MYC ChIP-seq in human pancreatic ductal adenocarcinoma cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE143804 | GEO | 2020/04/27
REPOSITORIES: GEO
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Project description:Pancreatic cancer is characterized by abundant desmoplastic stroma. Despite numerous theoretical and experimental efforts, therapeutic approaches targeting pancreatic cancer stroma have been largely unsuccessful, highlighting the need for more comprehensive assessment of inter- and intratumoral stromal heterogeneity in a large series of clinical tumors. Quantitative computation of FAP-dominant fibroblasts, ACTA2-dominant fibroblasts, and intratumoral collagen in whole-tissue sections from 215 treatment-naïve pancreatic cancers allowed us to identify three distinct stroma types (FAP-dominant fibroblast-rich stroma [F-stroma], ACTA2-dominant fibroblast-rich stroma [A-stroma], and collgen-rich stroma [C-stroma]), which were differentially associated with patient outcomes, molecular characteristics and the immunosuppressive tumor microenvironment. We explored differentially expressed genes between three distinct stroma types (F-stroma, A-stroma, and C-stroma) using frozen samples from 20 patients with pancreatic cancer.
2020-09-03 | GSE157353 | GEO
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: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.
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.
2015-09-07 | GSE71729 | GEO
Project description:In this study, we performed laser capture microdissection (LCM) of PDAC samples to define their cancer- and stroma-specific molecular subtypes and identify a prognostic gene expression signature for short-term and long-term survival. LCM and RNA-seq analysis of cancer and adjacent stroma of 19 treatment-naïve PDAC tumors were performed. Gene expression signatures were tested for their robustness in a large independent validation set. An RNA in situ hybridization (RNA-ISH) assay with pooled probes for genes associated with disease-free survival (DFS) was developed to probe 111 PDAC tumor samples. Gene expression profiling identified four subtypes of cancer cells (C1-C4) and three subtypes of cancer-adjacent stroma (S1-S3). These stroma-specific subtypes were associated with DFS (p=5.55E-07), with S1 associated with better prognoses when paired with C1 and C2. Thirteen genes were found to be predominantly expressed in cancer cells and corresponded with DFS in a validation using existing RNA-seq datasets. A second validation on an independent cohort of patients using RNA-ISH probes to six of these prognostic genes demonstrated significant association with overall survival (median 17 versus 25 months; p<0.02). Our results identified specific signatures from the epithelial and the stroma components of PDAC, which add clarity to the nature of PDAC molecular subtypes and may help predict survival.
2021-06-30 | GSE164665 | GEO
Project description:Tumor-stroma interactions are critical in pancreatic ductal adenocarcinoma (PDAC) progression and therapeutics. Patient-derived xenograft (PDX) models faithfully recapitulate tumor-stroma interactions in PDAC, but conventional antibody-based immunoassay is largely inadequate to resolve or quantify tumor and stromal proteins. A species-deconvolved proteomics approach embedded in the ultra-high-resolution (UHR)-IonStar workflow can unambiguously quantify the proteins from tumor (human-derived) and stroma (mouse-derived) in PDX samples, enabling unbiased investigation of their proteomes with excellent quantitative reproducibility. With this strategy, 3 PDAC PDXs were analyzed. They were showed differential responses to treatment with Gemcitabine combined with nab-Paclitaxel (GEM+PTX), which is a first-line treatment regimen for PDAC. For each PDAC PDX, samples were collected after 24 hour and 192 hour with/without treatment, and each condition contained four biological replicates.
2023-07-05 | PXD042267 | Pride
Project description:Pancreatic ductal adenocarcinoma (PDAC) is a leading causes of cancer mortality worldwide. Non-specific symptoms, lack of biomarkers in the early stages, and drug resistance due to the presence of a dense fibrous stroma all contribute to poor outcome of this disease. The extracellular matrix of PDAC is secreted by activated fibroblasts known as cancer associated fibroblasts (CAFs). These fibroblasts can also affect cancer cell aggressiveness by paracrine crosstalk with cancer and immune cells present inside the tumor mass. The interplay among tumoral cells, immune cells and CAFs involve a huge array of molecules especially cytokines. Given the importance of CAFs in PDAC pathology it is critical to recognize the mechanisms involved in the crosstalk between these cells. To this aim, we first identified the proteins released from the pancreatic cancer cell line MIA-PaCa2 by proteomic analysis of their conditioned medium (CM). Second, fibroblasts were treated with MIA-PaCa2 CM for 24 and 48 hours and their proteostatic changes were detected by proteomics. Pathway analysis indicated that fi-broblasts treated with CM undergo changes compatible with the activation of migra-tion, vasculogenesis, cellular homeostasis and metabolism of ammino acids and re-duced apoptosis. These biological activities are possibly regulated by ITGB3 and TGFB1/2 in an early stage (24 hours) while SMAD3 and STAT3 could be the key player at later times (48 hours). In conclusion this study shed light on the crosstalk between PDAC cells and associated fibroblasts.
