Predicting sulforaphane-induces adverse effects in prostatic cancer patients via in silico investigation

Abstract

Prostate cancer is a major cause of death in men. Traditional therapies have limited efficacy, leading to the increased interest in phytochemicals like sulforaphane (SFN), found in cruciferous vegetables. Literature data indicate numerous beneficial effects of SFN as an antioxidant, immunomodulator and antitumor agent, but the toxicity and thus safety of its use has not been sufficiently investigated. Also, SFN may selectively accumulate in prostate tissue. The aim of this work was to predict the positive and negative influence of SFN on gene expression in patients with prostate cancer by conducting in silico analysis. Publicly available database, Gene expression omnibus (GEO, https://www. ncbi.nlm.nih.gov/geo/) was used to obtain gene profiles of malignantly changed tissues and healthy tissues and then analyzed with GEO2R tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/) which identify differentially expressed genes between tumor and healthy tissue. Interactivenn tool (http://www.interactivenn.net/) helped with obtaining sets of genes that are consistently up- and down-regulated in prostate cancer. Toppgene tool (https://toppgene.cchmc.org/) was used to explore the role of the selected genes in gene ontology processes that could affect cancer progression, while GeneMania (https://genemania.org/) determined genes related to the set of genes and the type of interaction between all of them. To determine whether SFN has an effect on selected sets of genes, the Comparative Toxicogenomic Database (CTD, http://ctdbase.org/) was used. In prostate cancer, a total of 13 genes were consistently down-regulated, and 37 genes up-regulated. Down- regulated genes are involved in molecular functions, biological processes and pathways of muscle contraction and channel and enzyme functions, while up-regulated genes regulate processes at the level of the kidneys and the renin-angiotensin-aldosterone system. Network analysis showed that the type of interaction that dominated between downstream or upstream regulated genes and their related genes, was co-expression. Finally, SFN interacted with 21 dysregulated genes and reduced the expression of ERG and TMEFF2, while increased the expression of GSTM3, ACTG2 and CNN1 genes which can lead to positive effects such as improving antioxidant protection, suppressing expansion of tumor tissue and risk of developing bone metastases. In addition, SFN could contribute to the development of prostate cancer, by interacting with the genes already expressed in the tumor tissue. The conducted study indicates that the genomic signature of patients suffering from prostate cancer could be an important factor which determines the benefits and risks of SFN as an adjunctive therapy. It could be suggested that prostate cancer patients with increased expression of ABCC4 and ENTPD5 and decreased expression of MAMDC2, MYLK, PGM5, PPP1R3C and SYNM might not be the best candidates for SFN administration. (Serbia-China project: 451-03-1203/2021-09)