Cell Death & Drug Resistance Group, Centre for Cancer Research & Cell Biology, Queen's University Belfast, Belfast, UK.
Department of Physiology & Medical Physics, Royal College of Surgeons in Ireland, Dublin 2, Ireland.
Cell Death Differ. 2018 Nov;25(11):1952-1966. doi: 10.1038/s41418-018-0082-y. Epub 2018 Mar 2.
Apoptosis resistance contributes to treatment failure in colorectal cancer (CRC). New treatments that reinstate apoptosis competency have potential to improve patient outcome but require predictive biomarkers to target them to responsive patient populations. Inhibitor of apoptosis proteins (IAPs) suppress apoptosis, contributing to drug resistance; IAP antagonists such as TL32711 have therefore been developed. We developed a systems biology approach for predicting response of CRC cells to chemotherapy and TL32711 combinations in vitro and in vivo. CRC cells responded poorly to TL32711 monotherapy in vitro; however, co-treatment with 5-fluorouracil (5-FU) and oxaliplatin enhanced TL32711-induced apoptosis. Notably, cells from genetically identical populations responded highly heterogeneously, with caspases being activated both upstream and downstream of mitochondrial outer membrane permeabilisation (MOMP). These data, combined with quantities of key apoptosis regulators were sufficient to replicate in vitro cell death profiles by mathematical modelling. In vivo, apoptosis protein expression was significantly altered, and mathematical modelling for these conditions predicted higher apoptosis resistance that could nevertheless be overcome by combination of chemotherapy and TL32711. Subsequent experimental observations agreed with these predictions, and the observed effects on tumour growth inhibition correlated robustly with apoptosis competency. We therefore obtained insights into intracellular signal transduction kinetics and their population-based heterogeneities for chemotherapy/TL32711 combinations and provide proof-of-concept that mathematical modelling of apoptosis competency can simulate and predict responsiveness in vivo. Being able to predict response to IAP antagonist-based treatments on the background of cell-to-cell heterogeneities in the future might assist in improving treatment stratification approaches for these emerging apoptosis-targeting agents.
细胞凋亡抵抗导致结直肠癌 (CRC) 治疗失败。恢复细胞凋亡能力的新疗法有可能改善患者的预后，但需要预测性生物标志物将其靶向对有反应的患者群体。凋亡抑制蛋白 (IAPs) 抑制细胞凋亡，导致耐药性；因此，已经开发出 IAP 拮抗剂，如 TL32711。我们开发了一种系统生物学方法，用于预测 CRC 细胞对体外和体内化疗和 TL32711 联合治疗的反应。CRC 细胞在体外对 TL32711 单药治疗反应不佳；然而，与 5-氟尿嘧啶 (5-FU) 和奥沙利铂联合治疗可增强 TL32711 诱导的细胞凋亡。值得注意的是，来自遗传上相同的群体的细胞反应高度异质，半胱天冬酶在上游和线粒体外膜通透性 (MOMP) 下游均被激活。这些数据与关键凋亡调节剂的数量相结合，足以通过数学建模复制体外细胞死亡谱。在体内，凋亡蛋白表达明显改变，并且对这些条件的数学建模预测，凋亡抵抗性更高，但通过化疗和 TL32711 的联合治疗仍然可以克服。随后的实验观察结果与这些预测结果一致，并且观察到的对肿瘤生长抑制的影响与细胞凋亡能力高度相关。因此，我们深入了解了化疗/TL32711 联合治疗的细胞内信号转导动力学及其基于群体的异质性，并提供了证据证明细胞凋亡能力的数学建模可以模拟和预测体内的反应性。在未来，能够预测基于 IAP 拮抗剂的治疗反应，考虑到细胞间异质性，可能有助于改善这些新兴的凋亡靶向药物的治疗分层方法。
