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A comprehensive catalogue of functional genetic variations in the EGFR pathway: Protein–protein interaction analysis reveals novel genes and polymorphisms important for cancer research
Sevtap Savas,
Joseph Geraci,
Igor Jurisica,
Geoffrey Liu,
Corresponding Author
Sevtap Savas
Division of Applied Molecular Oncology, Department of Medical Biophysics, Ontario Cancer Institute, Toronto, Ontario, Canada
Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, 300 Prince Philip Drive Room H4333, A1B 3V6, St John's, Newfoundland, CanadaSearch for more papers by this authorJoseph Geraci
Division of Signaling Biology, Ontario Cancer Institute, Toronto, Ontario, Canada
Search for more papers by this authorIgor Jurisica
Division of Signaling Biology, Ontario Cancer Institute, Toronto, Ontario, Canada
Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
Search for more papers by this authorGeoffrey Liu
Division of Applied Molecular Oncology, Department of Medical Biophysics, Ontario Cancer Institute, Toronto, Ontario, Canada
Division of Medical Oncology and Hematology, Department of Medicine, Princess Margaret Hospital, Toronto, Ontario, Canada
Search for more papers by this authorSevtap Savas,
Joseph Geraci,
Igor Jurisica,
Geoffrey Liu,
Corresponding Author
Sevtap Savas
Division of Applied Molecular Oncology, Department of Medical Biophysics, Ontario Cancer Institute, Toronto, Ontario, Canada
Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, 300 Prince Philip Drive Room H4333, A1B 3V6, St John's, Newfoundland, CanadaSearch for more papers by this authorJoseph Geraci
Division of Signaling Biology, Ontario Cancer Institute, Toronto, Ontario, Canada
Search for more papers by this authorIgor Jurisica
Division of Signaling Biology, Ontario Cancer Institute, Toronto, Ontario, Canada
Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
Search for more papers by this authorGeoffrey Liu
Division of Applied Molecular Oncology, Department of Medical Biophysics, Ontario Cancer Institute, Toronto, Ontario, Canada
Division of Medical Oncology and Hematology, Department of Medicine, Princess Margaret Hospital, Toronto, Ontario, Canada
Search for more papers by this authorAbstract
The EGFR pathway is a critical signaling pathway deregulated in many solid tumors. In addition to the initiation and progression of cancer, the EGFR pathway is also implicated in variable treatment responses and prognoses. Genetic variation in the form of Single Nucleotide Polymorphisms (SNPs) can affect the function/expression of the EGFR pathway genes. Here, we applied a systematic and comprehensive approach utilizing diverse public databases and in silico analysis tools to select putative functional genetic variations from 244 genes involved in the EGFR pathway. Our data comprises 649 SNPs. Three hundred sixty SNPs are predicted to have biological consequences (functional SNPs). These SNPs can be directly used in further studies to test their association with risk, treatment response and prognosis in cancer. To systematically cover the EGFR pathway, we also performed a network-based analysis to further select putative functional SNPs from the genes whose protein products physically interact with the EGFR pathway proteins. We utilized protein–protein interaction information and focused on 14 proteins that have a high degree of connectivity (interacting with ≥10 proteins) with the EGFR pathway genes identified to have functional SNPs (f-EGFR genes). Two of these proteins (FYN and LCK) had interactions with 17 of the f-EGFR genes, yet both lacked any putative functional SNP. However, our analysis indicated the presence of potentially functional SNPs in 9 other highly interactive proteins. The genes and their SNPs identified in the network-based analysis represent potential candidates for gene–gene and SNP–SNP interaction studies in cancer research. © 2009 UICC
Supporting Information
Additional Supporting Information may be found in the online version of this article.
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| IJC_24535_sm_suppinfotable1.xls45.5 KB | Supporting Table 1. |
| IJC_24535_sm_suppinfotable2.xls43.5 KB | Supporting Table 2. |
| IJC_24535_sm_suppinfotable3.xls59.5 KB | Supporting Table 3. |
| IJC_24535_sm_suppinfotable4.xls69 KB | Supporting Table 4. |
| IJC_24535_sm_suppinfotable5.xls18.5 KB | Supporting Table 5. |
| IJC_24535_sm_suppinfotable6.xls55.5 KB | Supporting Table 6. |
| IJC_24535_sm_suppinfotable7.xls31 KB | Supporting Table 7. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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