Molecular subtypes in pancreatic adenocarcinoma [pancreatic cancer cell lines]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE77850 | GEO | 2016/06/01
SECONDARY ACCESSION(S): PRJNA311744
REPOSITORIES: GEO
Similar Datasets
Project description:The goal of the study was to examine the transcriptional profile of pancreatic cancer cell lines and assess if the molecular subtypes observed in tumor samples were represented in existing cell line models. Cell line models allow us to investigate if the molecular subtype observed in tumor have unique sensitivity profiles to anticancer drugs. 29 pancreatic cancer cell lines were compared to a mixed reference pool of 30 pancreatic cancer cell lines to identify cell line specific gene expression.
2016-06-01 | E-GEOD-77850 | biostudies-arrayexpress
Project description:Molecular subtypes in pancreatic adenocarcinoma
| PRJNA311745 | ENA
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.
2016-01-12 | E-MTAB-4029 | biostudies-arrayexpress
Project description:Broad-spectrum RAS inhibition holds the potential to benefit roughly a quarter of human cancer patients whose tumors are driven by RAS mutations. RMC-7977 is a highly selective inhibitor of the active GTP-bound forms of KRAS, HRAS, and NRAS, with affinity for both mutant and wild type (WT) variants. As >90% of human pancreatic ductal adenocarcinoma (PDAC) cases are driven by activating mutations in KRAS, we assessed the therapeutic potential of RMC-7977 in a comprehensive range of PDAC models, including human and murine cell lines, patient-derived organoids, human PDAC explants, subcutaneous and orthotopic cell-line or patient-derived xenografts, syngeneic allografts, and genetically engineered mouse models. We observed broad and pronounced anti-tumor activity across these models following direct RAS inhibition at doses and concentrations that were well-tolerated in vivo. Pharmacological analyses revealed divergent responses to RMC-7977 in tumor versus normal tissues. Treated tumors exhibited waves of apoptosis along with sustained proliferative arrest whereas normal tissues underwent only transient decreases in proliferation, with no evidence of apoptosis. Together, these data establish a strong preclinical rationale for the use of broad-spectrum RAS inhibition in the setting of PDAC.
2024-03-15 | PXD047878 | Pride
Project description:Pancreatic ductal adenocarcinoma (PDA) carries a dismal prognosis and current treatments are only modestly effective. We present evidence that this variation is caused in part by recurrent, pervasive molecular differences between tumors. mRNA expression profiles measured using microdissected PDA clinical samples reveal three dominant subtypes of disease; epithelial, mesenchymal and acinar-like. The classical and quasi-mesenchymal subtypes are observed in human and mouse PDA cell lines. Importantly, responses to cytotoxics and KRAS depletion in human PDA cell lines differ substantially between subtypes, and in opposing directions. Integrated genomics implicate and functional studies support overexpression of the trancription factor GATA6 as a driver of the epithelial subtype. These results provide a molecular framework for evaluating the prospects of personalized treatment in PDA. RNA was extracted from archival patient FFPE PDA samples and hybridized on Affymetrix U133 plus 2.0 microarrays. The CEL files were processed using R based Bioconductor and normalized values were obtained using RMA. RNA was extracted from human PDA cell line samples and hybridized on Affymetrix U133 plus 2.0 microarrays. The CEL files were processed using R based Bioconductor and normalized values were obtained using RMA. RNA was extracted from mouse PDA cell lines and hybridized on Affymetrix Mouse 430a 2.0 microarrays. The CEL files were processed using R based Bioconductor and normalized values were obtained using RMA.
2011-04-01 | E-GEOD-17891 | 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. 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).
2015-09-07 | E-GEOD-71729 | biostudies-arrayexpress
Project description:The goal of the study was to examine the transcriptional profile of pancreatic tumors to identify molecular subtypes in order to develop validated clinically useful gene expression signature with the potential to guide therapy decision. Tissue was obtained by snap freezing in liquid nitrogen as soon as removed. All tissue samples were stored at -80C. Samples were embedded in OCT and a 4ug section was taken for H/E staining. After QC procedure to ensure high quality RNA (RIN>7) and confirm PDAC histology, 78 samples were subjected to microarray analysis. All patients signed an Institutional Review Board approved consent for bio-banking, clinical data extraction and molecular analysis. 85 samples (77 tumors, 3 normal and 5 pancreatitis) were compared to a mixed reference pool of 66 tumor samples to identify gene expression patterns.
2016-06-01 | E-GEOD-77858 | biostudies-arrayexpress
Project description:Pancreatic ductal adenocarcinoma has a very poor prognosis, and new therapies and preclinical models are urgently needed. We developed patient-derived xenografts (PDXs), established PDX-derived cell lines (PDCLs), and generated cell line-derived xenografts (CDXs), and integrated these to create 13 matched trios, as systematic models for this cancer. Orthotopic implantation (OI) of PDCLs showed tumorigenesis and metastases to the liver and peritoneum. Morphological comparisons of OI-CDX and OI-PDX with passaged tumors showed that histopathological features of the original tumor were maintained in both models. Molecular alterations in PDX tumors (including those to KRAS, TP53, SMAD4, and CDKN2A) were similar to those in the respective PDCLs and CDX tumors. Comparing gene expression in PDCLs, ectopic tumors, and OI tumors, CXCR4 and CXCL12 genes were specifically upregulated in OI tumors, whose immunohistochemical profiles suggested epithelial-mesenchymal transition and adeno-squamous trans-differentiation. These patient-derived tumor models provide useful tools for preclinical research into pancreatic ductal adenocarcinoma. We performed comprehensive gene expression profiling of 13 pancreatic cancer cell lines, 14 CDX and 14 PDX tumors by Affymetrix Gene Chip HG-U133Plus2.0.
2022-02-16 | GSE157494 | GEO
Project description:Here we use high-resolution mass spectrometry (MS) to characterise the magnitude and complexity of global tyrosine phosphorylation PDAC. We profiled the endogenous tyrosine phosphorylation-based signaling in 36 cell lines from two cell line populations, quantifying around 2,000 tyrosine phosphorylation sites. This approach facilitated consistent segregation of PDAC cell lines into three subtypes with distinct signalling profiles, using both their global tyrosine phosphorylation patterns and a Random Forest derived 8 phosphorylation site signature. We extracted segregation-driving phosphosites, and subsequent pathway and network analysis to characterise the identified subtypes.
2016-06-09 | PXD003198 | Pride
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.
2015-09-07 | GSE71729 | GEO