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Core Signaling Pathways in Human Pancreatic Cancers Revealed by Global Genomic Analyses

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TLDR
It is found that pancreatic cancers contain an average of 63 genetic alterations, the majority of which are point mutations, which defined a core set of 12 cellular signaling pathways and processes that were each genetically altered in 67 to 100% of the tumors.
Abstract
There are currently few therapeutic options for patients with pancreatic cancer, and new insights into the pathogenesis of this lethal disease are urgently needed. Toward this end, we performed a comprehensive genetic analysis of 24 pancreatic cancers. We first determined the sequences of 23,219 transcripts, representing 20,661 protein-coding genes, in these samples. Then, we searched for homozygous deletions and amplifications in the tumor DNA by using microarrays containing probes for approximately 10(6) single-nucleotide polymorphisms. We found that pancreatic cancers contain an average of 63 genetic alterations, the majority of which are point mutations. These alterations defined a core set of 12 cellular signaling pathways and processes that were each genetically altered in 67 to 100% of the tumors. Analysis of these tumors' transcriptomes with next-generation sequencing-by-synthesis technologies provided independent evidence for the importance of these pathways and processes. Our data indicate that genetically altered core pathways and regulatory processes only become evident once the coding regions of the genome are analyzed in depth. Dysregulation of these core pathways and processes through mutation can explain the major features of pancreatic tumorigenesis.

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Modifiable and non-modifiable risk factors for pancreatic cancer: A review.

TL;DR: Preventive strategies at the population level and an effective screening program targeted at high-risk people may help in prevention and early detection of pancreatic ductal adenocarcinoma.
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Targeted high throughput sequencing in clinical cancer settings: formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity

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Oncolytic Viruses for Cancer Therapy: Overcoming the Obstacles.

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Identification of Colorectal Cancer Related Genes with mRMR and Shortest Path in Protein-Protein Interaction Network

TL;DR: This study developed a computational method to identify colorectal cancer-related genes based on the gene expression profiles, and the shortest path analysis of functional protein association networks, which indicated that the method may become a useful tool, or at least plays a complementary role to the existing method.
References
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Book

Pancreatic Cancer

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