Comparison of Prognostic miRNA Signature in Patients with Acute and Chronic Myeloid Leukemia by Bioinformatic Analysis

Year 2022, Volume: 4 Issue: 3, 447 - 453, 22.09.2022

Aynur Karadağ

https://doi.org/10.37990/medr.1118392

Cited By: 1

Abstract

Aim: In this study, differentially expressed miRNA profiles were determined using high-throughput expression data from samples of AML and CML patients to identify miRNAs involved in the therapeutic response.
Material and Methods: miRNA microarray datasets GSE142699 and GSE90773 were downloaded via the GEO database and analysis was performed with the online analysis tool GEO2R. Data no. GSE142699 was made with 24 control and 24 newly diagnosed AML patients, data no. GSE90773 was made with 8 control and 10 newly diagnosed CML patients. After the analysis, they were grouped according to fold change (FC) values and p<0.05. Potential target genes regulated by differentially expressed miRNAs were predicted using the miRDB and TargetScan databases. Target genes enrichment analysis was performed GO function and KEGG pathway analysis using the DAVID program. Then, hub genes were detected using the regulatory network Cytoscape over the target genes.
Results: There were 27 unique miRNAs whose expression increased and 161 decreased in the AML group. In the CML group, 52 unique miRNAs with increased expression and 122 unique miRNAs with decreased expression were found. After clustering analysis between the AML and CML groups, 11 miRNAs with decreased expression and 5 miRNAs with increased expression were found. 7 miRNAs that were similar but differently expressed in the two groups were filtered out. A total of 2525 predicted target genes were found from 7 miRNAs. It was revealed that differently expressed miRNAs affect 22 common signaling pathways, especially the pathways in cancer, MAPK signaling, and PI3K-Akt signaling.
Conclusion: Our findings demonstrated that the same miRNAs are involved as different regulators in human leukemia development. Different miRNA signatures in myeloid development may be candidates for biomarkers for clinical diagnosis and differentiation, prognosis, and treatment of myeloid leukemias.

Keywords

Bioinformatic analyses, GEO, Leukemia, AML, CML, MiRNA

Supporting Institution

Çalışma destek almamıştır.

Project Number

-

Thanks

-

Akut ve Kronik Miyeloid Lösemili Hastalarda Prognostik miRNA İmzasının Biyoinformatik Analiz ile Karşılaştırılması

Abstract

Amaç: Bu çalışmada, terapötik yanıtta yer alan miRNA’ları belirlemek için AML ve KML hastalarının örneklerinden alınan yüksek verimli ekspresyon verilerini kullanarak diferansiyel miRNA ekspresyonunu analiz ettik.
Materyal ve Metot: miRNA mikrodizi veri setleri GSE142699 ve GSE90773, GEO veritabanı aracılığıyla indirildi ve çevrimiçi analiz aracı GEO2R ile analizi yapıldı. GSE142699 nolu data, 24 kontrol ve 24 yeni teşhis edilmiş AML hastası, GSE90773 nolu data ise 8 kontrol ve 10 yeni tanı konmuş KML hastası ile yapılmıştır. Analiz sonrası kat değişimi (FC) değerlerine ve p<0.05’e göre gruplandırıldı. TargetScan ve miRDB veritabanları, diferansiyel olarak eksprese edilen miRNA’lar tarafından düzenlenen potansiyel hedef genlerini tahmin etmek için kullanıldı. Hedef genler DAVID programı kullanılarak, aday hedef genlerin zenginleştirme analizi GO fonksiyon ve KEGG yolu analizi gerçekleştirildi. Daha sonra hedef genler üzerinden düzenleyici ağ Cytoscape kullanılarak hub genler tesbit edildi.
Bulgular: AML grubunda ekspresyonu artan 27 ve azalan 161 benzersiz miRNA bulundu. KML grubunda ekspresyonu artmış 52 ve ekspresyonu azalmış 122 benzersiz miRNA bulundu. AML ve KML grupları arasında kümeleme analizinden sonra ekspresyonu azalmış 11 miRNA ve ekspresyonu artmış 5 miRNA bulundu. Benzer olan ancak iki grupta farklı eksprese edilen 7 miRNA filtrelenmiştir. 7 miRNA’dan toplam 2525 tahmin edilen hedef gen bulundu. Farklı eksprese edilen miRNA’ların 22 ortak sinyal yolunu, özellikle kanserdeki yolları, PI3K-Akt sinyalini ve MAPK sinyalini etkilediği ortaya çıkmıştır.
Sonuç: Bulgularımız, aynı miRNA’ların insan lösemi gelişiminde farklı düzenlenleyiciler olarak rol aldığını göstermiştir. Miyeloid gelişimindeki farklı miRNA imzaları, miyeloid lösemilerin klinik teşhisi ve ayrımı, prognozu ve tedavisi için kullanılabilecek birer biyobelirteç adayı olabilir.

