Establishment of a Patient‐Derived Xenograft Tumor From Hepatitis C–Associated Liver Cancer and Evaluation of Imatinib Treatment Efficacy. Issue 2 (25th August 2020) - Nazzal, Mustafa; Sur, Subhayan; Steele, Robert; Khatun, Mousumi; Patra, Tapas; Phillips, Nancy; Long, John; Ray, Ranjit; Ray, Ratna B.
Abstract : Background and Aims: Chronic hepatitis C virus (HCV) infection is one of the major causal factors for hepatocellular carcinoma (HCC). The treatment options for HCC are limited for lack of a convenient animal model for study in HCV infection and liver pathogenesis. This study aimed to develop a patient‐derived xenograft (PDX) tumor in mice by using a tumor from a patient with HCV‐associated HCC and evaluating this model's therapeutic potential. Approach and Results: After resection of the primary tumor from the patient liver, excess viable tumor was implanted into highly immunodeficient mice. A mouse xenograft tumor line was developed, and the tumor was successfully passaged for at least three rounds in immunodeficient mice. The patient's primary tumor and the mouse xenografts were histologically similar. Genetic profiling by short‐tandem‐repeat analysis verified that the HCC‐PDX model was derived from the HCC clinical specimen. HCV RNA present in the patient liver specimen was undetectable after passage as xenograft tumors in mice. Human albumin, α1 ‐antitrypsin, glypican‐3, α–smooth muscle actin, and collagen type 1A2 markers were detected in human original tumor tissues and xenograft tumors. Both the patient primary tumor and the xenograft tumors had a significantly higher level of receptor tyrosine kinase (c‐Kit) mRNA. Treatment of HCC‐PDX xenograft tumor–bearing mice with the c‐Kit inhibitor imatinib significantly reduced tumor growth and phospho‐Akt and cyclin D1 expression, as compared with untreated control tumors. Conclusions: Our results demonstrated establishment of an HCV‐associated HCC‐PDX model as a powerful tool for evaluating candidate drugs. Information on molecular changes in cancer‐specific gene expression facilitates efficient targeted therapies and treatment strategies.