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Using Stepwise Pharmacogenomics and Proteomics to Predict Hepatitis C Treatment Response in Difficult to Treat Patient Populations
Author(s) -
Naggie Susanna,
Clement Meredith,
Lusk Sam,
Osinusi Anu,
Himmel Tiffany,
Lucas Joseph E.,
Thompson Will J.,
Dubois Laura,
Moseley M. Arthur,
Clark Paul J.,
Kottilil Shyam,
Patel Keyur
Publication year - 2019
Publication title -
proteomics – clinical applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.948
H-Index - 54
eISSN - 1862-8354
pISSN - 1862-8346
DOI - 10.1002/prca.201800006
Subject(s) - pharmacogenomics , medicine , hepatitis c virus , hepatitis c , proteomics , immunology , ribavirin , peripheral blood mononuclear cell , cohort , biomarker , pharmacogenetics , oncology , logistic regression , genotyping , genotype , pharmacology , biology , virus , in vitro , biochemistry , gene
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.