Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Kim CM

PROVIDER: S-EPMC7206603 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Publications

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

Kim Chang Min CM Hwang Shin S Keam Bhumsuk B Yu Yun Suk YS Kim Ji Hoon JH Kim Dong-Sik DS Bae Si Hyun SH Kim Gun-Do GD Lee Jong Kyu JK Seo Yong Bae YB Nam Soon Woo SW Kang Koo Jeong KJ Buonaguro Luigi L Park Jin Young JY Kim Yun Soo YS Wang Hee Jung HJ

Liver cancer 20200218 2

<h4>Background/aim</h4>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.<h4>Methods</h4>Through quantitative real-time reverse transcri ...[more]

PMID: 32399432

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Project description:Transarterial chemoembolization (TACE) is a commonly used treatment modality in hepatocellular carcinoma (HCC). The ability to identify patients who will respond to TACE represents an important clinical need, and tumor gene expression patterns may be associated with TACE response. We investigated whether tumor transcriptome is associated with TACE response in patients with HCC. We analyzed transcriptome data of treatment-naïve tumor tissues from a Chinese cohort of 191 HCC patients, including 105 patients who underwent TACE following resection with curative intent. We then developed a gene signature, TACE Navigator, which was associated with improved survival in patients that received either adjuvant or post-relapse TACE. To validate our findings, we applied our signature in a blinded manner to three independent cohorts comprising an additional 130 patients with diverse ethnic backgrounds enrolled in three different hospitals who received either adjuvant TACE or palliative TACE. TACE Navigator stratified patients into Responders and Non-Responders which was associated with improved survival following TACE in our test cohort (Responders: 67 months vs Non-Responders: 39.5 months, p<0.0001). In addition, multivariable Cox model demonstrates that TACE Navigator was independently associated with survival (HR: 9.31, 95% CI: 3.46-25.0, p<0.001). In our validation cohorts, the association between TACE Navigator and survival remained robust in both Asian patients who received adjuvant TACE (Hong Kong: 60 months vs 25.6 months p=0.007; Shandong: 61.3 months vs 32.1 months, p=0.027) and European patients who received TACE as primary therapy (Mainz: 60 months vs 41.5 months, p=0.041). These results indicate that a TACE-specific molecular classifier is robust in predicting TACE response. This gene signature can be used to identify patients who will have the greatest survival benefit after TACE treatment and enable personalized treatment modalities for patients with HCC.

Dataset Information

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

Background/aim

Methods

Results

Conclusions

Publications

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

Similar Datasets

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