Genetic predisposition of responsiveness to therapy for chronic hepatitis C

Progress and Challenges in the Use of a Liver-on-a-Chip for Hepatotropic Infectious Diseases

The liver is a target organ of life-threatening pathogens and prominently contributes to the variation in drug responses and drug-induced liver injury among patients. Currently available drugs significantly decrease the morbidity and mortality of liver-dwelling pathogens worldwide; however, emerging clinical evidence reveals the importance of host factors in the design of safe and effective therapies for individuals, known as personalized medicine. Given the primary adherence of cells in conventional two-dimensional culture, the use of these one-size-fit-to-all models in preclinical drug development can lead to substantial failures in assessing therapeutic safety and efficacy. Advances in stem cell biology, bioengineering and material sciences allow us to develop a more physiologically relevant model that is capable of recapitulating the human liver. This report reviews the current use of liver-on-a-chip models of hepatotropic infectious diseases in the context of precision medicine including hepatitis virus and malaria parasites, assesses patient-specific responses to antiviral drugs, and designs personalized therapeutic treatments to address the need for a personalized liver-like model. Second, most organs-on-chips lack a monitoring system for cell functions in real time; thus, the review discusses recent advances and challenges in combining liver-on-a-chip technology with biosensors for assessing hepatocyte viability and functions. Prospectively, the biosensor-integrated liver-on-a-chip device would provide novel biological insights that could accelerate the development of novel therapeutic compounds.

ADAR RNA Modifications, the Epitranscriptome and Innate Immunity

Modified bases act as marks on cellular RNAs so that they can be distinguished from foreign RNAs, reducing innate immune responses to endogenous RNA. In humans, mutations giving reduced levels of one base modification, adenosine-to-inosine deamination, cause a viral infection mimic syndrome, a congenital encephalitis with aberrant interferon induction. These Aicardi-Goutières syndrome 6 mutations affect adenosine deaminase acting on RNA 1 (ADAR1), which generates inosines in endogenous double-stranded (ds)RNA. The inosine base alters dsRNA structure to prevent aberrant activation of antiviral cytosolic helicase RIG-I-like receptors. We review how effects of inosines, ADARs, and other modified bases have been shown to be important in innate immunity and cancer.

Pulmonary toxicity and RNA sequencing analyses of mouse in response to exposure to cellulose nanofibrils

OBJECTIVE

The growing applications of nanocelluloses in the fields of advanced nanocomposites, electronics, and medical devices necessitate investigation of their potential adverse effects on human health. The lungs are the primary and the most important route for the entry of nanocelluloses into the human body in occupational settings. However, data on the pulmonary toxicity of cellulose nanofibrils (CNFs) and its molecular mechanism are limited. This study investigated the pulmonary toxicity of CNFs and its genomic expression using the RNA sequencing approach.

MATERIALS AND METHODS

Female C57BL/6 mice were administered CNFs at 50 μg/mouse by oropharyngeal aspiration. Samples were collected at 3 and 14 days after exposure to CNFs (DAEC).

RESULTS

At three DAEC, the microscopic sections of lungs revealed a significant inflammatory response. In terms of gene expression alterations, 94 genes were up-regulated, and 107 genes were down-regulated. Most of these differentially expressed genes were involved in the inflammatory and immune responses, including chemokines, NK cells, killer cell lectin-like receptors, CD antigens, T cell-specific GTPases, immunity-related GTPase family M members, and interferon-induced proteins encoding genes. However, only 9 and 26 genes at 14 DAEC were significantly up- and down-regulated, respectively.

CONCLUSIONS

The pathological analysis of lung sections and the analysis of sequencing data suggested that the homeostasis of mice lungs was restored at 14 DAEC. The findings of this study provide insights into the pulmonary toxicity, and underlying toxicological mechanisms, caused by exposure to CNFs, and are useful for the assessment of the potential toxicity of nanocelluloses.

