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Walter Blum
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P1.09 - Mesothelioma (ID 695)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Mesothelioma
- Presentations: 1
- Moderators:
- Coordinates: 10/16/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P1.09-002 - Cellular Noise and Positional Effects Determine the Cell Stem State in Malignant Mesothelioma (ID 9029)
09:30 - 16:00 | Presenting Author(s): Walter Blum
- Abstract
Background:
Rapid recurrence after first-line therapy is a major concern in malignant mesothelioma (MM) and cancer stem cells (CSC) are assumed to be responsible for this phenomenon. Cellular noise is defined as the random variability of quantities, of for example proteins, in individual genetically identical cells. Since a cell’s differentiation status is also determined by levels of some transcription factors, as the result of cellular noise, all differentiated cells might de-differentiate to a stem cell state, if enough time is given for this event to occur.
Method:
In order to provide direct evidence for this hypothesis, the “stemness” of individual cells was continuously monitored in human and murine malignant mesothelioma cells over the period of several months. Re-expression of the top hierarchical stemness markers Sox2 and Oct4 evidenced by the appearance of eGFP driven by a genetically-encoded stemness reporter construct was observed in the subpopulation of differentiated eGFP(-) cells in the above cell types.
Result:
A transition event from a differentiated to a de-differentiated cell was found to be extremely rare. Yet, when it was occurring, the probability of the neighboring cells, not only the direct descendants of a novel eGFP(+) stem cell, to also become an eGFP(+) stem cell, was increased by a positional effect. This led to a clustered “mosaic” re-appearance of CSC. eGFP(+) cells were found to re-appear even from cell cultures derived from one single bulk eGFP(-) cell.
Conclusion:
Based on these findings, a novel tumor growth model was developed; it is well suited to accurately predict the clustered localization of cancer stem cells within a tumor mass, in congruence with our experimental in vitro and in vivo findings. The robustness of the model is currently tested on a large collection of human pleural mesothelioma cell lines bearing different mutations and being of diverse histological subtypes.
