Prognostic relevance of molecular subtypes and master regulators in pancreatic ductal adenocarcinoma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE62165 | GEO | 2016/08/17
SECONDARY ACCESSION(S): PRJNA263337
REPOSITORIES: GEO
Similar Datasets
Project description:Pancreatic cancer is poorly characterized at genetic and non-genetic levels. The current study evaluates in a large cohort of patients the prognostic relevance of molecular subtypes and key transcription factors in pancreatic ductal adenocarcinoma (PDAC).We performed gene expression analysis of whole-tumor tissue obtained from 118 surgically resected PDAC and 13 histologically normal pancreatic tissue samples. Cox regression models were used to study the effect on survival of molecular subtypes and 16 clinicopathological prognostic factors. In order to better understand the biology of PDAC we used iRegulon to identify transcription factors (TFs) as master regulators of PDAC and its subtypes.We confirmed the PDAssign gene signature as classifier of PDAC in molecular subtypes with prognostic relevance. We found molecular subtypes, but not clinicopathological factors, as independent predictors of survival. Regulatory network analysis predicted that HNF1A/B are among thousand TFs the top enriched master regulators of the genes expressed in the normal pancreatic tissue compared to the PDAC regulatory network. On immunohistochemistry staining of PDAC samples, we observed low expression of HNF1B in well differentiated towards no expression in poorly differentiated PDAC samples. We predicted IRF/STAT, AP-1, and ETS-family members as key transcription factors in gene signatures downstream of mutated KRAS.PDAC can be classified in molecular subtypes that independently predict survival. HNF1A/B seem to be good candidates as master regulators of pancreatic differentiation, which at the protein level loses its expression in malignant ductal cells of the pancreas, suggesting its putative role as tumor suppressor in pancreatic cancer.The study was registered at ClinicalTrials.gov under the number NCT01116791 (May 3, 2010).
| S-EPMC4983037 | biostudies-literature
Project description:Despite extensive biological and clinical studies, including comprehensive genomics and transcriptomics analysis, pancreatic ductal adenocarcinoma (PDAC) remains a devastating disease, with poor survival and no effective therapies to date. Correlation networks are emerging as a powerful approach to infer tumor biology and to prioritize candidate genes as biomarkers or drug targets. In this study we applied a weighted co-expression analysis to the functionally relevant proteome of 20 surgically resected patients with PDAC. We obtained twelve modules with overlapping yet distinct biology, which implicated metabolism and ECM complexes in several modules. Notably, one module enriched for metabolic processes and epithelial-mesenchymal-transition (EMT) was significantly associated with overall survival (p=0.01) and was validated in public RNA data (p=0.02). The prognostic value of three proteins (SPTBN1, KHSRP and PYGL) belonging to this module was confirmed using immunohistochemistry in a cohort of 82 radically resected patients.
2020-09-01 | PXD015744 | Pride
Project description:Despite extensive biological and clinical studies, including comprehensive genomics and transcriptomics analysis, pancreatic ductal adenocarcinoma (PDAC) remains a devastating disease, with poor survival and no effective therapies to date. Correlation networks are emerging as a powerful approach to infer tumor biology and to prioritize candidate genes as biomarkers or drug targets. In this study we applied a weighted co-expression analysis to the functionally relevant proteome of 20 surgically resected patients with PDAC. We obtained twelve modules with overlapping yet distinct biology, which implicated metabolism and ECM complexes in several modules. Notably, one module enriched for metabolic processes and epithelial-mesenchymal-transition (EMT) was significantly associated with overall survival (p=0.01) and was validated in public RNA data (p=0.02). The prognostic value of three proteins (SPTBN1, KHSRP and PYGL) belonging to this module was confirmed using immunohistochemistry in a cohort of 82 radically resected patients.
2024-11-15 | MSV000096427 | MassIVE
Project description:Pancreatic ductal adenocarcinoma (PDAC) is one of the most treatment-resistant malignancies in human. To perform transcriptomic profiling on PDAC, we collected primary PDAC tissues from surgically resected PDAC patients at the Memorial-Sloan Kettering Cancer Center (NY, USA). Morphogenesis of epithelial tissues relies on the precise developmental control of cell polarity and architecture. In the early Drosophila embryo, the primary epithelium forms during cellularisation, following a tightly controlled genetic programme where specific sets of genes are up-regulated. Some of them, for instance, control membrane invagination between the nuclei anchored at the apical surface of the syncytium. We used microarrays to detail transcritomic profiling of PDACs.
