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Gene Signature for Sorafenib Susceptibility in Hepatocellular Carcinoma: Different Approach with a Predictive Biomarker
Author(s) -
Kim Chang Min,
Hwang Shin,
Keam Bhumsuk,
Yu Yun Suk,
Kim Ji Hoon,
Kim Dong-Sik,
Bae Si Hyun,
Kim Gun-Do,
Lee Jong Kyu,
Seo Yong Bae,
Nam Soon Woo,
Kang Koo Jeong,
Buonaguro Luigi,
Park Jin Young,
Kim Yun Soo,
Wang Hee Jung
Publication year - 2020
Publication title -
liver cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.916
H-Index - 34
eISSN - 1664-5553
pISSN - 2235-1795
DOI - 10.1159/000504548
Subject(s) - original paper
Background/Aim: 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. Methods: Through quantitative real-time reverse transcription PCR, we analyzed the expression levels of seven actionable genes ( VEGFR2 , PDGFRB , c-KIT , c-RAF , EGFR , mTOR , and FGFR1 ) 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. Results: The responders had significantly higher TBS values than the nonresponders. With an area under the curve of 0.779, a TBS combining mTOR with VEGFR2 , c-KIT , and c-RAF 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. Conclusions: Our findings on patient stratification based on actionable molecular subtyping potentially provide a therapeutic strategy for improving sorafenib’s effectiveness in treating HCC.

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