scholarly journals Liver microsystems in vitro for drug response

2019 ◽  
Vol 26 (1) ◽  
Author(s):  
Jyong-Huei Lee ◽  
Kuan-Lun Ho ◽  
Shih-Kang Fan

Abstract Engineering approaches were adopted for liver microsystems to recapitulate cell arrangements and culture microenvironments in vivo for sensitive, high-throughput and biomimetic drug screening. This review introduces liver microsystems in vitro for drug hepatotoxicity, drug-drug interactions, metabolic function and enzyme induction, based on cell micropatterning, hydrogel biofabrication and microfluidic perfusion. The engineered microsystems provide varied microenvironments for cell culture that feature cell coculture with non-parenchymal cells, in a heterogeneous extracellular matrix and under controllable perfusion. The engineering methods described include cell micropatterning with soft lithography and dielectrophoresis, hydrogel biofabrication with photolithography, micromolding and 3D bioprinting, and microfluidic perfusion with endothelial-like structures and gradient generators. We discuss the major challenges and trends of liver microsystems to study drug response in vitro.

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 704-704
Author(s):  
Luca Vincenzo Cappelli ◽  
Danilo Fiore ◽  
Jude M Phillip ◽  
Liron Yoffe ◽  
Filomena Di Giacomo ◽  
...  

Abstract Background. T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive disease with few innovative treatment options. This is also contributed by the lack of models capable of capturing the complexity of the tumor and its microenvironment. Aims. To identify patient-specific vulnerabilities and novel therapeutic strategies in T-ALL and interrogate the mechanisms of the crosstalk between leukemic and stromal elements. Methods. We established a drug-testing platform using patient-derived-tumor-xenografts (PDTX) and a mixed-culture approach using E4ORF1-transduced endothelial cells (ECs) (Seandel M et al, PNAS 2008) to overcome host-mediated chemoresistance. We performed functional experiments using total and single-cell RNA sequencing. Results. First, we established a battery of 22 T-ALL PDTX models that matched both phenotypically (immune-histochemistry, flow cytometry) and genotypically (TCR rearrangement, transcriptome) with the primary patients' samples. We then challenged these models (n=14 samples belonging to different PDTX and serial passages within each model) with a library of compounds (n=433) targeting redundant proteins (n=634). Unsupervised clustering and Principal Component Analysis (PCA) demonstrated two clusters of T-ALL samples based on differential drug susceptibility. We could at least partially correlate these differences to specific transcriptomic signatures predictive of drug response (Figure 1A). We then defined a group of pan-active compounds across all models (n=40), which we validated using an independent screening with/without ECs (Figure 1B). We found that ECs counteracted the activity of selected compounds (i.e. TSA, THZ1 and MLN2238). By PCA, we observed distinct response profiles based on different T-ALL models. We vectorized the EC-rescue and found that the direction was the same across all 3 models tested, indicating that it relied on similar mechanisms regardless of model identity. Based on the known role of IGF1-IGFR1 as a supportive EC-rescue axis (Medyouf H et al, J Exp Med 2011), we performed the same screening with/without recombinant IGFBP-7 (500 ng/mL), a decoy IGF1 molecule. Remarkably, IGFBP-7 completely or partially abrogated the EC-mediated rescue of selected compounds [enzastaurin (PKC-β inhibitor), SC144 (GP130 inhibitor), CHIR124 (Chk1 inhibitor) and YM155 (Survivin inhibitor)] (Figure 1B). Drugs not rescued by ECs (n=30) were considered positive hits and 5 of them (ruxolitinib, tofacitinib, panobinostat, bortezomib, irinotecan) ultimately proved to be effective in vivo in randomized pre-clinical trials either alone or in combination (Figure 1C). Our stepwise endothelial-leukemia platform led to the discovery of "public" and "private" vulnerabilities and the proof-of-principle of prediction-guided in vivo pre-clinical trials. We propose a list of compounds that could be readily translated into T-ALL clinical trials (Figure 1D). We finally proved the validity of our platform using other disease models (i.e. B and T-lymphoma PDTXs). Mechanistically, at single-cell resolution, in vitro interacting T-ALL cells and ECs underwent reciprocal transcriptome changes, with T-ALL shifting towards stemness/undifferentiation and ECs towards tumor-ECs (TECs) phenotypes. Furthermore, in vitro EC-educated T-ALL cells mimicked distinct T-ALL subsets of the leukemic spleen of corresponding PDTX mice (Figure 1E). Conclusions. These data demonstrate that our EC-T-ALL culture system simulates in vivo conditions, offering a robust platform to study drug response, leukemia-host interactions and cell plasticity. This approach will improve the pre-clinical predictability of novel drugs/combinations for T-ALL, as well as for other hematologic malignancies, and propel the development of patient-tailored treatments. Figure 1 Figure 1. Disclosures Melnick: Janssen Pharmaceuticals: Research Funding; Sanofi: Research Funding; Daiichi Sankyo: Research Funding; Epizyme: Consultancy; Constellation: Consultancy; KDAC Pharma: Membership on an entity's Board of Directors or advisory committees. Elemento: AstraZeneca: Research Funding; Freenome: Consultancy, Other: Current equity holder in a privately-held company; Volastra Therapeutics: Consultancy, Other: Current equity holder, Research Funding; Champions Oncology: Consultancy; Owkin: Consultancy, Other: Current equity holder; One Three Biotech: Consultancy, Other: Current equity holder; Eli Lilly: Research Funding; Johnson and Johnson: Research Funding; Janssen: Research Funding. Chiaretti: amgen: Consultancy; pfizer: Consultancy; novartis: Consultancy; Incyte: Consultancy. Cerchietti: Celgene: Research Funding; Bristol Myers Squibb: Research Funding.


