Abstract
BackgroundRecent global genomic analyses identified 69 gene sets and 12 core signaling pathways genetically altered in pancreatic cancer, which is a highly malignant disease. A comprehensive understanding of the genetic signatures and signaling pathways that are directly correlated to pancreatic cancer survival will help cancer researchers to develop effective multi-gene targeted, personalized therapies for the pancreatic cancer patients at different stages. A previous work that applied a LASSO penalized regression method, which only considered individual genetic effects, identified 12 genes associated with pancreatic cancer survival.ResultsIn this work, we integrate pathway information into pancreatic cancer survival analysis. We introduce and apply a doubly regularized Cox regression model to identify both genes and signaling pathways related to pancreatic cancer survival.ConclusionsFour signaling pathways, including Ion transport, immune phagocytosis, TGFβ (spermatogenesis), regulation of DNA-dependent transcription pathways, and 15 genes within the four pathways are identified and verified to be directly correlated to pancreatic cancer survival. Our findings can help cancer researchers design new strategies for the early detection and diagnosis of pancreatic cancer.
Highlights
Recent global genomic analyses identified 69 gene sets and 12 core signaling pathways genetically altered in pancreatic cancer, which is a highly malignant disease
A comprehensive understanding of the genetic signatures and signaling pathways that are directly correlated to pancreatic cancer survival will help cancer researchers to develop effective multi-gene targeted, personalized therapies for the pancreatic cancer patients at different stages and improve survival rate
The aim of this work is to identify core signaling pathway sets and genetic signatures within those pathways related to pancreatic cancer survival
Summary
Recent global genomic analyses identified 69 gene sets and 12 core signaling pathways genetically altered in pancreatic cancer, which is a highly malignant disease. Stratford et al.’s work identified six genetic signatures [6] associated with metastatic pancreatic cancer using a sequence of statistical techniques, including the significance analysis of microarray (SAM) [7], centroid-based predictor [8], Pearson correlation, X-Tile [9], Kaplan-Meier estimator [10] and Cox model [11]. Though these genes could help discriminate high- and low-risk patients, the prediction was not based on survival time. A comprehensive understanding of the genetic signatures and signaling pathways that are directly correlated to pancreatic cancer survival will help cancer researchers to develop effective multi-gene targeted, personalized therapies for the pancreatic cancer patients at different stages and improve survival rate
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