Oncogenetic tree modeling of human hepatocarcinogenesis

Abstract

Classical Comparative Genomic Hybridization (CGH) has been used to identify recurrent genomic alterations in human HCC. Since hepatocarcinogenesis is considered a step-wise process, we applied oncogenetic tree modeling on all currently available classical CGH data to determine occurrence of genetic alterations over time. Nine losses (1p, 4q, 6q, 8p, 9p, 13q, 16p, 16q, 17p) and ten gains (1q, 5p, 6p, 7p, 7q, 8q, 17q, 20p, 20q, Xq) of genomic information were detected in more than 10% of cases and were selected 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 later during tumor progression. HBV-induced HCCs had significantly more chromosomal aberrations compared to HBV-negative tumors. Losses of 1p, 4q, and 13q were typically associated in HBV-induced HCCs, while 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 step-wise 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.