Pharmacogenomics in Asia: a systematic review on current trends and novel discoveries

While early pharmacogenomic studies have primarily been carried out in Western populations, there has been a notable increase in the number of Asian studies over the past decade. We systematically reviewed all pharmacogenomic studies conducted in Asia published before 2016 to highlight trends and identify research gaps in Asia. We observed that pharmacogenomic research in Asia was dominated by larger developed countries, notably Japan and Korea, and mainly driven by local researchers. Studies were focused on drugs acting on the CNS, chemotherapeutics and anticoagulants. Significantly, several novel pharmacogenomic associations have emerged from Asian studies. These developments are highly encouraging for the strength of regional scientific and clinical community and propound the importance of discovery studies in different populations.

TGF-β receptor maintains CD4 T helper cell identity during chronic viral infections

Suppression of CD8 and CD4 T cells is a hallmark in chronic viral infections, including hepatitis C and HIV. While multiple pathways are known to inhibit CD8 T cells, the host molecules that restrict CD4 T cell responses are less understood. Here, we used inducible and CD4 T cell-specific deletion of the gene encoding the TGF-β receptor during chronic lymphocytic choriomeningitis virus infection in mice, and determined that TGF-β signaling restricted proliferation and terminal differentiation of antiviral CD4 T cells. TGF-β signaling also inhibited a cytotoxic program that includes granzymes and perforin expression at both early and late stages of infection in vivo and repressed the transcription factor eomesodermin. Overexpression of eomesodermin was sufficient to recapitulate in great part the phenotype of TGF-β receptor-deficient CD4 T cells, while SMAD4 was necessary for CD4 T cell accumulation and differentiation. TGF-β signaling also restricted accumulation and differentiation of CD4 T cells and reduced the expression of cytotoxic molecules in mice and humans infected with other persistent viruses. These data uncovered an eomesodermin-driven CD4 T cell program that is continuously suppressed by TGF-β signaling. During chronic viral infection, this program limits CD4 T cell responses while maintaining CD4 T helper cell identity.

Genetic polymorphisms associated with rubella virus-specific cellular immunity following MMR vaccination

Rubella virus causes a relatively benign disease in most cases, although infection during pregnancy can result in serious birth defects. An effective vaccine has been available since the early 1970s and outbreaks typically do not occur among highly vaccinated (≥2 doses) populations. Nevertheless, considerable inter-individual variation in immune response to rubella immunization does exist, with single-dose seroconversion rates ~95 %. Understanding the mechanisms behind this variability may provide important insights into rubella immunity. In the current study, we examined associations between single nucleotide polymorphisms (SNPs) in selected cytokine, cytokine receptor, and innate/antiviral genes and immune responses following rubella vaccination in order to understand genetic influences on vaccine response. Our approach consisted of a discovery cohort of 887 subjects aged 11-22 at the time of enrollment and a replication cohort of 542 older adolescents and young adults (age 18-40). Our data indicate that SNPs near the butyrophilin genes (BTN3A3/BTN2A1) and cytokine receptors (IL10RB/IFNAR1) are associated with variations in IFNγ secretion and that multiple SNPs in the PVR gene, as well as SNPs located in the ADAR gene, exhibit significant associations with rubella virus-specific IL-6 secretion. This information may be useful, not only in furthering our understanding immune responses to rubella vaccine, but also in identifying key pathways for targeted adjuvant use to boost immunity in those with weak or absent immunity following vaccination.

Role of viral and host factors in interferon based therapy of hepatitis C virus infection

