Pharmacodynamic Modeling of Anti-Cancer Activity of Tetraiodothyroacetic Acid in a Perfused Cell Culture System

Unmodified or as a poly[lactide-co-glycolide] nanoparticle, tetraiodothyroacetic acid (tetrac) acts at the integrin αvβ3 receptor on human cancer cells to inhibit tumor cell proliferation and xenograft growth. To study in vitro the pharmacodynamics of tetrac formulations in the absence of and in conjunction with other chemotherapeutic agents, we developed a perfusion bellows cell culture system. Cells were grown on polymer flakes and exposed to various concentrations of tetrac, nano-tetrac, resveratrol, cetuximab, or a combination for up to 18 days. Cells were harvested and counted every one or two days. Both NONMEM VI and the exact Monte Carlo parametric expectation maximization algorithm in S-ADAPT were utilized for mathematical modeling. Unmodified tetrac inhibited the proliferation of cancer cells and did so with differing potency in different cell lines. The developed mechanism-based model included two effects of tetrac on different parts of the cell cycle which could be distinguished. For human breast cancer cells, modeling suggested a higher sensitivity (lower IC50) to the effect on success rate of replication than the effect on rate of growth, whereas the capacity (Imax) was larger for the effect on growth rate. Nanoparticulate tetrac (nano-tetrac), which does not enter into cells, had a higher potency and a larger anti-proliferative effect than unmodified tetrac. Fluorescence-activated cell sorting analysis of harvested cells revealed tetrac and nano-tetrac induced concentration-dependent apoptosis that was correlated with expression of pro-apoptotic proteins, such as p53, p21, PIG3 and BAD for nano-tetrac, while unmodified tetrac showed a different profile. Approximately additive anti-proliferative effects were found for the combinations of tetrac and resveratrol, tetrac and cetuximab (Erbitux), and nano-tetrac and cetuximab. Our in vitro perfusion cancer cell system together with mathematical modeling successfully described the anti-proliferative effects over time of tetrac and nano-tetrac and may be useful for dose-finding and studying the pharmacodynamics of other chemotherapeutic agents or their combinations

Risk Stratification and Population Management: Validation of the Patient Stratification Model Based on Electronic Health Record

Background/Aims: Population health management and patient risk stratification are essential components of health care delivery in order to achieve the Triple Aim of better health outcomes, better care and lower health care costs. Many current risk adjustment/risk stratification models are based on claims data, which often are unavailable in health care setting. This study evaluated an electronic health record-based patient stratification model (PSM) and its accuracy in predicting future utilization of high-cost health care services. Methods: A 24-item scoring system, PSM includes markers for chronic conditions, disease states, lab values, health behaviors and health care utilization. In this retrospective cohort study, we focused on adult (18+ years old) primary care patients from a regional health care system (N=250,903). Patients were classified based on demographics, place of residence (isolated rural or small rural, large rural, urban) and prevalence of PSM markers at baseline (9/1/11–8/31/12). The outcome measure in this analysis was defined as 3 or more emergency department (ED) visits at follow-up (9/1/12–8/31/13). We used a logistic regression model to estimate the odds ratio (OR) of the baseline factors on the outcome using both unweighted and weighted PSM scoring. Weights for the PSM markers were calculated as ratios of deviations of the OR from one and the sum of the deviations. The unweighted and weighted composite scoring systems were assessed on the basis of predictive characteristics of the models (c-statistic). In addition, we will examine interactions between age groups and PSM markers and use bootstrap methods of resampling to assess the variation in predictions. Results: The average age in the cohort was 49.0 (standard deviation: 19.2) years at baseline, with 37.0% being 40 or younger and 23.0% being 65 or older; 54.3% were female and 57.9% resided in rural areas. Frequent ED use at follow-up was observed in 2.7% of the study cohort. The c-statistics for the models using unweighted and weighted baseline PSM markers were 0.834 and 0.868, respectively, with a difference of 0.034 (95% confidence interval: 0.032–0.037). Discussion: A model that includes weighted PSM markers, demographics and place of residence had better accuracy in predicting future frequent ED use. Additional analyses will help with further refinement and calibration of the model

