Conducting bioinformatics analysis to predict sulforaphane-triggered adverse outcome pathways in healthy human cells
Authors
Božić, Dragica
Živančević, Katarina

Baralić, Katarina

Antonijević-Miljaković, Evica

Buha-Đorđević, Aleksandra

Ćurčić, Marijana

Bulat, Zorica

Antonijević, Biljana

Đukić-Ćosić, Danijela

Article (Published version)
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Sulforaphane (SFN) is a naturally occurring molecule present in plants from Brassica family. It becomes bioactive after hydrolytic reaction mediated by myrosinase or human gastrointestinal microbiota. Sulforaphane gained scientific popularity due to its antioxidant and anti-cancer properties. However, its toxicity profile and potential to cause adverse effects remain largely unidentified. Thus, this study aimed to generate SFN-triggered adverse outcome pathway (AOP) by looking at the relationship between SFN-chemical structure and its toxicity, as well as SFN-gene interactions. Quantitative structure-activity relationship (QSAR) analysis identified 2 toxophores (Derek Nexus software) that have the potential to cause chromosomal damage and skin sensitization in mammals or mutagenicity in bacteria. Data extracted from Comparative Toxicogenomics Database (CTD) linked SFN with previously proposed outcomes via gene interactions. The total of 11 and 146 genes connected SFN with chromosomal d...amage and skin diseases, respectively. However, network analysis (NetworkAnalyst tool) revealed that these genes function in wider networks containing 490 and 1986 nodes, respectively. The over-representation analysis (ExpressAnalyst tool) pointed out crucial biological pathways regulated by SFN-interfering genes. These pathways are uploaded to AOP-helpFinder tool which found the 2321 connections between 19 enriched pathways and SFN which were further considered as key events. Two major, interconnected AOPs were generated: first starting from disruption of biological pathways involved in cell cycle and cell proliferation leading to increased apoptosis, and the second one connecting activated immune system signaling pathways to inflammation and apoptosis. In both cases, chromosomal damage and/or skin diseases such as dermatitis or psoriasis appear as adverse outcomes.
Keywords:
Adverse outcome pathway / Chromosomal damage / Skin diseases / Sulforaphane / Toxicology systems approachSource:
Biomedicine and Pharmacotherapy, 2023, 160Publisher:
- Elsevier Masson s.r.l.
Funding / projects:
- The Ministry of Education, Science and Technological Development of the Republic of Serbia, in the framework of scientific cooperation with the People’s Republic of China (451-03-1203/2021-09)
- The State’s Key Project of Research and Development Plan of the People’s Republic of China (No. 2021YFE0110600)
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PharmacyTY - JOUR AU - Božić, Dragica AU - Živančević, Katarina AU - Baralić, Katarina AU - Antonijević-Miljaković, Evica AU - Buha-Đorđević, Aleksandra AU - Ćurčić, Marijana AU - Bulat, Zorica AU - Antonijević, Biljana AU - Đukić-Ćosić, Danijela PY - 2023 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4425 AB - Sulforaphane (SFN) is a naturally occurring molecule present in plants from Brassica family. It becomes bioactive after hydrolytic reaction mediated by myrosinase or human gastrointestinal microbiota. Sulforaphane gained scientific popularity due to its antioxidant and anti-cancer properties. However, its toxicity profile and potential to cause adverse effects remain largely unidentified. Thus, this study aimed to generate SFN-triggered adverse outcome pathway (AOP) by looking at the relationship between SFN-chemical structure and its toxicity, as well as SFN-gene interactions. Quantitative structure-activity relationship (QSAR) analysis identified 2 toxophores (Derek Nexus software) that have the potential to cause chromosomal damage and skin sensitization in mammals or mutagenicity in bacteria. Data extracted from Comparative Toxicogenomics Database (CTD) linked SFN with previously proposed outcomes via gene interactions. The total of 11 and 146 genes connected SFN with chromosomal damage and skin diseases, respectively. However, network analysis (NetworkAnalyst tool) revealed that these genes function in wider networks containing 490 and 1986 nodes, respectively. The over-representation analysis (ExpressAnalyst