The current standard of care (SOC) for hepatitis C virus (HCV) infection is the combination of pegylated interferon (PEG-IFN), Ribavirin and protease inhibitor for HCV genotype 1. Nevertheless, this treatment is successful only in 70-80% of the patients. In addition, the treatment is not economical and is of immense physical burden for the subject. It has been established now, that virus-host interactions play a significant role in determining treatment outcomes. Therefore identifying biological markers that may predict the treatment response and hence treatment outcome would be useful. Both IFN and Ribavirin mainly act by modulating the immune system of the patient. Therefore, the treatment response is influenced by genetic variations of the human as well as the HCV genome. The goal of this review article is to summarize the impact of recent scientific advances in this area regarding the understanding of human and HCV genetic variations and their effect on treatment outcomes. Google scholar and PubMed have been used for literature research. Among the host factors, the most prominent associations are polymorphisms within the region of the interleukin 28B (IL28B) gene, but variations in other cytokine genes have also been linked with the treatment outcome. Among the viral factors, HCV genotypes are noteworthy. Moreover, for sustained virological responses (SVR), variations in core, p7, non-structural 2 (NS2), NS3 and NS5A genes are also important. However, all considered single nucleotide polymorphisms (SNPs) of IL28B and viral genotypes are the most important predictors for interferon based therapy of HCV infection.

ADARs: viruses and innate immunity

Double-stranded RNA (dsRNA) functions both as a substrate of ADARs and also as a molecular trigger of innate immune responses. ADARs, adenosine deaminases that act on RNA, catalyze the deamination of adenosine (A) to produce inosine (I) in dsRNA. ADARs thereby can destablize RNA structures, because the generated I:U mismatch pairs are less stable than A:U base pairs. Additionally, I is read as G instead of A by ribosomes during translation and by viral RNA-dependent RNA polymerases during RNA replication. Members of several virus families have the capacity to produce dsRNA during viral genome transcription and replication. Sequence changes (A-G, and U-C) characteristic of A-I editing can occur during virus growth and persistence. Foreign viral dsRNA also mediates both the induction and the action of interferons. In this chapter our current understanding of the role and significance of ADARs in the context of innate immunity, and as determinants of the outcome of viral infection, will be considered.

Mechanisms of non-response to antiviral treatment in chronic hepatitis C

Treatment of chronic hepatitis C virus (HCV) infection has substantially evolved over the past decade after the Consensus Conference organized by the European Association for the Study of the Liver in 1999. Since then, the standard of care (SOC) for patients with chronic hepatitis C has been the combination of pegylated interferon (pegIFN) alpha-2a or -2b and ribavirin. In patients infected with HCV genotype 1, by far the most frequent HCV genotype worldwide, such treatment leads to a cure of infection in only 40% to 50% of cases. Several factors have been identified to play a role in the outcome of therapy, including the treatment schedule, disease characteristics, viral, and host factors. Human genetic factors have been identified by a recent landmark discovery. However, these factors only partly explain the ability of IFN and ribavirin therapy to cure HCV infection. Several studies have demonstrated that, in non-responders, interferon-stimulated genes were up-regulated prior to therapy through unclear mechanisms. These findings, together with clinical, biochemical and histological data, may help better identify responders before starting therapy. This becomes particularly important as the standard treatment is physically and economically demanding. The future treatment of patients infected with HCV genotype 1 will be based on the combination of pegIFN and ribavirin with a protease inhibitor, telaprevir or boceprevir. Promising results of this triple combination in phase III clinical trials have been recently reported at the Liver Meeting 2010. With this therapy, higher cure rates will be achieved, but specific issues will be raised, such as the emergence of resistance to the protease inhibitors. The goal of this review is to discuss mechanisms involved in the non-response to current and future standard treatments.

Atopy history and the genomics of wheezing after influenza vaccination in children 6-59 months of age

BACKGROUND

A multinational clinical trial compared the safety and efficacy of intranasal trivalent live attenuated influenza vaccine (LAIV) with intramuscular trivalent inactivated vaccine (TIV) in very young children prior to the 2004-5 influenza season [1]. Wheezing was noted more often in recipients of LAIV and laboratory-confirmed influenza infection was noted more often in recipients of TIV. We sought to determine whether epidemiologic or genetic factors were associated with these outcomes.

METHODS

Atopy surveys and DNA collections were performed in trial participants at two United States sites, Nashville, TN and Boston, MA. DNA samples were genotyped on Illumina Infinium 610 or 660-Quad. Standard allelic tests of association were performed.

