Published: December 27, 2018

Introduction {#sec1}
============

Acute myeloid leukemia (AML) is a clonal disorder characterized by a rapid accumulation of differentiation-arrested myeloid blasts. Remission can be achieved in most patients by a combination of cytarabine (AraC) and anthracycline therapy. However, few treatment improvements have arisen over the past decades ([@bib17]) and 40%--60% of patients still relapse ([@bib2], [@bib30]), which is associated in general with limited treatment options ([@bib3]).

Relapse is attributed to a minor subpopulation of cells referred to as leukemic stem cells (LSCs). LSCs are resilient to cytotoxic effects of chemotherapy, via mechanisms that include resistance to apoptosis, increased capacities to efflux drugs, and relative quiescence ([@bib24]). This quiescence in turn underlies resistance to compounds that target energy metabolism ([@bib4]).

Cellular quiescence is typically related to activation of hypoxia-signaling pathway, driven by hypoxia-inducible factor (HIF) complex, which constitutes a family of 3 heterodimeric transcription factors HIF-1, HIF-2, and HIF-3 ([@bib5], [@bib14], [@bib22]). The oxygen-dependent regulation of HIFs depends on stabilization of an associated α subunit. Hence, at oxygen levels above 5%, the α subunit is proteasomally degraded. In contrast, under hypoxic conditions the α subunit is stabilized, dimerizes with constitutively expressed β subunit, and promotes transcription of target genes regulating key cellular processes such as angiogenesis, proliferation, metabolism, and apoptosis ([@bib21]).

The most primitive hematopoietic stem cells (HSCs) reside in hypoxic niches in the bone marrow (BM) ([@bib15]). Thereby, HSCs are kept dormant and free of genetic changes that mostly occur during DNA replication. However, while HIF-1α signaling was reported to critically regulate HSC maintenance ([@bib23]), other studies showed that depletion of HIF-1α/HIF-2α had no such effect ([@bib8]). The HIF pathway has also been proposed to play important roles in AML, a notion supported by the preferential localization of chemotherapy-resistant AML cells to the hypoxic endosteal niche in the BM ([@bib10]). Accordingly, several studies have shown that loss of HIF-1/2 leads to abrogation of LSCs ([@bib16], [@bib29], [@bib31]). Contrasting these results are studies demonstrating that loss of HIF-1/2 does not impact on mouse models of AML, or alternatively can give rise to an even more severe leukemic phenotype ([@bib25], [@bib28]). Nonetheless, targeting hypoxia and HIFs has been considered a key anticancer approach ([@bib6], [@bib16], [@bib29]).

Here, we investigated the possibility to sensitize LSCs from a mouse model of AML to a clinically relevant chemotherapy regimen by targeting the hypoxia pathway via *Hif-1α*. Contrary to expectation, our work suggests a more aggressive disease outcome upon *Hif-1α* deletion, which challenges the general use of hypoxia targeting for therapeutic benefit in AML.

Results {#sec2}
=======

Deletion of *Hif-1α* Accelerates the Progression of Chemotherapy-Treated Leukemia {#sec2.1}
---------------------------------------------------------------------------------

To study effects of *Hif-1α* on the sensitivity of LSCs to chemotherapy, we bred *Hif-1α*^fl^ mice ([@bib18]) with Rosa26Cre-ER^T2^ mice ([@bib27]), generating a model that allows for *Hif-1α* deletion upon tamoxifen treatment ([Figure S1](#mmc1){ref-type="supplementary-material"}A). c-Kit^+^ cells from *Hif-1α*^fl/fl^;Rosa26Cre-ER^T2/+^ mice were transduced with MLL-AF9-GFP retrovirus and transplanted into mice, which led to development of MLL-AF9-driven AML. Primary leukemias were next used to study AML progression in secondary hosts.

