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http://dx.doi.org/10.4014/jmb.2207.07037

Identification and Validation of Novel Biomarkers and Potential Targeted Drugs in Cholangiocarcinoma: Bioinformatics, Virtual Screening, and Biological Evaluation  

Wang, Jiena (Department of Pharmacy, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University)
Zhu, Weiwei (Department of Pharmacy, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University)
Tu, Junxue (Department of Pharmacy, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University)
Zheng, Yihui (Department of Pharmacy, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University)
Publication Information
Journal of Microbiology and Biotechnology / v.32, no.10, 2022 , pp. 1262-1274 More about this Journal
Abstract
Cholangiocarcinoma (CCA) is a complex and refractor type of cancer with global prevalence. Several barriers remain in CCA diagnosis, treatment, and prognosis. Therefore, exploring more biomarkers and therapeutic drugs for CCA management is necessary. CCA gene expression data was downloaded from the TCGA and GEO databases. KEGG enrichment, GO analysis, and protein-protein interaction network were used for hub gene identification. miRNA were predicted using Targetscan and validated according to several GEO databases. The relative RNA and miRNA expression levels and prognostic information were obtained from the GEPIA. The candidate drug was screened using pharmacophore-based virtual screening and validated by molecular modeling and through several in vitro studies. 301 differentially expressed genes (DEGs) were screened out. Complement and coagulation cascades-related genes (including AHSG, F2, TTR, and KNG1), and cell cycle-related genes (including CDK1, CCNB1, and KIAA0101) were considered as the hub genes in CCA progression. AHSG, F2, TTR, and KNG1 were found to be significantly decreased and the eight predicted miRNA targeting AHSG, F2, and TTR were increased in CCA patients. CDK1, CCNB1, and KIAA0101 were found to be significantly abundant in CCA patients. In addition, Molport-003-703-800, which is a compound that is derived from pharmacophores-based virtual screening, could directly bind to CDK1 and exhibited anti-tumor activity in cholangiocarcinoma cells. AHSG, F2, TTR, and KNG1 could be novel biomarkers for CCA. Molport-003-703-800 targets CDK1 and work as potential cell cycle inhibitors, thereby having potential for consideration for new chemotherapeutics for CCA.
Keywords
Cholangiocarcinoma; miRNA; CDK1; virtual screening; molecular modeling;
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1 Peyrou M, Cereijo R, Quesada-Lopez T, Campderros L, Gavalda-Navarro A, Linares-Pose L, et al. 2020. The kallikrein-kinin pathway as a mechanism for auto-control of brown adipose tissue activity. Nat. Commun. 11: 2132.   DOI
2 Feinstein DI. 2015. Disseminated intravascular coagulation in patients with solid tumors. Oncology (Williston Park) 29: 96-102.
3 Chen D, Wu H, He B, Lu Y, Wu W, Liu H, et al. 2019. Five hub genes can be the potential DNA methylation biomarkers for cholangiocarcinoma using bioinformatics analysis. Onco Targets Ther. 12: 8355-8365.   DOI
4 De March M, Barrera-Vilarmau S, Crespan E, Mentegari E, Merino N, Gonzalez-Magana A, et al. 2018. p15PAF binding to PCNA modulates the DNA sliding surface. Nucleic Acids Res. 46: 9816-9828.   DOI
5 Kommalapati A, Tella SH, Borad M, Javle M, Mahipal A. 2021. FGFR inhibitors in oncology: Insight on the management of toxicities in clinical practice. Cancers (Basel) 13: 2968.   DOI
6 Strzalka W, Ziemienowicz A. 2011. Proliferating cell nuclear antigen (PCNA): a key factor in DNA replication and cell cycle regulation. Ann. Bot. 107: 1127-1140.   DOI
7 Khan SA, Tavolari S, Brandi G. 2019. Cholangiocarcinoma: Epidemiology and risk factors. Liver Int. 39 Suppl 1: 19-31.   DOI
8 Blechacz B. 2017. Cholangiocarcinoma: Current knowledge and new developments. Gut Liver 11: 13-26.   DOI
9 Zamolodchikov D, Duffield M, Macdonald LE, Alessandri-Haber N. 2022. Accumulation of high molecular weight kininogen in the brains of Alzheimer's disease patients may affect microglial function by altering phagocytosis and lysosomal cathepsin activity. Alzheimers Dement. 18: 1919-1929.   DOI
10 Ding L, Cao J, Lin W, Chen H, Xiong X, Ao H, et al. 2020. The roles of cyclin-dependent kinases in cell-cycle progression and therapeutic strategies in human breast cancer. Int. J. Mol. Sci. 21: 1960.   DOI
11 Coelho R, Silva M, Rodrigues-Pinto E, Cardoso H, Lopes S, Pereira P, et al. 2017. CA 19-9 as a marker of survival and a predictor of metastization in cholangiocarcinoma. GE Port. J. Gastroenterol. 24: 114-121.   DOI
12 Hanahan D, Weinberg RA. 2011. Hallmarks of cancer: the next generation. Cell 144: 646-674.   DOI
13 Roskoski R, Jr. 2019. Cyclin-dependent protein serine/threonine kinase inhibitors as anticancer drugs. Pharmacol. Res. 139: 471-488.   DOI
14 Rodrigues PM, Olaizola P, Paiva NA, Olaizola I, Agirre-Lizaso A, Landa A, et al. 2021. Pathogenesis of cholangiocarcinoma. Annu. Rev. Pathol. 16: 433-463.   DOI
15 Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, et al. 2017. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res. 45: D362-D368.   DOI
16 Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z. 2017. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 45: W98-W102.   DOI
17 Sunseri J, Koes DR. 2016. Pharmit: interactive exploration of chemical space. Nucleic Acids Res. 44: W442-448.   DOI
18 Cardinale V, Bragazzi MC, Carpino G, Torrice A, Fraveto A, Gentile R, et al. 2013. Cholangiocarcinoma: increasing burden of classifications. Hepatobiliary Surg. Nutr. 2: 272-280.