RESULTS

At the Nashville and Boston sites, a total of 99 children completed the trial, 6 (1 TIV, 5 LAIV) developed medically attended wheezing within 42 days following vaccination, and 8 (5 TIV, 3 LAIV) developed laboratory-confirmed influenza during the season. Eighty-one surveys and 70 DNA samples were collected. Family history of asthma (p=0.001) was associated with wheezing after vaccination. Of 468,458 single nucleotide polymorphisms tested in the genome-wide association study (GWAS), none achieved genome-wide significance for either wheezing after vaccination or laboratory-confirmed influenza infection.

CONCLUSIONS

Family history of asthma appears to be a risk factor for wheezing after influenza vaccination. Given the limitations of the sample size, our pilot study demonstrated the feasibility of performing a GWAS but was not able to determine genetic polymorphisms associated with wheezing after influenza immunization.

Evolution of interferon-based therapy for chronic hepatitis C

Since 1986, interferon-alfa (IFN-α) monotherapy has been administered for patients with chronic hepatitis C (CHC). However, sustained response rate is only about 8% to 9%. Subsequent introduction of ribavirin in combination with IFN-α was a major breakthrough in the treatment of CHC. Sustained virological responses (SVRs) rate is about 30% in hepatitis C virus genotype 1 (HCV-1) patients, and is about 65% in HCV-2 or -3 patients. After 2000, pegylated interferon (PegIFN) much improved the rates of SVR. Presently, PegIFN-α-ribavirin combination therapy has been current standard of care for patients infected with HCV. In patients with HCV-1, treatment for 48 weeks is optimal, but 24 weeks of treatment is sufficient in HCV-2 or -3 infected patients. Clinical factors have been identified as predictors for the efficacy of the IFN-based therapy. The baseline factor most strongly predictive of an SVR is the presence of HCV-2 or -3 infections. Rapid virological response (RVR) is the single best predictor of an SVR to PegIFN-ribavirin therapy. If patients can't achieve a RVR but achieve a complete early virological response (cEVR), treatment with current standard of care can provide more than 90% SVR rate. HCV-1 patients who do not achieve an EVR should discontinue the therapy. Recent advances of protease inhibitor may contribute the development of a novel triple combination therapy.

Hepatitis C: viral and host factors associated with non-response to pegylated interferon plus ribavirin

Treatment for chronic hepatitis C virus (HCV) infection has evolved considerably in the last years. The standard of care (SOC) for HCV infection consists in the combination of pegylated interferon (PEG-IFN) plus ribavirin. However, it only induces a sustained virological response (SVR) in half of genotype 1-infected patients. Several viral and host factors have been associated with non-response: steatosis, obesity, insulin resistance, age, male sex, ethnicity and genotypes. Many studies have demonstrated that in non-responders, some interferon-stimulated genes were upregulated before treatment. Those findings associated to clinical, biochemical and histological data may help detect responders before starting any treatment. This is a very important issue because the standard treatment is physically and economically demanding. The future of HCV treatment would probably consist in the addition of specifically targeted antiviral therapy for HCV such as protease and/or polymerase inhibitors to the SOC. In genotype 1 patients, very promising results have been reported when the protease inhibitor telaprevir or boceprevir is added to the SOC. It increases the SVR rates from approximately 50% (PEG-IFN plus ribavirin) to 70% (for patients treated with a combination of PEG-IFN plus ribavirin plus telaprevir). Different elements are associated with non-response: (i) viral factors, (ii) host factors and (iii) molecular mechanisms induced by HCV proteins to inhibit the IFN signalling pathway. The goal of this review is to present the mechanisms of non-response, to overcome it and to identify factors that can help to predict the response to anti-HCV therapy.

