ArticleScientific reports2020
Optimization of cell viability assays to improve replicability and reproducibility of cancer drug sensitivity screens.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers.
What it found
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Who cites it
102 citing papers in PubMed, 215 citations in OpenAlex.
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- Systematic interrogation of drug sensitivities in melanoma reveals potent synergistic and antagonistic drug combinations with translational potential.Communications medicine · 2026Article
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- Predicting targeted- and immunotherapeutic response outcomes in melanoma with single-cell Raman spectroscopy and AI.bioRxiv : the preprint server for biology · 2026Article
- Parallelized contactless microfluidic dispenser with superhydrophobic nozzles for scalable combinatorial screening.Biomicrofluidics · 2026Article
- AI accelerate the identification of druggable targets by 3D structures of proteins and compounds.NPJ precision oncology · 2026Review
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- Antiproliferative Activity Screening inACS omega · 2025Article
- The role of chimeric FAM72B transcripts generated by intergenic mRNA trans-splicing in breast cancer.Functional & integrative genomics · 2025Article
- Adjustment for day-to-day variability in the estimation of effective concentrations for the assessment of mixture toxicity.Archives of toxicology · 2025Article
- Cell villages and Dirichlet modeling map human cell fitness genetics.bioRxiv : the preprint server for biology · 2025Article
- Tempol Induces Oxidative Stress, ER Stress and Apoptosis via MAPK/Akt/mTOR Pathway Suppression in HT29 (Colon) and CRL-1739 (Gastric) Cancer Cell Lines.Current issues in molecular biology · 2025Article
- AI-Driven Drug Discovery: A Comprehensive Review.ACS omega · 2025Review
- Imaging 3D cell cultures with optical microscopy.Nature methods · 2025Review
- Synthesis and Characterization of λ-Carrageenan Oligosaccharide-Based Nanoparticles: Applications in MRI and In Vivo Biodistribution Studies.Biomacromolecules · 2025Article
42 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer drug development has been riddled with high attrition rates, in part, due to poor reproducibility of preclinical models for drug discovery. Poor experimental design and lack of scientific transparency may cause experimental biases that in turn affect data quality, robustness and reproducibility. Here, we pinpoint sources of experimental variability in conventional 2D cell-based cancer drug screens to determine the effect of confounders on cell viability for MCF7 and HCC38 breast cancer cell lines treated with platinum agents (cisplatin and carboplatin) and a proteasome inhibitor (bortezomib). Variance component analysis demonstrated that variations in cell viability were primarily associated with the choice of pharmaceutical drug and cell line, and less likely to be due to the type of growth medium or assay incubation time. Furthermore, careful consideration should be given to different methods of storing diluted pharmaceutical drugs and use of DMSO controls due to the potential risk of evaporation and the subsequent effect on dose-response curves. Optimization of experimental parameters not only improved data quality substantially but also resulted in reproducible results for bortezomib- and cisplatin-treated HCC38, MCF7, MCF-10A, and MDA-MB-436 cells. Taken together, these findings indicate that replicability (the same analyst re-performs the same experiment multiple times) and reproducibility (different analysts perform the same experiment using different experimental conditions) for cell-based drug screens can be improved by identifying potential confounders and subsequent optimization of experimental parameters for each cell line.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.