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.
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.
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.
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).
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.
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.