Hematopoietic stem and progenitor cells (HSPC) immunophenotypes define AML specimens at different stages of the human hematopoietic hierarchy

To define a surrogate phenotype for each stage of normal myeloid maturation, we need to assess by flow cytometry, the expression of markers used to characterize AML routinely on HSPCs. HSC, MPP, CMP, GMP, and GP/MP can be characterized by gating in the lineage negative cell population according to their expression of CD34, CD38, CD90, and CD45RA (Supplemental Fig. 1A, B). Unfortunately, the expression of those markers is not classically evaluated in AML. To overcome this issue, we evaluated the expression levels of four myeloid antigens (CD13, CD33, CD117, and myeloperoxidase [MPO]) as well as CD34 and HLA-DR in 10 normal human bone marrow samples. HSC and MPP were characterized by the absence of MPO expression (Fig. 1A and Supplemental Fig. 1C). The expression of specific myeloid markers such as CD13 or CD33 was detectable from the MPP stage onward. GMP displayed the highest MPO expression (>70% of cells). HLA-DR expression discriminated MP (HLA-DR positive) and GP (HLA-DR negative). These data show that six markers (i.e, CD34, CD117, CD13, CD33, MPO, and HLA-DR) used to diagnose AML in routine clinical practice are differentially expressed in six immunophenotypically defined stages of normal myelopoiesis.

Fig. 1: Phenotypic and clinical identification of AML subgroups.

A Model of the relative percentage of myeloid marker expression over the course of normal HSPC differentiation. The SLA is defined by the combination of expressions of five myeloid markers plus HLA-DR to differentiate GP-L (HLA-DR+) and MP-L (HLA-DR−); +≥20% of blasts; −<20% of blasts; +/− marker can be positive or negative. B Principal component analyses of 945 AML using the percentage of AML blasts expression of 16 markers by flow cytometry (CD4, CD7, CD13, CD33, CD117, MPOc, CD34, HLA-DR, CD56, CD64, CD38, CD65, CD16, CD14, CD11b, CD123). AML patients were classified according to their SLA as detailed in (A). C Pie chart of 2087 AML from TUH cohort segregated according to their SLA. D FAB classification according to SLA in the TUH cohort. Fisher’s exact test compared FAB classification in one SLA to all others. E Extramedullary involvement in SLA (see Table 1 for details). F Boxplots of leukocytosis at diagnosis in TUH cohort. G CFU-L in TUH cohort. Statistical analysis was performed comparing one SLA to all others (Mann–Whitney test).

To correlate each stage of normal hematopoiesis with that of individual AML, we transformed HSPC immunophenotypes into immunophenotypic AML signatures (Fig. 1A). Thus, the SLA was assigned to each sample, based on leukemic bulk phenotype, because in the hierarchy of leukemic cells, the majority are stopped in their differentiation pathway. We tested our six-marker immunophenotypic signature by looking at the principal component analysis distribution of 945 AML, extensively characterized by the expression of 16 antigens (Fig. 1B and Supplemental Fig. 2A and B). Our six-marker signature was sufficient to discriminate between different hematopoietic/leukemic groups (Supplemental Fig. 2C, D). Overall, we defined, by flow cytometry, the stage at which the leukemic cell population accumulated as the stage of leukemia differentiation arrest.

Our data show that AML with an immunophenotypic signature similar to that of HSC (henceforth termed HSC-L) represented 0.9% (Fig. 1C). TUH cohort comprised 21.9% of MPP-L, 30.2% of CMP-L, 17.2% of GMP-L, 24.1% of MP-L, and 5.7% of GP-L. HSC-L and MPP-L were enriched in AML classified as FAB M0, while MP-L was enriched in acute monoblastic leukemia (FAB M5) and GP-L in AML classified as FAB M1 (Fig. 1D). The FAB M6 and M7 represented 2.9% and 1.4% of the TUH cohort, respectively. Classified by phenotype, their SLA were heterogeneous (Fig. 1D). Nevertheless, the SLA of 63.3% of the FAB M6 and M7 was identified as MPP-L or CMP-L, stages prior to the MEP branch (Supplementary Fig. 1A), whereas the remainder (1.5% of the total cohort) may have been misclassified because of the absence of erythroid and megakaryocytic markers in our panel. Thus, flow-based analysis of SLA correlates with the morphologic phenotype used to assign the FAB sub-group although the correlation is not completely consistent.

