Unraveling the Anticancer Potential of SSRIs in Prostate Cancer by Combining Computational Systems Biology and In Vitro Analyses

Abstract

Selective serotonin reuptake inhibitors (SSRIs) are known to have anticancer activity against different types of cancer. In this study, an integrative informatics approach was applied to identify compound and genetic perturbations that produce similar effects to SSRIs to formulate systems biology hypotheses and identify biological pathways involved in the putative anticancer effects of SSRIs in prostate cancer. An 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay assessed the antiproliferative effects of SSRIs and drug combinations. Cell death mechanisms were studied using annexin V-FITC/PI staining, and the cell cycle analysis was carried out by counterstaining with propidium iodide. Relative gene expression was assessed using a real-time polymerase chain reaction (PCR). Computational results hypothesized that SSRIs could potentially exert anticancer effects in prostate cancer cell lines by modulating apoptotic and tumorigenesis pathways and significantly inhibiting the growth of prostate cancer cells in a time and concentration-dependent manner. The combination of SSRIs with cisplatin, 5-fluorouracil, and raloxifene resulted in either synergistic or additive effects. SSRIs resulted in a significant increase in the early and late apoptotic activity in PC3 cells. Dapoxetine, paroxetine, and sertraline resulted in cell cycle arrest at the G0/G1 phase. Treatment with either dapoxetine or paroxetine decreases the expression of Bcl-2, CASP8, DR5, and VEGF. At the same time, sertraline decreases the expression of Bcl-2 and VEGF and increases the expression of CASP8 and DR5. Results revealed that SSRIs can potentially act as antiproliferative agents against prostate cancer cells, and their activity is mediated through different signaling pathways.

Figure 1

Integrative Computational Systems Biology and Experimental Validation Workflow for Assessing the Anticancer Activities of SSRIs.

Figure 2

Chemical structures of SSRIs used in both experimental and computational studies. The two compounds denoted by asterisks and surrounded by a dotted rectangle have been included in the computational studies only.

Figure 3

Compound and genetic connections with SSRIs. A. Compound connections. B. Genetic connections including knockdown and overexpression. The predicted connections are found in the “name” column.

Figure 4

Effect of SSRIs on PC3 and DU-145 cell migration. The data shown represents the percentage of wound closure after 24 h of treatment duration. P-value <0.05 indicates statistical significance in comparison to the untreated sample. While asterisk: ns (not-significant) P > 0.05; * P ≤ 0.05; ** P ≤ 0.01; *** P ≤ 0.001; **** P ≤ 0.0001 (according to GraphPad prism 9).

Figure 5

Effect of SSRIs on PC3 mean colony number and size using colony formation assay. The experiment was performed in duplicate and repeated in two independent trials. P-value <0.05 indicates statistical significance in comparison to the untreated cells. While asterisk: ns (not-significant) P > 0.05; * P ≤ 0.05; ** P ≤ 0.01; *** P ≤ 0.001; **** P ≤ 0.0001 (according to GraphPad prism 9).

Figure 6

Dot plot for annexin V-FITC/PI staining expresses the effect of SSRIs for 48 h with IC₅₀ treatment on apoptosis of PC3. Q3 shows healthy viable cells, Q1 necrotic cells, Q2 late apoptotic, and Q4 early apoptotic cells.

Figure 7

Percentages of healthy, apoptotic, and necrotic cells expressed as mean ± SD expressing the effect of SSRIs for 48 h of treatment on apoptosis of PC3. P-value <0.05 express significantly different from respective untreated cells’ status; while asterisk: ns (not-significant) P > 0.05; * P ≤ 0.05; ** P ≤ 0.01; *** P ≤ 0.001; **** P ≤ 0.0001 (according to GraphPad prism 9).

Figure 8

Effect of dapoxetine, paroxetine, and sertraline (sub-IC₅₀) for 48 h of treatment on the PC3 cell cycle. Histogram of DNA content upon PI staining of respective samples showing G0/G1, S, and G2 phases of the cell cycle. Percentages represent DNA content upon PI staining of respective samples showing G0/G1, S, and G2 phases of the cell cycle.

Figure 9

Relative gene expression variations between PC3 and DU-145 prostate cancer cells. Fold difference was measured using the ΔΔCt method. Bcl-2: the gene for B-cell lymphoma, CASP8: the gene for caspase 8, DR5: the gene for death receptor 5, and VEGF: the gene for vascular endothelial growth factor.

Figure 10

Effect of SSRIs (dapoxetine, paroxetine, and sertraline) on RNA expression of specific genes; Bcl-2, CASP8, DR5, and VEGF in PC3 cells. Fold difference was measured using the ΔΔCt method. Bcl-2: the gene for B-cell lymphoma, CASP8: the gene for caspase 8, DR5: the gene for death receptor 5, and VEGF: the gene for vascular endothelial growth factor.