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.

Clinical Characteristics of Long-Term Survivors After Sorafenib Treatment for Unresectable Hepatocellular Carcinoma: A Korean National Multicenter Retrospective Cohort Study

“… 22 A recent study showed that stratification using VEGFR2, PDGFRB, c-KIT, c-RAF, EGFR, mTOR, and FGFR1 gene expression could predict sorafenib response. 23 However, these studies could not be evaluated due to the retrospective nature of our study and a lack of laboratory data.…”

The Role of IGF/IGF-1R Signaling in Hepatocellular Carcinomas: Stemness-Related Properties and Drug Resistance

“…The mechanism of drug resistance development may be related to changes in epigenetics in drug targets, upregulated transport processes, regulated cell death, or the tumor microenvironment [ 227 ]. The patient response rate of sorafenib is poor (0.7–3.0%); however, it is the recommend standard treatment for advanced HCC [ 228 ]. Hence, it is clear that alternative therapeutic strategies are needed.…”

Comprehensive Analysis of Mutation-Based and Expressed Genes-Based Pathways in Head and Neck Squamous Cell Carcinoma

“…We applied a novel algorithm that calculated the gene interaction score for the top 10 signal transduction pathways that divided the number of interactions for each interacting gene (between start genes and interacting genes) in a specific signal transduction pathway by the total number of interactions. Then we calculated each gene's treatment benefit prediction score (TBPS) by the sum of gene interaction scores included in the top 10 signal transduction pathways [12].…”