Oral squamous cell cancer protein-protein interaction network interpretation in comparison to esophageal adenocarcinoma
Gastroenterology and Hepatology from Bed to Bench,
3 April 2017
Aim: The aim of this study is to present the oral Squamous Cell Cancer protein-protein interaction network interpretation in comparison to esophageal adenocarcinoma.
Background: Oral squamous cell cancer (OSCC) is a common disease worldwide, with poor prognosis and limited treatment. Thus, introducing molecular markers through network analysis can be helpful.
Methods: STRING database (DB) was applied for network construction through Cytoscape 3.4.0. Clue GO handled the gene annotation for the retrieved clusters. Eight proteins were indicated to be differential in the network constitution.
Results: The centrality and clustering analysis indicate that TP53 plays an over-significant role in network integrity among eight most central proteins including TP53, AKT1, EGFR, MYC, JUN, CDH1, CCND1, and CTNNB1. The suggested biomarker set is very similar to the related biomarker panel of esophageal adenocarcinoma.
Conclusion: The ontology analysis implies that the prominent proteins are involved in regulation of smooth muscle cell proliferation, regulation of fibroblast proliferation, and response to UV-A processes. In conclusion, these proteins and their associated biological processes may be more critical compared to other reported biomarkers for OSCC. Nevertheless, validation studies are required for confirming the pivotal role of potential candidates. Similar biomarker panel of this disease and esophagus adenocarcinoma is corresponded to the origin of the two malignancies.
Pauls DL, Abramovitch A, Rauch SL, Geller DA. Obsessive-compulsive disorder: an integrative genetic and neurobiological perspective. Nature Reviews Neuroscience. 2014;15(6):410-24.
Yakob M, Fuentes L, Wang MB, Abemayor E, Wong DT. Salivary biomarkers for detection of oral squamous cell carcinoma: current state and recent advances. Current oral health reports. 2014;1(2):133-41.
Gallo C, Ciavarella D, Santarelli A, Ranieri E, Colella G, MUZIO LL, et al. Potential salivary proteomic markers of oral squamous cell carcinoma. Cancer Genomics-Proteomics. 2016;13(1):55-61.
Nooshinfar E, Bashash D, Safaroghli-Azar A, Bayati S, Rezaei-Tavirani M, Ghaffari SH, et al. Melatonin promotes ATO-induced apoptosis in MCF-7 cells: Proposing novel therapeutic potential for breast cancer. Biomedicine & Pharmacotherapy. 2016;83:456-65.
Dave JH, Vora HH, Ghosh NR, Trivedi TI. Mediator of DNA damage checkpoint protein 1 (MDC1) as a prognostic marker for patients with oral squamous cell carcinoma. Journal of Oral Pathology & Medicine. 2017.
Asadzade-Aghdaee H, Shahrokh S, Nourozinia M, Hosseini M, Keramatinia A, Jamalan M, et al. Introduction of inflammatory bowel disease biomarkers panel using protein-protein interaction (PPI) network analysis. Gastroenterology and Hepatology from bed to bench. 2016.
Rezaei-Tavirani M, Rezaei-Tavirani M, Mansouri V, Rostami-Nejad M, Valizadeh R, Mahdavi SM, et al. Introducing crucial protein panel of gastric adenocarcinoma disease. Gastroenterology and Hepatology from bed to bench. 2017.
Ardakani MJE, Safaei A, Oskouie AA, Haghparast H, Haghazali M, Shalmani HM, et al. Evaluation of liver cirrhosis and hepatocellular carcinoma using Protein-Protein Interaction Networks. Gastroenterology and Hepatology from bed to bench. 2016.
Safari-Alighiarloo N, Rezaei-Tavirani M, Taghizadeh M, Tabatabaei SM, Namaki S. Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis. PeerJ. 2016;4:e2775.
Okhovatian F. Towards understanding topological features of protein interactome map of muscle cancer. Arvand Journal of Health and Medical Sciences. 2017;1(4).
Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, et al. The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible. Nucleic Acids Research. 2016:gkw937.
Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, et al. STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic acids research. 2014:gku1003.
Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC bioinformatics. 2003;4(1):2.
Kovács IA, Palotai R, Szalay MS, Csermely P. Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics. PloS one. 2010;5(9):e12528.
Bindea G, Mlecnik B, Hackl H, Charoentong P, Tosolini M, Kirilovsky A, et al. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics. 2009;25(8):1091-3.
Bindea G, Galon J, Mlecnik B. CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico data. Bioinformatics. 2013:btt019.
Jiang S, Dong Y. HPV and Oral Squamous Cell Carcinoma: A Review of HPV-positive OSCC and Possible Strategies for Future. Current Problems in Cancer. 2017.
Minhas S, Kashif M, AItaf W, Nagi A. Oral Squamous Cell Carcinoma Epidemiological. Rawal Medical Journal. 2016;41(1).
Khanna V, Karjodkar F, Robbins S, Behl M, Arya S, Tripathi A. Estimation of serum ferritin level in potentially malignant disorders, oral squamous cell carcinoma, and treated cases of oral squamous cell carcinoma. 2017.
Asadzadeh-Aghdaee H, Mansouri V, Peyvandi AA, Moztarzadeh F, Okhovatian F, Lahmi F, et al. Topological and functional analysis of nonalcoholic steatohepatitis through protein interaction mapping. Gastroenterology and Hepatology From Bed to Bench. 2016;9(Suppl1):S23.
Joerger AC, Fersht AR. The p53 pathway: Origins, inactivation in cancer, and emerging therapeutic approaches. Annual review of biochemistry. 2016;85:375-404.
Coates P. p53–The Gene That Cracked the Cancer Code. Wiley Online Library; 2015.
Carneiro A, Isinger A, Karlsson A, Johansson J, Jönsson G, Bendahl P-O, et al. Prognostic impact of array-based genomic profiles in esophageal squamous cell cancer. BMC cancer. 2008;8(1):98.
Essack M. Transcription regulation and candidate diagnostic markers of esophageal cancer: University of the Western Cape; 2009.
Moroni M, Veronese S, Benvenuti S, Marrapese G, Sartore-Bianchi A, Di Nicolantonio F, et al. Gene copy number for epidermal growth factor receptor (EGFR) and clinical response to antiEGFR treatment in colorectal cancer: a cohort study. The lancet oncology. 2005;6(5):279-86.
Vivanco I, Sawyers CL. The phosphatidylinositol 3-kinase–AKT pathway in human cancer. Nature Reviews Cancer. 2002;2(7):489-501.
Dehm S, Senger M-A, Bonham K. SRC transcriptional activation in a subset of human colon cancer cell lines. FEBS letters. 2001;487(3):367-71.
Dunn EF, Iida M, Myers RA, Campbell D, Hintz K, Armstrong EA, et al. Dasatinib sensitizes KRAS mutant colorectal tumors to cetuximab. Oncogene. 2011;30(5):561-74.
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