Background: Although cells require nutrients to proliferate, most nutrient exchange rates of the NCI60 panel of cancer cell lines correlate poorly with their proliferation rate. Here, we provide evidence indicating that this inconsistency is rooted in the variability of cell size. Results: We integrate previously reported data characterizing genome copy number variations, gene expression, protein expression and exchange fluxes with our own measurements of cell size and protein content in the NCI60 panel of cell lines. We show that protein content, DNA content, and protein synthesis per cell are proportional to the cell volume, and that larger cells proliferate slower than smaller cells. We estimate the metabolic fluxes of these cell lines and show that their magnitudes are proportional to their protein synthesis rate and, after correcting for cell volume, to their proliferation rate. At the level of gene expression, we observe that genes expressed at higher levels in smaller cells are enriched for genes involved in cell cycle, while genes expressed at higher levels in large cells are enriched for genes expressed in mesenchymal cells. The latter finding is further corroborated by the induction of those same genes following treatment with TGFβ, and the high vimentin but low E-cadherin protein levels in the larger cells. We also find that aromatase inhibitors, statins and mTOR inhibitors preferentially inhibit the in vitro growth of cancer cells with high protein synthesis rates per cell. Conclusions: The NCI60 cell lines display various metabolic activities, and the type of metabolic activity that they possess correlates with their cell volume and protein content. In addition to cell proliferation, cell volume and/or biomarkers of protein synthesis may predict response to drugs targeting cancer metabolism.

Autophagy is an important cellular catabolic process that plays a variety of important roles, including maintenance of the amino acid pool during starvation, recycling of damaged proteins and organelles, and clearance of intracellular microbes. Currently employed autophagy detection methods include fluorescence microscopy, biochemical measurement, SDS-PAGE and western blotting, but they are time consuming, labor intensive, and require much experience for accurate interpretation. More recently, development of novel fluorescent probes have allowed the investigation of autophagy via standard flow cytometry. However, flow cytometers remain relatively expensive and require a considerable amount of maintenance. Previously, image-based cytometry has been shown to perform automated fluorescence-based cellular analysis comparable to flow cytometry. In this study, we developed a novel method using the Cellometer image-based cytometer in combination with Cyto-ID® Green dye for autophagy detection in live cells. The method is compared with flow cytometry by measuring macroautophagy in nutrient-starved Jurkat cells. Results demonstrate similar trends of autophagic response, but different magnitude of fluorescence signal increases, which may arise from different analysis approaches characteristic of the two instrument platforms. The possibility of using this method for drug discovery applications is also demonstrated through the measurement of dose-response kinetics upon induction of autophagy with rapamycin and tamoxifen. The described image-based cytometry/fluorescent dye method should serve as a useful addition to the current arsenal of techniques available in support of autophagy-based drug discovery relating to various pathological disorders.

Oncologists have investigated the effect of protein or chemical-based compounds on cancer cells to identify potential drug candidates. Traditionally, the growth inhibitory and cytotoxic effects of the drugs are first measured in 2D in vitro models, and then further tested in 3D xenograft in vivo models. Although the drug candidates can demonstrate promising inhibitory or cytotoxicity results in a 2D environment, similar effects may not be observed under a 3D environment. In this work, we developed an image-based high-throughput screening method for 3D tumor spheroids using the Celigo image cytometer. First, optimal seeding density for tumor spheroid formation was determined by investigating the cell seeding density of U87MG, a human glioblastoma cell line. Next, the dose–response effects of 17-AAG with respect to spheroid size and viability were measured to determine the IC₅₀ value. Finally, the developed high-throughput method was used to measure the dose response of four drugs (17-AAG, paclitaxel, TMZ, and doxorubicin) with respect to the spheroid size and viability. Each experiment was performed simultaneously in the 2D model for comparison. This detection method allowed for a more efficient process to identify highly qualified drug candidates, which may reduce the overall time required to bring a drug to clinical trial.

Trypan blue has long been the gold standard for staining dead cell to determine cell viability. The dye is excluded from membrane-intact live cells, but can enter and concentrate in membrane-compromised dead cells, rendering the cells dark blue. Over the years, there has been an understanding that trypan blue is inaccurate for cell viability under 80% without scientific support. We previously showed that trypan blue can alter the morphology of dead cells to a diffuse shape, which can lead to over-estimation of viability. Here, we investigate the origin of the dim and diffuse objects after trypan blue staining. Utilizing image and video acquisition, we show real-time transformation of cells into diffuse objects when stained with trypan blue. The same phenomenon was not observed when staining cells with propidium iodide. We also demonstrate the co-localization of trypan blue and propidium iodide, confirming these diffuse objects as cells that contain nuclei. The videos clearly show immediate cell rupturing after trypan blue contact. The formation of these diffuse objects was monitored and counted over time as cells die outside of the incubator. We hypothesize and demonstrate that rapid water influx may have caused the cells to rupture and disappear. Since some dead cells disappear after trypan blue staining, the total can be under-counted, leading to over-estimation of cell viability. This inaccuracy could affect the outcomes of cellular therapies, which require accurate measurements of immune cells that will be infused back into patients.