Limits...
Evaluation of impedance-based label-free technology as a tool for pharmacology and toxicology investigations.

Atienzar FA, Gerets H, Tilmant K, Toussaint G, Dhalluin S - Biosensors (Basel) (2013)

Bottom Line: In addition, specific RTCA profiles (signatures) were generated when HepG2 and HepaRG cells were exposed to calcium modulators, antimitotics, DNA damaging and nuclear receptor agents, with a percentage of prediction close to 80% for both cellular models.In a subsequent experiment, HepG2 cells were exposed to 81 proprietary UCB compounds known to be genotoxic or not.Based on the DNA damaging signatures, the RTCA technology allowed the detection of ca. 50% of the genotoxic compounds (n = 29) and nearly 100% of the non-genotoxic compounds (n = 52).

View Article: PubMed Central - PubMed

Affiliation: UCB Pharma SA, Non Clinical Development, Chemin du Foriest, 1420 Braine-l'Alleud, Belgium; E-Mails: helga.gerets@ucb.com (H.G.); karen.tilmant@ucb.com (K.T.); gaelle.toussaint@ucb.com (G.T.); stephane.dhalluin@ucb.com (S.D.).

ABSTRACT
The use of label-free technologies based on electrical impedance is becoming more and more popular in drug discovery. Indeed, such a methodology allows the continuous monitoring of diverse cellular processes, including proliferation, migration, cytotoxicity and receptor-mediated signaling. The objective of the present study was to further assess the usefulness of the real-time cell analyzer (RTCA) and, in particular, the xCELLigence platform, in the context of early drug development for pharmacology and toxicology investigations. In the present manuscript, four cellular models were exposed to 50 compounds to compare the cell index generated by RTCA and cell viability measured with a traditional viability assay. The data revealed an acceptable correlation (ca. 80%) for both cell lines (i.e., HepG2 and HepaRG), but a lack of correlation (ca. 55%) for the primary human and rat hepatocytes. In addition, specific RTCA profiles (signatures) were generated when HepG2 and HepaRG cells were exposed to calcium modulators, antimitotics, DNA damaging and nuclear receptor agents, with a percentage of prediction close to 80% for both cellular models. In a subsequent experiment, HepG2 cells were exposed to 81 proprietary UCB compounds known to be genotoxic or not. Based on the DNA damaging signatures, the RTCA technology allowed the detection of ca. 50% of the genotoxic compounds (n = 29) and nearly 100% of the non-genotoxic compounds (n = 52). Overall, despite some limitations, the xCELLigence platform is a powerful and reliable tool that can be used in drug discovery for toxicity and pharmacology studies.

No MeSH data available.


Related in: MedlinePlus

Effect of tamoxifen (calcium modulator) on cell index curves (RTCA) in HepG2, fresh HepaRG and A549 cells. HepG2 (A) and HepaRG (B) cells were exposed for at least 72 h to 0 (0.5% DMSO, red curve), 0.1 (green curve), 1 (purple curve), 10 (dark blue curve) and 100 (light blue curve) µM and A549 cells to 0 (control DMSO, red curve) and 20 µM (green curve) of tamoxifen (C from Abassi et al. [9]). Cell indexes were normalized with the last time point before compound addition. Panels A and B: each data point was calculated from triplicate values (except for control cells n = 6). Data represent the average ± standard deviation (except for panel C). The normalized time point is indicated by the vertical line. For more details, please refer to the Materials and Methods section.
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biosensors-03-00132-f003: Effect of tamoxifen (calcium modulator) on cell index curves (RTCA) in HepG2, fresh HepaRG and A549 cells. HepG2 (A) and HepaRG (B) cells were exposed for at least 72 h to 0 (0.5% DMSO, red curve), 0.1 (green curve), 1 (purple curve), 10 (dark blue curve) and 100 (light blue curve) µM and A549 cells to 0 (control DMSO, red curve) and 20 µM (green curve) of tamoxifen (C from Abassi et al. [9]). Cell indexes were normalized with the last time point before compound addition. Panels A and B: each data point was calculated from triplicate values (except for control cells n = 6). Data represent the average ± standard deviation (except for panel C). The normalized time point is indicated by the vertical line. For more details, please refer to the Materials and Methods section.

