Abstract 2731: Classification of HCC patient derived xenograft (PDX) models by transcriptome and microRNome profiling, and their resemblance to patients.
Authors: Sheng Guo, Wubin Qian, Jie Cai, Dawei Chen, Jie Yang, Zhun Wang, Xiaoming Song, Taiping Chen, Jean Pierre Wery, Yiyou Chen, Henry QX Li
Journal: Cancer Research (2013)

Abstract Hepatocellular carcinoma (HCC) is a disease of diverse types. Transcriptome analysis recently classified HCC into three major categories with distinct clinical parameters as well as cellular differentiation1. They are S1 (stem-like group with activation of the WNT pathway and TGF-β), S2 (activation of MYC and AKT), and S3 (hepatocyte differentiation). Patient derived xenografts (PDXs) have been suggested to be predictive experimental models (“Patient avatars”) because they have not been in vitro manipulated, and have the original patients’ histopathological and genetic profiles2,3. In order to assess the resemblance of these “avatar” to patients, we performed transcriptome profiling on a collection of HCC-PDXs using the same algorithm1. Twenty-two HCC-PDX models were classified into 3 groups, among which S1 and S2 are more closely related. Using the 572 genes generated from the algorithm, the same classifications were obtained by hierarchical clustering and principal component analysis (PCA), except for two outliers. The results demonstrate that our cohort of HCC-PDXs can be divided into the same three subclasses as those from patient samples1. In addition, Luk et al., recently classified HCC using expression levels of microRNA cluster at 14q32.2 locus, in which a stem-like HCC phenotype was associated with high expression4. We thus also used this criterion to classify our collection of HCC PDXs. The two resulting categories, 14q32.2-hi and 14q32.2-lo, can be compared to the S1, S2, S3 subclasses determined by mRNA profiling described above, in which S1 belongs to 14q32.2-lo and S2/3 belong to 14q32.2-hi (except LI1025, LI1078). The serum α-fetoprotein (AFP) and tumor AFP-mRNA levels were found to be strongly and positively correlated, and also associated with S21 and 14q32.2-hi4, consistent with previous reports1. Six stem-like markers were found not to be associated with S11, nor with 14q32.2-hi4, thus different from the report by Luk et al4. Activation of c-MET was found exclusively in S1 models, consistent with one of previous observations5, but not the other4. When all these models were treated with Sorafenib, a multi-kinase inhibitor, there seemed to be no correlation in the tumor responses between the subclasses. In summary, the data provided insights into the classifications of HCC by mRNA expression1 and 14q32.2 microRNA expression4, partially consistent with existing reports1,2. The results also show distinctive characteristics of our HCC-PDXs that merit further studies. Citation Format: Sheng Guo, Wubin Qian, Jie Cai, Dawei Chen, Jie Yang, Zhun Wang, Xiaoming Song, Taiping Chen, Jean Pierre Wery, Yiyou Chen, Henry QX Li. Classification of HCC patient derived xenograft (PDX) models by transcriptome and microRNome profiling, and their resemblance to patients. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2731. doi:10.1158/1538-7445.AM2013-2731