Yao Xiao1, Gang Xu2, Jordan M Cloyd3, Shunda Du1, Yilei Mao1, Timothy M Pawlik4. 1. Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China. 2. Department of Liver Surgery and Liver Transplant Center, West China Hospital of Sichuan University, Chengdu, China. 3. Department of Surgery, The Ohio State University Wexner Medical Center and James Cancer Hospital and Solove Research Institute, 395 W. 12th Ave., Suite 670, Columbus, OH, USA. 4. Department of Surgery, The Ohio State University Wexner Medical Center and James Cancer Hospital and Solove Research Institute, 395 W. 12th Ave., Suite 670, Columbus, OH, USA. tim.pawlik@osumc.edu.
Abstract
INTRODUCTION: There is a paucity of effective treatment options for advanced pancreatic neuroendocrine tumors (pNETs). Genome-wide analyses may allow for potential drugs to be identified based on differentially expressed genes (DEGs). METHODS: Oligo microarray data of RNA expression profiling of pNETs and normal pancreas tissues were downloaded from the Gene Expression Omnibus. Functional and pathway enrichment information of the DEGs was obtained using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. Corresponding homologous proteins were analyzed and potential therapeutic drugs for pNETs were identified using the Connectivity Map and Drug-Gene Interaction Database. RESULTS: Assessment of raw data from 12,610 pNET genes demonstrated that 1082 and 380 genes were upregulated and downregulated, respectively, compared with normal pancreas tissue. Upregulated pathways were associated with nitrogen metabolism (i.e., GABAergic synapse, and graft-versus-host disease), whereas downregulated pathways included C-type leptin receptor signaling pathway, pertussis and AMPK signaling pathway. In particular, the protein-protein interaction analysis revealed 10 upregulated hub genes (DYNLL1, GNB5, GNB2, GNG4, GNAI2, GNAI1, HIST2H2BE, NUP107, NUP133, and SNAP25) and 10 downregulated hub genes (CXCL8, F2, CXCL2, GCG, SST, INS, GALR3, CCL20, ADRA2B, and CXCL6). Using the Drug-Gene Interaction Database, candidate drugs for pNETs treatment included 3 EGFR inhibitors (canertinib, erlotinib, WZ-4-145), as well as other cell-signaling pathway inhibitors such as AG-592, acarbose, lonidamine, azacytidine, rottlerin, and HU-211. CONCLUSION: Using available genetic atlas data, potential drug candidates for treatment of pNETs were identified based on differentially expressed genes. These results may help focus efforts on identifying targeted agents with therapeutic efficacy to treat patients with pNETs.
INTRODUCTION: There is a paucity of effective treatment options for advanced pancreatic neuroendocrine tumors (pNETs). Genome-wide analyses may allow for potential drugs to be identified based on differentially expressed genes (DEGs). METHODS: Oligo microarray data of RNA expression profiling of pNETs and normal pancreas tissues were downloaded from the Gene Expression Omnibus. Functional and pathway enrichment information of the DEGs was obtained using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. Corresponding homologous proteins were analyzed and potential therapeutic drugs for pNETs were identified using the Connectivity Map and Drug-Gene Interaction Database. RESULTS: Assessment of raw data from 12,610 pNET genes demonstrated that 1082 and 380 genes were upregulated and downregulated, respectively, compared with normal pancreas tissue. Upregulated pathways were associated with nitrogen metabolism (i.e., GABAergic synapse, and graft-versus-host disease), whereas downregulated pathways included C-type leptin receptor signaling pathway, pertussis and AMPK signaling pathway. In particular, the protein-protein interaction analysis revealed 10 upregulated hub genes (DYNLL1, GNB5, GNB2, GNG4, GNAI2, GNAI1, HIST2H2BE, NUP107, NUP133, and SNAP25) and 10 downregulated hub genes (CXCL8, F2, CXCL2, GCG, SST, INS, GALR3, CCL20, ADRA2B, and CXCL6). Using the Drug-Gene Interaction Database, candidate drugs for pNETs treatment included 3 EGFR inhibitors (canertinib, erlotinib, WZ-4-145), as well as other cell-signaling pathway inhibitors such as AG-592, acarbose, lonidamine, azacytidine, rottlerin, and HU-211. CONCLUSION: Using available genetic atlas data, potential drug candidates for treatment of pNETs were identified based on differentially expressed genes. These results may help focus efforts on identifying targeted agents with therapeutic efficacy to treat patients with pNETs.
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