After comparing two different chemotherapy protocols ([Figure S1](#mmc1){ref-type="supplementary-material"}B), we used the one described by [@bib32], which resulted in severely decreased white blood cells, erythrocytes, and platelets, akin to what is observed in human patients. We then titrated the latency of the disease using different leukemic cell doses ([Figure S1](#mmc1){ref-type="supplementary-material"}C) and chose a dose of 10^4^ cells, which ensured a sufficiently long latency for posterior procedures. Cells from individual MLL-AF9-leukemic mice were transplanted into new recipients and subjected to *Hif-1α* deletion 10 days after transplantation, and to a standard chemotherapeutic protocol at day 20. As a control, we included mice injected with both vehicles but receiving no leukemic cells ([Figure 1](#fig1){ref-type="fig"}A).Figure 1Deletion of *Hif-1α* Leads to a Faster Progression of AML after Chemotherapy Treatment(A--H) Experimental design for the generation of leukemic clones, deletion of *Hif-1α*, and applied chemotherapy protocol (A). At day 28 after transplantation, mice were sacrificed and disease evolution was examined according to different parameters: total white blood cell count in PB (B), myeloid cells (Gr1^+^-CD11b^+^) (C), GFP^+^ cells in PB, BM, and spleen (D and E), splenomegaly (F), GFP^+^ c-Kit^+^ cells in BM and spleen (G), and GFP^+^ Lin^--^ c-Kit^+^ in BM and spleen (H). Results are from 1 of 2 experiments and depict results from 4 mice per group (3 for wild-type control mice). Plots represent mean ± SEM. ^∗^p \< 0.05, ^∗∗^p \< 0.01, ^∗∗∗^p \< 0.01. AraC, cytarabine; Dox, doxorubicin; CTX, chemotherapy; BM, bone marrow; Ctrl, control.See also [Figures S1](#mmc1){ref-type="supplementary-material"} and [S2](#mmc1){ref-type="supplementary-material"}.

Three days after the last injection, we started to observe mortality in the PBS group ([Figure S2](#mmc1){ref-type="supplementary-material"}A). We collected peripheral blood (PB), BM, spleen, and liver samples from half of the cohort and analyzed multiple disease parameters ([Figures 1](#fig1){ref-type="fig"}B--1F and [S2](#mmc1){ref-type="supplementary-material"}). As expected, disease progressed more slowly in the chemotherapy-treated (CTX) mice ([Figures 1](#fig1){ref-type="fig"}B--1F). More intriguingly, we observed a faster disease evolution upon *Hif-1α* deletion. This was seen in both CTX and PBS groups ([Figures 1](#fig1){ref-type="fig"}C--1F). When we assessed phenotypically more primitive GFP^+^ c-Kit^+^ or GFP^+^ Lin^--^ c-Kit^+^ cells, we observed a higher abundance in the *Hif-1α*-deleted (*Hif-1α*^--/--^) than in the *Hif-1α*-intact (*Hif-1α*^+/+^) group after chemotherapy ([Figures 1](#fig1){ref-type="fig"}G, 1H, and [S2](#mmc1){ref-type="supplementary-material"}). While these populations were very infrequent in BM of PBS groups, with no clear differences between *Hif-1α*^*--/--*^ and *Hif-1α*^+/+^ cells, a higher number of such cells upon *Hif-1α* deletion were observed in the spleens of the same animals. Taken together, these results demonstrate an increment of potential LSCs (c-Kit^+^) upon *Hif-1α*^*--/--*^ deletion, which was particularly significant after chemotherapy.

Deletion of *Hif-1α* Does Not Decrease the Frequency of LSCs after Chemotherapy Treatment {#sec2.2}
-----------------------------------------------------------------------------------------

