TİROZİN KİNAZ İNHİBİTÖRLERİNİN KARDİYOVASKÜLER TOKSİSİTE ANALİZİ İÇİN AĞ TOKSİKOLOJİSİ

Yıl 2024, Cilt: 48 Sayı: 3, 929 - 939, 10.09.2024

Fuat Karakuş

https://doi.org/10.33483/jfpau.1478733

Öz

Amaç: Bu çalışma, tirozin kinaz inhibitörlerinin neden olduğu kardiyovasküler toksisitelerin potansiyel moleküler mekanizmalarını ve hedeflerini araştırmayı amaçlamaktadır. Bu nedenle, sunitinib, sorafenib, pazopanib, axitinib ve bunların kardiyovasküler hastalıklarla ilişkilerine odaklanarak toksikogenomik veri madenciliği yapılmıştır.
Gereç ve Yöntem: Tirozin kinaz inhibitörleri ile kardiyovasküler hastalıklar arasındaki ortak genler, karşılaştırmalı toksikogenomik veritabanları aracılığıyla belirlenmiştir. Ayrıca, protein-protein etkileşimleri ve gen-gen etkileşimleri sırasıyla STRING ve GeneMANIA kullanılarak belirlenmiştir. Daha sonra, tirozin kinaz inhibitörü ile ilişkilendirilmiş kardiyovasküler hastalıklara ait merkezi proteinler Metascape kullanılarak belirlenmiştir. Bu toksisite ile ilişkili transkripsiyon faktörleri ve mikroRNA'lar sırasıyla ChEA3 ve MIENTURNET kullanılarak belirlenmiştir. Son olarak, gen ontolojisi zenginleştirme analizi ve en çok ilişkilendirilen moleküler yollar sırasıyla DAVID veritabanı ve Metascape kullanılarak belirlenmiştir.
Sonuç ve Tartışma: Toksikogenomik veri madenciliği, tirozin kinaz inhibitörleri ile kardiyovasküler hastalıklar arasında altı ortak geni ortaya çıkardı; bunlardan beşi (FLT1, FLT4, KDR, MAPK1 ve MAPK3) merkezi genler olarak belirlendi. Bu merkezi genler arasında fiziksel etkileşim baskın olarak gözlemlendi (%77.64). Sunitinib, sorafenib, pazopanib ve axitinib genel olarak bu protein aktivitelerini azaltmaktadır. Transkripsiyon faktörleri arasında SOX17 ve SOX18 öne çıkmaktadır, hsa-miR-199a-3p ise bu toksisite ile en önemli mikroRNA'dır. Ayrıca, Ras sinyal yolunun tirozin kinaz inhibitörleri ile ilişkilendirilen kardiyovasküler toksisitelerle çoğunlukla ilişkilendirildiği görülmüştür. Bu bulgular, sunitinib, sorafenib, pazopanib ve axitinib tarafından indüklenen kardiyovasküler hastalıkların altında yatan süreçleri anlamada önemli bir katkı yapmaktadır. Ayrıca, genler, proteinler, transkripsiyon faktörleri, mikroRNA'lar ve yollar da dahil olmak üzere yeni potansiyel terapötik hedefleri ortaya koymaktadır.

Anahtar Kelimeler

İn siliko veri madenciliği, kardiyovasküler hastalıklar, tirozin kinaz inhibitörleri

