Classification of Human Hepatocellular Carcinoma

将全球方法应用于分析包括人类疾病在内的复杂生物现象可能是有用的这一概念，在后基因组领域获得了相当大的支持。例如，几项独立研究表明，通过检查临床或实验肿瘤样本的全基因组转录图谱，可以识别以前未被识别的癌症不同亚型。事实上，从肿瘤细胞系和原发肿瘤的微阵列分析中获得的表达谱已被用于对包括黑色素瘤、乳腺癌、白血病和淋巴瘤在内的几种人类癌症进行分类。同样，通过比较基因组杂交(CGH)对肿瘤疾病中染色体变化的全球分析提供了整个基因组中DNA序列的得失的位置识别。在我们实验室最近对19个肝癌细胞系进行的CGH分析中，定义了一种独特的基因组不平衡模式，除了揭示DNA得失的新的复发区域外，还证实了先前CGH在原发性肝癌肿瘤中发现的基因组改变。这些结果表明，人肝细胞癌细胞系基本上保留了原发肿瘤的基因组变化。 我们目前正在使用cDNA微阵列技术来确定人类和小鼠肝脏肿瘤的全球表达谱。我们的长期目标是使用表达谱来构建人类和小鼠肝脏肿瘤的分子分类。在我们最初的方法中，我们使用了以前用CGH表征的肝癌细胞系，通过cDNA微阵列对全球基因表达进行了系统的表征。讨论了两个问题：(1)肝癌细胞系是否可用于定义可用于定义在肝脏肿瘤发展中至关重要的相互作用途径的表达模块；(2)转录组的表达模式是否反映了肝癌细胞系中保留的结构基因组变化。目前的研究结果显示，肝细胞癌有两种不同的亚型，它们通过数百种不同基因的差异表达而相互区分。值得注意的是，甲胎蛋白的表达与肝细胞癌的分子亚型高度相关。我们还鉴定了一组共同表达的已知和未知基因，这些基因是针对肝细胞癌亚型的。对每条染色体的基因表达模式的比较表明，肝癌内存在区域范围的表达偏见，反映了细胞系中的染色体异常。这些结果不仅确定了未被识别的肝细胞癌亚型，还为每一亚型提供了潜在的分子标记，可用于诊断和/或治疗目的。

The notion that application of global approaches to the analysis of complex biological phenomena including human diseases may be useful has gained considerable strength in the postgenome area. For example, several independent studies have illustrated that previously unrecognized distinct subtypes of cancers could be identified by examining the genome-wide transcriptional profiles of clinical or experimental tumor samples. In fact, expression profiles obtained from microarray analysis of both tumor cell lines and primary tumors have been used to classify several human cancers including melanoma, breast cancer, leukemias and lymphomas. Similarly, global analysis of chromosomal alterations in neoplastic diseases by comparative genomic hybridization (CGH) has provided positional identifications of gains and losses of DNA sequences in the entire genome. In a recent study from our laboratory using CGH analysis of 19 HCC cell lines, a distinct pattern of genomic imbalance was defined that, in addition to revealing novel recurrent regions of DNA gains and losses, also confirmed genomic alterations previously identified by CGH in primary HCC tumors. These results suggest that cell lines derived from human HCC essentially retain the genomic alterations of the primary tumors. We are currently using the cDNA microarray technique to define global expression profiles in liver tumors from both human and mouse. Our long-term goal is to use the expression profiles to construct a molecular classification of human and mouse liver tumors. In our initial approach we have used the HCC cell lines, previously characterized by CGH, to conduct a systematic characterization of global gene expression by cDNA microarray. Two questions were addressed: (1) are HCC cell lines useful in defining expression modules that can be utilized to define interactive pathways critical in development of liver tumors; and (2) is the structural genomic alterations retained in the HCC cell lines reflected in the expression patterns of the transcriptome. Current results have revealed two distinct subtypes of hepatocellular carcinoma (HCC) that are distinguished from each other by the differential expression of hundreds of different genes. Remarkably, expression of a-fetoprotein was highly correlated with the molecular subtypes of HCC. Sets of co-expressed known and unknown genes that are specific for the subtypes of HCC were also identified. Comparison of gene expression patterns for each chromosome revealed region-wide expression bias within HCC, reflecting chromosomal aberrations in cell lines. These results not only identified unrecognized subtypes of HCC, but also provided potential molecular markers for each subtype that can be useful for diagnostic and/or therapeutic purposes.