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:We performed RNA-seq analysis on Grem1 wild-type and Grem1-deleted pancreatic tumour tissues from Pdx1-Flp;KrasFSF-G12D;Trp53frt/frt (KPF) mice. We compared the transcriptome between these two groups of tumours with the aim to understand their molecular signatures and the relevance to human pancreatic ductal adenocarcinoma subtypes.
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.
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).
