// Kazuko Sakai 1,* , Haruhiko Takeda 2,7,* , Norihiro Nishijima 2 , Etsuro Orito 3 , Kouji Joko 4 , Yasushi Uchida 5 , Namiki Izumi 6 , Kazuto Nishio 1 and Yukio Osaki 2 1 Department of Genome Biology, Kinki University Faculty of Medicine, Ohono-Higashi, Osaka-Sayamashi, Osaka, Japan 2 Department of Gastroenterology and Hepatology, Osaka Red Cross Hospital, Osaka, Japan 3 Department of Gastroenterology and Hepatology, Nagoya Daini Red Cross Hospital, Nagoya City, Japan 4 Center for Liver-Biliary-Pancreatic Diseases, Matsuyama Red Cross Hospital, Matsuyama City, Japan 5 Department of Gastroenterology, Matsue Red Cross Hospital, Matsue City, Japan 6 Department of Gastroenterology and Hepatology, Musashino Red Cross Hospital, Musashino, Japan 7 Department of Gastroenterology and Hepatology, Graduate School of Medicine, Kyoto University, Shogoin-Kawaharacho, Kyoto, Japan * These authors have contributed equally to this work Correspondence to: Kazuto Nishio, email: // Keywords : hepatocellular cancer, sorafenib, response, mutation Received : March 05, 2015 Accepted : May 08, 2015 Published : May 25, 2015 Abstract The multi-kinase inhibitor sorafenib is now used as standard therapy for advanced hepatocellular carcinoma (HCC). Predictive biomarkers of response to sorafenib are thus necessary. The purpose of this study was to assess the feasibility of using targeted DNA and RNA sequencing to elucidate candidate biomarkers of sorafenib response using fine-needle biopsy, formalin-fixed paraffin-embedded (FFPE) specimens in patients with HCC. Targeted DNA and RNA deep sequencing were feasible for the evaluation of fine-needle biopsy FFPE specimens obtained from 46 patients with HCC treated with sorafenib. Frequent mutations of suppressor genes, such as CTNNB1 (34.8%) and TP53 (26.1%), were detected in the HCC tumors. After excluding these suppressor genes, the average numbers of detected oncogene mutations differed significantly between the non-PD and PD groups ( P = 0.0446). This result suggests that the oncogene mutational burden in the tumor might be associated with the clinical response to sorafenib. We have identified candidate gene expression ( TGFa , PECAM1 , and NRG1 ) in tumor for the prediction of sorafenib response and PFS by RNA sequencing. Our findings provide new insights into biomarkers for sorafenib therapy and allow us to discuss future therapeutic strategies.
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