Exosomal microRNAs Release as a Sensitive Marker for Drug-Induced Liver Injury<i>In Vitro</i>

Messner, Catherine Jane; Premand, Carine; Gaiser, Carine; Kluser, Tanja; Kübler, Eric; Suter‐Dick, Laura

doi:10.1089/aivt.2020.0008

Cited by 6 publications

(9 citation statements)

References 64 publications

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“…CYP3A4 is the most abundant isoform in the human liver, responsible for the metabolism of a large number of clinically used drugs (>50%) [ 60 ]. RIF is capable of transcriptionally inducing CYP3A4 and is a common method used to assess CYP induction and metabolic capacity of hepatocytes in vitro [ 44 , 61 , 62 , 63 ]. In accordance with our previous studies using a 3D HepaRG model, this cell line displays basal and inducible CYP3A4 activity in the MT [ 44 ].…”

Section: Discussionmentioning

confidence: 99%

“…Several miRNAs have been identified as potential DILI biomarkers in clinical samples, in vivo and in vitro models [ 25 , 32 , 38 , 39 , 40 , 41 , 42 , 43 ], including liver-specific miR-122-5p that is predominantly expressed by hepatocytes and released into the blood upon hepatocellular injury. APAP-induced liver injury is an example of DILI-elicited liver injury and miR-122-5p release [ 25 , 41 , 42 , 43 , 44 ]. A recent publication reported increased release of miR-122 from a bio-printed multicellular human model exposed to MTX [ 45 ].…”

Section: Introductionmentioning

confidence: 99%

“…A recent publication reported increased release of miR-122 from a bio-printed multicellular human model exposed to MTX [ 45 ]. Moreover, miR-122-5p was released in exosomes by 3D-HepaRG cells treated with MTX, before the onset of toxicity, demonstrating the sensitivity of miRNAs as early biomarkers [ 44 ]. Despite miR-122 being liver-specific and promising for identifying liver injury, its release from cells has been mainly associated with hepatocellular damage and is not specific to liver fibrosis.…”

Section: Introductionmentioning

confidence: 99%

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Identification of miR-199a-5p, miR-214-3p and miR-99b-5p as Fibrosis-Specific Extracellular Biomarkers and Promoters of HSC Activation

Messner

Schmidt

Özkul

et al. 2021

IJMS

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Liver fibrosis is characterized by the accumulation of extracellular matrix (ECM) resulting in the formation of fibrous scars. In the clinic, liver biopsies are the standard diagnostic method despite the potential for clinical complications. miRNAs are single-stranded, non-coding RNAs that can be detected in tissues, body fluids and cultured cells. The regulation of many miRNAs has been linked to tissue damage, including liver fibrosis in patients, resulting in aberrant miRNA expression/release. Experimental evidence also suggests that miRNAs are regulated in a similar manner in vitro and could thus serve as translational in vitro–in vivo biomarkers. In this work, we set out to identify and characterize biomarkers for liver fibrosis that could be used in vitro and clinically for research and diagnostic purposes. We focused on miRNAs released from hepatic 3D cultures exposed to methotrexate (MTX), which causes fibrosis, and acetaminophen (APAP), an acute hepatotoxicant with no clinically relevant association to liver fibrosis. Using a 3D in vitro model, we corroborated compound-specific responses as we show MTX induced a fibrotic response, and APAP did not. Performing miRNA-seq of cell culture supernatants, we identified potential miRNA biomarkers (miR-199a-5p, miR-214-3p, niRNA-125a-5p and miR-99b-5p) that were associated with a fibrotic phenotype and not with hepatocellular damage alone. Moreover, transfection of HSC with miR-199a-5p led to decreased expression of caveolin-1 and increased α-SMA expression, suggesting its role in HSC activation. In conclusion, we propose that extracellular miR-214-3p, miR-99b-5p, miR-125a-5p and specifically miR-199a-5p could contribute towards a panel of miRNAs for identifying liver fibrosis and that miR-199a-5p, miR-214-3p and miR-99b-5p are promoters of HSC activation.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identification of miR-199a-5p, miR-214-3p and miR-99b-5p as Fibrosis-Specific Extracellular Biomarkers and Promoters of HSC Activation

Messner

Schmidt

Özkul

et al. 2021

IJMS

Self Cite

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“…Messner and others characterized exosomal microRNA-122 in methotrexate and acetaminophen-induced toxicity in hepatic stem cells, HepaRG. They confirmed that microRNA-122 can be used as a sensitive biomarker for DILI (Messner et al, 2020).…”

