Categorizing Molecular Features of NOTCH4 Involved in Breast Cancer

Authors

  • Vinod P. Sinoorkar  PG Department of Bioinformatics, Walchand Centre for Biotechnology, Solapur, Maharashtra, India
  • Shrutika S. Pagul  PG Department of Bioinformatics, Walchand Centre for Biotechnology, Solapur, Maharashtra, India

DOI:

https://doi.org//10.32628/IJSRST196161

Keywords:

Cancer, Signal pathways, NOTCH, Drug target, Insilico.

Abstract

Breast cancer is one of the leading causes of cancer death in women. It is observed that hormonal, lifestyle and environmental factors that may increase the risk of breast cancer and often begins with cells in the milk-producing ducts (invasive ductal carcinoma), glandular tissue called lobules (invasive lobular carcinoma) or in other cells or tissue within the breast. The major signaling pathways involved in the breast cancer are Estrogen pathway, MAPK signaling pathway, PI3K/AKT signaling pathway, Notch signaling pathway, Wnt signaling pathway and P53 signaling pathway. Over the past decade, abnormal activation of Notch signaling in breast cancer has been stated by many different groups. In invasive breast cancer, the elevated expression of Notch signaling pathway components has been reported, including Jagged1-2, Dll1, Dll3, and Dll4, Notch receptor (Notch1 to Notch4). It is observed that increased JAG1-NOTCH4 signaling in human breast tumors is an important stimulator of cancer stem cells. The present investigation deals with the thorough understanding of molecular features of NOTCH4 protein emphasizing its key role in triggering the cancer pathway, by using different bioinformatics tools. The detailed insights into molecular features and the functional elements of NOTCH4 by analyzing its physicochemical parameters, secondary and tertiary structure prediction, domain analysis and intermolecular interactions, it can be considered as one of the potent drug target in breast cancer and can contribute to a novel alternate and promising treatment strategy for breast cancer through computer aided drug designing.

References

  1. J. Redig and S. S. McAllister. 2013. Breast cancer as a systemic disease: a view of metastasis, Journal of Internal Medicine, J Intern Med 2013; 274: 113–126.
  2. Emmanuel N. Kontomanolis , Sofia Kalagasidou, Stamatia Pouliliou, Xanthoula Anthoulaki, Nikolaos Georgiou, Valentinos Papamanolis, and Zacharias N. Fasoulakis. 2018. The Notch Pathway in Breast Cancer Progression, Scientific World Journal. 2018: 2415489, doi: 10.1155/2018/2415489.
  3. Rupen Shah, Kelly Rosso, S David Nathanson. 10 August 2014. Pathogenesis, prevention, diagnosis and treatment of breast cancer, World J Clin Oncol, 5(3): 283-298 ISSN 2218-4333, doi: 10.5306/wjco.v5.i3.283.
  4. Christy W. S. Tong, Mingxia Wu , William C. S. Cho and Kenneth K. W. 14 June 2018. Recent Advances in the Treatment of Breast Cancer, Front Oncol. 2018; 8: 227, doi: 10.3389/fonc.2018.00227.
  5. Ahmet AcarBruno M. SimõesRobert B. Clarke, and Keith Brennan. 20 Dec 2015. A Role for Notch Signalling in Breast Cancer and Endocrine Resistance, Stem Cell International, Volume 2016, Article ID 2498764.
  6. Rolf Apweiler, Amos Bairoch , Cathy H. Wu , Winona C. Barker , Brigitte Boeckmann , Serenella Ferro , Elisabeth Gasteiger , Hongzhan Huang , Rodrigo Lopez, Michele Magrane, Maria J. Martin, Darren A. Natale , Claire O'Donovan, Nicole Redaschi and Lai-Su L. Yeh. 2004. UniProt: the Universal Protein knowledgebase, Nucleic Acids Research, doi: 10.1093/nar/gkh131.
  7. Panu Artimo , Manohar Jonnalagedda, Konstantin Arnold, Delphine Baratin, Gabor Csardi, Edouard de Castro, Se verine Duvaud, Volker Flegel, Arnaud Fortier, Elisabeth Gasteiger, Aure lien Grosdidier, Ce line Hernandez, Vassilios Ioannidis, Dmitry Kuznetsov, Robin Liechti, Se bastien Moretti, Khaled Mostaguir, Nicole Redaschi, Gre goire Rossier, Ioannis Xenarios and Heinz Stockinger. 2012. ExPASy: SIB bioinformatics resource portal, Nucleic Acids Research, doi:10.1093/nar/gks400.
  8. Gasteiger E., Hoogland C., Gattiker A., Duvaud S., Wilkins M.R., Appel R.D., Bairoch A. 2005. Protein Identification and Analysis Tools on the ExPASy Server, (In) John M. Walker (ed): The Proteomics Protocols Handbook, Humana Press.
  9. C. Geourjon and G.Deleage. 1995. SOPMA: significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments, CABIOS.
  10. Torsten SchwedeJurgen Kopp, Nicolas Guex, and Manuel C. Peitsch. 1 Jul 2003. SWISS-MODEL: an automated protein homology-modeling server, Nucleic Acids Res.
  11. Laskowski R A, MacArthur M W, Moss D S, Thornton J M. 1993. PROCHECK - a program to check the stereochemical quality of protein structures. J. App. Cryst.
  12. Roger Sayle and Andrew Bisssell. 11 Nov 1993. RasMol: A Program for Fast Realistic Rendering of Molecular Structures with Shadows, Research Gate.
  13.  Franceschini A, Szklarczyk D, Frankild S, Kuhn M, Simonovic M, Roth A, Lin J, Minguez P, Bork P, von Mering C, Jensen L. J. 2013. STRING v9.1: protein-protein interaction networks, with increased coverage and integration Nucleic Acids Res. 41.
  14. Robert D. FinnJohn Tate, Jaina MistryPenny C. CoggillStephen John SammutHans-Rudolf Hotz, Goran CericKristoffer ForslundSean R. EddyErik L. L. Sonnhammer, and Alex Bateman. 2008. The Pfam protein families database, Nucleic Acid.

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Published

2019-02-28

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Section

Research Articles

How to Cite

[1]
Vinod P. Sinoorkar, Shrutika S. Pagul, " Categorizing Molecular Features of NOTCH4 Involved in Breast Cancer, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 6, Issue 1, pp.408-413, January-February-2019. Available at doi : https://doi.org/10.32628/IJSRST196161