Liu Yajuan J, Zhou Yang, Yeh Matthew M
Department of Pathology, University of Washington, 1959 NE Pacific Street, Box 357470, Seattle, WA 98195 USA.
Mol Cytogenet. 2014 Nov 25;7(1):81. doi: 10.1186/s13039-014-0081-8. eCollection 2014.
In the US, approximately 50% of hepatocellular carcinoma (HCC) is caused by hepatitis-C virus (HCV) infection. The molecular mechanism of a malignant transformation of hepatocyte induced by HCV infection is still largely unclear. There are several clinical and pathological staging systems for HCC, but none of them include biological parameters as predictors for prognosis and there has not been a standardized molecular classification of HCC. To understand the underlying pathogenic genetic alterations in HCV-associated HCC and aid in molecular classification of HCC and patient prognosis, microarray analysis of DNA copy number alterations in HCC were conducted using whole genome microarray with DNA from formalin-fixed paraffin-embedded (FFPE) specimens of both cancer tissues and paired nearby cirrhotic non-neoplastic tissues.
Our results show that the most common chromosomal aberrations (>5 Mb) observed in HCC were chromosomal gains of 1q (80%), 8q (60%), 7q (40%), 5p (33%), 7p (33%), Xq (33%), 5q (27%), and Xp (20%), as well as chromosome losses of 17p (40%), 4q21.21-q26 (33%), 8p (33%), 1p36.11-pter (20%), and 9p (20%). Statistically significant smaller copy number alterations (3.9 kb to 644 kb) were identified using STAC algorithm, including losses of FGFR3, RECQL4, NOTCH1, PTEN, TSC2, and/or ASPSCR1 and gains of ETV1and/or MAF. Correlation analysis between genetic data and pathological data showed that gain of 1q21.1-q23.2 and gain of 8q11.1q13.1 are significantly associated with grade 2-4 and moderately or poorly differentiated HCCs, and gain of chromosome 5q was significantly associated with HCCs with vascular invasion, while gain of chromosome 7q is significantly associated with stage I HCCs.
This study has provided a detailed map of genomic aberrations occurring in HCV-associated HCC and has suggested candidate genes. In addition, gene enrichment analysis on the recurrent abnormal regions indicated NF- kappaB and BMP signaling pathways in HCC development and progression. This study demonstrated that genomic microarray test can be used to distinguish HCC from non- neoplastic cirrhotic nodules and to identify prognostic factors associated with HCC progression using pathologically characterized FFPE samples. Our data support the utility of genomic microarray test for the diagnosis, risk stratification, and pathogenic studies of HCC.
在美国,约50%的肝细胞癌(HCC)由丙型肝炎病毒(HCV)感染引起。HCV感染诱导肝细胞恶性转化的分子机制仍不清楚。HCC有多种临床和病理分期系统,但均未将生物学参数纳入预后预测指标,且尚无标准化的HCC分子分类。为了解HCV相关HCC潜在的致病基因改变,辅助HCC分子分类及患者预后评估,我们使用全基因组芯片,对癌组织及配对的临近肝硬化非肿瘤组织的福尔马林固定石蜡包埋(FFPE)标本DNA进行了HCC DNA拷贝数改变的芯片分析。
我们的结果显示,HCC中最常见的染色体畸变(>5 Mb)为1q(80%)、8q(60%)、7q(40%)、5p(33%)、7p(33%)、Xq(33%)、5q(27%)和Xp(20%)染色体增加,以及17p(40%)、4q21.21 - q26(33%)、8p(33%)、1p36.11 - pter(20%)和9p(20%)染色体缺失。使用STAC算法鉴定出具有统计学意义的较小拷贝数改变(3.9 kb至644 kb),包括FGFR3、RECQL4、NOTCH1、PTEN、TSC2和/或ASPSCR1缺失以及ETV1和/或MAF增加。遗传数据与病理数据的相关性分析显示,1q21.1 - q23.2增加和8q11.1q13.1增加与2 - 4级及中低分化HCC显著相关,5q染色体增加与有血管侵犯的HCC显著相关,而7q染色体增加与I期HCC显著相关。
本研究提供了HCV相关HCC发生的基因组畸变详细图谱,并提出了候选基因。此外,对反复出现异常区域的基因富集分析表明NF-κB和BMP信号通路在HCC发生发展中起作用。本研究表明,基因组芯片检测可用于区分HCC与非肿瘤性肝硬化结节,并使用病理特征明确的FFPE样本识别与HCC进展相关的预后因素。我们的数据支持基因组芯片检测在HCC诊断、风险分层及致病机制研究中的应用。