Is 60 Days of Ciprofloxacin Administration Necessary for Postexposure Prophylaxis for Bacillus anthracis?▿

Sixty days of ciprofloxacin administration at 500 mg every 12 h is currently recommended for the prophylaxis of inhalational exposure to Bacillus anthracis. We examined Bacillus anthracis (Δ-Sterne strain) in our hollow-fiber infection model. We measured the ciprofloxacin concentrations achieved and the number of organisms present before heat shock (total population) and after heat shock (spore population). We fit a mathematical model to these data. Monte Carlo simulation with differing initial spore burdens (3, 5, and 6.9 log10 CFU/ml) demonstrated that 35 days of this regimen would completely clear the spore burden in 95% of patients. Durations of 110 days did not achieve 99.9% eradication, irrespective of initial burden, because of between-patient variance in drug pharmacokinetics. Given the absence of person-to-person transmission for Bacillus anthracis, adverse drug effects with long-term ciprofloxacin administration, and the possibility of engendering resistance in bodily flora, shorter prophylaxis duration should be given consideration, along with careful monitoring of all exposed individuals

Impact of Different Carbapenems and Regimens of Administration on Resistance Emergence for Three Isogenic Pseudomonas aeruginosa Strains with Differing Mechanisms of Resistance▿

We compared drugs (imipenem and doripenem), doses (500 mg and 1 g), and infusion times (0.5 and 1.0 [imipenem], 1.0 and 4.0 h [doripenem]) in our hollow-fiber model, examining cell kill and resistance suppression for three isogenic strains of Pseudomonas aeruginosa PAO1. The experiments ran for 10 days. Serial samples were taken for total organism and resistant subpopulation counts. Drug concentrations were determined by high-pressure liquid chromatography-tandem mass spectrometry (LC/MS/MS). Free time above the MIC (time > MIC) was calculated using ADAPT II. Time to resistance emergence was examined with Cox modeling. Cell kill and resistance emergence differences were explained, in the main, by differences in potency (MIC) between doripenem and imipenem. Prolonged infusion increased free drug time > MIC and improved cell kill. For resistance suppression, the 1-g, 4-h infusion was able to completely suppress resistance for the full period of observation for the wild-type isolate. For the mutants, control was ultimately lost, but in all cases, this was the best regimen. Doripenem gave longer free time > MIC than imipenem and, therefore, better cell kill and resistance suppression. For the wild-type organism, the 1-g, 4-h infusion regimen is preferred. For organisms with resistance mutations, larger doses or addition of a second drug should be studied

Effect of tetrac and nano-tetrac on cetuximab-induced anti-proliferation.

<p>(<b>A</b>) Human breast cancer MDA-MB-231 cells were treated with constant concentrations of 0.1 µg/mL of cetuximab in the presence or absence of 10⁻⁷ M tetrac in the perfusion bellows cell culture system for 8 d. Aliquots of cells were harvested and counted at the indicated time points. Levels of significance based on unadjusted t test (Holm t test) were the following: cetuximab, alone, vs. control at 6 d, P = 0.13 (0.13), and at 8 d, P = 0.006 (0.025); tetrac alone vs. control at 6 d, P = 0.052 (0.10), and at 8 d, P = 0.0004 (0.002); cetuximab + tetrac vs. control at 6 d, P = 0.008 (0.023), and at 8 d, P 0.0004 (0.002). *, <i>P</i><0.05 including α-adjustment for six comparisons (Holm t test). Multiple observations at each time point are multiple cell counts from one experiment. (<b>B</b>) Colo 205 cells in cell culture flasks were treated with two different constant concentrations of nano-tetrac and cetuximab, alone or in combination. Multiple observations at each time point are multiple cell counts from one experiment. Lines are model fitted cell counts. (<b>C</b>) Observed versus predicted cell counts corresponding to the experiment and modeling shown in (B).</p

The perfusion bellows cell culture system.

<p>Cells of cancer cell lines of interest are grown on plastic flakes suspended in a flow-through, bellows-agitated system that allows for homogeneous exposure of cells to drug/drug metabolite buffer solutions and air. The system permits frequent sampling of cells for viability. The direction of each arrow indicates the direction of influx and efflux of the culture medium. Components of system are not drawn to scale.</p

Tetrac and nano-tetrac suppress cell proliferation.

