DIFFERENTIAL EXPRESSION ANALYSIS OF KRUPPEL LIKE FACTORS 6 AND ANTAGONISTIC EFFECT STUDY OF CINNAMIC ACID - AN IN SILICO APPROACH
Objective: Krüppel-like factor 6 (KLF6) is the significant member of a DNA binding proteins which mainly involved in the transcriptional regulation as well various promising cellular processes such as cell proliferation and differentiation, cytokine signal-based inflammatory responses, and pluripotency activity of cells. Our computational studies involve KLF6 differential expression in breast cancer tissues based on web resources such as Oncomine and cBioportal.
Methods: Oncomine and TCGA data-based CBioportal were the databases used to explore the KLF6 expression, and KLF6 was underexpressed in many of the breast cancer tissues than normal breast tissues. Major breast cancer datasets such as Curtis and TCGA supported the clinical-pathological role of KLF6, mutational frequencies. Further prognosis analysis was carried out using Survexpress and it revealed the survival rate and risk group categorization. Thus, KLF6 was considered as a therapeutic target and natural compound cinnamic acid antagonistic efficacy was analyzed based on molecular docking and simulation studies.
Results: Systematic analysis of KLF6 gene expression in breast cancer would be helpful in exploring aspects of KLF6 as the potential drug target as well as prognostic disease marker identification. Molecular docking and dynamic study were carried out to evaluate the intermolecular interaction between the cinnamic acid and KLF6 and the docked complex stability after 5ns.
Conclusion: Thus, the computational study demonstrated the cinnamic acid role as an anticancer compound to combat the overexpression of KLF6 to combat cancer. Further, in vitro and in vivo studies need to be carried out to know the insights of antagonistic effect.
2. Kaczynski J, Cook T, Urrutia R. Sp1-and krüppel-like transcription factors. Genome Biol 2003;4:206.
3. Yamanaka S. Strategies and new developments in the generation of patient-specific pluripotent stem cells. Cell Stem Cell 2007;1:39-49.
4. Yang Y, Nakagawa H, Tetreault MP, Billig J, Victor N, Goyal A, et al. Loss of transcription factor KLF5 in the context of p53 ablation drives invasive progression of human squamous cell cancer. Cancer Res 2011;71:6475-84.
5. Narla G, Heath KE, Reeves HL, Li D, Giono LE, Kimmelman AC, et al. KLF6, a candidate tumor suppressor gene mutated in prostate cancer. Science 2001;294:2563-6.
6. DiFeo A, Narla G, Hirshfeld J, Camacho-Vanegas O, Narla J, Rose SL, et al. Roles of KLF6 and KLF6-SV1 in ovarian cancer progression and intraperitoneal dissemination. Clin Cancer Res 2006;12:3730-9.
7. Teixeira MS, Camacho-Vanegas O, Fernandez Y, Narla G, DiFeo A, Lee B, et al. KLF6 allelic loss is associated with tumor recurrence and markedly decreased survival in head and neck squamous cell carcinoma. Int J Cancer 2007;121:1976-83.
8. Benzeno S, Narla G, Allina J, Cheng GZ, Reeves HL, Banck MS, et al. Cyclin-dependent kinase inhibition by the KLF6 tumor suppressor protein through interaction with cyclin D1. Cancer Res 2004;64:3885-91.
9. Miyaki M, Yamaguchi T, Iijima T, Funata N, Mori T. Difference in the role of loss of heterozygosity at 10p15 (KLF6 locus) in colorectal carcinogenesis between sporadic and familial adenomatous polyposis and hereditary nonpolyposis colorectal cancer patients. Oncology 2006;71:131-5.
10. Sirach E, Bureau C, Péron JM, Pradayrol L, Vinel JP, Buscail L, et al. KLF6 transcription factor protects hepatocellular carcinoma-derived cells from apoptosis. Cell Death Differ 2007;14:1202-10.
11. Slavin DA, Koritschoner NP, Prieto CC, López-Díaz FJ, Chatton B, Bocco JL, et al. A new role for the kruppel-like transcription factor KLF6 as an inhibitor of c-jun proto-oncoprotein function. Oncogene 2004;23:8196-205.
12. Liu J, Du T, Yuan Y, He Y, Tan Z, Liu Z, et al. KLF6 inhibits estrogen receptor-mediated cell growth in breast cancer via a c-src-mediated pathway. Mol Cell Biochem 2010;335:29-35.
13. Gehrau RC, D’Astolfo DS, Dumur CI, Bocco JL, Koritschoner NP. Nuclear expression of KLF6 tumor suppressor factor is highly associated with overexpression of ERBB2 oncoprotein in ductal breast carcinomas. PLoS One 2010;5:e8929.
