Dataset Information

Next-Generation DILI Biomarkers: Prioritization of Biomarkers for Qualification and Best Practices for Biospecimen Collection in Drug Development.

ABSTRACT: The diagnosis and management of drug-induced liver injury (DILI) remains a challenge in clinical trials in drug development. The qualification of emerging biomarkers capable of predicting DILI soon after the initiation of treatment, differentiating DILI from underlying liver disease, identifying the causal entity, and assigning appropriate treatment options after DILI is diagnosed are needed. Qualification efforts have been hindered by lack of properly stored and consented biospecimens that are linked to clinical data relevant to a specific context of use. Recommendations are made for biospecimen collection procedures, with the focus on clinical trials, and for specific emerging biomarkers to focus qualification efforts.

SUBMITTER: Roth SE

PROVIDER: S-EPMC7006882 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Next-Generation DILI Biomarkers: Prioritization of Biomarkers for Qualification and Best Practices for Biospecimen Collection in Drug Development.

Roth Sharin E SE Avigan Mark I MI Bourdet David D Brott David D Church Rachel R Dash Ajit A Keller Douglas D Sherratt Philip P Watkins Paul B PB Westcott-Baker Lucas L Lentini Silvia S Merz Michael M Ramaiah Lila L Ramaiah Shashi K SK Stanley Ann Marie AM Marcinak John J

Clinical pharmacology and therapeutics 20190914 2

The diagnosis and management of drug-induced liver injury (DILI) remains a challenge in clinical trials in drug development. The qualification of emerging biomarkers capable of predicting DILI soon after the initiation of treatment, differentiating DILI from underlying liver disease, identifying the causal entity, and assigning appropriate treatment options after DILI is diagnosed are needed. Qualification efforts have been hindered by lack of properly stored and consented biospecimens that are ...[more]

PMID: 31314926

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Project description:Histopathological samples are a treasure-trove of DNA for clinical research. However, the quality of DNA can vary depending on the source or extraction method applied. Thus a standardized and cost-effective workflow for the qualification of DNA preparations is essential to guarantee interlaboratory reproducible results. The qualification process consists of the quantification of double strand DNA (dsDNA) and the assessment of its suitability for downstream applications, such as high-throughput next-generation sequencing. We tested the two most frequently used instrumentations to define their role in this process: NanoDrop, based on UV spectroscopy, and Qubit 2.0, which uses fluorochromes specifically binding dsDNA. Quantitative PCR (qPCR) was used as the reference technique as it simultaneously assesses DNA concentration and suitability for PCR amplification. We used 17 genomic DNAs from 6 fresh-frozen (FF) tissues, 6 formalin-fixed paraffin-embedded (FFPE) tissues, 3 cell lines, and 2 commercial preparations. Intra- and inter-operator variability was negligible, and intra-methodology variability was minimal, while consistent inter-methodology divergences were observed. In fact, NanoDrop measured DNA concentrations higher than Qubit and its consistency with dsDNA quantification by qPCR was limited to high molecular weight DNA from FF samples and cell lines, where total DNA and dsDNA quantity virtually coincide. In partially degraded DNA from FFPE samples, only Qubit proved highly reproducible and consistent with qPCR measurements. Multiplex PCR amplifying 191 regions of 46 cancer-related genes was designated the downstream application, using 40 ng dsDNA from FFPE samples calculated by Qubit. All but one sample produced amplicon libraries suitable for next-generation sequencing. NanoDrop UV-spectrum verified contamination of the unsuccessful sample. In conclusion, as qPCR has high costs and is labor intensive, an alternative effective standard workflow for qualification of DNA preparations should include the sequential combination of NanoDrop and Qubit to assess the purity and quantity of dsDNA, respectively.

Dataset Information

Next-Generation DILI Biomarkers: Prioritization of Biomarkers for Qualification and Best Practices for Biospecimen Collection in Drug Development.

Publications

Next-Generation DILI Biomarkers: Prioritization of Biomarkers for Qualification and Best Practices for Biospecimen Collection in Drug Development.

Similar Datasets

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