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Proteomics Clin Appl. 2019 May;13(3):e1800006. doi: 10.1002/prca.201800006. Epub 2018 Aug 22.

Using Stepwise Pharmacogenomics and Proteomics to Predict Hepatitis C Treatment Response in Difficult to Treat Patient Populations.

Author information

1
Infectious Diseases, Duke Clinical Research Institute, Durham, NC, USA.
2
Gilead Sciences, Inc, Foster City, CA, USA.
3
Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA.
4
Duke Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.
5
School of Medicine, University of Queensland, Brisbane, Australia.
6
University of Maryland School of Medicine, Baltimore, MD, USA.
7
University of Toronto, Toronto, ON, Canada.

Abstract

PURPOSE:

In the interferon era of hepatitis C virus (HCV) therapies, genotype/subtype, cirrhosis, prior treatment failure, sex, and race predicted relapse. Our objective is to validate a targeted proteomics platform of 17 peptides to predict sustained virologic response (SVR).

EXPERIMENTAL DESIGN:

Stored plasma from three, open-label, trials of HIV/HCV-coinfected subjects receiving interferon-containing regimens is identified. LC-MS/MS is used to quantitate the peptides directly from plasma, and IL28B genotyping is completed using stored peripheral blood mononuclear cells (PBMC). A logistic regression model is built to analyze the probability of SVR using responders and nonresponders to interferon-based regimens.

RESULTS:

The cohort (N = 35) is predominantly black (51.4%), male (86%), and with median age 48 years. Most patients achieve SVR (54%). Using multivariable models, it is verified that three human corticosteroid binding globulin (CBG) peptides are predictive of SVR in patients with the unfavorable IL28B genotypes (CT/TT). The model performs better than IL28B alone, with an area under the curve of 0.870.

CONCLUSIONS AND CLINICAL RELEVANCE:

In HIV/HCV-coinfected patients, three human CBG peptides that accurately predict treatment response with interferon-based therapy are identified. This study suggests that a stepwise approach combining a genetic predictor followed by targeted proteomics can improve the accuracy of clinical decision-making.

KEYWORDS:

IL28B; hepatitis C virus; human Immunodeficiency virus; pharmacogenomics; proteomics

PMID:
30058111
PMCID:
PMC6353701
[Available on 2020-05-01]
DOI:
10.1002/prca.201800006
[Indexed for MEDLINE]

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