Endocrinology ◽  
2003 ◽  
Vol 144 (12) ◽  
pp. 5578-5584 ◽  
Author(s):  
Philippe Linscheid ◽  
Dalma Seboek ◽  
Eric S. Nylen ◽  
Igor Langer ◽  
Mirjam Schlatter ◽  
...  

1992 ◽  
Vol 284 (2) ◽  
pp. 545-550 ◽  
Author(s):  
M Otter ◽  
J Kuiper ◽  
R Bos ◽  
D C Rijken ◽  
T J van Berkel

The interaction of 125I-labelled tissue-type plasminogen activator (125I-t-PA) with freshly isolated rat parenchymal and endothelial liver cells was studied. Binding experiments at 4 degrees C with parenchymal cells and endothelial liver cells indicated the presence of 68,000 and 44,000 high-affinity t-PA-binding sites, with an apparent Kd of 3.5 and 4 nM respectively. Association of 125I-t-PA with parenchymal cells was Ca(2+)-dependent and was not influenced by asialofetuin, a known ligand for the galactose receptor. Association of 125I-t-PA with liver endothelial cells was Ca(2+)-dependent and mannose-specific, since ovalbumin (a mannose-terminated glycoprotein) inhibited the cell association of t-PA. Association of 125I-t-PA with liver endothelial cells was inhibited by anti-(human mannose receptor) antiserum. Anti-(galactose receptor) IgG had no effect on 125I-t-PA association with either cell type. Degradation of 125I-t-PA at 37 degrees C by both cell types was inhibited by chloroquine or NH4Cl, indicating that t-PA is degraded lysosomally. in vitro experiments with three monoclonal antibodies (MAbs) demonstrated that anti-t-PA MAb 1-3-1 specifically decreased association of 125I-t-PA with the endothelial cells, and anti-t-PA Mab 7-8-4 inhibited association with the parenchymal cells. Results of competition experiments in rats in vivo with these antibodies were in agreement with findings in vitro. Both antibodies decreased the liver uptake of 125I-t-PA, while a combination of the two antibodies was even more effective in reducing the liver association of 125I-t-PA and increasing its plasma half-life. We conclude from these data that clearance of t-PA by the liver is regulated by at least two pathways, one on parenchymal cells (not galactose/mannose-mediated) and another on liver endothelial cells (mediated by a mannose receptor). Results with the MAbs imply that two distinct sites on the t-PA molecule are involved in binding to parenchymal cells and liver endothelial cells.


