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Evaluation of skin response after erbium:yttrium–aluminum–garnet laser irradiation: a network analysis approach

Majid Rezaei-tavirani, Mostafa Rezaei Tavirani, Mona Zamanian Azodi, Mohammadreza Razzaghi, Hamideh Moravvej Farshi




Introduction: Application of laser in medicine and cosmetic purposes has raised grossly in recent years. There are contradictory finding about its side effects. In this research critical differentially expressed proteins after irradiation erbium:yttrium–aluminum–garnet (Er:YAG) laser on skin are investigated.

Methods: Proteome data including 31 proteins were obtained from a proteomics investigation of laser irradiation, Er:YAG on female mouse skin that are published by Pan et al. The query proteins and 100 related ones were included in the protein-protein interaction (PPI) network. The central nodes were determined and all of nodes were included in action maps. Expression, activation, inhibition, binding, and reaction were considered in action plan.

Results: Numbers of 16 proteins were recognized by STRING database and were included in the network. Except PHRF1, the other 15 query proteins were included in the main connected component of the constructed network. Ten central nodes of the network and ten numbers of top query proteins based on degree value were identified as central proteins of the network. All nodes of the network analyzed via action maps and the important acted nodes were determined as RPSA, GAPDH, TPT1, DCTN2, HSPB1, and PDIA3.

Conclusion: Two balanced processes including cancer promotion and cancer prevention were after irradiation were identified.


Laser irradiation; Erbium:yttrium–aluminum–garnet (Er:YAG); Skin Care; Proteomics; Protein-protein interaction network analysis; Biological process


Gladstone GJ. Laser Skin Resurfacing. Oculoplastic Surgery Atlas. Springer; 2018:51-54.

Pan TL, Wang PW, Lee WR, et al. Systematic evaluations of skin damage irradiated by an erbium:YAG laser: histopathologic analysis, proteomic profiles, and cellular response. J Dermatol Sci. 2010;58(1):8-18. doi:10.1016/j. jdermsci.2010.02.001

Asadzadeh-Aghdaei H, Zamanian Azodi M, Vafaee R, Moravvej Farshi H, Naderi N. SRC and TP53 play critical role in low-grade dysplasia colorectal mucosa transformation into cancer. Gastroenterol Hepatol Bed Bench. 2018;11(Suppl 1):S104-s110.

Naderi N, Zamanian Azodi M, Daskar Abkenar E, Shahidi Dadras M, Talaei R. Insulin dysregulation plays a critical role in colon inflammation: a bioinformatics approach. Gastroenterol Hepatol Bed Bench. 2018;11(Suppl 1):S85-s91.

Schwanhausser B, Gossen M, Dittmar G, Selbach M. Global analysis of cellular protein translation by pulsed SILAC. Proteomics. 2009;9(1):205-209. doi:10.1002/ pmic.200800275

Wu CH, Huang H, Yeh LS, Barker WC. Protein family classification and functional annotation. Comput Biol Chem. 2003;27(1):37-47.

Stelzl U, Worm U, Lalowski M, et al. A human proteinprotein interaction network: a resource for annotating the proteome. Cell. 2005;122(6):957-968. doi:10.1016/j. cell.2005.08.029

Rual JF, Venkatesan K, Hao T, et al. Towards a proteomescale map of the human protein-protein interaction network. Nature. 2005;437(7062):1173-1178. doi:10.1038/ nature04209

Rezaei Tavirani M, Bashash D, Tajik Rostami F, et al. Celiac disease microarray analysis based on System

Biology Approach. Gastroenterol Hepatol Bed Bench. 2018;11(3):216-224.

Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498-2504. doi:10.1101/gr.1239303

Szklarczyk D, Morris JH, Cook H, et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45(D1):D362-d368. doi:10.1093/nar/gkw937

Assenov Y, Ramirez F, Schelhorn SE, Lengauer T, Albrecht M. Computing topological parameters of biological networks. Bioinformatics. 2008;24(2):282-284. doi:10.1093/bioinformatics/btm554

Zamanian-Azodi M, Rezaei-Tavirani M. Investigation of health benefits of cocoa in human colorectal cancer cell line, HT-29 through interactome analysis. Gastroenterol Hepatol Bed Bench. 2019;12(1):67-73.

Bindea G, Galon J, Mlecnik B. CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico data. Bioinformatics. 2013;29(5):661-663.doi:10.1093/bioinformatics/btt019

Asadzadeh-Aghdaei H, Zamanian Azodi M, Vafaee R, Moravvej Farshi H, Naderi N. SRC and TP53 play critical role in low-grade dysplasia colorectal mucosa transformation into cancer. Gastroenterol Hepatol Bed Bench. 2018;11(Suppl 1):S104-s110.

Ganjali M, Seifalian AM, Mozafari M. Effect of Laser Irradiation on Cell Cycle and Mitosis. J Lasers Med Sci. 2018;9(4):249-253. doi:10.15171/jlms.2018.45

Kong S, Aoki A, Iwasaki K, et al. Biological effects of Er:YAG laser irradiation on the proliferation of primary human gingival fibroblasts. J Biophotonics. 2018;11(3). doi:10.1002/jbio.201700157

Ash C, Town G, Whittall R, Tooze L, Phillips J. Lasers and intense pulsed light (IPL) association with cancerous

lesions. Lasers Med Sci. 2017;32(8):1927-1933. doi:10.1007/s10103-017-2310-y

Basset-Seguin N, Moles JP, Mils V, Dereure O, Guilhou JJ. TP53 tumor suppressor gene and skin carcinogenesis. J Invest Dermatol. 1994;103(5 Suppl):102s-106s.

Carpten JD, Faber AL, Horn C, et al. A transforming mutation in the pleckstrin homology domain of AKT1

in cancer. Nature. 2007;448(7152):439-444. doi:10.1038/nature05933

DOI: https://doi.org/10.22037/jlms.v10i3.24698