Single-cell genotyping demonstrates complex clonal diversity in acute myeloid leukemia

Abstract

Clonal evolution in cancer-the selection for and emergence of increasingly malignant clones during progression and therapy, resulting in cancer metastasis and relapse-has been highlighted as an important phenomenon in the biology of leukemia and other cancers. Tracking mutant alleles to determine clonality from diagnosis to relapse or from primary site to metastases in a sensitive and quantitative manner is most often performed using next-generation sequencing. Such methods determine clonal frequencies by extrapolation of allele frequencies in sequencing data of DNA from the metagenome of bulk tumor samples using a set of assumptions. The computational framework that is usually used assumes specific patterns in the order of acquisition of unique mutational events and heterozygosity of mutations in single cells. However, these assumptions are not accurate for all mutant loci in acute myeloid leukemia (AML) samples. To assess whether current models of clonal diversity within individual AML samples are appropriate for common mutations, we developed protocols to directly genotype AML single cells. Single-cell analysis demonstrates that mutations of FLT3 and NPM1 occur in both homozygous and heterozygous states, distributed among at least nine distinct clonal populations in all samples analyzed. There appears to be convergent evolution and differential evolutionary trajectories for cells containing mutations at different loci. This work suggests an underlying tumor heterogeneity beyond what is currently understood in AML, which may be important in the development of therapeutic approaches to eliminate leukemic cell burden and control clonal evolution-induced relapse.

Figure 1. Describing clonal evolution in bulk AML samples obscures underlying diversity

(A) Large, next-generation sequencing (NGS) efforts identify the mutant allele frequencies (AF) in bulk samples for multiple genes simultaneously (genes A-H). These AF are then used to calculate the population frequency of the clones that contain each mutation by assuming all mutations are heterozygous and are added sequentially (a clone containing the cluster of mutations including A/B would be the “founder” clone, and the subclones must contain A/B/C/D and would then be assumed to be subsequent to the founder clone). Mutant alleles below the threshold of detection, which depends on the type of NGS used, the sample quality and the coverage/filtering, cannot be attributed to a cancer clone mathematically. (B) Examples of clonal distributions for Gene A that would produce the same allele frequency when analyzed in the bulk sample. If the mutation is not constrained to be heterozygous, then the same allele frequency observed in a bulk sample can be obtained in many different distributions of zygosity. When combining multiple mutations, this allows for an exponentially increasing number of possible genotype combinations that would each produce the observed overall allele frequencies for each mutant allele. (C) Many combinations of genotypes exist even when multiple mutations occur in the same sample. In the case of two mutations, there are 9 possible mutation/zygosity combinations that could occur in individual cells, which, depending on their relative proportions, could reconstitute the bulk allele frequencies.

Figure 2. Validation of single cell genotyping via a comparison to the bulk data

A reference patient sample containing two different FLT3-ITDs of different lengths was analyzed by single cell genotyping for FLT3 during technique validation. The approach used for bulk analyses clinically is to determine the allele ratio (AR) of mutant (ITD-1 or ITD-2) alleles to that of the wild type (WT) as demonstrated in (A). Adaptation of this technique to single cells was applied to the reference sample, with a total sample size of 593 cells. Error bars in (B) are the 99% confidence intervals for the population frequencies of each FLT3-ITD zygosity (WT=wild type, Het=heterozygous, Mut=homozygous mutant). Bulk allelic ratio was calculated via a bulk fragment analysis with the same primers used for single cell genotyping, converted to an allele frequency (AF=AR/(1-AR)), and compared to the calculated numbers obtained via single cell genotyping to ensure accuracy in the overall data set (C). These values were then tracked for the 7 patient samples analyzed for FLT3 and NPM1 (D).

Figure 3. Genetically distinct clonal frequencies in AML with respect to FLT3-ITD and NPM1

Bubble plot of the clonal distribution of six AML patient samples at diagnosis (and one analyzed at relapse, Pt4-R) showed the presence of all possible combined genotypes for the mutant genes present in each sample, although at a variable frequency. Pt1-4 and 4-R contained one each of FLT3-ITD and NPM1 mutations, and Pt5-6 had two FLT3-ITDs and an NPM1 mutation. Note that none of the samples with two ITD lengths had clones containing both ITDs simultaneously.

Figure 4. Comparison of observed clonal distributions to those calculated via bulk data

Observed cell numbers scored with each genetic identity in the single cells of each patient sample are shown in shaded bars. Null distributions generated by predicting clonal distributions based on technical uncertainty and existing assumptions of heterozygosity and concurrence of mutations to link mutant allele frequency and clonal frequency are shown as wireframe. This distribution is based on the allelic frequencies in the bulk samples (Figure 2D).