Pharmaceutics ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 310 ◽  
Author(s):  
Stella Zsikó ◽  
Kendra Cutcher ◽  
Anita Kovács ◽  
Mária Budai-Szűcs ◽  
Attila Gácsi ◽  
...  

The aim of this research was to investigate the stability of a lidocaine-loaded nanostructured lipid carrier dispersion at different temperatures, formulate a nanostructured lipid carrier gel, and test the penetration profile of lidocaine from the nanostructured lipid carrier gel using different skin penetration modeling methods. The formulations were characterized by laser diffraction, rheological measurements and microscopic examinations. Various in vitro methods were used to study drug release, diffusion and penetration. Two types of vertical Franz diffusion cells with three different membranes, including cellulose, Strat-M®, and heat separated human epidermis were used and compared to the Skin-parallel artificial membrane permeability assay (PAMPA) method. Results indicated that the nanostructured lipid carrier dispersion had to be gelified as soon as possible for proper stability. Both the Skin-PAMPA model and Strat-M® membranes correlated favorably with heat separated human epidermis in this research, with the Strat-M® membranes sharing the most similar drug permeability profile to an ex vivo human skin model. Our experimental findings suggest that even when the best available in vitro experiment is selected for modeling human skin penetration to study nanostructured lipid carrier gel systems, relevant in vitro/in vivo correlation should be made to calculate the drug release/permeation in vivo. Future investigations in this field are still needed to demonstrate the influence of membranes and equipment from other classes on other drug candidates.


2008 ◽  
Vol 52 (8) ◽  
pp. 2831-2835 ◽  
Author(s):  
R. Rustomjee ◽  
A. H. Diacon ◽  
J. Allen ◽  
A. Venter ◽  
C. Reddy ◽  
...  

ABSTRACT Tibotec Medicinal Compound 207 (TMC207) is a novel diarylquinoline with a unique mode of action that targets mycobacterial ATP synthase. TMC207 exhibits high in vitro activity against mycobacterial strains either susceptible or resistant to all first-line and many second-line drugs, including fluoroquinolones, and has shown exceptional in vivo activity against several mycobacterial species in different animal models. In this early bactericidal activity study, 75 treatment-naïve patients with smear-positive pulmonary tuberculosis were randomized to once-daily oral TMC207 (25 mg, 100 mg, or 400 mg), 600 mg rifampin (RIF), or 300 mg isoniazid (INH) for 7 days. Sixteen-hour overnight sputum collected at baseline and on each treatment day was plated in serial dilutions on selective agar plates. The bactericidal activity was expressed as the log10 decrease in CFU/ml sputum/day. Pharmacokinetic sampling was performed on day 7 of TMC207 administration up to 24 h postdose. The decreases in log10 CFU counts (± standard deviation) from baseline to day 7 were 0.04 ± 0.46 for 25 mg TMC207 (n = 14), 0.26 ± 0.64 for 100 mg TMC207 (n = 14), 0.77 ± 0.58 for 400 mg TMC207 (n = 14), 1.88 ± 0.74 for INH (n = 11), and 1.70 ± 0.71 for RIF (n = 14). Significant bactericidal activity of 400 mg TMC207 was observed from day 4 onward and was similar in magnitude to those of INH and RIF over the same period. The pharmacokinetics of TMC207 were linear across the dose range. In summary, TMC207 demonstrated bactericidal activity with a delayed onset and was well tolerated, and no study drug-related serious adverse events occurred.


