Functional heterogeneity of genetically defined subclones in acute myeloid leukemia

Abstract

The relationships between clonal architecture and functional heterogeneity in acute myeloid leukemia (AML) samples are not yet clear. We used targeted sequencing to track AML subclones identified by whole-genome sequencing using a variety of experimental approaches. We found that virtually all AML subclones trafficked from the marrow to the peripheral blood, but some were enriched in specific cell populations. Subclones showed variable engraftment potential in immunodeficient mice. Xenografts were predominantly comprised of a single genetically defined subclone, but there was no predictable relationship between the engrafting subclone and the evolutionary hierarchy of the leukemia. These data demonstrate the importance of integrating genetic and functional data in studies of primary cancer samples, both in xenograft models and in patients.

Figure 1. Mutational and subclonal comparison of peripheral blood and bone marrow leukemia samples

Unfractionated bone marrow and peripheral blood leukemia samples were characterized by targeted capture followed by deep sequencing. (A) Similarity of the variant allele fractions (VAFs) of somatic variants for 19 AML cases (all variants with coverage >50 from all samples are shown). Variants present in coding regions of the genome are shown red, non-coding in grey, and sex chromosome variants in blue. (B) Four representative cases of the peripheral blood versus the bone marrow samples, demonstrating cases with strong concordance (AML31 and AML28) and more variable subclonal distributions (AML43 and AML88). (C) Comparison of the VAFs of recurrent AML mutations in paired peripheral blood and bone marrow samples, including coding mutations in DNMT3A, FLT3 (both ITD and D835), NPMc, and canonical IDH1, IDH2, and KRAS/NRAS mutations. See also Figure S1 and Tables S1–S3.

Figure 2. Distribution of leukemia variants and subclones in peripheral blood cells

(A) Representative sample demonstrating the isolation of different cell populations by flow cytometry using a combination of side-scatter, CD45 and CD33, as well as CD19 and CD3 when sufficient cells were available. *, maturing myelomonocytic cells. Scale bar in photomicrographs represents 10 μm. (B–D) Correlation of the bone marrow VAF with flow sorted and enriched blasts (B), non-blast, non-lymphocytes, including maturing myelomonocytic cells and monocytes (C), and lymphocytes (D). Variants present in coding regions of the genome are shown red, non-coding in grey, and sex chromosome variants in blue. See also Figure S2 and Tables S4–S6.

Figure 3. Subclonal enrichment in distinct myeloid sub-populations

(A) Cells from AML31 were flow sorted and distinct morphologic populations were confirmed by morphologic examination. Note Auer Rod present in the myeloblast (*). Scale bar in photomicrographs represents 10 μm. (B) Clonality plot demonstrating the relationship of the de novo AML31 tumor and the relapse leukemia (Ding et al., 2012). Important coding mutations are highlighted. (C–E) Clonality plots demonstrating the relationship of the de novo leukemias to different cell populations; (C) AML31, blasts (top) and monocytes (bottom); (D) AML28, blasts (top) and maturing myelomonocytic cells (bottom); (E) AML87, blasts (top) and monocytes (bottom). For all clonality plots, only variants in computationally-identified clusters (SciClone, Miller et al., submitted) that are diploid (copy number = 2) and with coverage depth >50 are shown. See also Figure S3.

Figure 4. Single cell genotyping of primary AML samples

Individual cells from AML samples 28 and 31 were isolated by flow cytometry and single cell genotypes were determined by whole genome amplification and amplicon-based sequencing. (A) Flow sorting strategy for AML28, in which individual myeloid cells (excluding lymphocytes) or maturing myelomonocytic cells were collected. (B–G) Single cell genotyping results. B, C, and F show the proportion of cells harboring leukemia-associated variants predicted from the VAFs in unfractionated cells (in blue) and observed in individual cells (in red) for individual myeloid cells (B) and maturing myelomonocytic cells (C) from AML28, and peripheral blood from AML31 (F). For each comparison the predictions from unfractionated cells used VAFs obtained directly from deep sequencing read counts (and multiplied by 2 to correct for heterozygosity), and the observed single cell proportions were obtained from single cell genotyping experiments. Error bars show the 95% binomial confidence interval for each point estimate. D, E, and G show single cell genotype frequencies from sorted myeloid cells (D) and maturing myelomonocytic cells (E) from AML28 and peripheral blood from AML31 (G). The bottom panel in each figure shows the observed single cell genotypes, with each column representing a single observed genotype that consists of at least one of the founding clone or subclonal variants in each subclone (indicated in red). The height of the vertical bars and corresponding numbers show the frequency and absolute number of cells with the indicated genotype, respectively. Only genotypes observed in more than 2 cells in each single cell experiment are shown; additional genotypes were also observed in low numbers of cells that are likely due to allele “dropout” (due to unequal amplification of the two alleles), which we estimated to be 30% using control data from heterozygous SNPs (see Supplemental Experimental Procedures). See also Figure S4.

Figure 5. Rare subclones can have unique in vitro growth properties

Cells were grown in human hematopoietic cytokines in the presence or absence of MS5 stromal cells for 7 days. (A) Fold change in cell number after 7 days. (B) Percentage of EdU-positive cells; cells were incubated with EdU for the last 18 hours of culture. Mean values (n=3) are shown, error bars represent standard deviation. (C–E) Subclonal architecture of AML1 (C), AML43 (D) and AML31 (E) at day 0 (label: de novo), relapse (Ding et al., 2012) and day 7 of culture (label: in vitro). Each column shows the VAFs (indicated on the Y-axis) of founding clone and subclonal variants for each case. See also Figure S5.

Figure 6. Phenotype and Subclonal Composition of AML31 Xenografts

Mice were injected with unfractionated peripheral blood leukemia cells and followed for 12–16 weeks, at which time cells were harvested from the bone marrow. (A) Representative examples of the immunophenotypic properties of AML31 xenografts in individual NSG and NSG-SGM3 mice. Shown are expression patterns of human CD34 and CD11b in the human myeloid leukemia cells (mCD45⁻, hCD45⁺, CD33⁺). (B) Human CD45⁺CD33⁺ cells were purified by cell sorting, and DNA was analyzed by targeted deep sequencing of all known somatic variants in the sample. The VAFs for all founding clone and subclonal variants are shown for each individual AML31 xenograft and the peripheral blood sample (input, far left). See also Figure S6 and Table S7.

Figure 7. Model of AML31 Subclonal Architecture and Predicted Phenotypes

Schematic representation of the implications of AML clonal heterogeneity, based on the integrated analysis of AML31. The “% of de novo sample” values were calculated from sequencing the unfractionated AML samples, and are consistent with data obtained from the interrogation of individual cells.