Antithetical NFATc1-Sox2 and p53-miR-200 signalling networks governs pancreatic cancer cell plasticity and tumour progression
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ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) cells undergo epithelial mesenchymal transdifferentiation (EMT) in adaption to environmental cues, including inflammation, a process that combines tumour cell dedifferentiation with dissemination and acquisition of stemness features. However, the mechanisms coupling inflammation-induced signalling pathways with EMT and stemness remain largely unknown. Here, we reveal the inflammation-induced transcription factor NFATc1 as a central regulator of pancreatic cancer cell plasticity.
Project description:SW620 were transfected with siMYC or siCTR at time point 0h. 24h later cells were splitter 1:2, additional 24 h later (48h after transfection) cells were treated with BEZ235 (200nM) or DMSO. Cells were harvested after additional 24h (72h after siRNA transfection; 24h BEZ235 treatment.
Project description:Analysis of Retinoblastoma protein (Rb) (Hs.408528) dependent transcriptional changes following siRNA mediated ablation of the RET finger protein/ Tripartite protein (RFP/TRIM27) (Hs.440382). Common reference design, two biological replicates with two technical replicates each.
Project description:In lung cancer progression, p53 mutations are more often observed in invasive tumors than in non-invasive tumors, suggesting that p53 is involved in tumor invasion and metastasis. To understand the nature of p53 function as a tumor suppressor, it is crucial to elucidate the detailed mechanism of the alteration in epithelial cells, the main origin of solid tumors, following p53 inactivation. To elucidate the mechanism by which p53 loss enhances invasive and motile activities in human lung small airway epithelial cells (SAECs), we performed comprehensive expression profiling analyses between p53 knockdown and control cells using GeneChip Human Genome U133 plus 2.0 arrays. SAECs were infected with lentiviruses for the expressions of CDK4 devoid of binding ability to p16INK4A, Cyclin D1 and TERT to generate immotalized SAECs. At 18 population doublings, immortalized SAECs were transfected with the siRNAs (si-control, si-p53-#1 or si-p53-#2) and used for RNA extraction and hybridization on Affymetrix microarrays.
Project description:The aim of the experiment was to analyse gene expression profiles in Brca1 tumours arising from different mammary epithelial cell populations use a Cre-loxP based conditional knockout system. K14 promoter driving Cre expression caused Brca1 knockout in basal stem cells and thus stem cell origin tumours whereas Blg promoter driving Cre expression caused Brca1 knockout in luminal progenitor cells and thus progenitor origin tumours. Individual arrays were carried out on labelled cDNA made from RNA isolated from mouse mammary tumours. Only cDNA passing Almac diagnostics QC criteria were hybridised to arrays. Only arrays passing QC criteria after hybrisiation were subsequently analysed.
Project description:Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-year survival rate of 10-15% due to late-stage diagnosis and limited efficacy of existing treatments. This study utilized proteomics-based system modelling to generate multimodal datasets from various research models, including PDAC cells, spheroids, organoids, and tissues derived from murine and human samples. Identical mass spectrometry-based proteomics was applied across the different models. Preparation and validation of the research models and the proteomics were described in detail. The assembly datasets we present here contribute to the data collection on PDAC, which will be useful for systems modeling, data mining, knowledge discovery in databases, and bioinformatics of individual models. Further data analysis may lead to generation of research hypotheses, predictions of targets for diagnosis and treatment and relationships between data variables.
Project description:Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-year survival rate of 10-15% due to late-stage diagnosis and limited efficacy of existing treatments. This study utilized proteomics-based system modelling to generate multimodal datasets from various research models, including PDAC cells, spheroids, organoids, and tissues derived from murine and human samples. Identical mass spectrometry-based proteomics was applied across the different models. Preparation and validation of the research models and the proteomics were described in detail. The assembly datasets we present here contribute to the data collection on PDAC, which will be useful for systems modeling, data mining, knowledge discovery in databases, and bioinformatics of individual models. Further data analysis may lead to generation of research hypotheses, predictions of targets for diagnosis and treatment and relationships between data variables.
Project description:Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-year survival rate of 10-15% due to late-stage diagnosis and limited efficacy of existing treatments. This study utilized proteomics-based system modelling to generate multimodal datasets from various research models, including PDAC cells, spheroids, organoids, and tissues derived from murine and human samples. Identical mass spectrometry-based proteomics was applied across the different models. Preparation and validation of the research models and the proteomics were described in detail. The assembly datasets we present here contribute to the data collection on PDAC, which will be useful for systems modeling, data mining, knowledge discovery in databases, and bioinformatics of individual models. Further data analysis may lead to generation of research hypotheses, predictions of targets for diagnosis and treatment and relationships between data variables.
Project description:Pancreatic neuroendocrine neoplasms (PNENs) are biologically and clinically heterogeneous neoplasms. We used quantitative global proteomic analysis on 40 PNENs to compliment paired transcriptome data.
Project description:Canine distemper virus (CDV)-induced demyelinating leukoencephalitis (CDV-DL) in dogs is a translational animal model for human demyelinating diseases such as multiple sclerosis. The aim of this study was to perform an assumption-free microarray analysis of gene expression in different subgroups of CDV-DL as compared to normal controls. Dogs were classified into normal controls (group 1), acute CDV-DL lesions with CDV within the brain but without demyelination and inflammation (group 2), subacute lesions with demyelination but without inflammation (group 3), and subacute to chronic lesions with demyelination and inflammation (group 4).
Project description:Activation of endogenously expressed KRas[G12D] in the pancreas of mice gives rise primarily to early stage PanIN lesions, however such lesions can occasionally progress to end-stage ductal adenocarcinoma (PDAC). Progression of KRas[G12D]- initiated lesions to PDAC is accelerated by modest expression of MYC from the Rosa26 locus. Deletion of 1 copy of endogenous c-Myc or both copies of endogenous Zbtb17 (aka Miz1), slows progression to PDAC and extends healthful survival of Pdx1-Cre;lsl-KRas[G12D];Rosa26-lsl-MYC[DM] (KMC) mice. Tumours were removed from mice with all 4 genotypes and validated by histological examination prior to RNA-SEQ analysis.