Drug-drug interaction between metformin and sorafenib alters antitumor effect in hepatocellular carcinoma cells. Drug-drug interaction between metformin and sorafenib alters antitumor effect in hepatocellular carcinoma cells

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and is one of the leading causes of cancer-related deaths worldwide. The multi‐target inhibitor sorafenib is a first-line treatment for patients with advanced unresectable HCC. Recent clinical studies have evidenced that patients treated with sorafenib together with the anti-diabetic drug metformin have a survival disadvantage compared to patients receiving sorafenib only. Here, we examined whether a clinically relevant dose of metformin (50 mg/kg/d) could influence the antitumoral effects of sorafenib (15 mg/kg/d) in a subcutaneous xenograft model of human HCC growth using two different sequences of administration, i.e concomitant versus sequential dosing regimens. We observed that the administration of metformin six hours prior to sorafenib was significantly less effective in inhibiting tumor growth than concomitant administration of the two drugs. In vitro experiments confirmed that pretreatment of different human HCC cell lines with metformin reduced the effects of sorafenib on cell viability, proliferation and signaling. Transcriptomic analysis confirmed significant differences between xenografted tumors obtained under the concomitant and the sequential dosing regimens. Taken together, these observations call into question the benefit of parallel use of metformin and sorafenib in patients with advanced HCC and diabetes, as the interaction between the two drugs could ultimately compromise patient survival. To better characterize the molecular signatures driving the differential responses to concomitant and sequential biotherapies, we conducted a transcriptomic analysis on RNA extracted from tumor xenografts mice xenografed and treated with vehicle (control, n=3), metformin (50 mg/kg/day) combined to sorafenib (15 mg/kg/day) (concomitant schedule, n=3) or metformin (50 mg/kg/day) followed 6 hours later by sorafenib (15 mg/kg/day) (sequential schedule, n=3). Overall design: Total RNA was extracted from tumors collected from mice xenografed subcutaneously in the right flank with PLC/PRF5 cells and treated with vehicle (control, n=3), metformin (50 mg/kg/day) combined to sorafenib (15 mg/kg/day) (concomitant schedule, n=3) or metformin (50 mg/kg/day) followed 6 hours later by sorafenib (15 mg/kg/day) (sequential schedule, n=3). Total RNA was amplified and labelled using the GeneChipTM WT PLUS Reagent Kit (ThermoFischer Scientific). Each RNA sample was hybridized to Human ClariomTM S GeneChip (ThermoFischer Scientific). Arrays were scanned, and images were analyzed and controlled for hybridization artefacts. The microarray data were normalized using Signal Space Transformation-RMA (SST-RMA) which is optimized for under-estimation of true fold changes. Following normalization, differential expression was carried out using eBayes function and One-Way Anova statistical analysis. The analysis was carried out using Transcriptome Analysis Console software (ThermoFischer Scientific, version 4.0.2) with p < 0.05 considered as statistically significant. The differentially expressed genes were then subjected to absolute GSEA searching through more than 10,000 different cellular pathways.

肝细胞癌（hepatocellular carcinoma, HCC）是最常见的原发性肝脏恶性肿瘤，亦是全球范围内癌症相关死亡的主要诱因之一。多靶点抑制剂索拉非尼（sorafenib）是不可切除的晚期肝细胞癌患者的一线治疗方案。近期临床研究证实，相较于仅接受索拉非尼单药治疗的患者，联合应用抗糖尿病药物二甲双胍（metformin）的患者生存结局更劣。本研究采用人肝细胞癌皮下移植瘤模型，设置联合给药与序贯给药两种给药方案，旨在探究临床相关剂量的二甲双胍（50 mg/kg/d）是否会影响索拉非尼（15 mg/kg/d）的抗肿瘤效应。
实验结果显示，相较于两药联合给药方案，在索拉非尼给药前6小时给予二甲双胍的抗肿瘤生长效果显著更弱。体外实验进一步验证：用二甲双胍预处理不同人肝细胞癌细胞系，可削弱索拉非尼对细胞活力、增殖及信号通路的调控作用。转录组学分析证实，联合给药与序贯给药组的移植瘤转录谱存在显著差异。
综上，本研究结果对晚期肝细胞癌合并糖尿病患者并行使用二甲双胍与索拉非尼的临床获益提出质疑——两药的相互作用或最终损害患者的生存预后。为进一步阐明驱动联合与序贯生物治疗差异应答的分子特征，我们对移植瘤组织的RNA开展转录组学分析，受试小鼠均于右侧胁腹皮下接种PLC/PRF5细胞，分组处理如下：溶剂对照组（n=3）、二甲双胍（50 mg/kg/天）联合索拉非尼（15 mg/kg/天）联合给药组（n=3）、二甲双胍（50 mg/kg/天）给药6小时后予索拉非尼（15 mg/kg/天）序贯给药组（n=3）。
整体实验设计：从上述各组小鼠的移植瘤组织中提取总RNA。总RNA采用GeneChip™ WT PLUS Reagent Kit (ThermoFischer Scientific) 进行扩增与标记。每份RNA样本均与Human Clariom™ S GeneChip (ThermoFischer Scientific) 进行杂交。芯片扫描完成后，对图像进行分析并排查杂交伪影。微阵列数据采用信号空间转换-稳健多数组平均法（Signal Space Transformation-RMA, SST-RMA）进行标准化，该方法可优化对真实倍数变化的低估偏差。标准化完成后，采用eBayes函数与单因素方差分析进行差异表达分析。数据分析采用Transcriptome Analysis Console软件（ThermoFischer Scientific，版本4.0.2），以p < 0.05作为统计学显著性阈值。随后对差异表达基因进行绝对基因集富集分析（Gene Set Enrichment Analysis, GSEA），检索超过10000条不同的细胞通路。