Target specificity and off-target effects as determinants of cancer drug efficacy

2008 ◽  
Vol 4 (3) ◽  
pp. 273-280 ◽  
Author(s):  
Maria C Shoshan ◽  
Stig Linder
Keyword(s):  
Drug Efficacy ◽  
Cancer Drug ◽  
Target Specificity ◽  
Target Effects

scholarly journals A Microfluidic Spheroid Culture Device with a Concentration Gradient Generator for High-Throughput Screening of Drug Efficacy

Molecules ◽  
2018 ◽  
Vol 23 (12) ◽  
pp. 3355 ◽  
Author(s):  
Wanyoung Lim ◽  
Sungsu Park
Keyword(s):  
High Throughput ◽  
Concentration Gradient ◽  
High Throughput Screening ◽  
3D Cell Culture ◽  
Drug Efficacy ◽  
Cancer Drug ◽  
Spheroid Culture ◽  
Gradient Generator ◽  
Micro Channels

Three-dimensional (3D) cell culture is considered more clinically relevant in mimicking the structural and physiological conditions of tumors in vivo compared to two-dimensional cell cultures. In recent years, high-throughput screening (HTS) in 3D cell arrays has been extensively used for drug discovery because of its usability and applicability. Herein, we developed a microfluidic spheroid culture device (μFSCD) with a concentration gradient generator (CGG) that enabled cells to form spheroids and grow in the presence of cancer drug gradients. The device is composed of concave microwells with several serpentine micro-channels which generate a concentration gradient. Once the colon cancer cells (HCT116) formed a single spheroid (approximately 120 μm in diameter) in each microwell, spheroids were perfused in the presence of the cancer drug gradient irinotecan for three days. The number of spheroids, roundness, and cell viability, were inversely proportional to the drug concentration. These results suggest that the μFSCD with a CGG has the potential to become an HTS platform for screening the efficacy of cancer drugs.

scholarly journals A Microfluidic Spheroid Culture Device with a Concentration Gradient Generator for High-Throughput Screening of Drug Efficacy

2018 ◽  
Author(s):  
Wanyoung Lim ◽  
Sungsu Park
Keyword(s):  
High Throughput ◽  
Concentration Gradient ◽  
High Throughput Screening ◽  
3D Cell Culture ◽  
Drug Efficacy ◽  
Cancer Drug ◽  
Spheroid Culture ◽  
Gradient Generator ◽  
Micro Channels

Three-dimensional (3D) cell culture is considered more clinically relevant in mimicking the structural and physiological conditions of tumors in vivo compared to two-dimensional cell cultures. In recent years, high-throughput screening (HTS) in 3D cell arrays has been extensively used for drug discovery because of its usability and applicability. Herein, we developed a microfluidic spheroid culture device (μFSCD) with a concentration gradient generator (CGG) that enabled cells to form spheroids and grow in the presence of cancer drug gradients. The device is composed of concave microwells with several serpentine micro-channels which generate a concentration gradient. Once the colon cancer cells (HCT116) formed a single spheroid (approximately 120 μm in diameter) in each microwell, spheroids were perfused in the presence of the cancer drug gradient irinotecan for 3 days. The number of spheroids, roundness, and cell viability, were inversely proportional to the drug concentration. These results suggest that the μFSCD with a CGG has the potential to become an HTS platform for screening the efficacy of cancer drugs.

scholarly journals ABPP-HT - high-throughput activity-based profiling of deubiquitylating enzyme inhibitors in a cellular context

2020 ◽  
Author(s):  
Hannah Jones ◽  
Raphael Heilig ◽  
Roman Fischer ◽  
Benedikt M Kessler ◽  
Adan Pinto-Fernandez
Keyword(s):  
Sample Preparation ◽  
High Throughput ◽  
Enzyme Inhibitors ◽  
Drug Efficacy ◽  
Protein Profiling ◽  
Target Engagement ◽  
Molecule Inhibitor ◽  
Cellular Target ◽  
Cellular Context ◽  
Target Effects

