Project description:Sorafenib is the only approved targeted drug for hepatocellular carcinoma (HCC), but its effect on patients’ survival gain is limited and varies over a wide range depending on patho-genetic conditions. Thus, enhancing the efficacy of sorafenib and finding a reliable predictive biomarker are crucuial to achieve efficient control of HCCs. In this study, we employed a systems approach by combining transcriptome analysis of the mRNA changes in HCC cell lines in response to sorafenib with network analysis to investigate the action and resistance mechanism of sorafenib. Gene ontology and gene set analysis revealed that proteotoxic stress and apoptosis modules are activated in the presence of sorafenib. Further analysis of the endoplasmic reticulum (ER) stress network model combined with in vitro experiments showed that introducing an additional stress by treating the orally active protein disulfide isomerase (PDI) inhibitor (PACMA 31) can synergistically increase the efficacy of sorafenib in vitro and in vivo, which was confirmed using a mouse xenograft model. We also found that HCC patients with high PDI expression show resistance to sorafenib and poor clinical outcomes, compared to the low PDI expression group. These results suggest that PDI is a promising therapeutic target for enhancing the efficacy of sorafenib and can also be a biomarker for predicting sorafenib responsiveness.
Project description:Sorafenib is the only approved targeted drug for hepatocellular carcinoma (HCC), but its effect on patients’ survival gain is limited and varies over a wide range depending on patho-genetic conditions. Thus, enhancing the efficacy of sorafenib and finding a reliable predictive biomarker are crucuial to achieve efficient control of HCCs. In this study, we employed a systems approach by combining transcriptome analysis of the mRNA changes in HCC cell lines in response to sorafenib with network analysis to investigate the action and resistance mechanism of sorafenib. Gene ontology and gene set analysis revealed that proteotoxic stress and apoptosis modules are activated in the presence of sorafenib. Further analysis of the endoplasmic reticulum (ER) stress network model combined with in vitro experiments showed that introducing an additional stress by treating the orally active protein disulfide isomerase (PDI) inhibitor (PACMA 31) can synergistically increase the efficacy of sorafenib in vitro and in vivo, which was confirmed using a mouse xenograft model. We also found that HCC patients with high PDI expression show resistance to sorafenib and poor clinical outcomes, compared to the low PDI expression group. These results suggest that PDI is a promising therapeutic target for enhancing the efficacy of sorafenib and can also be a biomarker for predicting sorafenib responsiveness.
Project description:Sorafenib is the only approved targeted drug for hepatocellular carcinoma (HCC), but its effect on patients’ survival gain is limited and varies over a wide range depending on patho-genetic conditions. Thus, enhancing the efficacy of sorafenib and finding a reliable predictive biomarker are crucuial to achieve efficient control of HCCs. In this study, we employed a systems approach by combining transcriptome analysis of the mRNA changes in HCC cell lines in response to sorafenib with network analysis to investigate the action and resistance mechanism of sorafenib. Gene ontology and gene set analysis revealed that proteotoxic stress and apoptosis modules are activated in the presence of sorafenib. Further analysis of the endoplasmic reticulum (ER) stress network model combined with in vitro experiments showed that introducing an additional stress by treating the orally active protein disulfide isomerase (PDI) inhibitor (PACMA 31) can synergistically increase the efficacy of sorafenib in vitro and in vivo, which was confirmed using a mouse xenograft model. We also found that HCC patients with high PDI expression show resistance to sorafenib and poor clinical outcomes, compared to the low PDI expression group. These results suggest that PDI is a promising therapeutic target for enhancing the efficacy of sorafenib and can also be a biomarker for predicting sorafenib responsiveness.
Project description:Sorafenib is the only approved targeted drug for hepatocellular carcinoma (HCC), but its effect on patients’ survival gain is limited and varies over a wide range depending on patho-genetic conditions. Thus, enhancing the efficacy of sorafenib and finding a reliable predictive biomarker are crucuial to achieve efficient control of HCCs. In this study, we employed a systems approach by combining transcriptome analysis of the mRNA changes in HCC cell lines in response to sorafenib with network analysis to investigate the action and resistance mechanism of sorafenib. Gene ontology and gene set analysis revealed that proteotoxic stress and apoptosis modules are activated in the presence of sorafenib. Further analysis of the endoplasmic reticulum (ER) stress network model combined with in vitro experiments showed that introducing an additional stress by treating the orally active protein disulfide isomerase (PDI) inhibitor (PACMA 31) can synergistically increase the efficacy of sorafenib in vitro and in vivo, which was confirmed using a mouse xenograft model. We also found that HCC patients with high PDI expression show resistance to sorafenib and poor clinical outcomes, compared to the low PDI expression group. These results suggest that PDI is a promising therapeutic target for enhancing the efficacy of sorafenib and can also be a biomarker for predicting sorafenib responsiveness.
Project description:sorafenib is the treatment of reference for hepatocellular carcinoma (HCC). We applied sorafenib on the human HCC cell line Huh7 and the subclone shRb, carrying a stable knock-down of the expression of the RB1 gene, a key regulator of liver carcinogenesis. Our aim was to better understand the physiologic and metabolic consequences of the exposure of HCC cells to sorafenib. We used microarrays to detail the global programme of gene expression at an early time point (9h) after exposure to sorafenib Whole-genome microarrays were used to study the transcriptome of Huh7 cells exposed to Sorafenib
Project description:Molecular targeted therapy has shown promise as a treatment for advanced hepatocellular carcinoma (HCC). Sorafenib, a multikinase inhibitor, recently received FDA approval for the treatment of advanced HCC. However, although sorafenib is well tolerated, concern for its safety has been expressed. Celecoxib (CelebrexM-BM-.) is a selective cyclooxygenase-2 (COX-2) inhibitor wich exhibits antitumor effects in human HCC cells. The present study examined the interaction between celecoxib and sorafenib in two human liver tumor cell lines HepG2 and Huh7. Our data showed that each inhibitor reduced cell growth and the combination of celecoxib with sorafenib synergistically inhibited cell growth and increased apoptosis. To better understand the molecular mechanisms underlying the synergistic antitumor activity of combination, we investigated the expression profile of the combination-treated liver cancer cell lines, using microarray analysis. Combination treatment significantly altered expression levels of 1,986 and 2,483 transcripts in HepG2 and Huh7 cells, respectively. Genes, functionally involved in cell death, signal transduction and regulation of transcription were predominantly up-regulated, while genes implicated in metabolism, cell cycle control and DNA replication and repair were mainly down-regulated upon treatment. However, combination-treated HCC cell line displayed specificity in the expression and activity of crucial factors involved in hepatocarcinogenesis. The altered expression of some of these genes was confirmed by semiquantitative and quantitative RT-PCR and by Western blotting. Many novel genes emerged from our transcriptomics analyses, and further functional analyses may determine whether these genes can serve as potential molecular targets for more effective anti-HCC strategies. To identify new potential mechanisms of combined action of celecoxib and sorafenib, their effects on global gene expression in both cell lines were investigated and compared using the DNA microarray technology. Agilent 44K Human Whole Genome Oligonucleotide Microarrays (containing ~44,000 genes) were used to identify global gene expression changes in the HepG2 and Huh7 hepatocellular carcinoma (HCC) cell lines, following simultaneous treatment with 50 M-BM-5M celecoxib and 7.5 M-BM-5M sorafenib for 48 hours. All microarray experiments (a total of four) were performed in duplicates applying dye-swaps to avoid labeling bias.