NETWORK TOXICOLOGY FOR THE CARDIOVASCULAR TOXICITY ANALYSIS OF TYROSINE KINASE INHIBITORS

Öz

Objective: This study aims to explore potential molecular mechanisms and targets of cardiovascular toxicities caused by tyrosine kinase inhibitors. Therefore, toxicogenomic data mining was conducted focusing on sunitinib, sorafenib, pazopanib, axitinib, and their associations with cardiovascular diseases.
Material and Method: Common genes between tyrosine kinase inhibitors and cardiovascular diseases were uncovered via comparative toxicogenomic databases. Additionally, protein-protein and gene-gene interactions were identified using STRING and GeneMANIA, respectively. Subsequently, hub proteins associated with tyrosine kinase inhibitor-induced cardiovascular diseases were determined through Metascape. Transcription factors and microRNAs related to this toxicity were identified using ChEA3 and MIENTURNET, respectively. Finally, gene ontology enrichment analysis and the most associated molecular pathways were identified using the DAVID database and Metascape, respectively.
Result and Discussion: Toxicogenomic data mining revealed six genes common between tyrosine kinase inhibitors and cardiovascular diseases, with five of these genes (FLT1, FLT4, KDR, MAPK1, and MAPK3) identified as hub genes. Physical interaction was dominant among these hub genes (77.64%). Sunitinib, sorafenib, pazopanib, and axitinib generally downregulated the activities of these proteins. SOX17 and SOX18 were prominent among transcription factors, while hsa-miR-199a-3p was the most important microRNA associated with this toxicity. Moreover, the Ras signaling pathway was mostly associated with tyrosine kinase inhibitor-induced cardiovascular toxicities. These findings make a substantial contribution to understanding the processes underlying cardiovascular diseases induced by sunitinib, sorafenib, pazopanib, and axitinib. They also reveal novel potential therapeutic targets, including genes, proteins, transcription factors, microRNAs, and pathways.

