Deciphering the self-organizing principles governing the cellular composition and growth of tumors
Unlike developing tissues, tumors have long been considered as highly disorganized tissues. However, recent studies suggest that some tumors may be more organized than initially envisaged. In particular, tumors are often composed of different cell types with different proliferative properties, and it has been shown that the cellular composition is robustly maintained over time. However, the mecanisms regulating the cellular composition of tumors are unknown. Using a simple model of brain tumors in Drosophila, we have demonstrated that the growth and cellular composition is predictable and driven by a fine-tuned hierarchical scheme of cell divisions (DOI: 10.7554/eLife.50375). Moreover, we have observed a typical spatial organization of tumor cells suggesting robust underlying self-organizing rules. Using computer simulations combined with genetic manipulations and live imaging, our aim is to investigate whether the cellular composition and the growth of tumors is governed by emerging properties of the tumor cell populations.
Tumor self-organization, numerical simulation, confocal microscopy, image analysis, Drosophila genetics
Our objective is to investigate whether the spatial organization of the different cell types observed in tumors reflects self-organizing principles that determine the cellular composition and tumor growth rate. The student will investigate experimentally predictions made by a newly-developed 3D-numerical model. The aim will be to generate new quantitative data from the live imaging of growing tumors in different genetic contexts and integrate them into the model in order to uncover the tumor-specific self-organizing rules.
Proposed approach (experimental / theoretical / computational)
Our recent computer simulations suggest that tumor cells have to obey various rules of feedback mechanisms and differential adhesion in order to recapitulate the spatial organization and composition observed in tumors. Our aim is now to gain quantitative insights of cell dynamics and cellular organization in tumors using in vivo confocal microscopy in order to identify which simulation-based scenario fits with reality. In addition to improve the live imaging protocol, the candidate will have to use state-of-the-art image analysis tools and familiarize with Drosophila genetics to investigate further the underlying molecular mechanisms. He will also be introduced to the computer model in order to be able to feed the model with parameters gained from the in vivo observation.
The candidate will be co-supervised by a biologist (Cédric Maurange) and a physicist (Raphaël Clément), both localized in different teams of the Institute of Developmental Biology of Marseille (IBDM). He/she will share the time between the two labs.
In the biology lab, the candidate will familiarize with basic rules of tumor biology and Drosophila genetics, perform live imaging using confocal microscopy, and image analysis.
In the modeling lab, he/she will be introduced to the 3D numerical model of tumor growth and learn how to test novel predictions based on in vivo observations.
Thus, the candidate will be confronted to a multidisciplinary environment and will gain expertise in experimental biology, imaging and numerical modeling.
The candidate should have a Master (or international equivalent) in physics, biophysics or biology. A good knowledge in computer programming, numerical simulations, and a strong desire to carry out experimental work, in particular imaging of living tissues is mandatory.
Is this project the continuation of an existing project or an entirely new one? In the case of an existing project, please explain the links between the two projects
This project is the continuation of a collaborative project between CM and RC that aimed at generating numerical simulations of hierarchical tumors. These simulations have led to several scenarios providing some explanation for how tumor cells can self-organize to generate tumors with a predictable cellular composition and growth rate. The current project aims at generating quantitative measurements of cellular behaviors in tumors in order to identify the correct scenario and decipher the self-organizing rules governing tumor growth.
2 to 5 references related to the project
- Genovese S, Clement* R, Gaultier* C, Besse F, Narbonne-Reveau K, Daian F, Foppolo S, Luis N,M, Maurange C. (2019) Coopted temporal patterning governs cellular hierarchy, heterogeneity and metabolism in Drosophila neuroblast tumors. eLife. 2019 Sep 30;8:e50375. doi: 10.7554/eLife.50375.
- Maurange C. (2020) Temporal patterning in neural progenitors: from Drosophila development to childhood cancers. Disease Models & Mechanisms: dmm044883 doi: 10.1242/dmm.044883 Published 22 July 2020
- Schweisguth F, Corson F. (2019)Self-Organization in Pattern Formation. Dev Cell. 2019 Jun 3;49(5):659-677. doi: 10.1016/j.devcel.2019.05.019.
- Rich JN. (2016) Cancer stem cells: understanding tumor hierarchy and heterogeneity. Medicine (Baltimore). 2016 Sep;95(1 Suppl 1):S2-7. doi: 10.1097/MD.0000000000004764.
3 main publications from each PI over the last 5 years
1. Genovese S, Clement* R, Gaultier* C, Besse F, Narbonne-Reveau K, Daian F, Foppolo S, Luis N,M, Maurange C. (2019) Coopted temporal patterning governs cellular hierarchy, heterogeneity and metabolism in Drosophila neuroblast tumors. eLife. 2019 Sep 30;8:e50375. doi: 10.7554/eLife.50375.
2. Narbonne-Reveau K, Maurange C. Developmental regulation of regenerative potential in Drosophila by ecdysone through a bistable loop of ZBTB transcription factors. (2019) PLoS Biology. Feb 11;17(2):e3000149. doi: 10.1371/journal.pbio.3000149
3. Narbonne-Reveau* K, Lanet* E, Dillard* C, Foppolo S, Chen CH, Parrinello H, Rialle S, Sokol NS, Maurange C. (2016) Neural stem cell-encoded temporal patterning delineates an early window of malignant susceptibility in Drosophila. eLife. Jun 14;5. pii: e13463. doi: 10.7554/eLife.13463
4. Dehapiot B, Clément R, Bourdais A, Carrière V, Huet S, Halet G. RhoA- and Cdc42-induced antagonistic forces underlie symmetry breaking and spindle rotation in mouse oocytes. PLoS Biol. 2021 Sep 7;19(9):e3001376. doi: 10.1371/journal.pbio.3001376. PMID: 34491981; PMCID: PMC8448345.
5. B. Dehapiot, R. Clément, H. Alégot, G. Gazsó-Gerhát, J.-M. Philippe, T. Lecuit
Assembly of a persistent apical actin network by the formin Frl/Fmnl tunes epithelial cell deformability. Nature Cell Biology 2020
5. W. Kong, O. Loison, P. Shivakumar, E.H. Chan, M. Saadaoui, C. Collinet, P.-F. Lenne, R. Clément
Experimental validation of force inference in epithelia from cell to tissue scale, Scientific reports 2019
6. R. Clément, B. Dehapiot, C. Collinet, T. Lecuit, P.-F. Lenne
Viscoelastic dissipation stabilizes cell shape changes during tissue morphogenesis, Current Biology 2017