Project description:Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease with limited effective treatment options. PDAC tumors frequently harbor the constitutively activated form of KRAS which drives proliferative signaling, but directly targeting KRAS has so far been unsuccessful. To overcome this limitation, combinatorial treatment strategies have been developed to inhibit upstream activators and downstream effectors of KRAS signaling. One such combination using trametinib, a MEK1/2 inhibitor, and lapatinib, an EGFR/HER2 inhibitor, substantially reduced tumor growth in a patient-derived xenograft (PDX) model of PDAC. Although trametinib and lapatinib are both known to inhibit the canonical MAPK signaling cascade, the effects of this combination on other important pathways in pancreatic cancer remains unclear. To investigate this, we analyze global gene expression profiles from PDX models of PDAC treated with trametinib, lapatinib, or their combination. Our results show that trametinib induces similar yet less significant expression changes compared to combination while lapatinib has little to no effect as a monotherapy in the acute treatment setting. In the chronic treatment setting, we show that tumors exposured to prolonged treatment with trametinib plus lapatinib eventually leads to adapative resistance. Expression analyses of resistant tumors revealed concominant gene expression changes in upstream receptor tyrosine kinases (RTKs).
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: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 ductal adenocarcinoma (PDAC) has the worst prognosis of all common cancers, but divergent outcomes are apparent between patients. To delineate the intertumor heterogeneity that contributes to this, we aimed to identify clinically distinct gene expression-based subgroups. From a cohort of 345 resected pancreatic cancer cases, 90 samples with confirmed diagnosis of PDAC and sufficient tumor content were available for gene expression analysis by RNA sequencing. Unsupervised classification was applied, and a classifier was constructed. Species-specific transcript analysis on matching patient-derived xenografts (PDX, N=14) allowed construction of tumor- and stroma-specific classifiers for use on PDX models and cell lines.
Project description:A Cartes d'Identit des Tumeurs (CIT) project from the french Ligue Nationale Contre le Cancer (http://cit.ligue-cancer.net): 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. the MultiOmicClassification variable indicates groups resulting from the analysis, and the CIMPclass, the CpG Island Methylator Phenotype as estimated by the methylation analysis. This dataset, describes the miRNA-Seq data used in the multiOmics analysis.
Project description:The ex vivo modelling of pancreatic ductal adenocarcinoma (PDAC) using patient-derived cells is a promising tool to predict treatment responses. Matrigel-based organoid and organotypic approaches are limited by their undefined molecular composition, hindering the recapitulation of the tumour’s characteristic desmoplasia, which is known to promote drug resistance. To overcome these limitations, we used self-assembling peptide amphiphiles (PAs) gelled in a minimal extracellular matrix to model the pancreatic tumour microenvironment and to establish 3D multicellular cultures of patient-derived PDAC cells, pancreatic stellate cells and macrophages. Matrisome analysis of 3D cultures demonstrated consistent ECM protein deposition, which was highly reminiscent of the corresponding primary PDAC tissues. The proteomic data obtained was also compared to the corresponding patient-derived xenografts (PDX) in nude mice and Matrigel-based cultures. Characterisation of the chemosensitivity of the cultures revealed realistic treatment responses by PDAC cells in PA hydrogels based on the responses of their corresponding PDX tumours. Histological, transcriptional and functional techniques confirmed these similarities, which were not observed in Matrigel-based cultures. These findings demonstrate the biomimetic nature of PA hydrogels, which enable cultured cells to recreate the PDAC matrisome ex vivo and to respond to chemotherapeutic agents in a predictive manner.
Project description:Pancreatic ductal adenocarcinoma (PDAC) is a nearly uniformly lethal malignancy, with most patients facing an adverse clinical outcome. Given the pivotal role of aberrant Notch signaling in the initiation and progression of PDAC, we investigated the effect of MRK-003, a potent and selective γ-secretase inhibitor, in preclinical PDAC models. We used a panel of human PDAC cell lines, as well as patient-derived PDAC xenografts, to determine whether pharmacological targeting of the Notch pathway could inhibit pancreatic tumor growth and potentiate gemcitabine sensitivity. In vitro, MRK-003 treatment downregulated the canonical Notch target gene Hes-1, significantly inhibited anchorage independent growth, and reduced the subset of CD44+CD24+ and aldehyde dehydrogenase (ALDH)+ cells that have been attributed with tumor initiating capacity. Ex vivo pretreatment of PDAC cells with MRK-003 in culture significantly inhibited the subsequent engraftment in immunocompromised mice. In vivo, MRK-003 monotherapy significantly blocked tumor growth in 5 of 9 (56%) patient-derived PDAC xenografts. Moreover, a combination of MRK-003 and gemcitabine showed enhanced antitumor effects compared to gemcitabine alone in 4 of 9 (44%) PDAC xenografts. Baseline gene expression analysis of the treated xenografts indicated that upregulation of nuclear factor kappa B (NFκB) pathway components was associated with the sensitivity to single MRK-003, while upregulation in B-cell receptor (BCR) signaling and nuclear factor erythroid-derived 2-like 2 (NRF2) pathway correlated with response to the combination of MRK-003 with gemcitabine. The preclinical findings presented here provide further rationale for small molecule inhibition of Notch signaling as a therapeutic strategy in PDAC. Pancreatic ductal adenocarcinoma xenografts were grown in Athymic Nude-Foxn1nu mice. RNA was extracted and profiled in Affymetrix platform to identify genes correlating with sensitivity to MRK-003
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. the variable MultiOmicsClassification indicates the resulting sample's group. Whole-genome DNA methylation was analyzed using the Illumina Infinium HumanMethylation450 Beadchips. Integragen SA (Evry, France) carried out microarray experiments and hybridized to the BeadChip arrays following the manufacturer’s instructions. Illumina GenomeStudio software was used to extract the beta value DNA methylation score for each locus. We removed data from probes that contained SNPs or overlapped with a repetitive element that was not uniquely aligned to the human genome or regions of insertions and deletions in the human genome. The CpG Island Methylator Phenotype (CIMP) index was determined using methylation Illumina Infinium HumanMethylation450 BeadChips based on previous low throughput work (Toyota, 1999). In brief, all island CpG found to be unmethylated (<20% Beta-value) in all 25 normal pancreatic samples from the ICGC consortium (Nones, 2014) were selected. The CIMP index was calculated independently for each sample as the proportion of methylated (>30% Beta-value) CpGs among the selected normally unmethylated island CpG.
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.