Oncogenetic tree modeling of human hepatocarcinogenesis

Abstract

Classical comparative genomic hybridization (CGH) has been used to identify recurrent genomic alterations in human HCC. As hepatocarcinogenesis is considered as a stepwise process, we applied oncogenetic tree modeling on all available classical CGH data to determine occurrence of genetic alterations over time. Nine losses (1p, 4q, 6q, 8p, 9p, 13q, 16p, 16q and 17p) and ten gains (1q, 5p, 6p, 7p, 7q, 8q, 17q, 20p, 20q and Xq) of genomic information were used to build the oncogenetic tree model. Whereas gains of 1q and 8q together with losses of 8p formed a cluster that represents early etiology-independent alterations, the associations of gains at 6q and 17q as well as losses of 6p and 9p were observed during tumor progression. HBV-induced HCCs had significantly more chromosomal aberrations compared to HBV-negative tumors. Losses of 1p, 4q and 13q were associated with HBV-induced HCCs, whereas virus-negative HCCs showed an association of gains at 5p, 7, 20q and Xq. Using five aberrations that were significantly associated with tumor dedifferentiation a robust progression model of stepwise human hepatocarcinogensis (gain 1q → gain 8q → loss 4q → loss 16q → loss 13q) was developed. In silico analysis revealed that protumorigenic candidate genes have been identified for each recurrently altered hotspot. Thus, oncogenic candidate genes that are coded on chromosome arms 1q and 8q are promising targets for the prevention of malignant transformation and the development of biomarkers for the early diagnosis of human HCC that may significantly improve the treatment options and thus prognosis of HCC patients.