14. Paul S, Kundu R. Induction of apoptosis by fatty acid rich fraction of Solanum nigrum on cervical cancer cell lines. Int J Pharm Pharm Sci 2017;9:199-206.
15. Hoskins JA. The occurrence, metabolism and toxicity of cinnamic acid and related compounds. J Appl Toxicol 1984;4:283-92.
16. Kroon PA, Williamson G. Hydroxycinnamates in plants and food. J Sci Food Agric 1999;79:355-61.
17. Ahn BZ, Sok DE. Michael acceptors as a tool for anticancer drug design. Curr Pharm Design 1996;2:247-62.
18. Zou HB, Dong SY, Zhou CX, Hu LH, Wu YH, Li HB, et al. Design, synthesis, and SAR analysis of cytotoxic sinapyl alcohol derivatives. Bioorg Med Chem 2006;14:2060-71.
19. Su P, Shi Y, Wang J, Shen X, Zhang J. Anticancer agents derived from natural cinnamic acids. Anticancer Agents Med Chem 2015;15:980-7.
20. Rhodes DR, Yu J, Shanker K, Deshpande N, Varambally R, Ghosh D, et al. ONCOMINE: A cancer microarray database and integrated data-mining platform. Neoplasia 2004;6:1-6.
21. Dalman MR, Deeter A, Nimishakavi G, Duan ZH. Fold change and p-value cutoffs significantly alter microarray interpretations. BMC Bioinformatics 2012;13 Suppl 2:S11.
22. McCarthy DJ, Smyth GK. Testing significance relative to a fold-change threshold is a TREAT. Bioinformatics 2009;25:765-71.
23. Christy HJ, Priyadharshini L. Differential expression analysis of JAK/STAT pathway related genes in breast cancer. Meta Gene 2018;16:122-9.
24. Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, et al. The cBio cancer genomics portal: An open platform for exploring multidimensional cancer genomics data. Cancer Discov 2012;2:401-4.
25. Xia J, Gill EE, Hancock RE. NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data. Nat Protoc 2015;10:823-44.
26. Aguirre-Gamboa R, Gomez-Rueda H, Martínez-Ledesma E, Martínez-Torteya A, Chacolla-Huaringa R, Rodriguez-Barrientos A, et al. SurvExpress: An online biomarker validation tool and database for cancer gene expression data using survival analysis. PLoS One 2013;8:e74250.
27. Eswar N, Webb B, Marti-Renom MA, Madhusudhan MS, Eramian D, Shen MY, et al. Comparative protein structure modeling using MODELLER. Curr Protoc Protein Sci 2007;50:0209s50.
28. Eswar N, Webb B, Marti-Renom MA, Madhusudhan MS, Eramian D, Shen MY, et al. Comparative protein structure modeling using modeller. Curr Protoc Bioinformatics 2006;Chapter 5:Unit-5.6.
29. Kim S, Chen J, Cheng T, Gindulyte A, He J, He S, et al. PubChem 2019 update: Improved access to chemical data. Nucleic Acids Res 2019;47:D1102-D1109.
30. Daina A, Michielin O, Zoete V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep 2017;7:42717.
31. Christy J. Computational analysis of disease associated nssnps in mmp2. Int J Pharm Bio Sci 2013;4:504-12.
32. Christy HJ, Preethi B. Analyzing the effect of nssnps in cyp1a1 towards benzothiazoles binding. Int J Pharm Pharm Sci 2014;6:552-7.
33. Krammer A, Kirchhoff PD, Jiang X, Venkatachalam CM, Waldman M. LigScore: A novel scoring function for predicting binding affinities. J Mol Graph Model 2005;23:395-407.
34. Swift RV, Jusoh SA, Offutt TL, Li ES, Amaro RE. Knowledge-based methods to train and optimize virtual screening ensembles. J Chem Inf Model 2016;56:830-42.
35. Epifano F, Curini M, Genovese S, Blaskovich M, Hamilton A, Sebti SM. Prenyloxy phenyl propanoids as novel lead compounds for the selective inhibition of geranylgeranyl transferase I. Bioorg Med Chem Lett 2007;17:2639-42.
36. Brooks B, Bruccoleri R, Olafson B, States DJ, Swaminathan S, Karplus M. CHARMM: A program for macromolecular energy, minimization, and dynamics calculations. J Comput Chem 1983;4:187-217.
37. Mortier J, Rakers C, Bermudez M, Murgueitio MS, Riniker S, Wolber G, et al. The impact of molecular dynamics on drug design: Applications for the characterization of ligand-macromolecule complexes. Drug Discov Today 2015;20:686-702.
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