To evaluate the impact of chemotherapy and *Hif-1α* deletion on LSCs more directly, we performed limiting dilution analysis (LDA) ([Figure 2](#fig2){ref-type="fig"}A).Figure 2Deletion of *Hif-1α* Does Not Decrease LSC Frequency after Chemotherapy(A) Experimental design for the analysis of LSC frequency.(B) Limiting dilution analysis (LDA) from *in vitro* data. Variable numbers of GFP^+^ cells (4, 8, or 12 cells) from the 3 experimental groups were cultured *in vitro* under normoxic or hypoxic conditions and proliferative capacity was evaluated after 10 days. LSC frequencies were calculated using ELDA software. Plots show 1 representative of 3 independent experiments (cells from 3 different donors) with 96 replicates per group and condition.(C) Survival curves of mice transplanted with 10 or 100 GFP^+^ cells from mice treated with the combination of tamoxifen + chemotherapy (KO-CTX), tamoxifen + PBS (KO-PBS), or oil + chemotherapy (wt-CTX) (n = 4--6 mice per group from 1 experiment).(D) LDA from *in vivo* data. Recipient mice were injected intravenously with variable numbers of GFP^+^ cells from the 3 experimental groups (KO-CTX, KO-PBS, and wt-CTX). Mice survival was evaluated 2 months after transplantation, and frequency of LSCs was calculated using ELDA software.(E) Stem cell frequency of LSCs from the different experiments: hypoxia *in vitro* (red, n = 3), normoxia *in vitro* (blue, n = 3), and *in vivo* (green, n = 1) experiments. ^∗^p \< 0.05, two-way ANOVA.(F) LSC total numbers from the different experiments: hypoxia *in vitro* (red, n = 3), normoxia *in vitro* (blue, n = 3), and *in vivo* (green, n = 1) experiments. Plot shows mean ± SEM. ^∗^p \< 0.05, ^∗∗^p \< 0.01, two-way ANOVA. CTX, chemotherapy; KO, *Hif-1α*^--/--^; wt, *Hif-1α*^+/+^.

For an *in vitro* approach, we sorted 4, 8, or 12 GFP^+^ leukemic BM cells from each group into individual wells. Proliferation was next evaluated in both normoxic (20% oxygen) and hypoxic (1% oxygen) conditions ([Figures 2](#fig2){ref-type="fig"}B and 2E). We obtained the highest LSC frequency from PBS-*Hif-1α*^--/--^ cells (1/12.3 and 1/21.7 in hypoxia or normoxia, respectively, means from 3 independent experiments). Within CTX-treated cells, *Hif-1α*^--/--^ samples contained a higher LSC frequency compared with *Hif-1α*^+/+^ cells (1/26.8 versus 1/47.1 in hypoxia, and 1/40.4 versus 1/94.4 in normoxia, respectively, means from 3 independent experiments), although this failed to reach statistical significance.

We next assessed LSC frequencies *in vivo*, injecting 10, 10^2^, 10^3^, or 10^4^ GFP^+^ BM cells from each group into new recipients ([Figure 2](#fig2){ref-type="fig"}C). While transplantation of 10^3^ and 10^4^ cells resulted in 100% mortality, lower doses of 10 and 10^2^ cells indicated an LSC frequency highest in the PBS-*Hif-1α*^--/--^ group (1/18.8). Among CTX-treated samples, we observed a higher LSC frequency in the *Hif-1α*^--/--^ group (1/34.5) than in the *Hif-1α*^+/+^ group (1/56.1) ([Figures 2](#fig2){ref-type="fig"}D and 2E).

Estimation of total number of LSCs in the BM ([Figure 2](#fig2){ref-type="fig"}F) demonstrated that deletion of *Hif-1α* fails to reduce LSC frequencies/numbers after chemotherapy.

*Hif-1α* Deletion Affects Transcriptional Expression of Replication, Transcription, and Translation-Related Genes {#sec2.3}
-----------------------------------------------------------------------------------------------------------------

