BioProject

To perform an integrative profile of human pancreatic cancer (PDAC) to identify prognosis-significant genes and their related pathways. More...

To perform an integrative profile of human pancreatic cancer (PDAC) to identify prognosis-significant genes and their related pathways. A concordant survival-based whole genome in silico array analysis of DNA copy number, and mRNA & micro RNA (miRNA) expression in 25 early stage PDAC was performed. A novel composite score simultaneously integrated gene expression with regulatory mechanisms to identify the signature genes with the most levels of prognosis-significant evidence. The predominant signaling pathways were determined via a pathway-based approach. Independent patient cohorts (n= 150 and 42) were then used as in vitro validation of the array findings. We find that EGFR, SRC signaling, and PI3K/AKT pathway activation are strongly linked to clinical disease progression. Furthermore, we identify two discrete subsets of pancreatic tumors characterized by either SRC or PI3K/AKT signaling that may dictate variable responses to targeted therapy. Overall design: 42 human PDAC tumors and 7 non-malignant pancreas samples snap-frozen at the time of surgery were chosen. Representative H&E sections of each were evaluated by a practicing gastrointestinal pathologist to confirm diagnosis and determine relative percentage of malignant cells. Samples with tumor cell content >30% were chosen for final multi-platform analysis (N=25). Copy number analysis of Affymetrix SNP 6.0 arrays was performed for 25 PDAC samples. The HapMap270 file supplied by Affymetrix was used as the reference model for copy number inference. Less...