2021-09-23 | GSE184585 | GEO
Project description:Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis with very frequent post-surgical local recurrence. The combination of adjuvant chemotherapy with radiotherapy is under consideration to achieve a prolonged disease-free survival (DFS). To date, few studies have determined protein profiles that are associated with responsiveness to adjuvant chemoradiation. Here, we analyzed the proteomes of primary, surgically resected PDAC tumors subjected to adjuvant chemoradiation and achieving short DFS (median DFS of 6 months, n = 6) or a prolonged DFS (median DFS of 28 months, n = 6) using liquid chromatography tandem mass spectrometry.
2018-09-11 | PXD009254 | Pride
Project description:The aim of this study is to identify prognostic gene expression signatures associated with two molecularly distinct subtypes of colorectal cancer. Samples were taken from colorectal cancers in surgically resected specimens in 96 colorectal cancer patients. The expression profiles were determined using Affymetrix Human Genome U133Plus 2.0 arrays. This is a test set for validation of prognostic gene expression signature that was developed from GSE14333. All data were normalized by using the RMA method (affy package in R/Bioconductor).
2011-06-20 | GSE29971 | GEO
Project description:Pancreatic ductal adenocarcinoma (PDAC) poses a significant challenge due to its high heterogeneity and aggressiveness. Recognizing the urgency to delineate molecular subtypes, our study focused on the emerging field of lipid metabolism remodeling in PDAC, particularly exploring the prognostic potential and molecular classification associated with fatty acid biosynthesis. Here we identified a 7-gene signature associated with fatty acid biosynthesis-related genes (FRGs), providing a robust tool for survival prediction. The high- FRGs score group displayed a poorer prognosis, lower immune infiltration abundance, and a higher tumor mutational burden. Notably, ACSL5, a key gene in 7-gene signature panel was upregulated in PDAC. The biological function of ACSL5 were validated with in vitro assay. Finally, we unveiled that ACSL5 played a crucial role in pancreatic cancer progression, promoting tumor initiation, metastasis, and immune evasion.
2024-01-16 | GSE253315 | GEO
Project description:Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers due to its high metastasis rate in liver. However, little is known about the molecular features of hepatic metastases due to difficulty in obtaining fresh tissues and low tumor cellularity. Methods and Results: We conducted RNA sequencing for synchronous surgically resected PTs and the paired HMs from 14 hepatic oligometastatic PDACs and experimentally validated our findings in specimens from 35 of such cases. The comprehensive analysis of gene expressions showed largely similarity between PTs and HMs. However, hepatic metastases also showed unique characteristics, such as stronger abilities of proliferation, downregulation of EMT activity and metabolic rewiring. More interesting, altered tumor microenvironments were observed in hepatic metastases, especially higher proportion of tumor infiltrating M2 macrophage and upregulation of complement cascade. Further experiments demonstrate that expression of C1q increased continuously from normal to PTs to HMs, C1q was mainly produced from M2 macrophage, and C1q promoted migration and invasion of PDAC cells. Conclusion: Taken together, we found potential factors that contribute to different stages of PDAC metastasis. Our study broadens the understandings of molecular mechanisms driving PDAC metastasis.
2020-06-02 | GSE151580 | GEO
Project description:Glioblastoma multiforme (GBM) is the most common malignant brain tumor. GBM samples are classified into subtypes based on their transcriptomic and epigenetic profiles. Despite numerous studies to better characterize GBM biology, a comprehensive study to identify GBM subtype- specific master regulators, gene regulatory networks, and pathways is missing. Here, we used FastMEDUSA to compute master regulators and gene regulatory networks for each GBM subtype. We also ran Gene Set Enrichment Analysis and Ingenuity Pathway Analysis on GBM expression dataset from The Cancer Genome Atlas Project to compute GBM- and GBM subtype-specific pathways. Our analysis was able to recover some of the known master regulators and pathways in GBM as well as some putative novel regulators and pathways, which will aide in our understanding of the unique biology of GBM subtypes.
| S-EPMC4214595 | biostudies-literature
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