Our data indicated that *Hif-1α* deletion contributed to a more rapid disease progression ([Figure 1](#fig1){ref-type="fig"}). To tease out a potential mechanism, we therefore conducted single-cell RNA sequencing on leukemic cells from the 4 evaluated settings (*Hif-1α*^--/--^*/Hif-1α*^+/+^ ± chemotherapy) ([Figure 3](#fig3){ref-type="fig"}A). Aggregated data were subjected to dimensionality reduction using the t-distributed stochastic neighbor embedding (t-SNE) method ([Figure 3](#fig3){ref-type="fig"}B), revealing dramatically different transcriptional profiles of cells following chemotherapy, but less different according to *Hif-1α* status. This indicates either a modification of transcription upon chemotherapy or, more likely, a selective survival regardless of *Hif-1α* status.Figure 3Single-Cell RNA Sequencing of Leukemic Cells after Chemotherapy Treatment(A) Experimental design for single-cell RNA-sequencing analysis. After treatment with tamoxifen/oil and chemotherapy/PBS, GFP^+^ cells were collected at day 28 after transplantation and subjected to RNA processing.(B) t-SNE plots representing gene expression profiles of all individual cells analyzed: KO-CTX (n = 1,217 cells), KO-PBS (n = 1,696 cells), wt-CTX (n = 1,301 cells), and wt-PBS (n = 1,450 cells). Each dot represents one cell. K-means clustering groups cells into 10 clusters, which are represented by different colors. Differentially expressed genes in each cluster were correlated with the main biological function indicated at the right side of the plots.(C) Heatmap depicting significantly differentially expressed genes in single cells. Heatmap with the full set of genes can be found in [Figure S3](#mmc1){ref-type="supplementary-material"}. *Hif-1α* target genes are indicated by black dots.(D) Venn diagrams showing the distribution among groups of differentially expressed genes (adjusted p value \<0.05). Of note, there are no overlapping genes between chemotherapy- and PBS-treated groups among this set of differentially expressed genes.(E) Gene ontology (GO) and KEGG pathway enrichment analysis from uniquely differentially expressed genes in each group indicating the associated biological process.CTX, chemotherapy; IL1/TNF, interleukin-1/tumor necrosis factor; INF, interferon; dim, dimension; FDR, false discovery rate.See also [Figures S3](#mmc1){ref-type="supplementary-material"} and [S4](#mmc1){ref-type="supplementary-material"}.

By K-means clustering, we divided the entire dataset into 10 different clusters. We observed that clusters with functions related to more differentiated cells (e.g., immune system process, response to interleukin-1/tumor necrosis factor, innate immunity or response to virus/interferon) were predominant in PBS samples, while others (e.g., mitotic cell cycle, cellular response to DNA damage, and transcriptional regulation) were associated with CTX samples. Multiple genes related to myeloid differentiation were predominantly expressed in PBS samples (data not shown), strongly suggesting effective chemotherapy targeting of more mature leukemia-associated cells.

Pairwise sample comparisons produced a collection of 331 differentially expressed genes ([Figures S3](#mmc1){ref-type="supplementary-material"} and [3](#fig3){ref-type="fig"}C). When comparing significantly overexpressed genes among groups (adjusted p value \<0.05), we found a very different distribution of cells between CTX and PBS samples, but only a small subset of genes uniquely expressed in either *Hif-1α*^--/--^ or *Hif-1α*^+/+^ cells ([Figures 3](#fig3){ref-type="fig"}D and [S4](#mmc1){ref-type="supplementary-material"}). In single-cell analysis, this indicates that there are differences in transcriptional regulation or that analyzed cells from each sample are different.

To identify functional protein association networks among differentially expressed genes, we used the STRING database ([Figures 3](#fig3){ref-type="fig"}E and [4](#fig4){ref-type="fig"}). For the 4 sets of differentially expressed genes (log fold change \>0.4, adjusted p value \<0.05), we obtained a significant protein-protein interaction (PPI) enrichment score, indicating that there are more interactions among these proteins than a random set of proteins from the genome (PPI enrichment p values: *Hif-1α*^--/--^-CTX = 0; *Hif-1α*^+/+^-CTX = 1.03 × 10^−6^; *Hif-1α*^--/--^-PBS = 0; *Hif-1α*^+/+^-PBS = 0.0251). This indicates that genes in each set are at least partially biologically connected. To correlate these genes with a biological function, we performed gene ontology and KEGG pathway enrichment analyses ([Figure 3](#fig3){ref-type="fig"}E). This revealed that mRNA processing, DNA replication, and protein folding were significantly overrepresented in the *Hif-1α*^--/--^-CTX group, while the *Hif-1α*^+/+^-CTX group was associated with the HIF-1α pathway, glycolysis, and other carbon metabolism processes. In PBS groups, translation was the most represented pathway associated with *Hif-1α*^--/--^ cells, while no significant pathways could be assigned to *Hif-1α*^+/+^ cells.Figure 4Protein Association Networks Affected by ChemotherapyProtein association network analysis of differentially expressed set of genes (average log fold change \>0.4, adjusted p value \<0.05). Uniquely expressed genes from each group are indicated by its assigned color. Common genes among KO and wt samples, within each specific set (CTX- or PBS-treated), are shown in dark gray. Associated biological function to each gene is indicated, with the color of the border showing the main processes regulated by these genes. Interaction enrichment score \>0.5. CTX, chemotherapy.

