A PGC-1 alpha-Mediated Transcriptional Network Maintains Mitochondrial Redox and Bioenergetic Homeostasis against Doxorubicin-Induced Toxicity in Human Cardiomyocytes: Implementation of TT21C

摘要

Chemical toxicity testing is fast moving in a direction that relies increasingly on cell-based in vitro assays anchored on toxicity pathways according to the toxicity testing in the 21st century vision. Identifying points of departure (POD) via these assays and revealing their mechanistic underpinnings via computational modeling of the relevant pathways are critical and challenging steps. Here we used doxorubicin (DOX) as a prototype chemical to study mitochondrial toxicity in human AC16 cells. Mitochondrial toxicity has been linked to cardiovascular risk of DOX, which has limited its clinical use as an antitumor drug. Our in vitro study revealed a well-defined POD concentration of DOX below which adaptive induction of proliferator-activated receptor-gamma coactivator-1 alpha (PGC-1 alpha) -mediated mitochondrial genes, including NRF-1, MnSOD, UCP2, and COX1, concurred with negligible changes in mitochondrial superoxide and cytotoxicity. At higher DOX concentrations adversity became significant with elevated superoxide and suppressed ATP levels. A computational model was formulated to simulate the PGC-1 alpha-mediated transcriptional network comprising multiple negative feedback loops that underlie redox and bioenergetics homeostasis in the mitochondrion. The model recapitulated the transition phase from adaptive to adverse responses, supporting the notion that saturated induction of PGC-1 alpha-mediated gene network underpins POD. The model further predicts (follow-up experiments verified) that silencing PGC-1 alpha compromises the adaptive function of the transcriptional network, leading to disruption of mitochondria and cytotoxicity at lower DOX concentrations. In summary, our study demonstrates that combining pathway-focused in vitro assays and computational simulation of relevant biochemical network is synergistic for understanding dose-response behaviors in the low-dose region and identifying POD.