Research Article
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Identification of Thyroid Carcinoma Related Molecular Targets and Signatures Using Human Protein Interaction Network

Year 2019, Volume: 31 Issue: 3, 245 - 254, 01.09.2019
https://doi.org/10.7240/jeps.536218

Abstract

Thyroid cancer is a fatal
disease has a high incidence. Therefore, the determination of molecules
involved in thyroid cancer is very crucial for early diagnosis and treatment
strategies of the disease. In this study, high-dimensional functional genomic
data were integrated with system biology tools and the molecular targets and
signatures in thyroid cancer were determined. As a result of enrichment
analysis, it was determined that important cancer pathways, metabolic pathways
and immune system related pathways were activated. The protein- protein
interaction network was reconstructed using differential gene expression is
determined by advanced statistical analysis and the molecular targets and signatures
in thyroid cancer were determined as JUN, LRRK2, BCL2, CCND1, TLE1, MET, ICAM1,
DDB2 and RXRG. It was determined that these genes can differentiate tumor
samples and normal thyroid tissues via independent data analysis. Among these
proteins, JUN, TLE1 and DBB2 were found to be novel molecular targets. It is
predicted that these molecular targets can be used in the diagnosis and
treatment strategies of papillary thyroid cancer. However, it is necessary to
perform experimental studies with real time-PCR.

References

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İnsan Protein Etkileşim Ağı Kullanarak Tiroid Karsinomu İle İlgili Moleküler Hedef ve Biyoişaretçi Adayların Belirlenmesi

Year 2019, Volume: 31 Issue: 3, 245 - 254, 01.09.2019
https://doi.org/10.7240/jeps.536218

Abstract

Tiroid kanseri görülme
sıklığı yüksek olan ve ölümcül bir kanser türüdür. Dolayısıyla tiroid
kanserinde etkin rol alan moleküllerin belirlenmesi hastalığın erken tanı ve
tedavi stratejilerinin oluşturulması için çok önemlidir. Bu çalışmada yüksek
boyutlu işlevsel genomiks verilerinin sistem biyolojisi araçları ile
bütünleştirilerek analizi sonucu tiroid kanserine özgü moleküler hedefler ve
biyoişaretçi adaylar belirlenmiştir. Zenginleştirme analizi sonucunda önemli
kanser yolaklarının, metabolik yolakların ve immun sistem ilgili yolların
aktifleştiği belirlenmiştir. İleri istatistiksel analizler ile belirlenen gen
anlatımı farklılık gösteren genlerin protein etkileşim ağı oluşturulmuş ve
tiroid kanserine özgü moleküler hedefler ve biyoişaretçi adaylar JUN, LRRK2,
BCL2, CCND1, TLE1, MET, ICAM1, DDB2 ve RXRG olarak belirlenmiştir. Bağımsız bir
veri setinin analizi ile, bu genlerin tümör ve normal dokuları ayırt edebileceği
belirlenmiştir. Bu proteinler arasından JUN, TLE1 ve DBB2’nin yeni moleküler
hedef ve biyoişaretçi aday olabileceği bulunmuştur. Belirlenen hedeflerin
papiller tiroid kanserinin teşhis ve tedavi stratejilerinin oluşturulmasında
kullanılabileceği öngörülmektedir. Ancak söz konusu adayların eş zamanlı PCR
ile deneysel çalışmalarının yapılması gerekmektedir.

