Screening for TGFB Signaling Regulator expression in human HCC

Hepatocellular carcinoma (HCC) is one of the most deadly malignancies worldwide. Scientists have been studying the molecular mechanisms of HCC for years, but the understanding of it remains incomplete and scattered across the literature at different molecular levels. High-throughput omics technologies have been widely applied and provide large amounts of data. We have been studying the TGF-β signaling pathway in liver diseases for years, which has major impact on disease progression and hepatocarcinogenesis. TGF-β effects are highly cell type and context dependent and downstream signaling is intricately controlled by multiple positive and negative regulators at all levels from cell membrane to the nucleus. A large list of such TGF-β signaling regulators (TSRs) were recently identified with RNAi screens in HaCat cells, using a Smad binding element (SBE) luciferase reporter as a readout. We aim to translate these findings to liver cancer and to dissect relevant mechanisms that facilitate TGF-β related hepatocarcinogenesis, which may be used for predictions or as therapeutic targets.

Therefore, with a Bioinformatic approach, we have screened HCC expression databases either publicly available, generated within the SFB TRR77 on Liver Cancer or from our own collaborative projects, for expression of the above candidate TSRs. In total, HCC samples from 437 patients were compared to non-tumor surrounding tissue or normal liver samples. Furthermore, TSR expression was analysed in hepatic stellate cells upon culture activation and from BDL and CCl4 mouse models. From our in silico findings, we could reduce our initial TSR list to 52 genes that display expression modulation, when comparing HCC tissue with surrounding non-tumor tissue of the same patients or as compared to normal liver tissue samples in the different patient cohorts investigated. 30 of these genes are down-regulated while 22 are up-regulated in HCC, and we have selected some interesting candidates for further in vitro and in vivo analysis. For example, CTHRC1 [Up-regulated; ≈ 10 fold change average (FCA)], Hepcidine (Down-regulated; ≈ 2 FCA), BMPER (Down-regulated; ≈ 1.6 FCA), Dermatopontin (Down-regulated; ≈ 1.2 FCA), Decorin (Down-regulated; ≈ 2 FCA), SPARC (Up-regulated; ≈ 1.7 FCA) and CD109 (Up-regulated; ≈ 12 FCA). We will now correlate these in silico data with HCC stages and clinical outcomes. Based on our bioinformatics analysis, we have setup a human and mouse TSR panel that we will experimentally estimate in a Fluidigm qRT-PCR platform with our own patients collective (140 HCC patients), genetic (TGF-α/c-Myc, Mdr2ko) and chemical (DEN) mouse models of liver cancer. Furthermore, we are investigating HCC cell lines to delineate mechanisms that may connect our hits with TGF-β signaling and hepatocarcinogenesis.