From computational modelling of the intrinsic apoptosis pathway to a systems-based analysis of chemotherapy resistance: achievements, perspectives and challenges in systems medicine.

Our understanding of the mitochondrial or intrinsic apoptosis pathway and its role in chemotherapy resistance has increased significantly in recent years by a combination of experimental studies and mathematical modelling. This combined approach enhanced the quantitative and kinetic understanding of apoptosis signal transduction, but also provided new insights that systems-emanating functions (i.e., functions that cannot be attributed to individual network components but that are instead established by multi-component interplay) are crucial determinants of cell fate decisions. Among these features are molecular thresholds, cooperative protein functions, feedback loops and functional redundancies that provide systems robustness, and signalling topologies that allow ultrasensitivity or switch-like responses. The successful development of kinetic systems models that recapitulate biological signal transduction observed in living cells have now led to the first translational studies, which have exploited and validated such models in a clinical context. Bottom-up strategies that use pathway models in combination with higher-level modelling at the tissue, organ and whole body-level therefore carry great potential to eventually deliver a new generation of systems-based diagnostic tools that may contribute to the development of personalised and predictive medicine approaches. Here we review major achievements in the systems biology of intrinsic apoptosis signalling, discuss challenges for further model development, perspectives for higher-level integration of apoptosis models and finally discuss requirements for the development of systems medical solutions in the coming years.

Systems analysis of apoptosis protein expression allows the case-specific prediction of cell death responsiveness of melanoma cells.

Many cancer entities and their associated cell line models are highly heterogeneous in their responsiveness to apoptosis inducers and, despite a detailed understanding of the underlying signaling networks, cell death susceptibility currently cannot be predicted reliably from protein expression profiles. Here, we demonstrate that an integration of quantitative apoptosis protein expression data with pathway knowledge can predict the cell death responsiveness of melanoma cell lines. By a total of 612 measurements, we determined the absolute expression (nM) of 17 core apoptosis regulators in a panel of 11 melanoma cell lines, and enriched these data with systems-level information on apoptosis pathway topology. By applying multivariate statistical analysis and multi-dimensional pattern recognition algorithms, the responsiveness of individual cell lines to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) or dacarbazine (DTIC) could be predicted with very high accuracy (91 and 82% correct predictions), and the most effective treatment option for individual cell lines could be pre-determined in silico. In contrast, cell death responsiveness was poorly predicted when not taking knowledge on protein-protein interactions into account (55 and 36% correct predictions). We also generated mathematical predictions on whether anti-apoptotic Bcl-2 family members or x-linked inhibitor of apoptosis protein (XIAP) can be targeted to enhance TRAIL responsiveness in individual cell lines. Subsequent experiments, making use of pharmacological Bcl-2/Bcl-xL inhibition or siRNA-based XIAP depletion, confirmed the accuracy of these predictions. We therefore demonstrate that cell death responsiveness to TRAIL or DTIC can be predicted reliably in a large number of melanoma cell lines when investigating expression patterns of apoptosis regulators in the context of their network-level interplay. The capacity to predict responsiveness at the cellular level may contribute to personalizing anti-cancer treatments in the future.

Proteasome inhibition can induce an autophagy-dependent apical activation of caspase-8.

Antiapoptotic Bcl-2 family proteins are often highly expressed in chemotherapy-resistant cancers and impair mitochondrial outer membrane permeabilisation (MOMP), an important requirement for caspase activation via the intrinsic apoptosis pathway. Interestingly, although Bcl-2 overexpression in HeLa cervical cancer cells abrogated caspase processing in response to intrinsic apoptosis induction by staurosporine, tunicamycin or etoposide, residual caspase processing was observed following proteasome inhibition by bortezomib ([(1R)-3-methyl-1-({(2S)-3-phenyl-2-[(pyrazin-2-ylcarbonyl)amino]propanoyl}amino)butyl]boronic acid), epoxomicin (N-acetyl-N-methyl-lisoleucyl-L-isoleucyl-N-[(1S)-3-methyl-1-[[(2R)-2-methyloxiranyl]carbonyl]butyl]-L-threoninamide) or MG-132 (N-(benzyloxycarbonyl)leucinylleucinylleucinal). Similar responses were found in Bcl-2-overexpressing H460 NSCLC cells and Bax/Bak-deficient mouse embyronic fibroblasts. Mild caspase processing resulted in low DEVDase activities, which were MOMP independent and persisted for long periods without evoking immediate cell death. Surprisingly, depletion of caspase-3 and experiments in caspase-7-depleted MCF-7-Bcl-2 cells indicated that the DEVDase activity did not originate from effector caspases. Instead, Fas-associated death domain (FADD)-dependent caspase-8 activation was the major contributor to the slow, incomplete substrate cleavage. Caspase-8 activation was independent of death ligands, but required the induction of autophagy and the presence of Atg5. Depletion of XIAP or addition of XIAP-antagonising peptides resulted in a switch towards efficient apoptosis execution, suggesting that the requirement for MOMP was bypassed by activating the caspase-8/caspase-3 axis. Combination treatments of proteasome inhibitors and XIAP antagonists therefore represent a promising strategy to eliminate highly resistant cancer cells, which overexpress antiapoptotic Bcl-2 family members.