Author(s): Lemke J, von Karstedt S, Zinngrebe J, Walczak H
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Abstract Unlike other members of the TNF superfamily, the TNF-related apoptosis-inducing ligand (TRAIL, also known as Apo2L) possesses the unique capacity to induce apoptosis selectively in cancer cells in vitro and in vivo. This exciting discovery provided the basis for the development of TRAIL-receptor agonists (TRAs), which have demonstrated robust anticancer activity in a number of preclinical studies. Subsequently initiated clinical trials testing TRAs demonstrated, on the one hand, broad tolerability but revealed, on the other, that therapeutic benefit was rather limited. Several factors that are likely to account for TRAs' sobering clinical performance have since been identified. First, because of initial concerns over potential hepatotoxicity, TRAs with relatively weak agonistic activity were selected to enter clinical trials. Second, although TRAIL can induce apoptosis in several cancer cell lines, it has now emerged that many others, and importantly, most primary cancer cells are resistant to TRAIL monotherapy. Third, so far patients enrolled in TRA-employing clinical trials were not selected for likelihood of benefitting from a TRA-comprising therapy on the basis of a valid(ated) biomarker. This review summarizes and discusses the results achieved so far in TRA-employing clinical trials in the light of these three shortcomings. By integrating recent insight on apoptotic and non-apoptotic TRAIL signaling in cancer cells, we propose approaches to introduce novel, revised TRAIL-based therapeutic concepts into the cancer clinic. These include (i) the use of recently developed highly active TRAs, (ii) the addition of efficient, but cancer-cell-selective TRAIL-sensitizing agents to overcome TRAIL resistance and (iii) employing proteomic profiling to uncover resistance mechanisms. We envisage that this shall enable the design of effective TRA-comprising therapeutic concepts for individual cancer patients in the future.
This article was published in Cell Death Differ
and referenced in Journal of Computer Science & Systems Biology