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Dergiler / Turkish Journal of Biology / 2018 / Cilt: 42 - Sayı: 2

hsa-miR-301a- and SOX10-dependent miRNA-TF-mRNA regulatory circuits in breast cancer

Yasemin ÖZTEMUR ISLAKOĞLU
Senem NOYAN
Bala GÜR DEDEOĞLU
Sayfa
103–112
Yayın Tarihi
2022-10-17
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

It can be concluded that regulatorymotifs involving miRNAs and TFs may be useful for understanding breast cancer regulation and for predicting new biomarkers.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Breast cancer is the most common cancer among women and the molecular pathways that play main roles in breast cancerregulation are still not completely understood.
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Temel Bulgular & Veri:CircuitsDB2 analysis conducted with DE miRNAs and mRNAs resulted in 3 significant circuits that are SOX10- and hsamiR-301a-dependent.
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Sonuç & Katkı:It can be concluded that regulatorymotifs involving miRNAs and TFs may be useful for understanding breast cancer regulation and for predicting new biomarkers.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

Breast cancer is the most common cancer among women and the molecular pathways that play main roles in breast cancerregulation are still not completely understood. MicroRNAs (miRNAs) and transcription factors (TFs) are important regulators of geneexpression. It is important to unravel the relation of TFs, miRNAs, and their targets within regulatory networks to clarify the processesthat cause breast cancer and the progression of it. In this study, mRNA and miRNA expression studies including breast tumors andnormal samples were extracted from the GEO microarray database. Two independent mRNA studies and a miRNA study were selectedand reanalyzed. Differentially expressed (DE) mRNAs and miRNAs between breast tumor and normal samples were listed by using BRBArray Tools. CircuitsDB2 analysis conducted with DE miRNAs and mRNAs resulted in 3 significant circuits that are SOX10- and hsamiR-301a-dependent. The following significant circuits were characterized and validated bioinformatically by using web-based tools:SOX10→hsa-miR-301a→HOXA3, SOX10→hsa-miR-301a→KIT, and SOX10→hsa-miR-301a→NFIB. It can be concluded that regulatorymotifs involving miRNAs and TFs may be useful for understanding breast cancer regulation and for predicting new biomarkers.

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Bu Makaleye Atıf Yap

ISLAKOĞLU, Y. Ö., NOYAN, S., DEDEOĞLU, B. G. (2022). hsa-miR-301a- and SOX10-dependent miRNA-TF-mRNA regulatory circuits in breast cancer. Turkish Journal of Biology, Cilt: 42 - Sayı: 2, 103–112. https://ajindex.com/articles/600272

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Kaynakça (11)

  1. Calin GA, Dumitru CD, Shimizu M, Bichi R, Zupo S, Noch E, Aldler H, Rattan S, Keating M, Rai K et al (2002). Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. P Natl Acad Sci USA 99: 15524-15529.
  2. Edgar R, Domrachev M, Lash AE (2002). Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30: 207-210.
  3. Enerly E, Steinfeld I, Kleivi K, Leivonen SK, Aure MR, Russnes HG, Ronneberg JA, Johnsen H, Navon R, Rodland E et al (2011). miRNA-mRNA integrated analysis reveals roles for miRNAs in primary breast tumors. PLoS One 6: e16915. Friard O, Re A, Taverna D, De Bortoli M, Cora D (2010a). CircuitsDB: a database of mixed microRNA/transcription factor feed-forward regulatory circuits in human and mouse. BMC Bioinformatics 11: 435. Friard O, Re A, Taverna D, De Bortoli M, Corá D (2010b). CircuitsDB: a database of mixed microRNA/transcription factor feed-forward regulatory circuits in human and mouse. BMC Bioinformatics 11: 435. Iorio MV, Ferracin M, Liu CG, Veronese A, Spizzo R, Sabbioni S, Magri E, Pedriali M, Fabbri M, Campiglio M et al (2005). MicroRNA gene expression deregulation in human breast cancer. Cancer Res 65: 7065-7070.
  4. Jachetti E, Rigoni A, Bongiovanni L, Arioli I, Botti L, Parenza M, Cancila V, Chiodoni C, Festinese F, Bellone M et al (2017). Imatinib spares cKit-expressing prostate neuroendocrine tumors, whereas kills seminal vesicle epithelial–stromal tumors by targeting PDGFR-β. Mol Cancer Ther 16: 365-375.
  5. Joung JG, Fei Z (2009). Identification of microRNA regulatory modules in Arabidopsis via a probabilistic graphical model. Bioinformatics 25: 387-393.
  6. Joung JG, Hwang KB, Nam JW, Kim SJ, Zhang BT (2007). Discovery of microRNA-mRNA modules via population-based probabilistic learning. Bioinformatics 23: 1141-1147.
  7. Lagos-Quintana M, Rauhut R, Lendeckel W, Tuschl T (2001). Identification of novel genes coding for small expressed RNAs. Science 294: 853-858.
  8. Latchman S (1997). Transcription factors: an overview. Int J Biochem Cell Biol 2725: 1305-1312.
  9. Lee CH, Kuo WH, Lin CC, Oyang YJ, Huang HC, Juan HF (2013). MicroRNA-regulated protein-protein interaction networks and their functions in breast cancer. Int J Mol Sci 14: 11560-11606.
  10. Lee RC, Ambros V (2001). An extensive class of small RNAs in Caenorhabditis elegans. Science 294: 862-864.
  11. Lowery AJ, Miller N, Devaney A, McNeill RE, Davoren PA, Lemetre C, Benes V, Schmidt S, Blake J, Ball G