Keywords

Biyoinformatik analiz, GEO, Lösemi, AML, CML, MiRNA

Project Number

-

References

• 1. Morris, K.V. and J.S. Mattick, The rise of regulatory RNA. Nat Rev Genet, 2014. 15(6): p. 423-37.
• 2. Palazzo, A.F. and E.S. Lee, Non-coding RNA: what is functional and what is junk? Frontiers in Genetics, 2015. 6.
• 3. Bartel, D.P., MicroRNAs: genomics, biogenesis, mechanism, and function. Cell, 2004. 116(2): p. 281-97.
• 4. Collins, L.J. and D. Penny, The RNA infrastructure: dark matter of the eukaryotic cell? Trends Genet, 2009. 25(3): p. 120-8.
• 5. Albano, F., et al., SETBP1 and miR_4319 dysregulation in primary myelofibrosis progression to acute myeloid leukemia. J Hematol Oncol, 2012. 5: p. 48.
• 6. El-Daly, S.M., et al., miRs-134 and-370 function as tumor suppressors in colorectal cancer by independently suppressing EGFR and PI3K signalling. Scientific Reports, 2016. 6.
• 7. Bartel, D.P., Metazoan MicroRNAs. Cell, 2018. 173(1): p. 20-51.
• 8. Lagana, A., et al., Variability in the incidence of miRNAs and genes in fragile sites and the role of repeats and CpG islands in the distribution of genetic material. PLoS One, 2010. 5(6): p. e11166.
• 9. Grimwood, J., et al., The DNA sequence and biology of human chromosome 19. Nature, 2004. 428(6982): p. 529-35.
• 10. Starczynowski, D.T., et al., Genome-wide identification of human microRNAs located in leukemia-associated genomic alterations. Blood, 2011. 117(2): p. 595-607.
• 11. Garzon, R., et al., MicroRNA signatures associated with cytogenetics and prognosis in acute myeloid leukemia. Blood, 2008. 111(6): p. 3183-9.
• 12. Mi, S., et al., MicroRNA expression signatures accurately discriminate acute lymphoblastic leukemia from acute myeloid leukemia. Proc Natl Acad Sci U S A, 2007. 104(50): p. 19971-6.
• 13. Fayyad-Kazan, H., et al., Circulating miR-150 and miR-342 in plasma are novel potential biomarkers for acute myeloid leukemia. J Transl Med, 2013. 11: p. 31.
• 14. Lu, J., et al., MicroRNA expression profiles classify human cancers. Nature, 2005. 435(7043): p. 834-838. 15. Pulikkan, J.A., et al., Cell-cycle regulator E2F1 and microRNA-223 comprise an autoregulatory negative feedback loop in acute myeloid leukemia. Blood, 2010. 115(9): p. 1768-78.
• 16. Pulikkan, J.A., et al., C/EBP alpha regulated microRNA-34a targets E2F3 during granulopoiesis and is down-regulated in AML with CEBPA mutations. Blood, 2010. 116(25): p. 5638-5649. 17. Marcucci, G., et al., Clinical role of microRNAs in cytogenetically normal acute myeloid leukemia: miR-155 upregulation independently identifies high-risk patients. J Clin Oncol, 2013. 31(17): p. 2086-93.
• 18. Xiong, Q., et al., Characterization of miRNomes in acute and chronic myeloid leukemia cell lines. Genomics Proteomics Bioinformatics, 2014. 12(2): p. 79-91.
• 19. Polakova, K.M., et al., Expression patterns of microRNAs associated with CML phases and their disease related targets. Molecular Cancer, 2011. 10.
• 20. Mardani R, Jafari Najaf Abadi MH, Motieian M, Taghizadeh-Boroujeni S, Bayat A, Farsinezhad A, Gheibi Hayat SM, Motieian M, Pourghadamyari H. MicroRNA in leukemia: Tumor suppressors and oncogenes with prognostic potential. J Cell Physiol. 2019 Jun;234(6):8465-8486.
• 21. Szczepanek J. Role of microRNA dysregulation in childhood acute leukemias: Diagnostics, monitoring and therapeutics: A comprehensive review. World J Clin Oncol. 2020 Jun 24;11(6):348-369.
• 22. Jie Wang, Md. Nazim Uddin, Jian-ping Hao, Rong Chen, Yun-xia Xiang, Dai-qin Xiong, Yun Wu Identification of Potential Novel Prognosis-Related Genes Through Transcriptome Sequencing, Bioinformatics Analysis, and Clinical Validation in Acute Myeloid Leukemia. Front Genet. 2021; 12: 723001.
• 23. Yeh CH, Moles R, Nicot C. Clinical significance of microRNAs in chronic and acute human leukemia. Mol Cancer. 2016 May 14;15(1):37.
• 24. Zhou H, Jia X, Yang F, Shi P. miR-148a-3p suppresses the progression of acute myeloid leukemia via targeting cyclin-dependent kinase 6 (CDK6). Bioengineered. 2021 Dec;12(1):4508-4519.
• 25. Lin X, Ling Q, Lv Y, Ye W, Huang J, Li X, Guo Q, Wang J, Li Z, Jin J. Plasma exosome-derived microRNA-532 as a novel predictor for acute myeloid leukemia. Cancer Biomark. 2020;28(2):151-158.
• 26. Lin J, Ma JC, Yang J, Yin JY, Chen XX, Guo H, Wen XM, Zhang TJ, Qian W, Qian J, Deng ZQ. Arresting of miR-186 and releasing of H19 by DDX43 facilitate tumorigenesis and CML progression. Oncogene. 2018 May;37(18):2432-2443.