Cold Atmospheric Plasma and Silymarin Nanoemulsion Activate Autophagy in Human Melanoma Cells

Abstract

Background: Autophagy is reported as a survival or death-promoting pathway that is highly debatable in different kinds of cancer. Here, we examined the co-effect of cold atmospheric plasma (CAP) and silymarin nanoemulsion (SN) treatment on G-361 human melanoma cells via autophagy induction.

Methods: The temperature and pH of the media, along with the cell number, were evaluated. The intracellular glucose level and PI3K/mTOR and EGFR downstream pathways were assessed. Autophagy-related genes, related transcriptional factors, and autophagy induction were estimated using confocal microscopy, flow cytometry, and ELISA.

Results: CAP treatment increased the temperature and pH of the media, while its combination with SN resulted in a decrease in intracellular ATP with the downregulation of PI3K/AKT/mTOR survival and RAS/MEK transcriptional pathways. Co-treatment blocked downstream paths of survival pathways and reduced PI3K (2 times), mTOR (10 times), EGFR (5 times), HRAS (5 times), and MEK (10 times). CAP and SN co-treated treatment modulates transcriptional factor expressions (ZKSCAN3, TFEB, FOXO1, CRTC2, and CREBBP) and specific genes (BECN-1, AMBRA-1, MAP1LC3A, and SQSTM) related to autophagy induction.

Conclusion: CAP and SN together activate autophagy in G-361 cells by activating PI3K/mTOR and EGFR pathways, expressing autophagy-related transcription factors and genes.

Keywords: PI3K/mTOR pathway; autophagy; cold atmospheric plasma; silymarin nanoemulsion.

Figure 1

(a) Schematic diagram of the non-thermal cold atmospheric plasma (CAP) micro-dielectric barrier discharge (μ-DBD) plasma source with a distance of 2 mm from cell culture media. (b) Photograph of the μ-DBD plasma device showing plasma discharge using air as the feeder gas. (c) The μ-DBD device on time (T_on) and off-time (T_off). (d) Voltage and current waveforms for one cycle of the T_on period of the μ-DBD air CAP device. (e) Optical emission spectrum (OES) composition of the air μ-DBD CAP source between 200 nm and 800 nm.

Figure 2

(a) Estimation of temperature within cell media (RPMI-1640) after the exposure of air CAP at different time intervals; (b) effect of different CAP doses on the pH level of cell media; (c) assessment of the G-361 human melanoma cell count using a hemocytometer counter after the exposure of CAP at different time intervals; (d) microscopic evaluation of G-361 human melanoma cells at different CAP doses (scale bar = 200 μm). Data are the mean ± SE of three experiments. Statistical analysis was performed using a one-way ANOVA test followed by Dunnett’s test for comparisons. Each asterisk represents statistical differences between the treatment and control (*** p < 0.001 and **** p < 0.0001).

Figure 3

Estimation of intracellular glucose (ATP level) using fluorescent glucose analog 2-NBDG (a) employing flow cytometry in a bar graph; (b) calculated values in terms of the bar graph; (c) images were taken using confocal microscopy (intensity of green color represents the presence of glucose and blue indicates the nucleus); (d) captured images were expressed terms of Corrected Total Cell Fluorescence (CTCF) in a bar graph form. Data are the mean ± SE of three experiments. Statistical analysis was performed using a one-way ANOVA test followed by Dunnett’s test for comparisons. Each asterisk represents statistical differences between the treatment and control (**** p < 0.0001).

Figure 4

(a) Illustration of the CAP and silymarin nanoemulsion (SN)-mediated hypothesis about the blockage of PI3K/AKT/mTOR and RAS/MEK pathways for the activation of autophagy. Gene analysis of the GFR-mediated downstream expression of the (b) PI3K gene and (c) mTOR gene, and gene analysis of the Epidermal Growth factor (EGF)-mediated downstream expression of the (d) EGFR gene, (e) HRAS gene, and (f) MEK gene. Data are the mean ± SE of three experiments. Statistical analysis was performed using a one-way ANOVA test followed by Dunnett’s test for comparisons. Each asterisk represents statistical differences between the treatment and control (** p < 0.01, *** p < 0.001, and **** p < 0.0001).

Figure 5

Gene expression levels of autophagy-related transcriptional factors: (a) ZKSCAN3 gene; (b) TFEB gene; (c) FOXO1 gene; (d) CRTC2 gene; and (e) CREBBP gene. Expression of various gene levels directly responsible for autophagy: (f) BECN-1 (ATG-6); (g) AMBRA-1; (h) MAP1LC3A (ATG-8); and (i) SQSTM (p62). Data are the mean ± SE of three experiments. Statistical analysis was performed using a one-way ANOVA test followed by Dunnett’s test for comparisons. Each asterisk represents statistical differences between the treatment and control (* p < 0.05, *** p < 0.001, and **** p < 0.0001).

Figure 6

Interpretation of autophagic flux using a kit (Cyto ID® autophagy detection kit) (a) by confocal microscopy (green dots represent autophagic sites within G-361 cells and blue stains signify nuclei); (b) autophagy image intensities were expressed in terms of CTCF values using bar graphs; (c) flow cytometry evaluation of autophagy determination using anti-LC3B FITC-labeled dye; (d) FITC expression for autophagy was expressed in terms of a bar graph. Data are the mean ± SE of three experiments. Statistical analysis was performed using a one-way ANOVA test followed by Dunnett’s test for comparisons. Each asterisk represents statistical differences between the treatment and control (** p < 0.01 and **** p < 0.0001).