Ontology highlight
ABSTRACT:
PROVIDER: PRJNA891798 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR22044502_1.fastq.gz | Fastqsanger.gz | |||
| SRR22044502_2.fastq.gz | Fastqsanger.gz | |||
| SRR22044503_1.fastq.gz | Fastqsanger.gz | |||
| SRR22044503_2.fastq.gz | Fastqsanger.gz | |||
| SRR22044504_1.fastq.gz | Fastqsanger.gz |
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Project description:During pancreatic cancer progression, heterogeneous subclonal populations evolve in the primary tumor that possess differing capacities to metastasize and cause patient death. However, the genetics of metastasis reflects that of the primary tumor, and PDAC driver mutations arise early. This raises the possibility than an epigenetic process could be operative late. Using an exceptional resource of paired patient samples, we found that different metastatic subclones from the same patient possessed remarkably divergent malignant properties and global epigenetic programs. Global reprogramming was targeted to thousands of large chromatin domains across the genome that collectively specified malignant divergence. This was maintained by a metabolic shift within the pentose phosphate pathway, independent of KRAS driver mutations. Analysis of paired primary and metastatic tumors from multiple patients uncovered substantial epigenetic heterogeneity in primary tumors, which resolved into a terminally reprogrammed state in metastatic lesions. This supports a model whereby driver mutations accumulate early to initiate pancreatic tumorigenesis, followed by a period of subclonal evolution that generates sufficient intra-tumor heterogeneity for selection of epigenetic programs that may increase fitness during malignant progression and metastatic spread. To map the epigenomic landscape of pancreatic cancer progression as it evolves within patients. BS-Seq of 4 patients (A13, A38, A124 and A125). Patient A38 included local peritoneal metastasis and 2 distant metastsis (liver and lung mets). Patient A13 included 2 primary tumors and 1 distant lung metastasis. Each sample has been done with replicates. Patient A124 included 2 primary tumors and 1 normal pancreas.
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Project description:During pancreatic cancer progression, heterogeneous subclonal populations evolve in the primary tumor that possess differing capacities to metastasize and cause patient death. However, the genetics of metastasis reflects that of the primary tumor, and PDAC driver mutations arise early. This raises the possibility than an epigenetic process could be operative late. Using an exceptional resource of paired patient samples, we found that different metastatic subclones from the same patient possessed remarkably divergent malignant properties and global epigenetic programs. Global reprogramming was targeted to thousands of large chromatin domains across the genome that collectively specified malignant divergence. This was maintained by a metabolic shift within the pentose phosphate pathway, independent of KRAS driver mutations. Analysis of paired primary and metastatic tumors from multiple patients uncovered substantial epigenetic heterogeneity in primary tumors, which resolved into a terminally reprogrammed state in metastatic lesions. This supports a model whereby driver mutations accumulate early to initiate pancreatic tumorigenesis, followed by a period of subclonal evolution that generates sufficient intra-tumor heterogeneity for selection of epigenetic programs that may increase fitness during malignant progression and metastatic spread. To map the epigenomic landscape of pancreatic cancer progression as it evolves within patients. Chip-Seq (K27Me3, K36Me3, K9Me2/3, K4Me3 and K27Ac) of 2 patients (A13 and A38) and HPDE cell line. Patient A38 included local peritoneal metastasis and 2 distant metastsis (liver and lung mets), and 6AN treated and DMSO samples for lung matastasis. Patient A13 included 2 primary tumors and 1 distant lung metastasis. Each sample has been done with replicates.
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2018-12-11 | PXD008873 | Pride
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.
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Project description:In this comprehensive study, the authors have developed concise models integrating clinical, genomic and transcriptomic features to predict intrinsic resistance to anti-PD1 Immune Checkpoint Blockade (ICB) treatment in individual tumors. It's important to note that their validation was performed in smaller, independent cohorts, constrained by data availability. The authors have developed two Logistic Regression based models for Ipilimumab treated and Ipilimumab naive patients with metastatic melanoma. The main predictive features for the Ipilimumab treated patients are MHC-II HLA, LDH at treatment initiation and the presence of lymph node metastases (LN met), chosen using forward selection methodology. The main predictive features for the Ipilimumab naive patients are tumor heterogeneity, tumor ploidy and tumor purity, chosen using forward selection methodology.
Please note that in these models, the output ‘1’ means progressive disease (PD) and ‘0’ means non-PD. The original GitHub repository can be accessed at https://github.com/vanallenlab/schadendorf-pd1
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