SLA retain functional and genetic imprints of their normal counterparts

Following induction of the differentiation process, HSPCs lose their capacity to self-renew, in favor of proliferation and migration. We, therefore, investigated the functional characteristics of the six SLA using clinical data and clonogenic properties as surrogate markers of migration (extramedullary involvement) and proliferation (leucocytosis) capacities. Cell migration capacities and emigration from the bone marrow are known to be features acquired during differentiation [30]. As a result, the extramedullary disease was significantly more frequently observed in the MP-L group and surprisingly in the low HSC-L group (Fig. 1E). In detail, patients with GMP-L, GP-L, and MP-L displayed a higher rate of lymph node enlargement and leukemic gingival infiltration (Table 1). However, spleen enlargement was mostly seen in MPP-L. Interestingly, leucocytosis increased as SLA was further advanced in the differentiation process (Fig. 1F and Table 1). Moreover, the clonogenic capacities of the HSC-L, similar to normal HSC [31], were significantly lower than those of other SLA (Fig. 1G).

Since the SLA is defined by HSPCs phenotypes, we hypothesized that the expression of genes known to be expressed in AML could be related to the SLA. To test our hypothesis, we focus on well-described AML prognostic genes BAALC, ERG, and MN1 [32, 33] and analyzed the publicly available transcriptomic HSPCs database. Those three genes were overexpressed in HSC and their expression level decreased as hematopoietic differentiation progressed (Fig. 2A). Similarly, BAALC, ERG, and MN1 were overexpressed in HSC-L and MPP-L and repressed in GP-L and MP-L (Fig. 2B).

Fig. 2: Genetic validation of SLA classification.

A Expression of BAALC, ERG, and MN1 in four normal HSPCs datasets. Gene expressions were normalized calculating Z-score in each dataset. B Expression of BAALC, ERG, and MN1 according to SLA subgroups in TUH cohort (fluidigm, n = 171).

Therefore, we showed in the TUH cohort that the different SLAs retained specific biological characteristics of normal hematopoiesis.

SLA correlates with leukemic stem cell profiles of AML

We have previously shown that the level of CD34+CD38−CD123+ LSCs is an independent prognostic factor in AML treated with intensive chemotherapy [16, 34]. To study the relationship between SLA and LSC, we measured LSC levels in the TUH cohort (Fig. 3A). HSC-L/MPP-L had the highest levels of CD34+CD38−CD123+ LSCs (18.03% vs. 11.54% in CMP-L, 7.83% in GMP-L, <1% in MP-L and GP-L, Kruskal–Wallis test p < 0.0001).

Fig. 3: Stem cell properties are related to the SLA.

A Percentage of leukemic stem cells (CD34+CD38−CD123+) among blasts according to SLA in the TUH cohort (Kruskal–Wallis test). B–D Patient-derived xenograft from 70 AML patient samples in 446 mice. A group of five mice is classically used to test an AML sample with an injected dose of 107 cells per mouse. Engraftment is assessed in a delay of 16 weeks. B Percentage of mice with >0.5% of human leukemic cells detected in bone marrow samples by flow cytometry. C Evaluation of human leukemic engraftment in bone marrow samples of each experiment. Each point represents the mean of all PDX of a donor. D Expansion fold is calculated as a ratio between engrafted cells in mice bone marrow and spleen and injected leukemic cells.

To evaluate the stem properties of SLA subsets, we injected leukemic cells from 70 AML in 446 NGS mice (6.4 mice/sample, range 4–20). Early SLA (i.e., MPP-L and CMP-L, 31 AML, 209 mice) had higher number of engrafted mice (64.4% vs. 23.5%, p = 0.0001, Fig. 3B), higher levels of engraftment (21.5% vs. 4.7%, p = 0.0027, Fig. 3C), and greater expansion of leukemic cells (1.9 vs. 0.2-fold, p = 0.0002, Fig. 3D) than late SLA (GMP-L, MP-L, and GP-L, 38 AML, 237 mice).

Together, those data show that stem properties are enriched in early SLA (HSC-L, MPP-L, and CMP-L).

Oncogenic events are specific to SLA

To identify oncogenic events linked to specific SLA, we studied point mutations and cytogenetic anomalies. We screened 46 genes commonly mutated in myeloid malignancies from 409 patients of the TUH cohort and identified 1363 mutations or cytogenetic anomalies (Fig. 4A), with overall frequencies that were consistent with those published in previous studies [35, 36]. We identified at least one driver mutation in 399 patients (97.6%) and two or more driver mutations in 89.7% of the samples.

Fig. 4: Distribution of AML mutations and genetic abnormalities according to the SLA.

A Number of patients with specific mutations or genetic abnormalities (n = 409). B Volcano plots of relative risk of the presence of specific genetic anomalies in each SLA (n = 1967). C Volcano plots of relative risk of the presence of specific mutations in each SLA (n = 409). D Plots of relative risks of eight functional modules of mutations [35] in SLA.

Although co-mutation or mutual exclusivity profiles have been previously described in AML [35, 36], our cohort allowed a more comprehensive analysis of the driver mutations involved in the maturation block of SLA. We calculated the relative risks (RR) of cytogenetic abnormalities (n = 1967, Fig. 4B) and point mutations (n = 409, Fig. 4C) for each SLA.