19 Valle JW, Kelley RK, Nervi B, Oh DY, Zhu AX. 2021. Biliary tract cancer. Lancet 397: 428-444.   DOI
20 Gigante E, Paradis V, Ronot M, Cauchy F, Soubrane O, Ganne-Carrie N, et al. 2021. New insights into the pathophysiology and clinical care of rare primary liver cancers. JHEP Rep. 3: 100174.   DOI
21 Rizvi S, Khan SA, Hallemeier CL, Kelley RK, Gores GJ. 2018. Cholangiocarcinoma - evolving concepts and therapeutic strategies. Nat. Rev. Clin. Oncol. 15: 95-111.   DOI
22 Banales JM, Marin JJG, Lamarca A, Rodrigues PM, Khan SA, Roberts LR, et al. 2020. Cholangiocarcinoma 2020: the next horizon in mechanisms and management. Nat. Rev. Gastroenterol. Hepatol. 17: 557-588.   DOI
23 Lee YT, Tan YJ, Oon CE. 2018. Molecular targeted therapy: Treating cancer with specificity. Eur. J. Pharmacol. 834: 188-196.   DOI
24 Alamri MA, Alamri MA. 2019. Pharmacophore and docking-based sequential virtual screening for the identification of novel Sigma 1 receptor ligands. Bioinformation 15: 586-595.   DOI
25 Bayat A. 2002. Science, medicine, and the future: Bioinformatics. BMJ 324: 1018-1022.   DOI
26 Pereira CA, Saye M, Reigada C, Silber AM, Labadie GR, Miranda MR, et al. 2020. Computational approaches for drug discovery against trypanosomatid-caused diseases. Parasitology 147: 611-633.   DOI
27 Manzoni C, Kia DA, Vandrovcova J, Hardy J, Wood NW, Lewis PA, et al. 2018. Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences. Brief. Bioinform. 19: 286-302.   DOI
28 Palta S, Saroa R, Palta A. 2014. Overview of the coagulation system. Indian J. Anaesth. 58: 515-523.   DOI
29 Iqbal D, Rehman MT, Bin Dukhyil A, Rizvi SMD, Al Ajmi MF, Alshehri BM, et al. 2021. High-throughput screening and molecular dynamics simulation of natural product-like compounds against Alzheimer's disease through multitarget approach. Pharmaceuticals (Basel) 14: 937.   DOI
30 Batool M, Ahmad B, Choi S. 2019. A structure-based drug discovery paradigm. Int. J. Mol. Sci. 20: 2783.   DOI
31 Chen Z, Li HL, Zhang QJ, Bao XG, Yu KQ, Luo XM, et al. 2009. Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets. Acta Pharmacol. Sin. 30: 1694-1708.   DOI
32 Clough E, Barrett T. 2016. The gene expression omnibus database. Methods Mol. Biol. 1418: 93-110.   DOI
33 Wang Z, Jensen MA, Zenklusen JC. 2016. A practical guide to the cancer genome atlas (TCGA). Methods Mol. Biol. 1418: 111-141.   DOI
34 Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. 2015. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43: e47.   DOI
35 Robinson MD, McCarthy DJ, Smyth GK. 2010. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26: 139-140.   DOI
36 Agarwal V, Bell GW, Nam JW, Bartel DP. 2015. Predicting effective microRNA target sites in mammalian mRNAs. Elife 4: e05005.   DOI
37 Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, et al. 2013. NCBI GEO: archive for functional genomics data sets-update. Nucleic Acids Res. 41: D991-995.
38 Huang da W, Sherman BT, Lempicki RA. 2009. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4: 44-57.   DOI
39 Su G, Morris JH, Demchak B, Bader GD. 2014. Biological network exploration with Cytoscape 3. Curr. Protoc. Bioinformatics 47: 8.13-1-24.
40 Chin CH, Chen SH, Wu HH, Ho CW, Ko MT, Lin CY. 2014. cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst. Biol. 8 Suppl 4: S11.   DOI
41 Wong NW, Chen Y, Chen S, Wang X. 2018. OncomiR: an online resource for exploring pan-cancer microRNA dysregulation. Bioinformatics 34: 713-715.   DOI
42 Wood DJ, Korolchuk S, Tatum NJ, Wang LZ, Endicott JA, Noble MEM, et al. 2019. Differences in the conformational energy landscape of CDK1 and CDK2 suggest a mechanism for achieving selective CDK inhibition. Cell. Chem. Biol. 26: 121-130 e125.   DOI
43 Molvarec A, Kalabay L, Derzsy Z, Szarka A, Halmos A, Stenczer B, et al. 2009. Preeclampsia is associated with decreased serum alpha(2)-HS glycoprotein (fetuin-A) concentration. Hypertens. Res. 32: 665-669.   DOI
44 Wieczorek E, Ozyhar A. 2021. Transthyretin: from structural stability to osteoarticular and cardiovascular diseases. Cells 10: 1768.   DOI