<p>(<b>A</b>) MDA-MB-231 cells were treated with two constant concentrations of either tetrac or nano-tetrac (10⁻⁶ and 2.5×10⁻⁶ M) and cells harvested at the time points indicated. Total cell numbers from each treatment were used as indicators of tetrac- or nano-tetrac-induced anti-proliferation. Nano-tetrac appeared more effective. (<b>B</b>) MDA-MB-231 cells were treated with constant concentrations of 10⁻⁹ to 10⁻⁵ M nano-tetrac and cells harvested at the time points indicated. Total cell counts from each treatment were used as indicators of anti-proliferative effect. Model-fitted lines are shown. (<b>C</b>) The effect of nano-tetrac (10⁻⁹–10⁻⁶ M) on proliferation of U87MG glioma cells is shown. As with MDA-MB-231 cells in (<b>B</b>), a concentration-dependent effect was obtained. Multiple observations at each time point represent results from 3 repeat experiments. Error bars in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001073#pcbi-1001073-g006" target="_blank">Fig. 4A</a> are standard deviations from 3 experiments.</p

Tetrac induces apoptosis in MDA-MB-231 cells.

<p>(<b>A</b>) MDA-MB-231 cells grown in the perfusion bellows cell culture system were treated with different constant concentrations of tetrac (10⁻⁷ M to 10⁻⁵ M) for 12 d, and harvested on the days indicated. Two million cells from each sample were prepared for flow cytometry as described in the <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001073#s4" target="_blank">Materials and Methods</a> section. Over 1–3 d treatment with these 4 concentrations of tetrac, the percentages of cells in G₁, S or G₂/M phases remained approximately the same, while TUNEL levels rose, particularly with the highest tetrac concentration, to 90% of the cells examined by day 3. (<b>B</b>) By days 11 and 12, the percentage of cells in phase G₁ remained at approximately 40% except for cells exposed to the highest nano-tetrac concentration (20% in phase G₁); TUNEL levels rose at the same concentration. Percentages of cells in G₂/M and S phases were relatively constant. (<b>C</b>) Increases in TUNEL reactivity were not remarkable with either 10⁻⁶ or 10⁻⁵ M tetrac, whereas 10⁻⁶ M nano-tetrac caused a 3-fold increase in apoptosis. These results, obtained after exposure of cells to tetrac formulations for 3 d, confirm prior studies showing that nano-tetrac is more effective than tetrac at similar concentrations in causing changes consistent with a pro-apoptotic effect on cancer cells <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001073#pcbi.1001073-Glinskii1" target="_blank">[8]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001073#pcbi.1001073-Yalcin1" target="_blank">[9]</a>.</p

Expression of pro-apoptotic genes by tetrac and nano-tetrac.

<p>(<b>A</b>) U87MG human glioblastoma cells and (<b>B</b>) MDA-MB-231 breast cancer cells were treated with constant concentrations of 10⁻⁶ M tetrac or nano-tetrac in the perfusion bellows cell culture system. Cells were harvested after 2 d of treatment and total RNA was extracted. RT-PCR was carried out as described in the <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001073#s4" target="_blank">Materials and Methods</a> section. Nano-tetrac significantly stimulated (P<0.02) the expression of pro-apoptotic genes (<i>p53</i>, <i>BAD</i>, <i>PIG3</i>, <i>p21</i>) <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001073#pcbi.1001073-elDeiry1" target="_blank">[34]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001073#pcbi.1001073-Yang1" target="_blank">[35]</a> in U87MG cells, while unmodified tetrac was effective only as an inducer of expression of <i>c-jun</i>. The results in MDA-MB-231 cells were different, in that tetrac enhanced the expression of <i>c-jun</i>, <i>c-fos</i> and <i>p21</i> (each, P<0.05 vs. control) to a moderate degree. Nano-tetrac induced expression of <i>BAD</i> (P = 0.001), <i>PIG3</i> (P = 0.037) and <i>p21</i> (P = 0.05). Together, results in the figure demonstrate the variable nature of responses to tetrac in the two cell lines and a more consistent response of each cell line to nano-tetrac.</p