MPP-L and CMP-L show criteria of secondary AML

MPP-L and CMP-L are phenotypically defined as CD34+ AML, positive for myeloid markers (CD13+CD33+CD117+); and differ by their expression of cytoplasmic MPO (<10% for MPP-L and within the range of 10–70% for CMP-L). MPP-L and CMP-L show more often cytogenetic abnormalities of AML MRC (Fig. 4B) such as del(7q) (RR:1.85, p < 0.0001; RR:1.61, p < 0.0001; for MPP-L and CMP-L, respectively), del(17p) (RR:1.77, p = 0.0010; RR:1.53, p = 0.0033, respectively) and del(12p) (RR:1.63, p = 0.015; RR:1.46, p = 0.021, respectively). MPP-L and CMP-L are also enriched in secondary AML (s-AML) mutations [37] in normal karyotype (n = 200, Supplemental Fig. 3A, B): ASXL1 (MPP-L RR:6.1; p = 0.0006), SRSF2 (MPP-L RR:5.0; p = 0.0021), EZH2 (MPP-L RR:7.7; p = 0.024), ZRSR2 (MPP-L RR:5.8; p = 0.046), STAG2 (MPP-L RR:2.9; p = 0.092), and SF3B1 (CMP-L RR:3.3; p = 0.050), BCOR (CMP-L RR:2.7; p = 0.089). In order to investigate the relationship between secondary AML and SLA, we rigorously classified 409 AML patients as clinical s-AML (post-MDS or MPN), molecular s-AML (defined as AML with mutations in any of the eight genes frequently altered in MDS [37]) or karyotypic s-AML (Fig. 5). MPP-L and CMP-L were classified s-AML in 68% and 56%, respectively (RR:3.0, p < 0.0001). In addition, inv(3) (RR:3.0, p < 0.0001), t(9;22) (RR:2.4, p = 0.0011), CSF3R (normal karyotype RR:12.3, p < 0.0001) and RUNX1 mutations (RR:3.3, p < 0.0001) were enriched in MPP-L.

Fig. 5: Secondary AML according to the SLA.

Definition of secondary AML in 409 patients based on an association of clinical (history of MDS or MPN), molecular (mutations in any of the eight genes frequently altered in MDS [37]) and/or karyotypic abnormalities as defined by WHO.

Gene mutations can be further functionally classified into eight categories [35] (Fig. 4D and Supplemental Fig. 3C). MPP-L were enriched in mutations in epigenetic modifiers (RR: 2.1, p = 0.001), spliceosome (RR:1.9, p = 0.01) and myeloid transcription factors (mainly RUNX1 and ETV6 mutations, RR:1.9, p = 0.008).

Bi-allelic CEBPA mutations and CBF abnormalities are specific of GMP-L

GMP-L is defined with a classic phenotype CD34+CD13+CD33+CD117+ and high expression of cytoplasmic MPO (>70%). Astonishingly, it was very specific of three abnormalities (Fig. 4B, C): inv(16) (RR:5.6, p < 0.0001), t(8;21) (RR:5.2, p < 0.0001) and CEBPA mutations (RR:4.8, p < 0.0001). We further studied CEBPA mutations in 871 AML from the TUH cohort and found the mutation in 35.7% of GMP-L (46/129, RR:6.2, p < 0.0001, Supplemental Fig. 4A), the majority of which were bi-allelic mutations (72%, 33/46). Overall, CBF abnormalities represented 33% of GMP-L (119/360 patients).

MP-L and GP-L are the two sides of NPM1 mutated AML

MP-L and GP-L are phenotypically defined as CD34− AML, positive for myeloid markers (CD13+CD33+CD117+/−); and differ by their expression of HLA-DR (≥20% for MP-L and <20% for GP-L). Both groups frequently expressed NPM1 mutation (MP-L RR:3.8, p < 0.0001; GP-L RR:6.0, p < 0.0001, Fig. 4C). However, NPM1 mutations were associated with mutations of DNMT3A (RR:2.3, p < 0.0001) and FLT3 (RR:2.1, p < 0.0001) in MP-L, and with TET2 mutations in GP-L, (RR:4.6, p < 0.0001). Mutations in TET2, IDH1, and IDH2 are largely mutually exclusive and lead to similar epigenetic changes [38]. Since the TET2 mutations were enriched in GP-L, we looked at the distribution of IDH1 and IDH2 mutations in the TUH cohort and found that these mutations were also enriched in GP-L (Supplemental Fig. 4B). Indeed, the GP-L subgroup was composed of NPM1/TET2 mutated and NPM1/IDH1 or NPM1/IDH2 mutated patients (52% and 20% of GP-L, respectively). Of note, besides the NPM1-mutated MP-L subset which accounts for 64% of all MP-L and 82% of normal karyotype MP-L, MLL fusions were enriched in this SLA (RR:2.4, p < 0.0001; Fig. 4B) although their frequency is modest (59 patients in TUH cohort including 32 MP-L).