References

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  • [2] Xing, M. (2013). Molecular pathogenesis and mechanisms of thyroid cancer. Nature Reviews Cancer., 13(3), 184.
  • [3] Elisei, R., Ugolini, C., Viola, D., Lupi, C., Biagini, A., Giannini, R., Romei, C., Miccoli, P., Pinchera, A. ve Basolo, F. (2008). BRAF(V600E) mutation and outcome of patients with papillary thyroid carcinoma: a 15-year median follow-up study. J Clin Endocrinol Metab., 93, 3943–3949.
  • [4] Yip, L., Nikiforova, M.N., Carty, S.E., Yim, J.H., Stang, M.T., Tublin, M.J., Lebeau, S.O., Hodak, S.P., Ogilvie, J.B. ve Nikiforov Y.E. (2009). Optimizing surgical treatment of papillary thyroid carcinoma associated with BRAF mutation. Surgery., 146,1215–1223.
  • [5] Handkiewicz-Junak, D., Swierniak, M., Rusinek, D., Oczko-Wojciechowska, M., Dom, G., Maenhaut, C., Unger, K., Detours V., Bogdanova, T.,Thomas, G.,Likhtarov, I., Jaksik, R.,Kowalska, M., Chmielik, E., Jarzab, M., ve Swierniak A. (2016). Gene signature of the post-Chernobyl papillary thyroid cancer. European journal of nuclear medicine and molecular imaging., 43(7), 1267-1277.
  • [6] Chien, M. N., Yang, P. S., Lee, J. J., Wang, T. Y., Hsu, Y. C. ve Cheng, S. P. (2017). Recurrence-associated genes in papillary thyroid cancer: An analysis of data from The Cancer Genome Atlas. Surgery., 161(6), 1642-1650.
  • [7] Vasko, V., Espinosa, A. V., Scouten, W., He, H., Auer, H., Liyanarachchi, S., Larin, A., Savchenko, V., Francis, G. L. de la Chapelle, A., Saji, M. ve Ringel M.D. (2007). Gene expression and functional evidence of epithelial-to-mesenchymal transition in papillary thyroid carcinoma invasion. Proceedings of the National Academy of Sciences., 104(8), 2803-2808.
  • [8] Burniat, A., Jin, L., Detours, V., Driessens, N., Goffard, J. C., Santoro, M., Rothstein, J. Dumont, J. E., Miot F. ve Corvilain, B. (2008). Gene expression in RET/PTC3 and E7 transgenic mouse thyroids: RET/PTC3 but not E7 tumors are partial and transient models of human papillary thyroid cancers. Endocrinology., 149(10), 5107-5117.
  • [9] McFadden, D. G., Vernon, A., Santiago, P. M., Martinez-McFaline, R., Bhutkar, A., Crowley, D. M., McMahon, M., Sadow P. M. ve Jacks, T. (2014). p53 constrains progression to anaplastic thyroid carcinoma in a Braf-mutant mouse model of papillary thyroid cancer. Proceedings of the National Academy of Sciences., 111(16), E1600-E1609.
  • [10] Zhao, H. ve Li, H. (2018). Network-based meta-analysis in the identification of biomarkers for papillary thyroid cancer. Gene., 661, 160-168.
  • [11] Yu, J., Mai, W., Cui, Y. ve Kong, L. (2016). Key genes and pathways predicted in papillary thyroid carcinoma based on bioinformatics analysis. Journal of endocrinological investigation., 39(11), 1285-1293.
  • [12] Barrett, T., Troup, D.B., Wilhite, S.E., Ledoux, P., Evangelista, C., Kim, I .F., Tomashevsky, M., Marshall, K.A., Phillippy, K.H., Sherman, P.M., Muertter, R.N., Holko, M., Ayanbule, O., Yefanov, A. ve Soboleva, A. (2011). NCBI GEO: archive for functional genomics data sets-10 years on, Nucleic Acids Res., 39(Database issue): D1005--D1010.
  • [13] Handkiewicz-Junak, D., Swierniak, M., Rusinek, D., Oczko-Wojciechowska, M., Dom, G., Maenhaut, C., Unger, K., Detours, V., Bogdanova, T., Thomas, G., Likhtarov, I., Jaksik, R Kowalska, M., Chmielik, E., Jarzab, M., Swierniak, A. ve Jarzab, B. (2016). Gene signature of the post-Chernobyl papillary thyroid cancer. European journal of nuclear medicine and molecular imaging., 43(7), 1267-1277.
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  • [15] Vasko, V., Espinosa, A. V., Scouten, W., He, H., Auer, H., Liyanarachchi, S., Larin, A., Savchenko, V., Francis, G. L., Chapelle, A., Saji, M., ve Ringel, M.D. (2007). Gene expression and functional evidence of epithelial-to-mesenchymal transition in papillary thyroid carcinoma invasion. Proceedings of the National Academy of Sciences., 104(8), 2803-2808.
  • [16] Smyth G.K. (2005). Limma: linear models for microarray data. In: Bioinformatics and Computational Biology Solutions using R and Bioconductor, R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W. Huber (eds.), Springer, New York, 397-420.
