Spårning av klonal evolution i cancer som ett verktyg för att styra behandling

Drug resistance represents a fundamental obstacle to the successful treatment of many cancer types, including that of BCP-ALL. This malignancy is a leading cause of pediatric cancer deaths. Despite a generally good prognosis, 10% of children still relapse. Additionally, current therapy is responsible for increasing pediatric deaths and serious comorbidities.

Therefore, highlighting an urgent need for less toxic treatments.

With this task at hand, we have recently explored the relative contributions of genetic and epigenetic factors to the emergence of treatment resistance during induction chemotherapy.

Our preliminary results suggest that phenotypic diversity - not genetic - is the prime substrate for selection during this early phase of treatment in childhood BCP-ALL.Nonetheless, analysis of matching diagnostic and relapse samples has previously shown only partial overlap between these both at the genomic and transcriptional level, suggesting that the relapsing disease might, at some point following treatment, also transit through a stage of genetic homogeneity as a consequence of either a clonal sweep or stochastic selection.

The scope of this research proposal is to develop a systems biology-inspired integrative framework, which combines thoughtfully designed cell biology experiments with the design and calibration of mathematical models, to support predictions of optimal treatment dose modulation and identification of dynamic response biomarkers.