SLA correlates by chemoresistance and outcome of patients treated by intensive chemotherapy

We investigated ex-vivo chemosensitivity and the response to intensive chemotherapy of AML patients according to their SLA. Ex-vivo apoptosis testing of 47 AML samples incubated with cytarabine (AraC) showed that MPP-L and CMP-L had a significantly higher IC50 than GMP-L and GP/MP-L (>1000 vs. 540 and 33 μM, respectively, Fig. 6A). Moreover, AML patients with immature SLA had a higher percentage of residual blasts in bone marrow at day 15 after intensive chemotherapy (Fig. 6B) and consequently, a lower complete response rate than patients with more mature SLA (HSC/MPP-L 72%; CMP-L 76%; GMP-L 87%; MP-L 85%; GP-L 79%; p < 0.0001). As a result, overall survival was significantly worse in patients with immature compared to mature SLA (p < 0.0001, Fig. 6C and Supplemental Fig. 5A) even though the early death rate was higher in hyperleukocytic SLA (GP-L and MP-L, Table S2). The cumulative incidence of relapse (CIR) was also significantly higher in the immature SLA group (p < 0.0001, Fig. 6D and Supplemental Fig. 6A). The correlation between SLA and response to chemotherapy was confirmed in younger AML patients (Supplemental Figs. 5B and 6B). Consistent with their chemoresistance status, allogeneic stem cell transplant in first complete remission was of great survival benefit for MPP-L and CMP-L and showed little or no survival improvement in the other groups (Table S3). Interestingly, SLA of relapsed AML (n = 193) was identical or more immature to diagnostic, in most of the cases (57% and 27%, respectively, Table S4). When a more mature SLA was identified at relapse (16%, 30/193), we observed, when available, a modification of the mutational profile in half of the cases (8/16).

Fig. 6: Response to chemotherapy according to the SLA.

A In vitro testing of cytarabine (AraC) activity in 47 AML samples. B Early chemosensitivity according to SLA was evaluated in patients by measuring the percentage of residual blasts in bone marrow at day 15 of induction chemotherapy (n = 475). C Prognostic impact of SLA on overall survival for patients from TUH cohort treated with intensive chemotherapy (n = 1266). See Table S2 for multivariate analysis results. D Prognostic impact of SLA on overall survival for younger patients (<60 years) from TUH cohort treated with intensive chemotherapy (n = 638).

In multivariate models, SLA classification retained independent prognostic values for overall survival, event-free survival, and cumulative incidence of relapse (Tables S5 and S6). Of note, GP-L represented a good prognostic subgroup, with a plateau of CIR at 37% in the TUH cohort (Supplemental Fig. 6A) and 19% in those under 60 (Supplemental Fig. 6B).

Altogether, these data indicate that the chemoresistance of AML cells is, at least in part, a consequence of innate (SLA imprint) and acquired (oncogenic events) mechanisms (see Table S7 for the summary of characteristics of SLA).

Validation in an independent cohort of 1209 AML patients

To robustly validate our signatures, we took advantage of a second AML cohort: 1209 patients diagnosed at Bordeaux University Hospital (BUH cohort, see Table S1). Similarly, to the TUH cohort, the BUH cohort comprised 0.7% of HSC-L, 11.7% of MPP-L, 27.9% of CMP-L, 28.4% of GMP-L, 21.9% of MP-L, and 9.4% of GP-L (Supplemental Fig. 7A). HSC-L and MPP-L were enriched in AML classified as FAB M0, while MP-L were enriched in acute monoblastic leukemia (FAB M5) and GP-L in AML classified as FAB M1 (Supplemental Fig. 7B). Leukocytosis increased as SLA was further advanced in the differentiation process (Supplemental Fig. 7C).

In the BUH cohort, we found that inv(3) (Supplemental Fig. 8A) were enriched in MPP-L, whereas ASXL1 mutation and t(9;22) were increased but not statistically specific to this SLA (Supplemental Fig. 8B, C); inv(16), t(8;21) and bi-allelic CEBPA mutations were enriched in GMP-L (Supplemental Fig. 8D, E); MLL fusions and NPM1 and DNMT3A mutations were enriched in MP-L (Supplemental Fig. 8F–H) whereas NPM1 and TET2 and IDH mutations were enriched in GP-L (Supplemental Fig. 8I–K).

In the BUH cohort, SLA retained their prognostic factor, with increased D15 blasts (Supplemental Fig. 9A), and worse OS and CIR (Supplemental Fig. 9B, C) in immature SLA.