Pharmacogenomics of chronic hepatitis C therapy with genome-wide association studies

Chronic hepatitis C (CHC) is a liver disease characterized by infection with the hepatitis C virus (HCV) persisting for more than six months. Patients with CHC often stop pursuing the pegylated interferon (peg-IFN) and ribavirin (RBV) treatment because of the high cost and associated adverse effects. Therefore, it is highly desirable, both clinically and economically, to establish the determinants of response to distinguish responders from nonresponders, and to predict the possible outcomes of the peg-IFN and RBV treatments. The aim of this study was to review recent data on the pharmacogenomics of the drug efficacy of IFN in CHC patients. Single nucleotide polymorphisms (SNPs) can be used to understand the relationship between genetic inheritance and IFN therapeutic response. In the recent advent of scientific research, the genome-wide association study (GWAS), which is an alternative to the candidate-gene approach, is widely utilized to examine hundreds of thousands of SNPs by high-throughput genotyping technologies. In addition to the candidate-gene approach, the GWAS approach has recently been employed to study the determinants of HCV's response to therapy. Several recent findings have demonstrated that some SNPs in the interleukin 28B gene are closely associated with IFN responsiveness. These results promise to lead to mechanistic findings related to IFN responsiveness in this disease, and will probably have major contributions for individualized medicine and therapeutic decision making.

Pharmacogenomics of drug efficacy in the interferon treatment of chronic hepatitis C using classification algorithms

Chronic hepatitis C (CHC) patients often stop pursuing interferon-alfa and ribavirin (IFN-alfa/RBV) treatment because of the high cost and associated adverse effects. It is highly desirable, both clinically and economically, to establish tools to distinguish responders from nonresponders and to predict possible outcomes of the IFN-alfa/RBV treatments. Single nucleotide polymorphisms (SNPs) can be used to understand the relationship between genetic inheritance and IFN-alfa/RBV therapeutic response. The aim in this study was to establish a predictive model based on a pharmacogenomic approach. Our study population comprised Taiwanese patients with CHC who were recruited from multiple sites in Taiwan. The genotyping data was generated in the high-throughput genomics lab of Vita Genomics, Inc. With the wrapper-based feature selection approach, we employed multilayer feedforward neural network (MFNN) and logistic regression as a basis for comparisons. Our data revealed that the MFNN models were superior to the logistic regression model. The MFNN approach provides an efficient way to develop a tool for distinguishing responders from nonresponders prior to treatments. Our preliminary results demonstrated that the MFNN algorithm is effective for deriving models for pharmacogenomics studies and for providing the link from clinical factors such as SNPs to the responsiveness of IFN-alfa/RBV in clinical association studies in pharmacogenomics.

Individualized treatment of chronic hepatitis C with pegylated interferon and ribavirin

Chronic infection with hepatitis C virus (HCV) is a major public health problem, with perhaps 180 million people infected worldwide. A significant proportion of these will eventually develop clinical complications, such as cirrhosis, liver decompensation and hepatocellular carcinoma. Sustained virological response (SVR) to antiviral therapy is associated with improvement in liver histology and survival free of liver-related complications. Great effort has been made to improve SVR rate by adapting the duration of therapy according to HCV genotype and to on-treatment response. Rapid virological response (RVR, undetectable HCV RNA at week 4) usually has a high positive predictive value for achieving SVR and early virological response (EVR, ≥ 2 log reduction or undetectable HCV RNA at week 12) exhibits a high negative predictive value for non-response. Individualized approach can improve cost-effectiveness of HCV antiviral therapy by reducing side effects and the costs of therapy associated with unnecessary exposure to treatment and through extending therapy for those with unfavorable features. This article summarizes recent data on strategies of individualized treatment in naïve patients with mono-infection by the different HCV genotypes. The management of common side effects, the impact of HCV infection on health-related quality of life and the potential applications of host genomics in HCV therapy are also briefly discussed.

