Analysis of variability in high throughput screening data: applications to melanoma cell lines and drug responses

Abstract

High-throughput screening (HTS) strategies and protocols have undergone significant development in the last decade. It is now possible to screen hundreds of thousands of compounds, each exploring multiple biological phenotypes and parameters, against various cell lines or model systems in a single setting. However, given the vast amount of data such studies generate, the fact that they use multiple reagents, and are often technician-intensive, questions have been raised about the variability, reliability and reproducibility of HTS results. Assessments of the impact of the multiple factors in HTS studies could arguably lead to more compelling insights into the robustness of the results of a particular screen, as well as the overall quality of the study. We leveraged classical, yet highly flexible, analysis of variance (ANOVA)-based linear models to explore how different factors contribute to the variation observed in a screening study of four different melanoma cell lines and 120 drugs over nine dosages studied in two independent academic laboratories. We find that factors such as plate effects, appropriate dosing ranges, and to a lesser extent, the laboratory performing the screen, are significant predictors of variation in drug responses across the cell lines. Further, we show that when sources of variation are quantified and controlled for, they contextualize claims of inconsistencies and reveal the overall quality of the HTS studies performed at each participating laboratory. In the context of the broader screening study, we show that our analysis can also elucidate the robust effects of drugs, even those within specific cell lines.

Optimization of cell viability assays to improve replicability and reproducibility of cancer drug sensitivity screens

“…In the current study, we describe a number of biological (cell type, medium composition and volume, and seeding density) and technical (edge effect, drug type, dose, storage, and treatment time, assay duration time, dose-response metric) factors that should be taken into consideration to achieve more reliable and reproducible drug-dose sensitivity screens in 2D models. Although many of these factors are known to affect drug response, few studies have proposed strategies to quantify and correct sources of experimental variability in cell-based drug screens using QCM [6][7][8]16,18,19,32 . The optimization strategy used here can be adapted to other cell-based and animal model systems by first identifying confounding factors in the experimental setup, followed by optimization of critical experimental parameters and assessment of data quality.…”

Nonlinear mixed effects dose response modeling in high throughput drug screens: application to melanoma cell line analysis

“…Additionally, the SK-MEL-2 cell line was received directly from Memorial Sloan Kettering Cancer Center through the Cancer Cell Line Encyclopedia (CCLE) repository and MeWo cell line from the Developmental Therapeutics Program's NCI-60 repository. The Translational Genomics Research Institute (TGen) had access to all other UACC-cell lines through the UACC [ 14 ]. All cell lines were of low passage number.…”

“…Differences in protocols used, the media within which the cells are suspended, the precise formulation of the drugs used in the screening, the origins of the cell lines used, among other items, can create differences in outcome of studies involving what are thought to be the same cell lines. It is arguable that many of these technical sources of variation in cell line-based HTS studies can be identified and possibly controlled for in well-designed experiments [ 14 ]. However, the analytical methods used to draw inferences about the relationship between a subset of cell lines’ observed dose-dependent responses to a drug and characteristics of those cell lines (e.g., their genomic, transcriptomic, or proteomic profiles) also play an important (and often overlooked) role in the identification of factors that might mitigate a tumor's response to a drug.…”

Linhagens de células de melanoma: Mutações e impacto em vias de transdução de sinal / Melanoma cell lines: Mutations and impact on signal transduction pathways

“…De fato, diversas plataformas para triagem de compostos estão descritas na literatura, inclusive no contexto de melanoma. O uso de triagem em larga escala, do inglês High Throughput Screening -HTS, se destaca na quantidade e velocidade de aquisição de dados, como exemplificado no ensaio de responsividade de 30 linhagens de melanoma a 120 candidatos a fármacos (Ding et al, 2017).…”