Anahtar Kelimeler

Cardiovascular diseases, in silico data mining, tyrosine kinase inhibitors

Kaynakça

• 1. Wang, H., Wang, Y., Li, J., He, Z., Boswell, S.A., Chung, M., You, F., Han, S. (2023). Three tyrosine kinase inhibitors cause cardiotoxicity by inducing endoplasmic reticulum stress and inflammation in cardiomyocytes. BMC Medicine, 21(1), 147. [CrossRef]
• 2. Richards, C.J., Je, Y., Schutz, F.A., Heng, D.Y., Dallabrida, S.M., Moslehi, J.J., Choueiri, T.K. (2011). Incidence and risk of congestive heart failure in patients with renal and nonrenal cell carcinoma treated with sunitinib. Journal of Clinical Oncology: Official Journal of The American Society of Clinical Oncology, 29(25), 3450-3456. [CrossRef]
• 3. Escudier, B., Eisen, T., Stadler, W.M., Szczylik, C., Oudard, S., Siebels, M., Negrier, S., Chevreau, C., Solska, E., Desai, A.A., Rolland, F., Demkow, T., Hutson, T.E., Gore, M., Freeman, S., Schwartz, B., Shan, M., Simantov, R., Bukowski, R.M., TARGET Study Group. (2007). Sorafenib in advanced clear-cell renal-cell carcinoma. The New England Journal of Medicine, 356(2), 125-134. [CrossRef]
• 4. Llovet, J.M., Ricci, S., Mazzaferro, V., Hilgard, P., Gane, E., Blanc, J.F., de Oliveira, A.C., Santoro, A., Raoul, J.L., Forner, A., Schwartz, M., Porta, C., Zeuzem, S., Bolondi, L., Greten, T.F., Galle, P.R., Seitz, J.F., Borbath, I., Häussinger, D., Giannaris, T., Shan, M., Moscovici, M., Voliotis, D., Bruix, J. (2008). Sorafenib in advanced hepatocellular carcinoma. The New England Journal of Medicine, 359(4), 378-390. [CrossRef]
• 5. Chu, T.F., Rupnick, M.A., Kerkela, R., Dallabrida, S.M., Zurakowski, D., Nguyen, L., Woulfe, K., Pravda, E., Cassiola, F., Desai, J., George, S., Morgan, J.A., Harris, D.M., Ismail, N.S., Chen, J.H., Schoen, F.J., Van den Abbeele, A.D., Demetri, G.D., Force, T., Chen, M.H. (2007). Cardiotoxicity associated with tyrosine kinase inhibitor sunitinib. Lancet, 370(9604), 2011-2019. [CrossRef]
• 6. Van Leeuwen, M.T., Luu, S., Gurney, H., Brown, M.R., Pearson, S.A., Webber, K., Hunt, L., Hong, S., Delaney, G.P., Vajdic, C.M. (2020). Cardiovascular Toxicity of Targeted Therapies for Cancer: An Overview of Systematic Reviews. JNCI Cancer Spectrum, 4(6), pkaa076. [CrossRef]
• 7. Narayan, H.K., Sheline, K., Wong, V., Kuo, D., Choo, S., Yoon, J., Leger, K., Kutty, S., Fradley, M., Tremoulet, A., Ky, B., Armenian, S., Guha, A. (2023). Cardiovascular toxicities with pediatric tyrosine kinase inhibitor therapy: An analysis of adverse events reported to the Food and Drug Administration. Pediatric Blood & Cancer, 70(2), e30059. [CrossRef]
• 8. Kertmen, N., Kavgaci, G., Yildirim, H.C., Dizdar, O. (2024). Acute heart failure following pazopanib treatment: a literature review featuring two case reports. Anti-Cancer Drugs, 35(3), 302-304. [CrossRef]
• 9. Godo, S., Yoshida, Y., Kawamorita, N., Mitsuzuka, K., Kawazoe, Y., Fujita, M., Kudo, D., Nomura, R., Shimokawa, H., Kushimoto, S. (2018). Life-threatening Hyperkalemia Associated with Axitinib Treatment in Patients with Recurrent Renal Carcinoma. Internal Medicine (Tokyo, Japan), 57(19), 2895-2900. [CrossRef]
• 10. Chen, M.H., Kerkelä, R., Force, T. (2008). Mechanisms of cardiac dysfunction associated with tyrosine kinase inhibitor cancer therapeutics. Circulation, 118(1), 84-95. [CrossRef]
• 11. Zhang W. (2018). Fundamentals of network biology. Chapter 21: Network Pharmacology and Toxicology, World Scientific, pp. 391–411. [CrossRef]
• 12. Davis, A.P., Wiegers, T.C., Johnson, R.J., Sciaky, D., Wiegers, J., Mattingly, C.J. (2023). Comparative Toxicogenomics Database (CTD): update 2023. Nucleic Acids Research, 51(D1), D1257-D1262. [CrossRef]
• 13. Bardou, P., Mariette, J., Escudié, F., Djemiel, C., Klopp, C. (2014). jvenn: an interactive Venn diagram viewer. BMC Bioinformatics, 15(1), 293. [CrossRef]
• 14. Szklarczyk, D., Kirsch, R., Koutrouli, M., Nastou, K., Mehryary, F., Hachilif, R., Gable, A.L., Fang, T., Doncheva, N.T., Pyysalo, S., Bork, P., Jensen, L.J., von Mering, C. (2023). The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Research, 51(D1), D638-D646. [CrossRef]
• 15. Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B., Ideker, T. (2003). Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research, 13(11), 2498-2504. [CrossRef]