2019 ◽  
Vol 35 (14) ◽  
pp. i501-i509 ◽  
Author(s):  
Hossein Sharifi-Noghabi ◽  
Olga Zolotareva ◽  
Colin C Collins ◽  
Martin Ester

Abstract Motivation Historically, gene expression has been shown to be the most informative data for drug response prediction. Recent evidence suggests that integrating additional omics can improve the prediction accuracy which raises the question of how to integrate the additional omics. Regardless of the integration strategy, clinical utility and translatability are crucial. Thus, we reasoned a multi-omics approach combined with clinical datasets would improve drug response prediction and clinical relevance. Results We propose MOLI, a multi-omics late integration method based on deep neural networks. MOLI takes somatic mutation, copy number aberration and gene expression data as input, and integrates them for drug response prediction. MOLI uses type-specific encoding sub-networks to learn features for each omics type, concatenates them into one representation and optimizes this representation via a combined cost function consisting of a triplet loss and a binary cross-entropy loss. The former makes the representations of responder samples more similar to each other and different from the non-responders, and the latter makes this representation predictive of the response values. We validate MOLI on in vitro and in vivo datasets for five chemotherapy agents and two targeted therapeutics. Compared to state-of-the-art single-omics and early integration multi-omics methods, MOLI achieves higher prediction accuracy in external validations. Moreover, a significant improvement in MOLI’s performance is observed for targeted drugs when training on a pan-drug input, i.e. using all the drugs with the same target compared to training only on drug-specific inputs. MOLI’s high predictive power suggests it may have utility in precision oncology. Availability and implementation https://github.com/hosseinshn/MOLI. Supplementary information Supplementary data are available at Bioinformatics online.


Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 1234-1234 ◽  
Author(s):  
Laura M. De Castro ◽  
Jude C. Jonassaint ◽  
Jennifer G. Johnson ◽  
Milena Batchvarova ◽  
Marilyn J. Telen

Abstract Sickle red blood cells (SS RBC) are abnormally adhesive to both endothelial cells (ECs) and components of the extracellular matrix (ECM). Epinephrine (epi) has been shown to elevate cAMP in SS RBC and increase adhesion of SS RBC to ECs in a protein kinase A-dependent manner. In vitro and in vivo studies performed in our lab have led to the hypothesis that adrenergic stimuli such as epi may initiate or exacerbate vaso-occlusion and thus contribute to the association of vaso-occlusive events with physiologic stress. We are conducting a prospective, dose-escalation pilot clinical study to investigate whether in vivo administration of one dose of propranolol either down-regulates baseline SS RBC adhesion in vitro or prevents its upregulation by epi. In addition, this study will provide additional safety data regarding the use of propranolol in normotensive patients with sickle cell disease (SCD). Figure Figure To date, we have completed the first two dose cohorts. 11 subjects (9 SS and 1 Sβ° thalassemia; 7 females, 3 males) have participated. No severe adverse events were noted. Cohorts 1 and 2 had mean pre-propranolol blood pressure (BP) of 116 (5.9 SD)/ 60.4 (3.98 SD) and 106.8 (4.68 SD)/ 58 (3.9 SD), respectively; this difference was not statistically significant. Minimal and asymptomatic changes in BP were noted in both cohorts after drug administration, with biphasic systolic and diastolic BP nadirs at 45 and 240 minutes. No clinically significant changes in heart rate were observed. Adhesion studies were performed using a graduated height flow chamber on the day of RBC collection. RBC adhesion to ECs was studied before and after epi stimulation and was measured at sheer stresses ranging from 1 to 3 dyne/cm2. Baseline adhesion measurements were validated by comparing percent (%) adhesion assayed at 2 different times within 7 days—at screening and before propranolol dose on the study drug day. We observed no significant difference in adhesion at the 2 different time points without propranolol. Comparison of % adhesion of epi-stimulated RBC to ECs before and 1 hour after propranolol showed that propranolol given in vivo significantly inhibited both non-stimulated and epi-stimulated SS RBC adhesion (p=0.04 and p=0.001, respectively). Lastly, comparison of SS RBC adhesion at both drug doses confirmed the drug-related inhibition of adhesion (p<0.004). We conclude that propranolol administered in vivo decreases SS RBC baseline adhesion to ECs and substantially abrogates epi-stimulated adhesion to ECs, as measured in vitro. Although we have thus far studied only a small number of patients and low propranolol doses, we expect to confirm these results with the 3rd cohort, in which a higher dose of propranolol will be used. If our findings continue to show that propranolol can decrease both SS RBC baseline and epi-stimulated adhesion to ECs, study of propranolol on a larger scale would be warranted in order to ascertain its safety and efficacy as an anti-adhesive therapy in SCD.


Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 3583-3583 ◽  
Author(s):  
Daniel Sullivan ◽  
Seema Singhal ◽  
Michael Schuster ◽  
James Berenson ◽  
Peter Gimsing ◽  
...  

Abstract Background: PXD101 is a small molecule HDAC inhibitor of the hydroxamate class, which demonstrates broad anti-neoplastic activity in vitro and in vivo. PXD101 has antiproliferative activity on multiple myeloma cell lines, and shows additive/synergistic effects with standard agents used in myeloma, against these cell lines. PXD101 is being tested as monotherapy and in combination with standard agents for treatment of multiple myeloma. Methods: The primary objective of this study was to assess the activity of PXD101 alone or with dexamethasone, in multiple myeloma patients (pts) who have failed at least 2 prior therapies. Response was measured using the Blade criteria. PXD101 was administered as a 30-min IV infusion on Days 1–5 of a 3-wk cycle, at a dose of 1000 mg/m2/d (900 mg/m2/d in earlier patients). Patients are initially treated with PXD101 alone for two cycles. At the end of cycle two and every cycle thereafter, pts are evaluated for tumor response and continue on the study as follows: pts with objective response or stable disease continue on PXD101 monotherapy, while pts who have progressive disease (PD) are treated with a combination of PXD101 + dexamethasone (Dex). Dex was given orally 40 mg daily on Days 2–5 and 10–13 of the treatment cycle. Results: To date, 24 pts have been enrolled, 19 for which data are currently available. These pts have received a median of 5 (range 2–10) prior therapies. Seventeen pts are evaluable, 12 of whom are evaluable for ≥ 2 cycles, and 5 evaluable for 1 cycle only; 2 pts are unevaluable due to inconsistent baseline that prevented response assessment. Of the 5 pts evaluable for 1 cycle only, 4 discontinued due to PD and one withdrew from study. The 12 pts evaluable for ≥ 2 cycles received a median of 4 treatment cycles (range 2–12); 6 of these patients went on to receive PXD101+Dex. In these 12 pts, duration of PXD101 monotherapy was for 2–4 cycles, with almost all pts (10) receiving only 2 cycles. PXD101+Dex treatment in 6 pts was for 1–10 cycles (10, 6, 4, 4, 3, and 1). In 12 pts on monotherapy for ≥ 2 cycles, there were 6 SD (duration 6–12 wks) and 6 PD. The short duration of SD in PXD101 monotherapy was attributed to patient withdrawal or moving to Dex addition in spite of disease stabilization. All 6 pts receiving PXD101+Dex had previously received at least 2 Dex-containing regimens. One pt had MR (duration 6 wks), and 5 pts had SD. One pt has had SD for 35 wks, with 90% decrease in serum M-component sustained in the last 12 wks; another pt has had SD for 15 wks. In 69 cycles of treatment there were 7 Grade 3/4 adverse events assessed by the investigator as potentially related to study drug. These include anemia (2), infection, respiratory distress, hyperglycemia, thrombocytopenia, and fatigue. Conclusions: PXD101 treatment has resulted in stabilization of advanced and progressive disease, providing clinical benefit to patients. PXD101 combination with dexamethasone led to an MR as well as long duration of stable disease in patients who have previously received multiple Dex regimens. These observations support the continued exploration of PXD101 in combination with other agents for treatment of multiple myeloma.


Biomaterials ◽  
2017 ◽  
Vol 131 ◽  
pp. 98-110 ◽  
Author(s):  
Marco Costantini ◽  
Stefano Testa ◽  
Pamela Mozetic ◽  
Andrea Barbetta ◽  
Claudia Fuoco ◽  
...  
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