Author(s): Bychkov ML, Gasparian ME, Dolgikh DA, Kirpichnikov MP
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Abstract TRAIL (tumor necrosis factor-related apoptosis-inducing ligand) mediates apoptosis in cancer cells through death receptors DR4 and DR5 preferring often one receptor over another in the cells expressing both receptors. Receptor selective mutant variants of TRAIL and agonistic antibodies against DR4 and DR5 are highly promising anticancer agents. Here using DR5 specific mutant variant of TRAIL--DR5-B we have demonstrated for the first time that the sensitivity of cancer cells can be shifted from one TRAIL death receptor to another during co-treatment with anticancer drugs. First we have studied the contribution of DR4 and DR5 in HCT116 p53+/+ and HCT116 p53-/- cells and demonstrated that in HCT116 p53+/+ cells the both death receptors are involved in TRAIL-induced cell death while in HCT116 p53-/- cells prevailed DR4 signaling. The expression of death (DR4 and DR5) as well as decoy (DcR1 and DcR2) receptors was upregulated in the both cell lines either by TRAIL or by bortezomib. However, combined treatment of cells with two drugs induced strong time-dependent and p53-independent internalization and further lysosomal degradation of DR4 receptor. Interestingly DR5-B variant of TRAIL which do not bind with DR4 receptor also induced elimination of DR4 from cell surface in combination with bortezomib indicating the ligand-independent mechanism of the receptor internalization. Eliminatory internalization of DR4 resulted in activation of DR5 receptor thus DR4-dependent HCT116 p53-/- cells became highly sensitive to DR5-B in time-dependent manner. Internalization and degradation of DR4 receptor depended on activation of caspases as well as of lysosomal activity as it was completely inhibited by Z-VAD-FMK, E-64 and Baf-A1. In light of our findings, it is important to explore carefully which of the death receptors is active, when sensitizing drugs are combined with agonistic antibodies to the death receptors or receptor selective variants of TRAIL to enhance cancer treatment efficiency.
This article was published in PLoS One
and referenced in Journal of Computer Science & Systems Biology