An in-silico study examining the induction of apoptosis by Cryptotanshinone in metastatic melanoma cell lines

Abstract

Background: Metastatic melanoma is an aggressive form of skin cancer that evades various anti-cancer treatments including surgery, radio-,immuno- and chemo-therapy. TRAIL-induced apoptosis is a desirable method to treat melanoma since, unlike other treatments, it does not harm non-cancerous cells. The pro-inflammatory response to melanoma by nF κB and STAT3 pathways makes the cancer cells resist TRAIL-induced apoptosis. We show that due to to its dual action on DR5, a death receptor for TRAIL and on STAT3, Cryptotanshinone can be used to increase sensitivity to TRAIL.

Methods: The development of chemoresistance and invasive properties in melanoma cells involves several biological pathways. The key components of these pathways are represented as a Boolean network with multiple inputs and multiple outputs.

Results: The possible mutations in genes that can lead to cancer are captured by faults in the combinatorial circuit and the model is used to theoretically predict the effectiveness of Cryptotanshinone for inducing apoptosis in melanoma cell lines. This prediction is experimentally validated by showing that Cryptotanshinone can cause enhanced cell death in A375 melanoma cells.

Conclusion: The results presented in this paper facilitate a better understanding of melanoma drug resistance. Furthermore, this framework can be used to detect additional drug intervention points in the pathway that could amplify the action of Cryptotanshinone.

Keywords: Boolean networks; Cryptotanshinone; Melanoma; Stat3; Trail.

Fig. 1

Color coding for gene interactions in Figs. 3 through 8

Fig. 2

Legend for use in Figs. 3 through 8

Fig. 3

Extrinsic Apoptosis and the nF κB pathways

Fig. 4

JNK, p53, PI3K/AKT/mTOR and MAPK/ERK pathways

Fig. 5

DNA damage pathway

Fig. 6

Endoplasmic Reticulum Stress and the JNK pathway

Fig. 7

STAT3 pathway

Fig. 8

Mitochondrial Apoptosis Pathway

Fig. 9

Boolean representation of the drug action countering a stuck-at-one fault

Fig. 10

Boolean representation of the drug action countering a stuck-at-zero fault

Fig. 11

Legend showing the color coding scheme used in Figs. 12, 13 and 14

Fig. 12

Boolean network for the DNA Damage pathway

Fig. 13

Boolean network for the TRAIL, ER Stress and STAT3 pathway

Fig. 14

Boolean network for the PI3K/AKT/mTOR and MAPK/ERK pathway

Fig. 15

Apoptosis ratios for different inputs

Fig. 16

Apoptosis by CT in combination with a single drug in the presence of simultaneous occurrence of all faults

Fig. 17

All possible combinations of faults and drugs when the input is TRAIL, with Cryptotanshinone

Fig. 18

All possible combinations of faults and drugs when the input is TRAIL, without Cryptotanshinone

Fig. 19

Experimental results for each single drug in combination with CT