ArticleBMC cancer2019
An image-based assay to quantify changes in proliferation and viability upon drug treatment in 3D microenvironments.
Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 31 citations in OpenAlex.
- In situ detection of dead cells from live cells via a DC plus low frequency AC resistive pulse sensor.Biomedical microdevices · 2026Article
- Assessment of Cell Viability in Drug Therapy: IC50 and Other New Time-Independent Indices for Evaluating Chemotherapy Efficacy.Pharmaceutics · 2025Article
- A 3D spheroid model for assessing nanocarrier-based drug delivery to solid tumors.npj biomedical innovations · 2025Article
- Article
- Proteolysis-free amoeboid migration of melanoma cells through crowded environments via bleb-driven worrying.Developmental cell · 2024Article
- Nondestructive, quantitative viability analysis of 3D tissue cultures using machine learning image segmentation.APL bioengineering · 2024Article
- RhoA activation promotes glucose uptake to elevate proliferation in MAPK inhibitor resistant melanoma cells.bioRxiv : the preprint server for biology · 2024Article
- Three-Dimensional Spheroids for Cancer Research.Methods in molecular biology (Clifton, N.J.) · 2023Article
- 3D cancer models: One step closer toFrontiers in immunology · 2023Review
- In vivo 3D profiling of site-specific human cancer cell morphotypes in zebrafish.The Journal of cell biology · 2022Article
- 3D Tissue-Engineered Vascular Drug Screening Platforms: Promise and Considerations.Frontiers in cardiovascular medicine · 2022Review
- 3D Cell Culture Models as Recapitulators of the Tumor Microenvironment for the Screening of Anti-Cancer Drugs.Cancers · 2021Review
- Review
- Fibroblasts Influence Metastatic Melanoma Cell Sensitivity to Combined BRAF and MEK Inhibition.Cancers · 2021Article
- Real-time multi-angle projection imaging of biological dynamics.Nature methods · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundEvery biological experiment requires a choice of throughput balanced against physiological relevance. Most primary drug screens neglect critical parameters such as microenvironmental conditions, cell-cell heterogeneity, and specific readouts of cell fate for the sake of throughput.
methodsHere we describe a methodology to quantify proliferation and viability of single cells in 3D culture conditions by leveraging automated microscopy and image analysis to facilitate reliable and high-throughput measurements. We detail experimental conditions that can be adjusted to increase either throughput or robustness of the assay, and we provide a stand alone image analysis program for users who wish to implement this 3D drug screening assay in high throughput.
resultsWe demonstrate this approach by evaluating a combination of RAF and MEK inhibitors on melanoma cells, showing that cells cultured in 3D collagen-based matrices are more sensitive than cells grown in 2D culture, and that cell proliferation is much more sensitive than cell viability. We also find that cells grown in 3D cultured spheroids exhibit equivalent sensitivity to single cells grown in 3D collagen, suggesting that for the case of melanoma, a 3D single cell model may be equally effective for drug identification as 3D spheroids models. The single cell resolution of this approach enables stratification of heterogeneous populations of cells into differentially responsive subtypes upon drug treatment, which we demonstrate by determining the effect of RAK/MEK inhibition on melanoma cells co-cultured with fibroblasts. Furthermore, we show that spheroids grown from single cells exhibit dramatic heterogeneity to drug response, suggesting that heritable drug resistance can arise stochastically in single cells but be retained by subsequent generations.
conclusionIn summary, image-based analysis renders cell fate detection robust, sensitive, and high-throughput, enabling cell fate evaluation of single cells in more complex microenvironmental conditions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.