AbstractThe potency and selectivity of a small molecule inhibitor are key parameters to assess during the early stages of drug discovery. In particular, it is very informative for characterizing compounds in a relevant cellular context in order to reveal potential off-target effects and drug efficacy. Activity-based probes (ABPs) are valuable tools for that purpose, however, obtaining cellular target engagement data in a high-throughput format has been particularly challenging. Here, we describe a new methodology named ABPP-HT (high-throughput-compatible activity-based protein profiling), implementing a semi-automated proteomic sample preparation workflow that increases the throughput capabilities of the classical ABPP workflow approximately ten times while preserving its enzyme profiling characteristics. Using a panel of deubiquitylating enzyme (DUB) inhibitors, we demonstrate the feasibility of ABPP-HT to provide compound selectivity profiles of endogenous DUBs in a cellular context at a fraction of time as compared to previous methodologies.

scholarly journals Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
JungHo Kong ◽  
Heetak Lee ◽  
Donghyo Kim ◽  
Seong Kyu Han ◽  
Doyeon Ha ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cancer Patient ◽  
Cancer Patients ◽  
Three Dimensional ◽  
Predictive Biomarkers ◽  
Drug Efficacy ◽  
Cancer Drug ◽  
Drug Responses ◽  
Anti Cancer ◽  
Culture Models

Abstract Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. However, current machine-learning-based predictions of drug response often fail to identify robust translational biomarkers from preclinical models. Here, we present a machine-learning framework to identify robust drug biomarkers by taking advantage of network-based analyses using pharmacogenomic data derived from three-dimensional organoid culture models. The biomarkers identified by our approach accurately predict the drug responses of 114 colorectal cancer patients treated with 5-fluorouracil and 77 bladder cancer patients treated with cisplatin. We further confirm our biomarkers using external transcriptomic datasets of drug-sensitive and -resistant isogenic cancer cell lines. Finally, concordance analysis between the transcriptomic biomarkers and independent somatic mutation-based biomarkers further validate our method. This work presents a method to predict cancer patient drug responses using pharmacogenomic data derived from organoid models by combining the application of gene modules and network-based approaches.

Harnessing the self-assembly of peptides for the targeted delivery of anti-cancer agents

2020 ◽  
Vol 7 (8) ◽  
pp. 1996-2010 ◽  
Author(s):  
Stephanie J. Franks ◽  
Kate Firipis ◽  
Rita Ferreira ◽  
Katherine M. Hannan ◽  
Richard J. Williams ◽  
...  
Keyword(s):  
Self Assembly ◽  
Targeted Delivery ◽  
Drug Efficacy ◽  
The Self ◽  
Cancer Drug ◽  
Self Assembling ◽  
Anti Cancer ◽  
Therapeutic Molecules ◽  
Peptide Hydrogels

Self-assembling peptide hydrogels can effectively transport, hold and release therapeutic molecules in a spatially and temporally controlled manner and, in doing so, improve anti-cancer drug efficacy while reducing non-specific toxicity.

Dynamical Analysis of Drug Efficacy and Mechanism of Action Using GFP Reporters

2016 ◽  
pp. 316-353
Author(s):  
Jianping Hua ◽  
Chao Sima ◽  
Milana Cypert ◽  
Edward R. Dougherty ◽  
Jeffery M. Trent ◽  
...  
Keyword(s):  
Drug Testing ◽  
Fluorescent Protein ◽  
Drug Efficacy ◽  
Dynamical Analysis ◽  
Cancer Drug ◽  
Colon Cancer Cell Lines ◽  
Modeling Experiment ◽  
Green Fluorescent ◽  
Gfp Reporters ◽  
Fluorescent Protein Reporter

To the development of effective cancer drug, it is necessary to, first, identify drugs and their possible combinations that could exert desired control over the type of cancer being considered; second, have a drug testing method that allows one to assess the variety of responses that can be provoked by drugs. To facilitate such an experiment-modeling-experiment cycle for drug development, a method based on the dynamical systems of pathways is presented. It involves a three-state experimental design: (1) formulate an oncologic pathway model of relevant cancer; (2) perturb the pathways with the drugs of known effects on components of the pathways of interest; and (3) measure process activity indicators at various points on cell populations. To evaluate the drug response in a high-throughput manner, a green fluorescent protein reporter-based technology has been developed. The authors apply the dynamical approach to several issues in the context of colon cancer cell lines.

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