Deciphering Fatty Acid Biosynthesis-Driven Molecular Subtypes in Pancreatic Ductal Adenocarcinoma with Prognostic Insights
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PROVIDER: PRJNA1065269 | ENA |
REPOSITORIES: ENA
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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:To evaluate 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 control samples.
2016-08-17 | GSE62165 | 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) 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:Histological subtypes drive distinct prognostic immune signatures in classical Hodgkin lymphoma.
| PRJNA877867 | ENA
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 (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.
2011-04-01 | GSE17891 | GEO
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:Pervasive subtypes of pancreatic ductal adenocarcinoma (PDA) and their differing response to therapy.
| PRJNA120077 | 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