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

Chang Min Kim, Shin Hwang, Bhumsuk Keam, Yun Suk Yu, Ji Hoon Kim, Dong‐Sik Kim, Si Hyun Bae, Gun‐Do Kim, Jong‐Kyu Lee, Yong Bae Seo, Soon Woo Nam, Koo Jeong Kang, Luigi Buonaguro, Jin Young Park, Yun Soo Kim, Hee-Jung Wang

2020Liver Cancer25 citationsDOIOpen Access PDF

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.

Topics & Concepts

SorafenibHepatocellular carcinomaSubtypingMedicineOncologyInternal medicineBiomarkerGene signatureCancer researchGeneGene expressionBiologyComputer scienceBiochemistryProgramming languageHepatocellular Carcinoma Treatment and PrognosisCancer Mechanisms and TherapyLiver physiology and pathology
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