Evaluation of protein clustering of pancreatic cancer

Abstract

Pancreatic cancer (PC) is one of the most malignant tumors with a very poor prognosis. Late diagnosis and lack of effective therapeutic method is the weak point in pancreatic cancer therapy. For pancreatic cancer clustering analysis, thirty proteins were selected from Wiki pathway and sequence comparison was prepared by Needleman-Wunsch algorithm. Similarity scores were obtained by comparing of these proteins and the relevant dissimilarity matrix was constructed. Graphical illustrations of clustering data were performed by R software using package cluster to find subgraphs with maximal density. Finally the interactions of these proteins with their neighbors that was obtained from Mentha, Reactome-Fls Databases by the application of PSICQUIC source in Cytoscape software are presented. The result of this study showed that CREB-binding protein and epidermal growth factor receptor are reported in Wiki Pathway Androgen receptor and most significant hub that involved in pancreatic cancer, but not in the high close relationship. In conclusion cell cycle and signaling pathway have highlighted its importance in pancreatic cancer, as well as its potential as a therapeutic target in PC.

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