3D heterospecies spheroids of pancreatic stroma and cancer cells demonstrate key phenotypes of pancreatic ductal adenocarcinoma
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ABSTRACT:
PROVIDER: PRJNA717000 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14061806.fastq.gz | Fastqsanger.gz | |||
| SRR14061807.fastq.gz | Fastqsanger.gz | |||
| SRR14061808.fastq.gz | Fastqsanger.gz | |||
| SRR14061809.fastq.gz | Fastqsanger.gz | |||
| SRR14061810.fastq.gz | Fastqsanger.gz |
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Project description:Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, partly due to the dense desmoplasia and a lack of suitable model systems to study. In the present work, we developed a 3D heterospecies spheroid model to study the microenvironmental interactions between tumor cells and stellate cells which can also be employed to test therapeutic regimens. We set up monospheroids and heterospheroids made up from murine pancreatic stellate cells (mPSCs) and human PDAC cells (Panc1), which allowed for direct isolation of mRNA from a mixed cell population followed by an in silico separation of the RNA-seq reads. Global transcript level changes for cells in heterospheroids versus monospheroids were calculated, followed by gene set enrichment analysis and molecular subtype analysis. We observed an apparent shift of Panc1 from the classical to the squamous/basal-like phenotype upon co-culture with mPSCs. Moreover, mPSCs acquired a different cancer-associated fibroblast-related phenotype upon co-culture with Panc1. We analyzed the tumor cell-specific chemosensitivities towards gemcitabine, paclitaxel and SN38 and compared these to published pharmacotranscriptomic signatures. In conclusion, our heterospecies spheroid model reflected key aspects of PDAC and facilitated the study of intercellular interactions between tumor and stroma while additionally proving to be a good model for studying therapeutic responses.
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2020-09-03 | GSE157353 | GEO
Project description:Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, partly due to the dense desmoplasia and a lack of suitable model systems to study. In the present work, we developed a 3D heterospecies spheroid model to study the microenvironmental interactions between tumor cells and stellate cells which can also be employed to test therapeutic regimens. We set up monospheroids and heterospheroids made up from murine pancreatic stellate cells (mPSCs) and human PDAC cells (Panc1), which allowed for direct isolation of mRNA from a mixed cell population followed by an in silico separation of the RNA-seq reads. Global transcript level changes for cells in heterospheroids versus monospheroids were calculated, followed by gene set enrichment analysis and molecular subtype analysis. We observed an apparent shift of Panc1 from the classical to the squamous/basal-like phenotype upon co-culture with mPSCs. Moreover, mPSCs acquired a different cancer-associated fibroblast-related phenotype upon co-culture with Panc1. We analyzed the tumor cell-specific chemosensitivities towards gemcitabine, paclitaxel and SN38 and compared these to published pharmacotranscriptomic signatures. In conclusion, our heterospecies spheroid model reflected key aspects of PDAC and facilitated the study of intercellular interactions between tumor and stroma while additionally proving to be a good model for studying therapeutic responses.
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Project description:Expression data from human pancreatic ductal adenocarcinomas by stroma types
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Project description:Pancreatic ductal adenocarcinoma (PDAC) remains a lethal disease with a 5-year survival of 4%. A key hallmark of PDAC is extensive stromal involvement, which makes capturing precise tumor-specific molecular information difficult. Here, we have overcome this problem by applying blind source separation to a diverse collection of PDAC gene expression microarray data, which includes primary, metastatic, and normal samples. By digitally separating tumor, stroma, and normal gene expression, we have identified and validated two tumor-specific subtypes including a “basal-like†subtype which has worse outcome, and is molecularly similar to basal tumors in bladder and breast cancer. Furthermore, we define 'normal' and 'activated' stromal subtypes which are independently prognostic. Our results provide new insight into the molecular composition of PDAC which may be used to tailor therapies or provide decision support in a clinical setting where the choice and timing of therapies is critical. Analysis of the landscape of gene expression in pancreatic adenocarcinoma. Data include 145 primary and 61 metastatic PDAC tumors, 17 cell lines, 46 pancreas and 88 distant site adjacent normal samples. Arrays represent distinct samples. The SPOT column in the raw data file (linked to each sample record) contains Agilent feature extraction numbers (included in the 'GPL4133-20424.txt' linked to the platform records).
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2020-01-25 | E-MTAB-6830 | biostudies-arrayexpress
Project description:Pancreatic ductal adenocarcinoma (PDAC) remains a lethal disease with a 5-year survival of 4%. A key hallmark of PDAC is extensive stromal involvement, which makes capturing precise tumor-specific molecular information difficult. Here, we have overcome this problem by applying blind source separation to a diverse collection of PDAC gene expression microarray data, which includes primary, metastatic, and normal samples. By digitally separating tumor, stroma, and normal gene expression, we have identified and validated two tumor-specific subtypes including a “basal-like†subtype which has worse outcome, and is molecularly similar to basal tumors in bladder and breast cancer. Furthermore, we define 'normal' and 'activated' stromal subtypes which are independently prognostic. Our results provide new insight into the molecular composition of PDAC which may be used to tailor therapies or provide decision support in a clinical setting where the choice and timing of therapies is critical.
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