Supplementary Material for: Gene Signature for Sorafenib Susceptibility in Hepatocellular Carcinoma: Different Approach with a Predictive Biomarker

<b><i>Background/Aim:</i></b> Uniform treatment of hepatocellular carcinoma (HCC) with molecular targeted drugs (e.g., sorafenib) results in a poor overall tumor response when tumor subtyping is absent. Patient stratification based on actionable gene expression is a method that can potentially improve the effectiveness of these drugs. Here we aimed to identify the clinical application of actionable genes in predicting response to sorafenib. <b><i>Methods:</i></b> Through quantitative real-time reverse transcription PCR, we analyzed the expression levels of seven actionable genes (<i>VEGFR2</i>, <i>PDGFRB</i>, <i>c-KIT</i>, <i>c-RAF</i>, <i>EGFR</i>, <i>mTOR</i>, and <i>FGFR1</i>) in tumors versus noncancerous tissues from 220 HCC patients treated with sorafenib. Our analysis found that 9 responders did not have unique clinical features compared to nonresponders. A receiver operating characteristic curve evaluated the predictive performance of the treatment benefit score (TBS) calculated from the actionable genes. <b><i>Results:</i></b> The responders had significantly higher TBS values than the nonresponders. With an area under the curve of 0.779, a TBS combining <i>mTOR</i> with <i>VEGFR2</i>, <i>c-KIT</i>, and <i>c-RAF</i> was the most significant predictor of response to sorafenib. When used alone, sorafenib had a 0.7–3% response rate among HCC patients, but when stratifying the patients with actionable genes, the tumor response rate rose to 15.6%. Furthermore, actionable gene expression is significantly correlated with tumor response. <b><i>Conclusions:</i></b> Our findings on patient stratification based on actionable molecular subtyping potentially provide a therapeutic strategy for improving sorafenib’s effectiveness in treating HCC.

<b><i>背景与研究目的：</i></b> 在未进行肿瘤分型的情况下，对肝细胞癌（hepatocellular carcinoma, HCC）采用分子靶向药物（molecular targeted drugs，如索拉非尼（sorafenib））的统一治疗，整体肿瘤应答效果不佳。基于可操作基因表达（actionable gene expression）进行患者分层（patient stratification），是潜在提升此类药物疗效的可行方案。本研究旨在明确可操作基因在预测索拉非尼治疗应答中的临床应用价值。<b><i>研究方法：</i></b> 本研究通过实时定量逆转录聚合酶链反应（quantitative real-time reverse transcription PCR），分析了220例接受索拉非尼治疗的肝细胞癌患者的肿瘤组织与癌旁组织中7个可操作基因（<i>血管内皮生长因子受体2（VEGFR2）</i>、<i>血小板衍生生长因子受体β（PDGFRB）</i>、<i>c-KIT</i>、<i>c-RAF</i>、<i>表皮生长因子受体（EGFR）</i>、<i>雷帕霉素靶蛋白（mTOR）</i>及<i>成纤维细胞生长因子受体1（FGFR1）</i>）的表达水平。分析发现，9名应答者与无应答者相比，并无独特临床特征。本研究采用受试者工作特征曲线（receiver operating characteristic curve, ROC曲线），评估了由可操作基因计算得到的治疗获益评分（treatment benefit score, TBS）的预测性能。<b><i>研究结果：</i></b> 应答者的TBS值显著高于无应答者。联合<i>雷帕霉素靶蛋白（mTOR）</i>、<i>血管内皮生长因子受体2（VEGFR2）</i>、<i>c-KIT</i>及<i>c-RAF</i>组成的TBS，其曲线下面积（area under the curve, AUC）为0.779，是预测索拉非尼治疗应答的最显著预测因子。单独使用索拉非尼时，肝细胞癌患者的肿瘤应答率仅为0.7%~3%；但通过可操作基因对患者进行分层后，肿瘤应答率提升至15.6%。此外，可操作基因的表达水平与肿瘤应答显著相关。<b><i>研究结论：</i></b> 本研究基于可操作分子分型的患者分层研究结果，有望为提升索拉非尼治疗肝细胞癌的疗效提供新的治疗策略。