1st International Conference on Chemo and BioInformatics, ICCBIKG 2021, (470-473)
AUTHOR(S) / АУТОР(И): Dragica Božić, Katarina Živančević, Katarina Baralić, Dragana Javorac, Aleksandra Buha Đorđević, Evica Antonijević Miljaković, Đurđica Marić, Marijana Ćurčić, Zorica Bulat, Biljana Antonijević, Danijela Đukić-Ćosić
E-ADRESS / Е-АДРЕСА: firstname.lastname@example.org
ABSTRACT / САЖЕТАК:
The aim of this study was to predict the molecular mechanisms and pathways of immunomodulator sulforaphane (SFN) against carcinoma using in silico toxicogenomic data mining. Three key tools applied in our analysis were Comparative Toxicogenomics Database (CTD; http://CTD.mdibl. org), ToppGene Suite portal (https://toppgene.cchmc.org) and Reactome Knowledgebase (https://reactome.org). Sulforaphane interacted with a total of 1896, among which NFE2L2, NQO1, HMOX1, GCLC, TXNRD1, IL1B, IFNG, AGT, KEAP1, and CASP3 had the highest number of interactions. In the CTD, there were direct evidences that SFN interacts with a total of 169 genes to express a therapeutic effect against different types of cancer such as: hepatocellular carcinoma (113), colorectal neoplasms (67), uterine cervical neoplasms (10), and adenomatous polyposis coli (4). This set of genes was further uploaded into the Gene Mania software, ToppGene Suite portal, and Reactome Knowledgebase, which confirmed that molecular functions, biological processes and pathways of SFN-affected genes were mostly related to oxidoreductase activity, regulation of immune system, and apoptosis. In conclusion, we may suggest that SFN interacts with host immunity to enhance the eradication of tumor cells mainly by inducing immune-response and stimulating apoptotic process of tumor cells. Moreover, its antioxidative activity could contribute to better anti-cancerogenic effects.
KEY WORDS / КЉУЧНЕ РЕЧИ:
bioinformatics, carcinoma, sulforaphane, data mining, toxicogenomics
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