Mentions: The objective was to determine if similar RTCA profiles could be generated with compounds sharing the same mechanism of action in these two cellular models. A score of 1 or 0 was given when the profile (produced in HepG2 and fresh HepaRG cells) was comparable or not, respectively, to those generated in A549 cells (non-small lung cancer cells) reported in the paper of Abassi et al. [9]. We have decided to use the profiles generated in A549 cells, because the publication [9] gives access to profiles generated with a large number of compounds (Figure 1, Figure 2, Figure 3, Figure 4, Figure 5). Please refer to the discussion for more details. Twenty µM was tested in the paper of Abassi et al. [9], whereas a range of concentrations (0.1, 1, 10 and 100 µM) was used in the present manuscript. Indeed, these concentrations in the range 0.1–100 µM are commonly tested to populate our internal databases. Overall, 76.5 and 82.4% of signatures were reproduced in HepG2 and HepaRG cells, respectively, compared to A549 cells. Interestingly, when the HepG2 and HepaRG results were combined, the % of success reached 94.1% (i.e., only 1/17 compound was not detected in both models i.e., celecoxib). Similar results were obtained in both cellular models with calcium modulators and nuclear receptor compounds. All four compounds targeting nuclear receptors produced specific profiles in both cellular models (Table 2). Four out of five compounds known to be calcium modulators also generated typical RTCA profiles in both models. Nevertheless, different responses were also obtained in both models for 5/17 compounds tested. For instance, noscapine gave an antimitotic specific RTCA profile in HepaRG cells, but not in HepG2 cells, whereas camptothecin generated a DNA damaging profile in HepG2 cells, but not in HepaRG cells (Table 2).


Evaluation of impedance-based label-free technology as a tool for pharmacology and toxicology investigations.

Atienzar FA, Gerets H, Tilmant K, Toussaint G, Dhalluin S - Biosensors (Basel) (2013)

Effect of tamoxifen (calcium modulator) on cell index curves (RTCA) in HepG2, fresh HepaRG and A549 cells. HepG2 (A) and HepaRG (B) cells were exposed for at least 72 h to 0 (0.5% DMSO, red curve), 0.1 (green curve), 1 (purple curve), 10 (dark blue curve) and 100 (light blue curve) µM and A549 cells to 0 (control DMSO, red curve) and 20 µM (green curve) of tamoxifen (C from Abassi et al. [9]). Cell indexes were normalized with the last time point before compound addition. Panels A and B: each data point was calculated from triplicate values (except for control cells n = 6). Data represent the average ± standard deviation (except for panel C). The normalized time point is indicated by the vertical line. For more details, please refer to the Materials and Methods section.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4263586&req=5

