Abstract
In this paper, we analyse the behaviour of osteosarcoma cancer cells which are either exposed to the anticancer agent Topotecan or not exposed to any external agent. For the analyses of cell lineage data encoded from time lapse microscopy, we choose data mining tools that generate interpretable models of the data, and we address their statistical significance. We consider the mortality of unexposed cancer cells; the static and dynamic cytotoxic effects of the anticancer agent; the prediction of the clonal potential of resistant populations; and the differences between exposed and unexposed populations. We find that the anticancer agent affects the cells dynamics and events ratios i.e. (death/division, etc.) proportionately to its concentration, but it is ineffective at stopping the proliferation of the cancer at all dosages considered. In addition, we observe that cells exposed to the anticancer agent have greater displacements over time, indicating a putative relationship between cytotoxic effect and cell motility.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 10th IEEE International Conference on Data Mining Workshops, ICDMW 2010 |
| Pages | 732-739 |
| Number of pages | 8 |
| DOIs | |
| Publication status | Published - 2010 |
| Event | 10th IEEE International Conference on Data Mining Workshops, ICDMW 2010 - Sydney, NSW, Australia Duration: 14 Dec 2010 → 17 Dec 2010 |
Publication series
| Name | Proceedings - IEEE International Conference on Data Mining, ICDM |
|---|---|
| ISSN (Print) | 1550-4786 |
Conference
| Conference | 10th IEEE International Conference on Data Mining Workshops, ICDMW 2010 |
|---|---|
| Country/Territory | Australia |
| City | Sydney, NSW |
| Period | 14/12/10 → 17/12/10 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Cancer
- Cell lineage
- Data mining
- Drug resistance
- Topotecan
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