Fig. 5

Evolution of relapse lymphoblast population. a Estimated size (number of cells) of the relapse population at the time of diagnosis according to the computed doubling time. Error bars represent the estimates of cell populations from the first and third quartile of the doubling time estimates, which are 10.1 and 11.36 respectively (see Additional file 2: Fig. S9). Horizontal dotted lines represent sizes corresponding to one cell and 10⁸ cells (0.01% of the population: the threshold of clinical relapse). Asterisks denote patients with estimates above the threshold of 0.01. The resolution limit of the dPCR is also represented by a horizontal line (~ 1:10,000). b Schematic representation of the two considered scenarios of relapse of T-ALL patients after treatment. Mutations in T-ALL cells are represented as different geometric figures. In the first scenario (resistant), one mutation in the primary T-ALL below the limit of detection of the sequencing and the digital PCR (red star) provides resistance to the treatment. All cells with this mutation survive the bottleneck posed by the treatment, and thus, this mutation and all other common to the resistant cells (hitchhikers) appear in the relapse population at CCF 1. In the second scenario (non-resistant), a group of cells with an ensemble of mutations survive the treatment. c Distribution (frequency) of CCF values of mutations in primary T-ALLs in the in-house cohort that are identified in their relapse counterparts as fixed (> 0.9 relapse CCF). Mutations are grouped within CCF bins. Each line represents one patient, for example, the dash brown line corresponds to PAT8, discussed in the text. d Distribution (frequency) of CCF values of mutations in synthetic primary T-ALL populations in evolutionary simulations following the non-resistant scenario. The dots represent mutations binned at different CCF values with the frequency that each bin represents with respect to all mutations in each synthetic relapse population. The average results of six simulation settings with different values of fitness of driver mutations and number of cell generations are presented