Section: Introductionmentioning

confidence: 69%

Predicting Drug-Induced Liver Injury Using Machine Learning on a Diverse Set of Predictors

et al. 2021

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A major challenge in drug development is safety and toxicity concerns due to drug side effects. One such side effect, drug-induced liver injury (DILI), is considered a primary factor in regulatory clearance. The Critical Assessment of Massive Data Analysis (CAMDA) 2020 CMap Drug Safety Challenge goal was to develop prediction models based on gene perturbation of six preselected cell-lines (CMap L1000), extended structural information (MOLD2), toxicity data (TOX21), and FDA reporting of adverse events (FAERS). Four types of DILI classes were targeted, including two clinically relevant scores and two control classifications, designed by the CAMDA organizers. The L1000 gene expression data had variable drug coverage across cell lines with only 247 out of 617 drugs in the study measured in all six cell types. We addressed this coverage issue by using Kru-Bor ranked merging to generate a singular drug expression signature across all six cell lines. These merged signatures were then narrowed down to the top and bottom 100, 250, 500, or 1,000 genes most perturbed by drug treatment. These signatures were subject to feature selection using Fisher’s exact test to identify genes predictive of DILI status. Models based solely on expression signatures had varying results for clinical DILI subtypes with an accuracy ranging from 0.49 to 0.67 and Matthews Correlation Coefficient (MCC) values ranging from -0.03 to 0.1. Models built using FAERS, MOLD2, and TOX21 also had similar results in predicting clinical DILI scores with accuracy ranging from 0.56 to 0.67 with MCC scores ranging from 0.12 to 0.36. To incorporate these various data types with expression-based models, we utilized soft, hard, and weighted ensemble voting methods using the top three performing models for each DILI classification. These voting models achieved a balanced accuracy up to 0.54 and 0.60 for the clinically relevant DILI subtypes. Overall, from our experiment, traditional machine learning approaches may not be optimal as a classification method for the current data.

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“…They also retained the ability to respond to TGF-β1 (1 ng/mL) stimulation, as shown by the decrease in albumin expression and the increase in the expression of α-SMA, that correspond to hepatocellular injury and HSC activation, respectively. Both are known events that occur during liver fibrosis progression [ 29 , 30 , 31 ]. In contrast, dissociation of MTs with Accutase and Accumax led to a lower number of functional HepaRGs, as indicated by the lower number of albumin positive cells following day 3 dissociation ( Figure 3 A).…”

Section: Resultsmentioning

confidence: 99%

Single Cell Gene Expression Analysis in a 3D Microtissue Liver Model Reveals Cell Type-Specific Responses to Pro-Fibrotic TGF-β1 Stimulation

Messner

Babrak

Titolo

et al. 2021

IJMS

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3D cell culture systems are widely used to study disease mechanisms and therapeutic interventions. Multicellular liver microtissues (MTs) comprising HepaRG, hTERT-HSC and THP-1 maintain multicellular interactions and physiological properties required to mimic liver fibrosis. However, the inherent complexity of multicellular 3D-systems often hinders the discrimination of cell type specific responses. Here, we aimed at applying single cell sequencing (scRNA-seq) to discern the molecular responses of cells involved in the development of fibrosis elicited by TGF-β1. To obtain single cell suspensions from the MTs, an enzymatic dissociation method was optimized. Isolated cells showed good viability, could be re-plated and cultured in 2D, and expressed specific markers determined by scRNA-seq, qRT-PCR, ELISA and immunostaining. The three cell populations were successfully clustered using supervised and unsupervised methods based on scRNA-seq data. TGF-β1 led to a fibrotic phenotype in the MTs, detected as decreased albumin and increased αSMA expression. Cell-type specific responses to the treatment were identified for each of the three cell types. They included HepaRG damage characterized by a decrease in cellular metabolism, prototypical inflammatory responses in THP-1s and extracellular matrix remodeling in hTERT-HSCs. Furthermore, we identified novel cell-specific putative fibrosis markers in hTERT-HSC (COL15A1), and THP-1 (ALOX5AP and LAPTM5).

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Exosomal microRNAs Release as a Sensitive Marker for Drug-Induced Liver InjuryIn Vitro

Cited by 6 publications

References 64 publications

Identification of miR-199a-5p, miR-214-3p and miR-99b-5p as Fibrosis-Specific Extracellular Biomarkers and Promoters of HSC Activation

Identification of miR-199a-5p, miR-214-3p and miR-99b-5p as Fibrosis-Specific Extracellular Biomarkers and Promoters of HSC Activation

Predicting Drug-Induced Liver Injury Using Machine Learning on a Diverse Set of Predictors

Single Cell Gene Expression Analysis in a 3D Microtissue Liver Model Reveals Cell Type-Specific Responses to Pro-Fibrotic TGF-β1 Stimulation

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