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cancer development is believed to be governed by appearance and accumulation of driving mutations that collectively reprogram molecular mechanisms at the level of global cell populations. however, these mutations may also have more general systemic effects: in particular, they may trigger diversification of cell properties leading to an increased cell-to-cell variability at the basis of the remarkable adaptation potential of cancer cells. single-cell rna-seq profiling provides an exciting opportunity to investigate the heterogeneity of cancer cell populations directly by measuring individual cancer cell transcriptomes. ewing sarcoma (es), a pediatric cancer characterized by the expression of ews-fli1, an aberrant chimeric transcription factor, is characterized by very few somatic mutations and a very low sub-clonal genetic heterogeneity. nevertheless, it exhibits all features of the remarkable adaptation potential of cancer cells suggesting that this potential is not a simple consequence of a mutation-based darwinian selection process. we aim at characterizing and mathematical modeling the effects of a ews-fli1 on the structure of the cell-to-cell transcriptome variability. inducible systems have been previously characterized and mathematically modeled at the averaged cell population level. pilot studies already proved the feasibility of the single cell rna-seq approach. the objectives of the project are: 1) characterize the dynamics of cell-to-cell variability induced by ews-fli1 activation and map the variance distribution onto various cellular functions- 2) explicitly model the process of adaptation in cancer cell populations mediated by biological networks- 3) validate the predictions in targeted experiments. the partners of the project are geographically co-localized, have proven expertise in both wet and computational systems biology and have a long record of successful collaboration on the systems biology of es.