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Pharmacogenomics of hepatitis C infections: personalizing therapy.

ABSTRACT: It is a widely held view that drug response genes have not proved as useful in clinical practice as anticipated at the start of the genomic era. An exception is in the treatment for chronic hepatitis C virus (HCV) genotype 1 infection with pegylated interferon ? and ribavirin. In 2009, four independent genome-wide analyses identified IL28B polymorphisms that predict drug response in chronic hepatitis C (CHC). This discovery had immediate clinical impact. First, the IL28B genotype could be used to personalize therapy. In the 2 years since discovery, most of the more than 100,000 CHC patients commencing therapy for CHC in the West will have considered IL28B genotype testing. Second, the discovery has supported clinical trials for the use of the protein encoded by the gene known as interferon lambda. Third, it is expected that new insights into HCV pathogenesis will follow from studies of how IL28B affects HCV viral clearance and, ultimately, this will lead to new therapeutic strategies for CHC. This review discusses how IL28B genotyping is now used in personalizing therapy and, with the dramatically changing clinical landscape in CHC, with the advent of direct-acting antivirals, the prospects ahead.

SUBMITTER: Booth DR

PROVIDER: S-EPMC3580439 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Pharmacogenomics of hepatitis C infections: personalizing therapy.

Booth David R DR Ahlenstiel Golo G George Jacob J

Genome medicine 20121226 12

It is a widely held view that drug response genes have not proved as useful in clinical practice as anticipated at the start of the genomic era. An exception is in the treatment for chronic hepatitis C virus (HCV) genotype 1 infection with pegylated interferon α and ribavirin. In 2009, four independent genome-wide analyses identified IL28B polymorphisms that predict drug response in chronic hepatitis C (CHC). This discovery had immediate clinical impact. First, the IL28B genotype could be used t ...[more]

PMID: 23268841

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Project description:BackgroundClear cell RCC (ccRCC) accounts for approximately 75% of the renal cancer cases. Surgery treatment seems to be the best efficacious approach for the majority of patients. However, a consistent fraction (30%) of cases progress after surgery with curative intent. It is currently largely debated the use of adjuvant therapy for high-risk patients and the clinical and molecular parameters for stratifying beneficiary categories. In addition, the treatment of advanced forms lacks reliable driver biomarkers for the appropriated therapeutic choice. Thus, renal cancer patient management urges predictive molecular indicators and models for therapy-decision making.MethodsHere, we developed and optimized new models and tools for ameliorating renal cancer patient management. We isolated from fresh tumor specimens heterogeneous multi-clonal populations showing epithelial and mesenchymal characteristics coupled to stem cell phenotype. These cells retained long lasting-tumor-propagating capacity provided a therapy monitoring approach in vitro and in vivo while being able to form parental tumors when orthotopically injected and serially transplanted in immunocompromised murine hosts.ResultsIn line with recent evidence of multiclonal cancer composition, we optimized in vitro cultures enriched of multiple tumor-propagating populations. Orthotopic xenograft masses recapitulated morphology, grading and malignancy of parental cancers. High-grade but not the low-grade neoplasias, resulted in efficient serial transplantation in mice. Engraftment capacity paralleled grading and recurrence frequency advocating for a prognostic value of our developed model system. Therefore, in search of novel molecular indicators for therapy decision-making, we used Reverse-Phase Protein Arrays (RPPA) to analyze a panel of total and phosphorylated proteins in the isolated populations. Tumor-propagating cells showed several deregulated kinase cascades associated with grading, including angiogenesis and m-TOR pathways.ConclusionsIn the era of personalized therapy, the analysis of tumor propagating cells may help improve prediction of disease progression and therapy assignment. The possibility to test pharmacological response of ccRCC stem-like cells in vitro and in orthotopic models may help define a pharmacological profiling for future development of more effective therapies. Likewise, RPPA screening on patient-derived populations offers innovative approach for possible prediction of therapy response.

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Pharmacogenomics of hepatitis C infections: personalizing therapy.

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Pharmacogenomics of hepatitis C infections: personalizing therapy.

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