Literature DB >> 19104144

Predicting response to hepatitis C therapy.

Thomas S Oh1, Charles M Rice.   

Abstract

Current treatment for chronic hepatitis C is expensive, is often accompanied by burdensome side effects, and, sadly, fails in almost half of cases. The ability to predict such failures prior to treatment could save a great deal of pain and expense for the patient with HCV. In this issue of the JCI, Aurora and colleagues describe the development of genetic markers predictive of treatment response based on a study of viral sequence variation (see the related article beginning on page 225). Genome-wide covariation analyses of pretreatment virus sequences from 94 patients showed distinct patterns of mutations strongly associated with the ultimate success or failure of treatment. Such analyses suggest markers predictive of response to therapy and may lead to new insights into the underlying biology of hepatitis C.

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Year:  2009        PMID: 19104144      PMCID: PMC2613453          DOI: 10.1172/JCI38069

Source DB:  PubMed          Journal:  J Clin Invest        ISSN: 0021-9738            Impact factor:   14.808


  13 in total

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2.  Mutual information without the influence of phylogeny or entropy dramatically improves residue contact prediction.

Authors:  S D Dunn; L M Wahl; G B Gloor
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3.  Inferring protein-protein interactions in viral proteins by co-evolution of conserved side chains.

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4.  Correlated mutations and residue contacts in proteins.

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Journal:  Proteins       Date:  1994-04

Review 5.  Epidemiology of hepatitis C: geographic differences and temporal trends.

Authors:  A Wasley; M J Alter
Journal:  Semin Liver Dis       Date:  2000       Impact factor: 6.115

6.  The prevalence of hepatitis C virus infection in the United States, 1999 through 2002.

Authors:  Gregory L Armstrong; Annemarie Wasley; Edgar P Simard; Geraldine M McQuillan; Wendi L Kuhnert; Miriam J Alter
Journal:  Ann Intern Med       Date:  2006-05-16       Impact factor: 25.391

7.  Pretreatment sequence diversity differences in the full-length hepatitis C virus open reading frame correlate with early response to therapy.

Authors:  Maureen J Donlin; Nathan A Cannon; Ermei Yao; Jia Li; Abdus Wahed; Milton W Taylor; Steven H Belle; Adrian M Di Bisceglie; Rajeev Aurora; John E Tavis
Journal:  J Virol       Date:  2007-05-23       Impact factor: 5.103

8.  Genetic variability in hepatitis C virus and its role in antiviral treatment response.

Authors:  M Torres-Puente; J M Cuevas; N Jiménez-Hernández; M A Bracho; I García-Robles; B Wrobel; F Carnicer; J Del Olmo; E Ortega; A Moya; F González-Candelas
Journal:  J Viral Hepat       Date:  2008-03       Impact factor: 3.728

9.  Prediction of efficient virological response to pegylated interferon/ribavirin combination therapy by NS5A sequences of hepatitis C virus and anti-NS5A antibodies in pre-treatment sera.

Authors:  Ahmed El-Shamy; Mikiko Sasayama; Motoko Nagano-Fujii; Noriko Sasase; Susumu Imoto; Soo Ryang Kim; Hak Hotta
Journal:  Microbiol Immunol       Date:  2007       Impact factor: 1.955

10.  Correlation between pre-treatment quasispecies complexity and treatment outcome in chronic HCV genotype 3a.

Authors:  Isabelle Moreau; John Levis; Orla Crosbie; Elizabeth Kenny-Walsh; Liam J Fanning
Journal:  Virol J       Date:  2008-07-09       Impact factor: 4.099

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  4 in total

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2.  Potential treatment options and future research to increase hepatitis C virus treatment response rate.

Authors:  Veronica Tencate; Bruno Sainz; Scott J Cotler; Susan L Uprichard
Journal:  Hepat Med       Date:  2010-10

3.  Treatment of hepatitis C infections with interferon: a historical perspective.

Authors:  Robert M Friedman; Sara Contente
Journal:  Hepat Res Treat       Date:  2010-09-06

Review 4.  Interferons as Therapy for Viral and Neoplastic Diseases: From Panacea to Pariah to Paragon.

Authors:  Robert M Friedman; Sara Contente
Journal:  Pharmaceuticals (Basel)       Date:  2009-12-15
  4 in total

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