Toward complete laser ablation of melanoma contaminant cells in a co-culture outgrowth model via image cytometry
✍ Scribed by Feimo Shen; Jeffrey H. Price
- Publisher
- John Wiley and Sons
- Year
- 2006
- Tongue
- English
- Weight
- 353 KB
- Volume
- 69A
- Category
- Article
- ISSN
- 0196-4763
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
Background:
Contaminant cancer cells in autologous transplant tissue can cause relapse and the rates are unknown. A method capable of removing all contaminant cells with a high probability detected by cytomic analyses would be useful. Neither 100% cell purging nor techniques for measuring the probability of success have been developed. Here, we report a method for removing 100% of the cells under ideal staining conditions and quantify the probability of success.
Methods:
Laser ablation was combined with previously reported automated microscopy to purge contaminant cells and evaluate 100% ablation in a co‐culture model of prestained mouse melanoma cells mixed with mouse NIH‐3T3 cells. Melanoma passage efficiency was measured by: (1) micropipetting single cells into microtiter wells and (2) ablating all but one melanoma cell in co‐cultures.
Results:
(74 ± 5)% of single melanoma cells pipetted into microtiter plate wells divided at least once. With ablation of all but one contaminant cell in co‐cultures, melanoma dominated in (62 ± 8)% cultures in 21 days. With 100% ablation in six additional experiments, no melanoma outgrowth was observed, giving a >99.1% probability that all contaminant melanoma cells were purged.
Conclusions:
We successfully demonstrated a model for complete ablation within a defined probability using automated high‐content image cytometry with ideal staining conditions. The results show that the instrumentation is capable of delivering 100% ablation at a defined probability and establishes the basis for further studies with clinical models wherein pretherapeutic cytomic analyses of unique cellular expression and/or morphological characteristics will be key for contaminant cancer cell identification. © 2006 International Society for Analytical Cytology