tool) pointed out crucial biological pathways regulated by SFN-interfering genes. These pathways are uploaded to AOP-helpFinder tool which found the 2321 connections between 19 enriched pathways and SFN which were further considered as key events. Two major, interconnected AOPs were generated: first starting from disruption of biological pathways involved in cell cycle and cell proliferation leading to increased apoptosis, and the second one connecting activated immune system signaling pathways to inflammation and apoptosis. In both cases, chromosomal damage and/or skin diseases such as dermatitis or psoriasis appear as adverse outcomes. PB - Elsevier Masson s.r.l. T2 - Biomedicine and Pharmacotherapy T1 - Conducting bioinformatics analysis to predict sulforaphane-triggered adverse outcome pathways in healthy human cells VL - 160 DO - 10.1016/j.biopha.2023.114316 ER -
@article{ author = "Božić, Dragica and Živančević, Katarina and Baralić, Katarina and Antonijević-Miljaković, Evica and Buha-Đorđević, Aleksandra and Ćurčić, Marijana and Bulat, Zorica and Antonijević, Biljana and Đukić-Ćosić, Danijela", year = "2023", abstract = "Sulforaphane (SFN) is a naturally occurring molecule present in plants from Brassica family. It becomes bioactive after hydrolytic reaction mediated by myrosinase or human gastrointestinal microbiota. Sulforaphane gained scientific popularity due to its antioxidant and anti-cancer properties. However, its toxicity profile and potential to cause adverse effects remain largely unidentified. Thus, this study aimed to generate SFN-triggered adverse outcome pathway (AOP) by looking at the relationship between SFN-chemical structure and its toxicity, as well as SFN-gene interactions. Quantitative structure-activity relationship (QSAR) analysis identified 2 toxophores (Derek Nexus software) that have the potential to cause chromosomal damage and skin sensitization in mammals or mutagenicity in bacteria. Data extracted from Comparative Toxicogenomics Database (CTD) linked SFN with previously proposed outcomes via gene interactions. The total of 11 and 146 genes connected SFN with chromosomal damage and skin diseases, respectively. However, network analysis (NetworkAnalyst tool) revealed that these genes function in wider networks containing 490 and 1986 nodes, respectively. The over-representation analysis (ExpressAnalyst tool) pointed out crucial biological pathways regulated by SFN-interfering genes. These pathways are uploaded to AOP-helpFinder tool which found the 2321 connections between 19 enriched pathways and SFN which were further considered as key events. Two major, interconnected AOPs were generated: first starting from disruption of biological pathways involved in cell cycle and cell proliferation leading to increased apoptosis, and the second one connecting activated immune system signaling pathways to inflammation and apoptosis. In both cases, chromosomal damage and/or skin diseases such as dermatitis or psoriasis appear as adverse outcomes.", publisher = "Elsevier Masson s.r.l.", journal = "Biomedicine and Pharmacotherapy", title = "Conducting bioinformatics analysis to predict sulforaphane-triggered adverse outcome pathways in healthy human cells", volume = "160", doi = "10.1016/j.biopha.2023.114316" }
Božić, D., Živančević, K., Baralić, K., Antonijević-Miljaković, E., Buha-Đorđević, A., Ćurčić, M., Bulat, Z., Antonijević, B.,& Đukić-Ćosić, D.. (2023). Conducting bioinformatics analysis to predict sulforaphane-triggered adverse outcome pathways in healthy human cells. in Biomedicine and Pharmacotherapy Elsevier Masson s.r.l.., 160. https://doi.org/10.1016/j.biopha.2023.114316
Božić D, Živančević K, Baralić K, Antonijević-Miljaković E, Buha-Đorđević A, Ćurčić M, Bulat Z, Antonijević B, Đukić-Ćosić D. Conducting bioinformatics analysis to predict sulforaphane-triggered adverse outcome pathways in healthy human cells. in Biomedicine and Pharmacotherapy. 2023;160. doi:10.1016/j.biopha.2023.114316 .
Božić, Dragica, Živančević, Katarina, Baralić, Katarina, Antonijević-Miljaković, Evica, Buha-Đorđević, Aleksandra, Ćurčić, Marijana, Bulat, Zorica, Antonijević, Biljana, Đukić-Ćosić, Danijela, "Conducting bioinformatics analysis to predict sulforaphane-triggered adverse outcome pathways in healthy human cells" in Biomedicine and Pharmacotherapy, 160 (2023), https://doi.org/10.1016/j.biopha.2023.114316 . .