Molecular and contextual markers of hepatitis C virus and drug abuse

The spread of hepatitis C virus (HCV) infection involves a complex interplay of social risks, and molecular factors of both virus and host. Injection drug abuse is the most powerful risk factor for HCV infection, followed by sexual transmission and additional non-injection drug abuse factors such as co-infection with other viruses and barriers to treatment. It is clearly important to understand the wider context in which the factors related to HCV infection occur. This understanding is required for a comprehensive approach leading to the successful prevention, diagnosis, and treatment of HCV. An additional consideration is that current treatments and advanced molecular methods are generally unavailable to socially disadvantaged patients. Thus, the recognition of behavioral/social, viral, and host factors as components of an integrated approach to HCV is important to help this vulnerable group. Equally important, this approach is key to the development of personalized patient treatment - a significant goal in global healthcare. In this review, we discuss recent findings concerning the impact of drug abuse, epidemiology, social behavior, virology, immunopathology, and genetics on HCV infection and the course of disease.

A support vector machine approach to assess drug efficacy of interferon-alpha and ribavirin combination therapy

BACKGROUND

Interferon-alpha (IFNalpha) in combination with ribavirin can be used for the treatment of patients with chronic hepatitis C. This therapeutic approach achieves an overall sustained response rate of approximately 40%, but treatment takes 6-12 months and patients often experience significant adverse reactions.

OBJECTIVE

We aim to develop a tool to distinguish potential responders from nonresponders prior to initiation of IFNalpha-ribavirin treatment.

METHODS

Using single nucleotide polymorphisms (SNPs) and viral genotype, we applied the support vector machine (SVM) algorithm to build a tool to predict responsiveness to IFNalpha-ribavirin combination therapy. Furthermore, we utilized the SVM algorithm with the recursive feature elimination method to identify a subset of factors that are significantly more influential than the others.

RESULTS AND CONCLUSION

The SVM model is a promising method for inferring responsiveness to IFNalpha dealing with the complex nonlinear relationship between factors (such as SNPs and viral genotype) and successful therapy. In this study, we demonstrate that our tool may allow patients and doctors to make more informed decisions by analyzing host SNP and viral genotype information.

Gene-gene and gene-environment interactions in interferon therapy for chronic hepatitis C

INTRODUCTION

In studies of pharmacogenomics, it is essential to address gene-gene and gene-environment interactions to describe complex traits involving pharmacokinetic and pharmacodynamic mechanisms. In this work, our goal is to detect gene-gene and gene-environment interactions resulting from an analysis of chronic hepatitis C patients' clinical factors including SNPs, viral genotype, viral load, age and gender.

MATERIALS & METHODS

We collected blood samples from 523 chronic hepatitis C patients who had received interferon and ribavirin combination therapy. Based on the treatment strategy for chronic hepatitis C patients, we focused our search for candidate genes involved in pathways related to interferon signaling and immunomodulation. To investigate gene-gene and gene-environment interactions, we implemented an artificial neural network-based method for identifying significant interactions between clinical factors with the fivefold crossvalidation method and permutation tests. The artificial neural network model was trained by an algorithm with an adaptive momentum and learning rate.

RESULTS

A total of 20 SNPs were selected from six candidate genes including adenosine deaminase-RNA-specific (ADAR), caspase 5 (CASP5), interferon consensus sequence binding protein 1 (ICSBP1), interferon-induced protein 44 (IFI44), phosphoinositide-3-kinase catalytic gamma polypeptide (PIK3CG), and transporter 2 ATP-binding cassette subfamily B (TAP2) genes. By applying our artificial neural network-based approach, IFI44 was found in the significant two-locus, three-locus and four-locus gene-gene effect models, as well as in the significant two-factor and three-factor gene-environment effect models. Furthermore, viral genotype remained in the best two-factor, three-factor and four-factor gene-environment models. These results support the hypothesis that IFI44 and viral genotype may play a role in the pharmacogenomics of interferon treatment. In addition, our approach identified a panel of ten clinical factors that may be more significant than the others for further study.

CONCLUSION

We demonstrated that our artificial neural network-based approach is a promising method to assess the gene-gene and gene-environment interactions for interferon and ribavirin combination treatment in chronic hepatitis C patients by using clinical factors such as SNPs, viral genotype, viral load, age and gender.

