Detection of network structure changes by graphical chain modeling: A case study of hepatitis C virus-related hepatocellular carcinoma

One of the most characteristic features of biological molecular networks is that the network structure itself changes, depending on the cellular environment. Indeed, activated molecules show a variety of responses to distinctive cell conditions, and subsequently the network structures of active molecules also change. Here we present an approach to trace the network structure changes by using the graphical chain model developed from the gene expression data. The previous procedure for applying the graphical chain model to the expression profiles of a limited number of genes has been improved to analyze the entire set of genes. Furthermore, the chain model has been rearranged according to the association strength, and was scrutinized to identify the candidates of essential gene-gene relationships for the network changes, by using the path consistency algorithm. The improved procedure was applied to the expression profiles of 8,427 genes, which were measured in two distinctive stages of liver cancer progression. As a result, the chain model of the 18 gene cluster relationships with strong associations was inferred, in which the coordination of clusters was described in the cell stage progression, and the gene-gene relationships between known cancer-related genes causing the progression were further refined. Thus, the present procedure is a useful method to model the network structure changes in the cell stage progression, and to clarify the gene candidates for the progression. ©2009 IEEE

Gene Systems Network Inferred from Expression Profiles in Hepatocellular Carcinogenesis by Graphical Gaussian Model

Hepatocellular carcinoma (HCC) in a liver with advanced-stage chronic hepatitis C (CHC) is induced by hepatitis C virus, which chronically infects about 170 million people worldwide. To elucidate the associations between gene groups in hepatocellular carcinogenesis, we analyzed the profiles of the genes characteristically expressed in the CHC and HCC cell stages by a statistical method for inferring the network between gene systems based on the graphical Gaussian model. A systematic evaluation of the inferred network in terms of the biological knowledge revealed that the inferred network was strongly involved in the known gene-gene interactions with high significance (P<10−4), and that the clusters characterized by different cancer-related responses were associated with those of the gene groups related to metabolic pathways and morphological events. Although some relationships in the network remain to be interpreted, the analyses revealed a snapshot of the orchestrated expression of cancer-related groups and some pathways related with metabolisms and morphological events in hepatocellular carcinogenesis, and thus provide possible clues on the disease mechanism and insights that address the gap between molecular and clinical assessments

Hepatic ISG expression is associated with genetic variation in interleukin 28B and the outcome of IFN therapy for chronic hepatitis C

金沢大学医薬保健研究域医学系Background & Aims: Multiple viral and host factors are related to the treatment response to pegylated-interferon and ribavirin combination therapy; however, the clinical relevance and relationship of these factors have not yet been fully evaluated. Methods: We studied 168 patients with chronic hepatitis C who received pegylated-interferon and ribavirin combination therapy. Gene expression profiles in the livers of 91 patients were analyzed using an Affymetrix genechip (Affymetrix, Santa Clara, CA). The expression of interferon-stimulated genes (ISGs) was evaluated in all samples by real-time polymerase chain reaction. Genetic variation in interleukin 28B (IL28B; rs8099917) was determined in 91 patients. Results: Gene expression profiling of the liver differentiated patients into 2 groups: patients with up-regulated ISGs and patients with down-regulated ISGs. A high proportion of patients with no response to treatment was found in the up-regulated ISGs group (P = .002). Multivariate logistic regression analysis showed that ISGs (<3.5) (odds ratio [OR], 16.2; P < .001), fibrosis stage (F1-F2) (OR, 4.18; P = .003), and ISDR mutation (<2) (OR, 5.09; P = .003) were strongly associated with the viral response. The IL28B polymorphism of 91 patients showed that 66% were major homozygotes (TT), 30% were heterozygotes (TG), and 4% were minor homozygotes (GG). Interestingly, hepatic ISGs were associated with the IL28B polymorphism (OR, 18.1; P < .001), and its expression was significantly higher in patients with the minor genotype (TG or GG) than in those with the major genotype (TT). Conclusions: The expression of hepatic ISGs is strongly associated with treatment response and genetic variation of IL28B. The differential role of host and viral factors as predicting factors may also be present. © 2010 AGA Institute

Effects of Carbon-ion Beam and Lapatinib Alone, or in Combination in HER2 Positive Breast Cancer Stem-like Cells

In the present study, we attempt to investigate effects of carbon-ion beam alone, or in combination with lapatinib, a dual tyrosine kinase inhibitor, on targeting HER2-positive breast cancer stem-like cells (CSCs). Spheroid formation assays confirmed that ESA+/CD24- cells have CSC properties compared to ESA-/CD24+ cells in HER2-positive breast cancer cells. Carbon-ion beam combined with lapatinib significantly suppressed spheroid formation compared to X-rays combined with lapatinib or carbon ion beam alone. Carbon-ion beam combined with lapatinib greatly enhanced apoptosis and also induced autophagy-related expression of Beclin1 and LC3 compared to carbon-ion beam alone, X-rays alone, or X-rays combined with lapatinib. In addition, a large-sized gammaH2AX foci in CSCs were induced by carbon ion beam combined with lapatinib treatment in CSCs compared to cells receiving X-rays or carbon-ion beam alone. In conclusion, combination of carbon-ion beam irradiation and lapatinib has a high potential to kill HER2-positive breast CSCs, causing severe irreparable DNA damage, enhanced autophagy, and apoptosis.第78回日本癌学会学術総

Combination of carbon-ion beam and dual tyrosine kinase inhibitor, lapatinib, effectively destroys HER2 positive breast cancer stem-like cells

To investigate whether carbon-ion beam alone, or in combination with lapatinib, has a beneficial effect in targeting HER2-positive breast cancer stem-like cells (CSCs) compared to that of X-rays, human breast CSCs derived from BT474 and SKBR3 cell lines were treated with a carbon-ion beam or X-rays irradiation alone or in combination with lapatinib, and then cell viability, spheroid formation assays, apoptotic analyses, gene expression analysis of related genes, and immunofluorescent gamma-H2AX foci assays were performed. Spheroid formation assays confirmed that ESA+/CD24- cells have CSC properties compared to ESA-/CD24+ cells. CSCs were more highly enriched after X-ray irradiation combined with lapatinib, whereas carbon-ion beam combined with lapatinib significantly decreased the proportion of CSCs. Carbon-ion beam combined with lapatinib significantly suppressed spheroid formation compared to X-rays combined with lapatinib or carbon ion beam alone. Cell cycle analysis showed that carbon ion beam combined with lapatinib predominantly enhanced sub-G1 and G2/M arrested population compared to that of carbon-ion beam, X-ray treatments alone. Carbon-ion beam combined with lapatinib significantly enhanced apoptosis and carbon-ion beam alone dose-dependently increased autophagy-related expression of Beclin1 and in combination with lapatinib greatly enhanced ATG7 expression at protein levels. In addition, a large sized gamma H2AX foci in CSCs were induced by carbon ion beam combined with lapatinib treatment in CSCs compared to cells receiving X-rays or carbon-ion beam alone. Altogether, combination of carbon-ion beam irradiation and lapatinib has a high potential to kill HER2-positive breast CSCs, causing severe irreparable DNA damage, enhanced autophagy, and apoptosis