Innovative in vitro models for breast cancer drug discovery

2016 ◽  
Vol 21 ◽  
pp. 11-16 ◽  
Author(s):  
Elke Kaemmerer ◽  
Tayner E. Rodriguez Garzon ◽  
Aaron M. Lock ◽  
Carrie J. Lovitt ◽  
Vicky M. Avery
Keyword(s):  
Breast Cancer ◽  
Drug Discovery ◽  
In Vitro Models ◽  
Cancer Drug ◽  
Cancer Drug Discovery

Abstract 4741: Improving pancreatic cancer drug discovery by leveraging genomics to select better in vitro models

2015 ◽  
Author(s):  
Yoonjeong Cha ◽  
Andrew Lysaght ◽  
Rain Cui ◽  
Brian Weiner ◽  
Sarah Kolitz ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Drug Discovery ◽  
In Vitro Models ◽  
Cancer Drug ◽  
Cancer Drug Discovery

Abstract 2675: Characterization of human thioesterase 2 and its potential for breast cancer drug discovery

2010 ◽  
Author(s):  
Melissa K. Ritchie ◽  
Lynnette C. Johnson ◽  
Laura A. Watts ◽  
Steven J. Kridel ◽  
W. Todd Lowther
Keyword(s):  
Breast Cancer ◽  
Drug Discovery ◽  
Cancer Drug ◽  
Cancer Drug Discovery

2D and 3D thermally bioprinted human MCF-7 breast cancer cells: A promising model for drug discovery.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 2605-2605 ◽  
Author(s):  
Aleli Campbell ◽  
Alexander Philipovskiy ◽  
Rosalinda Heydarian ◽  
Armando Varela-Ramirez ◽  
Denisse A. Gutierrez ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Drug Discovery ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
In Vitro Models ◽  
Nuclear Staining ◽  
Chaperone Proteins ◽  
High Concentrations ◽  
Mcf 7

2605 Background: Breast cancer (BC) is the second leading cause of cancer death following lung cancer. Bioprinting, the use of computer aided process to print biological living and non-living material to create patterns in 2D or 3D structures, is a novel technique that has been proposed to be used to develop tissue engineered solutions for a wide array of clinical applications, e.g., skin grafting. We investigate here if bioprinted breast cancer cells show some of the hallmarks of cancer tissues, and thus may represent good in vitro models for drug discovery. Methods: For this study, MCF-7 BC cells were cultured, stained, counted and turned into a bioink solution by suspending in phosphate buffered saline solution. The cells were bioprinted over a 96-well plate and pre-incubated for 18 hours in DMEM and RPMI media with 10% Fetal Bovine Serum and Charcoal Stripped Serum, respectively. After 18 hours of incubation the media was supplemented with Tamoxifen at 5µM, 10µM, 50µM, 90µM and 110µM concentrations. Cytotoxicity was measured 24 hours post-treatment using a differential nuclear staining assay and an INCell 2000 bioimager system. Results: Bioprinted cells exposed to high concentrations of Tamoxifen (90 µM and 110µM) exhibited a viability of 8.2% and 10.8%, respectively. Whereas viability of manually seeded cells at those concentrations was 0.11% and 0.05%. Viability of negative and positive controls was at 7.6% and 97.0% for the bioprinted samples and for the normally seeded cells was 4.9% and 98.8% respectively. Conclusions: In our study, we have established a novel 2D/3D breast tumor model applying bioprinting technology for drug discovery. The higher cell viability of MCF-7’s at high concentrations of Tamoxifen could be attributed to the hormesis effect and activation of chaperone proteins, e.g., HSP70 and HSP90, possibly caused by bioprinting. We hypothesize that bioprinted MCF-7 cells also show increased levels of chaperone proteins, which may in a way mimic their in vivo behavior. In this novel in vitro 2D/3D model, the bioprinted cells show a more biological relevant behavior than normally cultured cells. Insights into the cell behavior after bioprinting may elucidate how to build improved in vitro models for BC research.

Bioinformatics Approaches for Anti-cancer Drug Discovery

2019 ◽  
Vol 21 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Kening Li ◽  
Yuxin Du ◽  
Lu Li ◽  
Dong-Qing Wei
Keyword(s):  
Drug Discovery ◽  
Cancer Therapy ◽  
Biological Network ◽  
Computational Prediction ◽  
Cancer Drug ◽  
Cancer Drugs ◽  
Cancer Drug Discovery ◽  
Anti Cancer

Drug discovery is important in cancer therapy and precision medicines. Traditional approaches of drug discovery are mainly based on in vivo animal experiments and in vitro drug screening, but these methods are usually expensive and laborious. In the last decade, omics data explosion provides an opportunity for computational prediction of anti-cancer drugs, improving the efficiency of drug discovery. High-throughput transcriptome data were widely used in biomarkers’ identification and drug prediction by integrating with drug-response data. Moreover, biological network theory and methodology were also successfully applied to the anti-cancer drug discovery, such as studies based on protein-protein interaction network, drug-target network and disease-gene network. In this review, we summarized and discussed the bioinformatics approaches for predicting anti-cancer drugs and drug combinations based on the multi-omic data, including transcriptomics, toxicogenomics, functional genomics and biological network. We believe that the general overview of available databases and current computational methods will be helpful for the development of novel cancer therapy strategies.

scholarly journals Integration of Molecular Docking and In Vitro Studies: A Powerful Approach for Drug Discovery in Breast Cancer

2020 ◽  
Vol 10 (19) ◽  
pp. 6981
Author(s):  
Claudia Cava ◽  
Isabella Castiglioni
Keyword(s):  
Breast Cancer ◽  
Molecular Docking ◽  
Drug Discovery ◽  
Biological Response ◽  
Metastatic Breast ◽  
In Vitro Studies ◽  
Cancer Drug ◽  
In Vitro Techniques ◽  
Medical Needs

Molecular docking in the pharmaceutical industry is a powerful in silico approach for discovering novel therapies for unmet medical needs predicting drug–target interactions. It not only provides binding affinity between drugs and targets at the atomic level, but also elucidates the fundamental pharmacological properties of specific drugs. The purpose of this review was to illustrate newer and emergent uses of docking when combined with in vitro techniques for drug discovery in metastatic breast cancer. We grouped the selected articles into five main categories; namely, systematic repositioning of drugs, natural drugs, new synthesized molecules, combinations of drugs, and drug latentiation. We focused on new promising drugs that have a good affinity with their targets, thus inducing a favorable biological response. This review suggests that the integration of molecular docking and in vitro studies can accelerate cancer drug discovery showing a good consistency of the results between the two approaches.

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