2022-05-20 | PXD030974 | Pride
Project description:Intratumoral phenotypic heterogeneity has been described in many tumor types, where it can contribute to drug resistance and disease recurrence. We analyzed ductal and neuroendocrine markers in pancreatic ductal adenocarcinoma, revealing heterogeneous expression of the neuroendocrine marker Synaptophysin within ductal lesions. Higher percentages of Cytokeratin-Synaptophysin dual positive tumor cells correlate with shortened disease-free survival. We observe similar lineage marker heterogeneity in mouse models of pancreatic ductal adenocarcinoma, where lineage tracing indicates that Cytokeratin-Synaptophysin dual positive cells arise from the exocrine compartment. Mechanistically, MYC binding is enriched at neuroendocrine genes in mouse tumor cells and loss of MYC reduces ductal-neuroendocrine lineage heterogeneity, while deregulated MYC expression in KRAS mutant mice increases this phenotype. Neuroendocrine marker expression is associated with chemoresistance and reducing MYC levels decreases gemcitabine-induced neuroendocrine marker expression and increases chemosensitivity. Altogether, we demonstrate that MYC facilitates ductal-neuroendocrine lineage plasticity in pancreatic ductal adenocarcinoma, contributing to poor survival and chemoresistance.
| S-EPMC5701042 | biostudies-literature
Project description:To investigate the paracrine effects of stromal elements on cancer cells, we developed a “stromal” culture system, which incorporates structural and diffusible stroma-derived elements into homotypic cultures amenable to functional genomics and metabolomics. We show that microenvironmental cues co-regulate cancer metabolism and gene expression. Stromal inputs broadly influence histone acetylation in the cancer epigenome, coinciding with induction of genes implicated in anabolic metabolism and inflammation. The gene expression and metabolic changes induced by stromal factors overlap with those previously identified following oncogenic Kras, suggesting functional complementarity between cell-autonomous and microenvironmental pathways. We implicate the BET family of epigenetic readers as key transducers of stromal inputs to drive alterations in gene expression and suggest paracrine epigenome regulation as a conduit through which stromal signals drive metabolic and immune adaptation to a challenging tumor microenvironment.
2017-02-23 | GSE70971 | GEO
Project description:Pancreatic cancer is the 3rd most prevalent cause of cancer related deaths in United states alone, with over 55000 patients being diagnosed in 2019 alone and nearly as many succumbing to it. Late detection, lack of effective therapy and poor understanding of pancreatic cancer systemically contributes to its poor survival statistics. Obesity and high caloric intake linked co-morbidities like type 2 diabetes (T2D) have been attributed as being risk factors for a number of cancers including pancreatic cancer. Studies on gut microbiome has shown that lifestyle factors as well as diet has a huge effect on the microbial flora of the gut. Further, modulation of gut microbiome has been seen to contribute to effects of intensive insulin therapy in mice on high fat diet. In another study, abnormal gut microbiota was reported to contribute to development of diabetes in Db/Db mice. Recent studies indicate that microbiome and microbial dysbiosis plays a role in not only the onset of disease but also in its outcome. In colorectal cancer, Fusobacterium has been reported to promote therapy resistance. Certain intra-tumoral bacteria have also been shown to elicit chemo-resistance by metabolizing anti-cancerous agents. In pancreatic cancer, studies on altered gut microbiome have been relatively recent. Microbial dysbiosis has been observed to be associated with pancreatic tumor progression. Modulation of microbiome has been shown to affect response to anti-PD1 therapy in this disease as well. However, most of the studies in pancreatic cancer and microbiome have remained focused om immune modulation. In the current study, we observed that in a T2D mouse model, the microbiome changed significantly as the hyperglycemia developed in these animals. Our results further showed that, tumors implanted in the T2D mice responded poorly to Gemcitabine/Paclitaxel (Gem/Pac) standard of care compared to those in the control group. A metabolomic reconstruction of the WGS of the gut microbiota further revealed that an enrichment of bacterial population involved in drug metabolism in the T2D group.
2020-11-30 | E-MTAB-8739 | biostudies-arrayexpress