biosensors-03-00132-f003: Effect of tamoxifen (calcium modulator) on cell index curves (RTCA) in HepG2, fresh HepaRG and A549 cells. HepG2 (A) and HepaRG (B) cells were exposed for at least 72 h to 0 (0.5% DMSO, red curve), 0.1 (green curve), 1 (purple curve), 10 (dark blue curve) and 100 (light blue curve) µM and A549 cells to 0 (control DMSO, red curve) and 20 µM (green curve) of tamoxifen (C from Abassi et al. [9]). Cell indexes were normalized with the last time point before compound addition. Panels A and B: each data point was calculated from triplicate values (except for control cells n = 6). Data represent the average ± standard deviation (except for panel C). The normalized time point is indicated by the vertical line. For more details, please refer to the Materials and Methods section.
Mentions: The objective was to determine if similar RTCA profiles could be generated with compounds sharing the same mechanism of action in these two cellular models. A score of 1 or 0 was given when the profile (produced in HepG2 and fresh HepaRG cells) was comparable or not, respectively, to those generated in A549 cells (non-small lung cancer cells) reported in the paper of Abassi et al. [9]. We have decided to use the profiles generated in A549 cells, because the publication [9] gives access to profiles generated with a large number of compounds (Figure 1, Figure 2, Figure 3, Figure 4, Figure 5). Please refer to the discussion for more details. Twenty µM was tested in the paper of Abassi et al. [9], whereas a range of concentrations (0.1, 1, 10 and 100 µM) was used in the present manuscript. Indeed, these concentrations in the range 0.1–100 µM are commonly tested to populate our internal databases. Overall, 76.5 and 82.4% of signatures were reproduced in HepG2 and HepaRG cells, respectively, compared to A549 cells. Interestingly, when the HepG2 and HepaRG results were combined, the % of success reached 94.1% (i.e., only 1/17 compound was not detected in both models i.e., celecoxib). Similar results were obtained in both cellular models with calcium modulators and nuclear receptor compounds. All four compounds targeting nuclear receptors produced specific profiles in both cellular models (Table 2). Four out of five compounds known to be calcium modulators also generated typical RTCA profiles in both models. Nevertheless, different responses were also obtained in both models for 5/17 compounds tested. For instance, noscapine gave an antimitotic specific RTCA profile in HepaRG cells, but not in HepG2 cells, whereas camptothecin generated a DNA damaging profile in HepG2 cells, but not in HepaRG cells (Table 2).

Bottom Line: In addition, specific RTCA profiles (signatures) were generated when HepG2 and HepaRG cells were exposed to calcium modulators, antimitotics, DNA damaging and nuclear receptor agents, with a percentage of prediction close to 80% for both cellular models.In a subsequent experiment, HepG2 cells were exposed to 81 proprietary UCB compounds known to be genotoxic or not.Based on the DNA damaging signatures, the RTCA technology allowed the detection of ca. 50% of the genotoxic compounds (n = 29) and nearly 100% of the non-genotoxic compounds (n = 52).

View Article: PubMed Central - PubMed

Affiliation: UCB Pharma SA, Non Clinical Development, Chemin du Foriest, 1420 Braine-l'Alleud, Belgium; E-Mails: helga.gerets@ucb.com (H.G.); karen.tilmant@ucb.com (K.T.); gaelle.toussaint@ucb.com (G.T.); stephane.dhalluin@ucb.com (S.D.).

ABSTRACT
The use of label-free technologies based on electrical impedance is becoming more and more popular in drug discovery. Indeed, such a methodology allows the continuous monitoring of diverse cellular processes, including proliferation, migration, cytotoxicity and receptor-mediated signaling. The objective of the present study was to further assess the usefulness of the real-time cell analyzer (RTCA) and, in particular, the xCELLigence platform, in the context of early drug development for pharmacology and toxicology investigations. In the present manuscript, four cellular models were exposed to 50 compounds to compare the cell index generated by RTCA and cell viability measured with a traditional viability assay. The data revealed an acceptable correlation (ca. 80%) for both cell lines (i.e., HepG2 and HepaRG), but a lack of correlation (ca. 55%) for the primary human and rat hepatocytes. In addition, specific RTCA profiles (signatures) were generated when HepG2 and HepaRG cells were exposed to calcium modulators, antimitotics, DNA damaging and nuclear receptor agents, with a percentage of prediction close to 80% for both cellular models. In a subsequent experiment, HepG2 cells were exposed to 81 proprietary UCB compounds known to be genotoxic or not. Based on the DNA damaging signatures, the RTCA technology allowed the detection of ca. 50% of the genotoxic compounds (n = 29) and nearly 100% of the non-genotoxic compounds (n = 52). Overall, despite some limitations, the xCELLigence platform is a powerful and reliable tool that can be used in drug discovery for toxicity and pharmacology studies.

No MeSH data available.


Related in: MedlinePlus