Comparison of mono- and coculture: advantages and challenges
| . | Monoculture . | Coculture . |
|---|---|---|
| Spontaneous apoptosis | (−) Samples with low viability (<0.25) present a technical challenge | (+) Samples with low viability are rescued from spontaneous apoptosis |
| Plate-positional effects | (−) Edge effect: edge wells have systematically lower viabilities | (+) No edge effect |
| Reproducibility | (+) Good correlation (r = 0.92) | (+) Good correlation (r = 0.88) |
| Microenvironmental effects | (−) No signals from the microenvironment | (+) Ex vivo model of the bone marrow microenvironment |
| Drug sensitivity | (+) Drug sensitivity profiles can be used for personalized medicine (citations) | (++) Drug sensitivity profiles in presence of microenvironment signals |
| Drug-gene associations | (++) Many drug-gene associations are correlated with the clinical outcome | (+) Directions of drug-gene associations preserved. Lower effect size estimates. Variance reduction enhances some associations |
| Experimental complexity | (+) Easy to handle | (−) More labor-intense |
| Image analysis | (+) Straightforward | (−) Requires additional staining or machine learning to separate cancer cells from stromal cells |
| . | Monoculture . | Coculture . |
|---|---|---|
| Spontaneous apoptosis | (−) Samples with low viability (<0.25) present a technical challenge | (+) Samples with low viability are rescued from spontaneous apoptosis |
| Plate-positional effects | (−) Edge effect: edge wells have systematically lower viabilities | (+) No edge effect |
| Reproducibility | (+) Good correlation (r = 0.92) | (+) Good correlation (r = 0.88) |
| Microenvironmental effects | (−) No signals from the microenvironment | (+) Ex vivo model of the bone marrow microenvironment |
| Drug sensitivity | (+) Drug sensitivity profiles can be used for personalized medicine (citations) | (++) Drug sensitivity profiles in presence of microenvironment signals |
| Drug-gene associations | (++) Many drug-gene associations are correlated with the clinical outcome | (+) Directions of drug-gene associations preserved. Lower effect size estimates. Variance reduction enhances some associations |
| Experimental complexity | (+) Easy to handle | (−) More labor-intense |
| Image analysis | (+) Straightforward | (−) Requires additional staining or machine learning to separate cancer cells from stromal cells |