pancreatic ductal adenocarcinoma.
Project description:Background/Aims: Microarray-based comparative genomic hybridisation (CGH) has allowed high-resolution analysis of DNA copy number alterations across the entire cancer genome. Recent advances in bioinformatics tools enable us to perform a robust and highly sensitive analysis of array CGH data and facilitate the discovery of novel cancer-related genes. Methods: We analysed a total of 29 pancreatic ductal adenocarcinoma (PDAC) samples (six cell lines and 23 microdissected tissue specimens) using 1 Mb-spaced CGH arrays. The transcript levels of all genes within the identified regions of genetic alterations were then screened using our Pancreatic Expression Database. Results: In addition to 238 high-level amplifications and 35 homozygous deletions, we identified 315 minimal common regions of “non-random” genetic alterations (115 gains and 200 losses) which were consistently observed across our tumour samples. The small size of these aberrations (median size of 880 kb) contributed to the reduced number of candidate genes included (on average 12 Ensembl-annotated genes). The database has further specified the genes whose expression levels are consistent with their copy number status. Such genes were UQCRB, SQLE, DDEF1, SLA, ERICH1 and DLC1, indicating that these may be potential target candidates within regions of aberrations. Conclusion: This study has revealed multiple novel regions that may indicate the locations of oncogenes or tumour suppressor genes in PDAC. Using the database, we provide a list of novel target genes whose altered DNA copy numbers could lead to significant changes in transcript levels in PDAC. (Harada et al. Pancreatology) Keywords: pancreatic ductal adenocarcinima, tissue microdissection, array CGH, genetic alterations A panel of 23 microdissected PDAC tissues and 6 PDAC-derived cell lines were analysed using Sanger's CGH arrays with 1 Mb resolution. Clinical info of the samples used is provided as a supplementary file.
Project description:This project describes the establishment and validation of a murine orthotopic xenograft model using fresh human tumor samples that recapitulates the critical components of human pancreatic adenocarcinoma. The authors discuss the proven and theoretical advantages of the model as well as future translational implications. Background: Relevant preclinical models that recapitulate the key features of human pancreatic ductal adenocarcinoma (PDAC) are needed in order to provide biologically tractable models to probe disease progression and therapeutic responses and ultimately improve patient outcomes for this disease. Here, we describe the establishment and clinical, pathological, molecular and genetic validation of a murine, orthotopic xenograft model of PDAC. Methods: Human PDACs were resected and orthotopically implanted and propagated in immunocompromised mice. Patient survival was correlated with xenograft growth and metastatic rate in mice. Human and mouse tumor pathology were compared. Tumors were analyzed for genetic mutations, gene expression, receptor tyrosine kinase (RTK) activation, and cytokine expression. Results: Fifteen human PDACs were propagated orthotopically in mice. Xenografts developed peritoneal and liver metastases. Time to growth and metastatic efficiency in mice each correlated with patient survival. Tumor architecture, nuclear grade and stromal content were similar in patient and xenografted tumors. Propagated tumors closely exhibited the genetic and molecular features known to characterize pancreatic cancer (e.g. high rate of KRAS, p53, SMAD4 mutation and EGFR activation). The correlation coefficient of gene expression between patient tumors and xenografts propagated through multiple generations was 93 to 99%. Analysis of gene expression demonstrated distinct differences between xenografts from fresh patient tumors versus commercially available PDAC cell lines. Conclusions: Our orthotopic xenograft model derived from fresh human PDACs closely recapitulates the clinical, pathologic, genetic and molecular aspects of human disease. This model has resulted in the identification of rational therapeutic strategies to be tested in clinical trials and will permit additional therapeutic approaches and identification of biomarkers of response to therapy. 47 Samples in total were generated for normal pancreatic tissue in patients, pancreatic tumors in patients, pancreatic tumors propagated in a mouse xenograft model, and pancreatic cancer cell lines in vitro. Clustering analysis was performed to evaluate the differences between patient tumors, xenograft tumors, established cancer cell lines, and cell lines derived from xenografts.
Project description:Background/Aims: Microarray-based comparative genomic hybridisation (CGH) has allowed high-resolution analysis of DNA copy number alterations across the entire cancer genome. Recent advances in bioinformatics tools enable us to perform a robust and highly sensitive analysis of array CGH data and facilitate the discovery of novel cancer-related genes. Methods: We analysed a total of 29 pancreatic ductal adenocarcinoma (PDAC) samples (six cell lines and 23 microdissected tissue specimens) using 1 Mb-spaced CGH arrays. The transcript levels of all genes within the identified regions of genetic alterations were then screened using our Pancreatic Expression Database. Results: In addition to 238 high-level amplifications and 35 homozygous deletions, we identified 315 minimal common regions of “non-random” genetic alterations (115 gains and 200 losses) which were consistently observed across our tumour samples. The small size of these aberrations (median size of 880 kb) contributed to the reduced number of candidate genes included (on average 12 Ensembl-annotated genes). The database has further specified the genes whose expression levels are consistent with their copy number status. Such genes were UQCRB, SQLE, DDEF1, SLA, ERICH1 and DLC1, indicating that these may be potential target candidates within regions of aberrations. Conclusion: This study has revealed multiple novel regions that may indicate the locations of oncogenes or tumour suppressor genes in PDAC. Using the database, we provide a list of novel target genes whose altered DNA copy numbers could lead to significant changes in transcript levels in PDAC. (Harada et al. Pancreatology) Keywords: pancreatic ductal adenocarcinima, tissue microdissection, array CGH, genetic alterations
Project description:RNA sequencing of pancreatic ductal adenocarcinoma (PDAC) primary cultures from five different patient-derived xenograft models grown either in adherent conditions selecting for non-CSCs or in CSC-enriching anchorage-independent sphere conditions. A and B are two biological duplicates, from the same patient-derived xenograft model of PDAC.
Project description:Determine methylation pattern in PDAC a genome-wide analysis was performed in a cohort of 167 PDAC and 29 adjacent pancreatic tissues samples using the Infinium 450k methylation arrays (Illumina). 167 pancreatic tumors (PDAC) x 29 adjacent -non tumor samples.
Project description:miRNAs are known to be involved in PDAC tumorigenesis, but only a few biologically relevant gene targets have been identified. Here we show that three miRNAs (miR-21, miR-23a and miR-27a) act in concert for the cooperative suppression of several tumor suppressor genes of which we experimentally validated PDCD4, BTG2 and NEDD4L. The synergistic inhibition of this triple miRNA combination is capable of reducing PDAC growth in a mouse model greater than inhibition of oncomiR-21 alone. Patients samples of normal pancreas (n=6) or pancreatic ductal adenocarcinoma (PDAC; n=6) were retrieved during surgery and placed in RNA Later stabilization fluid and then kept at minus 80 until required.
Project description:miRNAs are known to be involved in PDAC tumorigenesis, but only a few biologically relevant gene targets have been identified. Here we show that three miRNAs (miR-21, miR-23a and miR-27a) act in concert for the cooperative suppression of several tumor suppressor genes of which we experimentally validated PDCD4, BTG2 and NEDD4L. The synergistic inhibition of this triple miRNA combination is capable of reducing PDAC growth in a mouse model greater than inhibition of oncomiR-21 alone. Patients samples of normal pancreas (n=9) or pancreatic ductal adenocarcinoma (PDAC; n=9) were retrieved during surgery and placed in RNA Later stabilization fluid and then kept at minus 80 until required.