Microarray gene-expression profiles of 139 pancreatic tumor,102 adjacent non-tumor tissue from patients with pancreatic ductal adenocarcinoma and 3 normal pancreas from donors.
In order to identify key pathways associated with disease aggressiveness and therapeutics resistance in the most agrressive subset of PDAC, we analyzed gene expression profiling of tumor and adjacent non-tumor tissues from PDAC cases. Non-negative matrix factorization (NMF) clustering, using gene expression profile form PDAC tumors, revealed three patient subsets. A 142-gene signature specific to the subset with the worst patient survival, predicted prognosis and stratified patients with significantly different survival. Mechanistic and functional analyses of most aggressive subset revealed a HNF1B/Clusterin Axis negatively regulate pancreatic cancer progression and potentially be useful in designing novel strategies to attenuate disease progression. Affymetrix data from from these dataset were partially earlier submited by us as GEO accession#: GSE28735 and GSE 62452. The batch effect between the different sets of data was removed using Partek Genomic Suite and this normalized data was submitted to GEO in this submission.
Overall design
We selected probes with s.d. >0.6 as the intrinsically variable genes and performed non-negative matrix factorization (NMF) analysis with consensus clustering to identify subsets of the pancreatic adenocarcinoma with cophenetic coefficient > 0.94. This analysis discovered three molecular subsets. Integrative gene expression analysis of these subsets identified a 148 specific gene signature were further submitted to Ingenuity Pathway Analysis (IPA).
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