Olaparib Inhibits Tumor Growth of Hepatoblastoma in Patient Derived Xenograft Models.

BACKGROUND AND AIMS Hepatoblastoma (HBL) is a devastating pediatric liver cancer with multiple treatment options, but it ultimately requires surgery for a cure. The most malicious form of HBL is a chemo-resistant aggressive tumor that is characterized by rapid growth, metastases, and poor response to treatment. Very little is known of the mechanisms of aggressive HBL, and recent focuses have been on developing alternative treatment strategies. In this study, we examined the role of human chromosomal regions, called aggressive liver cancer domains (ALCDs), in liver cancer and evaluated the mechanisms that activate ALCDs in aggressive HBL. RESULTS We found that ALCDs are critical regions of the human genome that are located on all human chromosomes, preferentially in intronic regions of the oncogenes and other cancer-associated genes. In aggressive HBL and in patients with Hepatocellular (HCC), JNK1/2 phosphorylates p53 at Ser6, which leads to the ph-S6-p53 interacting with and delivering the poly(adenosine diphosphate ribose) polymerase 1 (PARP1)/Ku70 complexes on the oncogenes containing ALCDs. The ph-S6-p53-PARP1 complexes open chromatin around ALCDs and activate multiple oncogenic pathways. We found that the inhibition of PARP1 in patient-derived xenografts (PDXs) from aggressive HBL by the Food and Drug Administration (FDA)-approved inhibitor olaparib (Ola) significantly inhibits tumor growth. Additionally, this is associated with the reduction of the ph-S6-p53/PARP1 complexes and subsequent inhibition of ALCD-dependent oncogenes. Studies in cultured cancer cells confirmed that the Ola-mediated inhibition of the ph-S6-p53-PARP1-ALCD axis inhibits proliferation of cancer cells. CONCLUSIONS In this study, we showed that aggressive HBL is moderated by ALCDs, which are activated by the ph-S6-p53/PARP1 pathway. By using the PARP1 inhibitor Ola, we suppressed tumor growth in HBL-PDX models, which demonstrated its utility in future clinical models.