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

Abstract

<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.