  • [17] Huang D.W., Sherman, B.T., Tan, Q., Kir, J., Liu, D., Bryant, D., Guo, Y., Stephens, R., Baseler, M. W., Lane, H. C. ve Lempicki, R.A. (2007). DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists, Nucleic Acids Res., 35(Web Server issue), W169--W175.
  • [18] Karagoz, K., Sevimoglu, T., ve Arga, K. Y. (2016). Integration of multiple biological features yields high confidence human protein interactome. Journal of theoretical biology., 403, 85-96.
  • [19] Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B. ve Ideker, T. (2003). Cytoscape: a software environment for integrated models of biomolecular interaction networks, Genome Res., 13(11), 2498-504.
  • [20] Stelzer, G., Rosen, R., Plaschkes, I., Zimmerman, S., Twik, M., Fishilevich, S., Iny Stein, T., Nudel, R., Lieder, I., Mazor, Y., Kaplan, S., Dahary, D., Warshawsky, D., Guan – Golan, Y., Kohn, A., Rappaport, N., Safran, M., ve Lancet D. (2016), The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analysis , Current Protocols in Bioinformatics., 54, 1.30.1.
  • [21] Kitahara, C. M. ve Sosa, J. A. (2016). The changing incidence of thyroid cancer. Nature Reviews Endocrinology., 12(11), 646.
  • [22] TC Sağlık Bakanlığı, Türkiye Halk Sağlığı Kurumu, Kanser istatistikleri, (2016).
  • [23] Liu, E. T. (2010). Foundations for Systems Biomedicine: an Introduction. In Systems Biomedicine Academic Press, Singapur. 1-13
  • [24] Calimlioglu, B., Karagoz, K., Sevimoglu, T., Kilic, E., Gov, E. ve Arga, K. Y. (2015). Tissue-specific molecular biomarker signatures of type 2 diabetes: an integrative analysis of transcriptomics and protein–protein interaction data. Omics: a journal of integrative biology., 19(9), 563-573.
  • [25] Kori, M., Gov, E. ve Arga, K. Y. (2016). Molecular signatures of ovarian diseases: Insights from network medicine perspective. Systems biology in reproductive medicine., 62(4), 266-282.
  • [26] Gov, E., Kori, M. ve Arga, K. Y. (2017). Multiomics analysis of tumor microenvironment reveals Gata2 and miRNA-124-3p as potential novel biomarkers in ovarian cancer. Omics: a journal of integrative biology., 21(10), 603-615.
  • [27] Manzella, L., Stella, S., Pennisi, M., Tirrò, E., Massimino, M., Romano, C., Vigneri, P. (2017). New insights in thyroid cancer and p53 family proteins. International journal of molecular sciences., 18(6), 1325.
  • [28] Ramírez-Moya, J., Wert-Lamas, L. ve Santisteban, P. (2018). MicroRNA-146b promotes PI3K/AKT pathway hyperactivation and thyroid cancer progression by targeting PTEN. Oncogene., 37(25), 3369.
  • [29] Zhao, J., Li, Z., Chen, Y., Zhang, S., Guo, L., Gao, B., Zhang, X. (2019). MicroRNA 766 inhibits papillary thyroid cancer progression by directly targeting insulin receptor substrate 2 and regulating the PI3K/Akt pathway. International journal of oncology., 54(1), 315-325.
  • [30] Knauf, J. A., Sartor, M. A., Medvedovic, M., Lundsmith, E., Ryder, M., Salzano, M., Fagin, J. A. (2011). Progression of BRAF-induced thyroid cancer is associated with epithelial–mesenchymal transition requiring concomitant MAP kinase and TGFβ signaling. Oncogene., 30(28), 3153.
  • [31] Ashton, T. M., Fokas, E., Kunz-Schughart, L. A., Folkes, L. K., Anbalagan, S., Huether, M., Stratford, M. (2016). The anti-malarial atovaquone increases radiosensitivity by alleviating tumour hypoxia. Nature communications., 7, 12308.
  • [32] Zhang, Y., Sui, F., Ma, J., Ren, X., Guan, H., Yang, Q., Hou, P. (2016). Positive feedback loops between NrCAM and major signaling pathways contribute to thyroid tumorigenesis. The Journal of Clinical Endocrinology & Metabolism., 102(2), 613-624.
  • [33] Liang, W. ve Sun, F. (2018). Identification of key genes of papillary thyroid cancer using integrated bioinformatics analysis. Journal of endocrinological investigation., 41(10), 1237-1245.
  • [34] Yamada, T. ve Masuda, M. (2017). Emergence of TNIK inhibitors in cancer therapeutics. Cancer science., 108(5), 818-823.
  • [35] Lopez-Bergami, P., Lau, E. ve Ronai, Z. E. (2010). Emerging roles of ATF2 and the dynamic AP1 network in cancer. Nature Reviews Cancer., 10(1), 65.
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There are 47 citations in total.

