Spaniards have their daily siesta, Germans like sausages and Belgians love beer. Stereotypes can certainly be misleading, just like judging a cell by its membership to a particular cell type, the so-called population-based analysis. Nowadays we know that tumors are tremendously heterogeneous and, in the era of single-cell sequencing, we have the exquisite opportunity to study each individual cell with unprecedented resolution. Acute lymphoblastic leukemia (ALL), which is the most common cancer in children, shows extensive genetic intratumoral heterogeneity. This heterogeneity might be the underlying reason for an incomplete response to treatment and for the development of relapse. In order to envision its clinical implementation, it is essential to first i) generate a single-cell map and ii) accumulate evidence on how the subclonal composition affects the response to treatment. With this aim, I will build a comprehensive single-cell overview of the composition, development and response to therapy for the aggressive subtype T-cell ALL. I will perform integrative single-cell genome and transcriptome profiling of ex vivo carefully selected pediatric samples at diagnosis, during drug treatment and in case of relapse. This approach will provide realtime temporal information about the sensitivity of each cell type to the therapy and about how relapse can develop. I will use state-of-the-art single-cell technologies to which the host institute has early access. Moreover, I will apply my previous single-cell expertise and bring a unique mix of experimental and computational skills to the lab. The results of scTALLmap, will have significant impact in leukemia by paving the way for improved risk-stratification based on the cellular heterogeneity and the presence of high-risk subclones at diagnosis. Ultimately, it will permit the design of novel and more personalized therapeutic modalities sparing toxicity and targeting the full complement of leukemia subclones.
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