Abstract
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.
| Original language | English |
|---|---|
| Journal | International Journal of Biological Sciences |
| Volume | 15 |
| Issue number | 12 |
| Pages (from-to) | 2654-2663 |
| Number of pages | 10 |
| ISSN | 1449-2288 |
| DOIs | |
| Publication status | Published - 2019 |
Funding
We thank the Center for Cancer Research Genomics Core for performing NanoString digital gene expression analysis. We also thank Dr. Brad Wood from the NIH Clinical Center for critical reading of this manuscript. This work was funded by the Intramural Research Program of NIH, National Cancer Institute, and Center for Cancer Research (Z01 BC 010313 and Z01 BC 010877) and was partially funded by the CCR Office of Science and Technology Resources. JJ, XW, and NL were supported by the National Natural Science Foundation of China [No.81672905] and the Fundamental Research Funds for the Central Universities [No. 2016QN81012]. LZ is supported by the National Natural Scientific Fund of China (81472713). JM is supported by grants from the German Research Foundation (MA 4443/2-2) and the Volkswagen Foundation (Lichtenberg program).
