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Issue 250: When cancer is diagnosed, the evolutionary processes shaping its genetic makeup have been active for an unknown time span, posing a formidable challenge for understanding the dynamics of tumor initiation and growth. In our recent paper, we combined deep whole genome sequencing with mathematical modeling to retrospectively infer when and how neuroblastoma, the most frequent solid tumor in infants with very diverse clinical outcome, arises. Using neutral mutation accumulation as a molecular clock, our analysis revealed that the first oncogenic mutations occurred in a transient population of neuroblasts within the first trimester of pregnancy, irrespective of clinical subtype. However, while low-risk tumors immediately commenced growing, high-risk tumors showed prolonged evolution at tumor initiation and started to expand only after telomere-maintenance mechanisms had been positively selected in a pre-malignant cell population. We propose that the clonal mutation burden, which scales with the duration of initial evolution and is hence higher in high-risk than in low-risk tumors, may be an accurate predictor of clinical outcome.