Association of TGF-beta1 codon 25 (G915C) polymorphism with hepatitis C virus infection

Cytokines play a key role in the regulation of immune responses. In hepatitis C virus infection (HCV), the production of abnormal cytokine levels appears to contribute to the progression of the disease, viral persistence, and affects response to therapy. Cytokine genes are polymorphic at specific sites, and certain polymorphisms located within coding/regulatory regions have been shown to affect the overall expression and secretion of cytokines. The aim of the present study was to identify potential markers of cytokines genes associated with the susceptibility to HCV infection. The cohort was composed of 128 individuals infected by HCV and 94 healthy controls. Genotyping was carried out by PCR-SSP. The distributions of the following polymorphisms were compared in these groups: TNF-alpha (-308G/A [rs1800629]), TGF-beta1 (codon 10 T/C [rs1982073], codon 25 G/C [rs1800471]), IL-10 (-1082 A/G [rs 1800896]; -819T/C [rs1800871]; -592A/C [rs 1800872]), IL-6 (-174G/C [rs1800795]), and IFN-gamma (+874T/A [rs2430561]). This study demonstrated a statistically significant difference in the frequency of TGF-beta1 codon 25 polymorphism between healthy subjects and those infected with HCV. No associations were observed between polymorphisms of TNF-alpha, IFN-gamma, IL-10, TGF-beta1 codon 10, and IL-6 and HCV infection. These findings suggest that TGF-beta1 codon 25 polymorphism could be a host genetic factor associated with susceptibility to HCV infection.

Antiproliferative activity of the human IFN-alpha-inducible protein IFI44

The interferon-alpha (IFN-alpha)-inducible protein IFI44 is associated with hepatitis C virus (HCV) infection, and its function is unknown. We show here in two human melanoma cell lines (ME15 and D10) that transcription starts 4 h after induction, and peak protein levels are reached 24 h after stimulation. We show by immunofluorescence, viral overexpression, and cellular fractionation that IFI44 is a cytoplasmic protein. Overexpression of IFI44 cDNA induces an antiproliferative state in vitro, even in cells that are not responsive to IFN-alpha. IFI44 contains a perfect GTP binding site but has no homology to known GTPases or G proteins. Based on these results, we propose a model in which IFI44 binds intracellular GTP, and this depletion abolishes extracellular signal-regulated kinase (ERK) signaling and results finally in cell cycle arrest.

Efficacy of interferon treatment for chronic hepatitis C predicted by feature subset selection and support vector machine

Chronic hepatitis C is a disease that is difficult to treat. At present, interferon might be the only drug, which can cure this kind of disease, but its efficacy is limited and patients face the risk of side effects and high expense, so doctors considering interferon must make a serious choice. The purpose of this study is to establish a simple model and use the clinical data to predict the interferon efficacy. This model is a combination of Feature Subset Selection and the Classifier using a Support Vector Machine (SVM). The study indicates that when five features have been selected, the identification by the SVM is as follows: the identification rate for the effective group is 85%, and the ineffective group 83%. Analysis of selected features show that HCV-RNA level, hepatobiopsy, HCV genotype, ALP and CHE are the most significant features. The results thus serve for the doctors' reference when they make decisions regarding interferon treatment.

Pattern-recognition techniques with haplotype analysis in pharmacogenomics

Single nucleotide polymorphisms (SNPs) can be used in clinical association studies to determine the contribution of genes to drug efficacy. However, it would be extremely inefficient to test all the 10 million common SNPs for an association study. Here we review haplotype analysis and pattern-recognition techniques to systematically select candidate SNPs for candidate-gene association studies in pharmacogenomics. First, we survey linkage disequilibrium methods to identify tag SNPs and explore the use of haplotypes as genetic markers that are correlated and associated with drug efficacy. Secondly, we investigate pattern-recognition algorithms and statistical analyses to assess drug efficacy based on SNPs and other factors. Finally, we study pattern-recognition approaches to evaluate the epistasis among genes and SNPs. These techniques may provide tools for clinical association studies and help find genes/SNPs involved in responses to therapeutic drugs or adverse drug reactions.