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Content archived on 2024-06-18

Signaling Networks of Ovarian Cancer Metastates, Stem Cells and Maturation Phenotypes

Objective

Tumors are by definition both variable and highly adaptive, allowing them to grow beyond their original onset site and invade other organs, and in the process evading physiological intra and extracellular anti-tumor responses, and sometimes chemotherapy. This study proposes that ovarian cancers, and the heterogeneous cells that compose them, can be defined as a cell population(s) with an immature surface and signaling phenotype (with attendant self-replicative capacities) as well as a population(s) of cells with a more 'mature cell' phenotype. The expectation is that these two stages define a parent-daughter cell hierarchy and that this series of maturation events can be modeled akin to normal differentiation – with a set of pools of cells with a defined, stable phenotype linked to each other through transition state intermediates. Here, I apply a single cell systems biology approach to map signaling states at each stage of this proposed cancer-associated differentiation of ovarian cancer using perturbation mapping and high throughput systems biology approaches. The proposal will define the mechanistic underpinnings of ovarian cancer stem cells and the more mature phenotypes, the signaling states of cancer stem cells and daughter cells within patients that are resistant to cancer therapy, and finally a map that delineates the robustness profiles of the cancer-associated differentiation signaling networks and thereby optimal entry points for therapeutic interventions.

Fields of science (EuroSciVoc)

Topic(s)

Call for proposal

FP7-PEOPLE-2009-IOF
See other projects for this call

Funding Scheme

MC-IOF - International Outgoing Fellowships (IOF)

Coordinator

EUROPEAN MOLECULAR BIOLOGY LABORATORY
EU contribution
€ 244 439,90
Address
Meyerhofstrasse 1
69117 Heidelberg
Germany
Region
Baden-Württemberg Karlsruhe Heidelberg, Stadtkreis
Activity type
Research Organisations
Links
Total cost
No data