Measuring Cancer Drug Sensitivity and Resistance in Cultured Cells

Abstract

Measuring the potencies of small molecule drugs in cell lines is a critical aspect of preclinical pharmacology. Such experiments are also prototypical of high-throughput experimentation in multi-well plates. The procedure is simple in principle, but many unrecognized factors can affect the results, potentially making data unreliable. The procedures for measuring drug response described here were developed by the NIH LINCS program (http://www.lincsproject.org/) and improve reproducibility. Key features include maximizing uniform cell growth during the assay period, accounting for the effects of cell density on response, and correcting sensitivity measures for differences in proliferation rates. Two related protocols are described: one involves an endpoint measure well suited to large-scale studies and the second a time-dependent measurement that reveals changes in response over time. The methods can be adapted to other types of plate-based experiments. This protocol has a companion in this issue, focused on experimental design and data analysis.

Alternative drug sensitivity metrics improve preclinical cancer pharmacogenomics

“…By contrast, E max values do not have this property as they are strongly confounded by proliferation rates 1,4 . Collecting GR values requires only modest changes in experimental approach 5,6 and calculations can be performed online (GRcalculator.org).…”

The impact of non-genetic heterogeneity on cancer cell death

“…Cell death in response to a drug is typically not instantaneous, and different lethal stimuli kill cells with unique kinetics. These kinetics can be quantified using different methods, models and metrics, some of which integrate rates of death and proliferation into systematic descriptions of population dynamics (Tyson et al 2012; Harris et al 2016; Grootjans et al 2016; Niepel et al 2017; Forcina et al 2017) (Figure 1C). Logically, the effects of time and lethal stimulus dose are not independent, and measuring cell death at different time points can result in different estimates of IC 50 values (Alley et al 1988; Harris et al 2016).…”

Designing Drug‐Response Experiments and Quantifying their Results

“…The following considerations impact the final design: For cell lines and experimental setup in which strong edge effects have been observed, we recommend avoiding using the outermost wells. Potential causes and solutions for edge effects have been discussed elsewhere (Lundholt, Scudder, & Pagliaro, ; also see Internet Resources for helpful hints on how to manage edge effects), and are also covered in the accompanying article to this one in Current Protocols in Chemical Biology (Niepel et al., ). If enough wells are available on each plate to accommodate the experimental design, the scripts we provide automatically avoid using wells at the edge of the plate. Multiple untreated (or vehicle‐treated) controls should be included on each plate.…”

“…We recommend that an untreated plate, prepared in parallel to the plates to be treated, be fixed at the time the other plates are being exposed to drugs. For evaluating time‐dependent GR values and metrics, the number of cells must be measured at multiple time points. This can be done either as a time course where samples are measured multiple times in a non‐destructive manner, or with multiple plates fixed at different time points. Further experimental parameters such as cell plating, recovery time, and control treatments are discussed in an accompanying article (Niepel et al., ) and should be determined prior to generating treatment files.…”

“…r Further experimental parameters such as cell plating, recovery time, and control treatments are discussed in an accompanying article (Niepel et al, 2017) and should be determined prior to generating treatment files.…”