Details

Primary Language Turkish
Journal Section Research Articles
Authors

Esra Göv 0000-0002-5256-4778

Publication Date September 1, 2019
Published in Issue Year 2019 Volume: 31 Issue: 3

Cite

APA Göv, E. (2019). İnsan Protein Etkileşim Ağı Kullanarak Tiroid Karsinomu İle İlgili Moleküler Hedef ve Biyoişaretçi Adayların Belirlenmesi. International Journal of Advances in Engineering and Pure Sciences, 31(3), 245-254. https://doi.org/10.7240/jeps.536218
AMA Göv E. İnsan Protein Etkileşim Ağı Kullanarak Tiroid Karsinomu İle İlgili Moleküler Hedef ve Biyoişaretçi Adayların Belirlenmesi. JEPS. September 2019;31(3):245-254. doi:10.7240/jeps.536218
Chicago Göv, Esra. “İnsan Protein Etkileşim Ağı Kullanarak Tiroid Karsinomu İle İlgili Moleküler Hedef Ve Biyoişaretçi Adayların Belirlenmesi”. International Journal of Advances in Engineering and Pure Sciences 31, no. 3 (September 2019): 245-54. https://doi.org/10.7240/jeps.536218.
EndNote Göv E (September 1, 2019) İnsan Protein Etkileşim Ağı Kullanarak Tiroid Karsinomu İle İlgili Moleküler Hedef ve Biyoişaretçi Adayların Belirlenmesi. International Journal of Advances in Engineering and Pure Sciences 31 3 245–254.
IEEE E. Göv, “İnsan Protein Etkileşim Ağı Kullanarak Tiroid Karsinomu İle İlgili Moleküler Hedef ve Biyoişaretçi Adayların Belirlenmesi”, JEPS, vol. 31, no. 3, pp. 245–254, 2019, doi: 10.7240/jeps.536218.
ISNAD Göv, Esra. “İnsan Protein Etkileşim Ağı Kullanarak Tiroid Karsinomu İle İlgili Moleküler Hedef Ve Biyoişaretçi Adayların Belirlenmesi”. International Journal of Advances in Engineering and Pure Sciences 31/3 (September 2019), 245-254. https://doi.org/10.7240/jeps.536218.
JAMA Göv E. İnsan Protein Etkileşim Ağı Kullanarak Tiroid Karsinomu İle İlgili Moleküler Hedef ve Biyoişaretçi Adayların Belirlenmesi. JEPS. 2019;31:245–254.
MLA Göv, Esra. “İnsan Protein Etkileşim Ağı Kullanarak Tiroid Karsinomu İle İlgili Moleküler Hedef Ve Biyoişaretçi Adayların Belirlenmesi”. International Journal of Advances in Engineering and Pure Sciences, vol. 31, no. 3, 2019, pp. 245-54, doi:10.7240/jeps.536218.
Vancouver Göv E. İnsan Protein Etkileşim Ağı Kullanarak Tiroid Karsinomu İle İlgili Moleküler Hedef ve Biyoişaretçi Adayların Belirlenmesi. JEPS. 2019;31(3):245-54.