Dataset Information

Predicting in vivo anti-hepatofibrotic drug efficacy based on in vitro high-content analysis.

ABSTRACT: BACKGROUND/AIMS: Many anti-fibrotic drugs with high in vitro efficacies fail to produce significant effects in vivo. The aim of this work is to use a statistical approach to design a numerical predictor that correlates better with in vivo outcomes. METHODS: High-content analysis (HCA) was performed with 49 drugs on hepatic stellate cells (HSCs) LX-2 stained with 10 fibrotic markers. ~0.3 billion feature values from all cells in >150,000 images were quantified to reflect the drug effects. A systematic literature search on the in vivo effects of all 49 drugs on hepatofibrotic rats yields 28 papers with histological scores. The in vivo and in vitro datasets were used to compute a single efficacy predictor (E(predict)). RESULTS: We used in vivo data from one context (CCl(4) rats with drug treatments) to optimize the computation of E(predict). This optimized relationship was independently validated using in vivo data from two different contexts (treatment of DMN rats and prevention of CCl(4) induction). A linear in vitro-in vivo correlation was consistently observed in all the three contexts. We used E(predict) values to cluster drugs according to efficacy; and found that high-efficacy drugs tended to target proliferation, apoptosis and contractility of HSCs. CONCLUSIONS: The E(predict) statistic, based on a prioritized combination of in vitro features, provides a better correlation between in vitro and in vivo drug response than any of the traditional in vitro markers considered.

SUBMITTER: Zheng B

PROVIDER: S-EPMC3206809 | biostudies-other | 2011

REPOSITORIES: biostudies-other

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Predicting in vivo anti-hepatofibrotic drug efficacy based on in vitro high-content analysis.

Zheng Baixue B Tan Looling L Mo Xuejun X Yu Weimiao W Wang Yan Y Tucker-Kellogg Lisa L Welsch Roy E RE So Peter T C PT Yu Hanry H

PloS one 20111102 11

<h4>Background/aims</h4>Many anti-fibrotic drugs with high in vitro efficacies fail to produce significant effects in vivo. The aim of this work is to use a statistical approach to design a numerical predictor that correlates better with in vivo outcomes.<h4>Methods</h4>High-content analysis (HCA) was performed with 49 drugs on hepatic stellate cells (HSCs) LX-2 stained with 10 fibrotic markers. ~0.3 billion feature values from all cells in >150,000 images were quantified to reflect the drug eff ...[more]

PMID: 22073152

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Project description:BACKGROUND/OBJECTIVES: Human leishmaniases are parasitic diseases causing severe morbidity and mortality. No vaccine is available and numerous factors limit the use of current therapies. There is thus an urgent need for innovative initiatives to identify new chemotypes displaying selective activity against intracellular Leishmania amastigotes that develop and proliferate inside macrophages, thereby causing the pathology of leishmaniasis. METHODOLOGY/PRINCIPAL FINDINGS: We have developed a biologically sound High Content Analysis assay, based on the use of homogeneous populations of primary mouse macrophages hosting Leishmania amazonensis amastigotes. In contrast to classical promastigote-based screens, our assay more closely mimics the environment where intracellular amastigotes are growing within acidic parasitophorous vacuoles of their host cells. This multi-parametric assay provides quantitative data that accurately monitors the parasitic load of amastigotes-hosting macrophage cultures for the discovery of leishmanicidal compounds, but also their potential toxic effect on host macrophages. We validated our approach by using a small set of compounds of leishmanicidal drugs and recently published chemical entities. Based on their intramacrophagic leishmanicidal activity and their toxicity against host cells, compounds were classified as irrelevant or relevant for entering the next step in the drug discovery pipeline. CONCLUSIONS/SIGNIFICANCE: Our assay represents a new screening platform that overcomes several limitations in anti-leishmanial drug discovery. First, the ability to detect toxicity on primary macrophages allows for discovery of compounds able to cross the membranes of macrophage, vacuole and amastigote, thereby accelerating the hit to lead development process for compounds selectively targeting intracellular parasites. Second, our assay allows discovery of anti-leishmanials that interfere with biological functions of the macrophage required for parasite development and growth, such as organelle trafficking/acidification or production of microbicidal effectors. These data thus validate a novel phenotypic screening assay using virulent Leishmania amastigotes growing inside primary macrophage to identify new chemical entities with bona fide drug potential.

Dataset Information

Predicting in vivo anti-hepatofibrotic drug efficacy based on in vitro high-content analysis.

Publications

Predicting in vivo anti-hepatofibrotic drug efficacy based on in vitro high-content analysis.

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