• 16. Zhou, Y., Zhou, B., Pache, L., Chang, M., Khodabakhshi, A.H., Tanaseichuk, O., Benner, C., Chanda, S.K. (2019). Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nature Communications, 10(1), 1523. [CrossRef]
• 17. Warde-Farley, D., Donaldson, S.L., Comes, O., Zuberi, K., Badrawi, R., Chao, P., Franz, M., Grouios, C., Kazi, F., Lopes, C.T., Maitland, A., Mostafavi, S., Montojo, J., Shao, Q., Wright, G., Bader, G.D., Morris, Q. (2010). The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Research, 38(Web Server issue), W214-W220. [CrossRef]
• 18. Keenan, A.B., Torre, D., Lachmann, A., Leong, A.K., Wojciechowicz, M.L., Utti, V., Jagodnik, K.M., Kropiwnicki, E., Wang, Z., Ma'ayan, A. (2019). ChEA3: Transcription factor enrichment analysis by orthogonal omics integration. Nucleic Acids Research, 47(W1), W212-W224. [CrossRef]
• 19. Licursi, V., Conte, F., Fiscon, G., Paci, P. (2019). MIENTURNET: an interactive web tool for microRNA-target enrichment and network-based analysis. BMC Bioinformatics, 20(1), 545. [CrossRef]
• 20. Sherman, B.T., Hao, M., Qiu, J., Jiao, X., Baseler, M.W., Lane, H.C., Imamichi, T., Chang, W. (2022). DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Research, 50(W1), W216-W221. [CrossRef]
• 21. Benjamini, Y., Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of The Royal Statistical Society: Series B (Methodological), 57(1), 289-300. [CrossRef]
• 22. Shi, H.Y., Xie, M.S., Yang, C.X., Huang, R.T., Xue, S., Liu, X.Y., Xu, Y.J., Yang, Y.Q. (2022). Identification of SOX18 as a New Gene Predisposing to Congenital Heart Disease. Diagnostics (Basel, Switzerland), 12(8), 1917. [CrossRef]
• 23. Zhao, L., Jiang, W.F., Yang, C.X., Qiao, Q., Xu, Y.J., Shi, H.Y., Qiu, X.B., Wu, S.H., Yang, Y.Q. (2021). SOX17 loss-of-function variation underlying familial congenital heart disease. European Journal of Medical Genetics, 64(5), 104211. [CrossRef]
• 24. Hernández-García, A., Pendleton, K.E., Kim, S., Li, Y., Kim, B.J., Zaveri, H.P., Jordan, V.K., Berry, A. M., Ljungberg, M.C., Chen, R., Lanz, R.B., Scott, D.A. (2023). SOX7 deficiency causes ventricular septal defects through its effects on endocardial-to-mesenchymal transition and the expression of Wnt4 and Bmp2. Human Molecular Genetics, 32(13), 2152-2161. [CrossRef]
• 25. Knöfler, M., Meinhardt, G., Vasicek, R., Husslein, P., Egarter, C. (1998). Molecular cloning of the human Hand1 gene/cDNA and its tissue-restricted expression in cytotrophoblastic cells and heart. Gene, 224(1-2), 77–86. [CrossRef]
• 26. Joris, V., Gomez, E.L., Menchi, L., Lobysheva, I., Di Mauro, V., Esfahani, H., Condorelli, G., Balligand, J.L., Catalucci, D., Dessy, C. (2018). MicroRNA-199a-3p and MicroRNA-199a-5p take part to a redundant network of regulation of the NOS (NO Synthase)/NO pathway in the endothelium. Arteriosclerosis, Thrombosis, and Vascular Biology, 38(10), 2345-2357. [CrossRef]
• 27. Eulalio, A., Mano, M., Dal Ferro, M., Zentilin, L., Sinagra, G., Zacchigna, S., Giacca, M. (2012). Functional screening identifies miRNAs inducing cardiac regeneration. Nature, 492(7429), 376-381. [CrossRef]
• 28. Ramos-Kuri, M., Rapti, K., Mehel, H., Zhang, S., Dhandapany, P.S., Liang, L., García-Carrancá, A., Bobe, R., Fischmeister, R., Adnot, S., Lebeche, D., Hajjar, R.J., Lipskaia, L., Chemaly, E.R. (2015). Dominant negative Ras attenuates pathological ventricular remodeling in pressure overload cardiac hypertrophy. Biochimica et Biophysica Acta, 1853(11 Pt A), 2870-2884. [CrossRef]
• 29. Zhao, C.Z., Zhao, X.M., Yang, J., Mou, Y., Chen, B., Wu, H.D., Dai, D.P., Ding, J., Hu, S.J. (2016). Inhibition of farnesyl pyrophosphate synthase improves pressure overload induced chronic cardiac remodeling. Scientific Reports, 6, 39186. [CrossRef]
• 30. Linglart, L., Gelb, B.D. (2020). Congenital heart defects in Noonan syndrome: Diagnosis, management, and treatment. American Journal of Medical Genetics. Part C, Seminars in Medical Genetics, 184(1), 73-80. [CrossRef]
• 31. Ramos-Kuri, M., Meka, S.H., Salamanca-Buentello, F., Hajjar, R.J., Lipskaia, L., Chemaly, E.R. (2021). Molecules linked to Ras signaling as therapeutic targets in cardiac pathologies. Biological Research, 54(1), 23. [CrossRef]
• 32. Kanehisa, M., Furumichi, M., Sato, Y., Kawashima, M., Ishiguro-Watanabe, M. (2023). KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Research, 51(D1), D587-D592. [CrossRef]