Gene expression in nontumoral liver tissue and recurrence-free survival in hepatitis C virus-positive HCC

Background/Aims: Recurrence-free survival (RFS) following curative resection of hepatocellular carcinoma (HCC) in subjects with hepatitis C virus (HCV) infection is highly variable. Traditional clinico-pathological endpoints are recognized as weak predictors of RFS. It has been suggested that gene expression profiling of HCC and nontumoral liver tissue may improve prediction of RFS, aid in understanding of the underlying liver disease, and guide individualized therapy. The goal of this study was to create a gene expression predictor of HCC recurrence in subjects with HCV. Methods: Frozen samples of the tumors and nontumoral liver were obtained from 47 subjects with HCV-associated HCC. Additional nontumoral liver samples were obtained from HCV-free subjects with metastatic liver tumors. Gene expression profiling data was used to determine the molecular signature of HCV-associated HCC and to develop a predictor of RFS. Results: The molecular profile of the HCV-associated HCC confirmed central roles for MYC and TGF-beta1 in liver tumor development. Gene expression in tumors was found to have poor predictive power with regards to RFS, but analysis of nontumoral tissues yielded a strong predictor for RFS in late-recurring (>1 year) subjects. Importantly, nontumoral tissue-derived gene expression predictor of RFS was highly significant in both univariable and multivariable Cox proportional hazard model analyses. Conclusions: Microarray analysis of the nontumoral tissues from subjects with HCV-associated HCC delivers novel molecular signatures of RFS, especially among the late-recurrence subjects. The gene expression signature of the predictor gives important insights into the pathobiology of HCC recurrence and used in design of the individualized therapy. 43 tumor (JT) and 44 non-tumor (JNT) liver tissues surgically resected from patients with HCV-associated hepatocellular carcinoma; 8 non-tumor liver tissues (control samples, JC) surgically resected from HCV- or HBV-free patients with metastatic liver tumor. Inter-batch normalization was carried out using Distance Weighted Discrimination procedure. The supplementary file 'GSE17856_Readme.txt' contains a description of the replicates used for normalization. The 'GSE17856_US14702406_2514850*' files are the raw data files for the replicates.

背景与目的：合并丙型肝炎病毒（hepatitis C virus, HCV）感染的肝细胞癌（hepatocellular carcinoma, HCC）患者接受根治性切除术后的无复发生存期（recurrence-free survival, RFS）差异显著。传统临床病理终点指标作为RFS的预测因子，其预测效力较为有限。已有研究表明，对HCC及非肿瘤肝组织开展基因表达谱分析，或可提升RFS的预测效能，助力阐明潜在肝脏疾病的发病机制，并指导个体化治疗方案的制定。本研究旨在构建针对HCV相关HCC患者的HCC复发基因表达预测模型。

方法：本研究从47例HCV相关HCC患者中获取肿瘤组织与非肿瘤肝组织的冰冻样本；同时从无HCV感染的转移性肝肿瘤患者中采集额外的非肿瘤肝组织样本。通过基因表达谱分析，明确HCV相关HCC的分子特征，并开发RFS预测模型。

结果：HCV相关HCC的分子特征分析证实，原癌基因MYC与转化生长因子β1（transforming growth factor-β1, TGF-β1）在肝脏肿瘤发生过程中发挥核心调控作用。研究发现，肿瘤组织的基因表达对RFS的预测效能较差，但对非肿瘤组织的分析结果显示，其可有效预测晚期复发（术后复发时间>1年）患者的RFS。尤为关键的是，基于非肿瘤组织的RFS基因表达预测模型在单变量及多变量考克斯比例风险模型（Cox proportional hazard model）分析中均呈现显著统计学意义。

结论：对合并HCV相关HCC患者的非肿瘤肝组织进行基因芯片（microarray）分析，可获得与RFS相关的新型分子特征，尤其在晚期复发患者群体中表现突出。该预测模型的基因表达特征可为HCC复发的病理生物学机制提供重要见解，并可用于指导个体化治疗方案的设计。

本数据集包含43份来自HCV相关HCC患者手术切除的肿瘤组织（JT）样本与44份对应非肿瘤肝组织（JNT）样本，以及8份来自无HCV或乙型肝炎病毒（hepatitis B virus, HBV）感染的转移性肝肿瘤患者手术切除的非肿瘤肝组织对照样本（JC）。本数据集采用距离加权判别法（Distance Weighted Discrimination）进行批次间标准化处理。补充文件“GSE17856_Readme.txt”中包含了用于标准化的重复样本说明。文件“GSE17856_US14702406_2514850*”为重复样本的原始数据文件。