Discussion {#sec3}
==========

Relapse of AML remains a major therapeutic challenge, not least because of the few therapeutic options for many of these patients, which in most cases is restricted to palliative care.

One potential strategy for eradicating LSCs, responsible for relapse in AML, is to sensitize them to chemotherapy. We here explored whether targeting the HIF pathway could be used for this using an MLL-AF9 murine AML model, which was subjected to a standard and clinically relevant chemotherapy protocol. In our work, *Hif-1α*^--/--^ cells displayed a faster evolution of the disease compared with *Hif-1α*^+/+^ cells following chemotherapy. While the results are consistent with our previous work ([@bib25]) and recently published data ([@bib28]), they appear in sharp contrast to previous studies ([@bib29], [@bib31]) in which *Hif-1α* was critical for LSCs maintenance.

In our work, we used the Rosa26Cre-ER^T2^ rather than the more commonly used Mx1-Cre model, which is associated with significant leakiness ([@bib26]). This allowed us to study the effect of *Hif-1α* inhibition specifically in AML cells of the same founder clone, which circumvents the risk that different leukemic clones have intrinsically different behavior. Inducing the deletion in Rosa26Cre-ER^T2^ mice requires injection of tamoxifen that might itself affect the initiation of MLL-AF9 leukemia ([@bib20]). However, as the described effect of tamoxifen is a regression of the disease, the isolated effect of knocking out *Hif-1α* could be even more pronounced than the one we report.

The standard chemotherapy regimen for AML is a combination of AraC and an anthracycline (such as doxorubicin). Doxorubicin has itself been attributed *Hif*-inhibiting properties ([@bib13]). Different disease progression in CTX-*Hif-1α*^--/--^ and *Hif-1α*^+/+^ samples indicates that even if doxorubicin is inhibiting HIF function, this effect is not complete and can be further increased by alternative means.

There is evidence that c-Kit deregulation and overexpression could be factors contributing to the chemotherapy resistance in AML ([@bib1]). The higher numbers of c-Kit^+^ cells in the *Hif-1α*^--/--^ chemotherapy group might therefore be an indicator of higher drug resistance of these cells, with c-Kit being a well-described stem cell marker of murine MLL-AF9-driven LSCs ([@bib12]). However, our c-Kit expression data correlated poorly with LSC frequencies measured by LDA. Previously it was thought that chemotherapy promoted LSC enrichment ([@bib10], [@bib19]). However, although cytarabine decreases the frequency of LSCs in human AML models ([@bib7]), it fails to promote enrichment either of quiescent cells or more primitive CD34^+^CD38^--^ cells, emphasizing that functional assessments are critical. We did not observe an increment in LSC frequencies measured by LDA but observed a substantial reduction (around 3-fold) of the total bulk of leukemic cells, indicating an overall enrichment of LSCs following chemotherapy. In addition, we observed an increased frequency of c-Kit^+^ cells by *Hif-1α* deletion, which further supports the increased aggressive phenotype of *Hif-1α*^--/--^ cells.

*Hif-1α* is rapidly degraded in normoxia and *Hif-1α*^+/+^ cells should thus theoretically behave as *Hif-1α*^--/--^ cells, which would suggest similar LSC frequencies between *Hif-1α*^--/--^ and *Hif-1α*^+/+^ cells in normoxia. Somewhat surprisingly, we observed a higher LSC frequency of *Hif-1α*^--/--^ cells, although not significant (p = 0.1079). One possibility is that this indicates the involvement of one or more *Hif-1α*-oxygen-independent mechanisms. For instance, it is well established that *Hif-1α* can be induced by the PTEN/PI3K/AKT axis ([@bib33]), a pathway that appears to extend also to MLL-AF9 leukemia ([@bib9]). Regardless, even if hypoxia in general promotes a quiescent state of cells, such conditions seem to promote AML cell proliferation, which is also in line with previous results on human AML ([@bib7]).

After chemotherapy, we observed a more aggressive phenotype as a consequence of *Hif-1α* deletion. We hypothesized that this faster development of disease could be explained by two scenarios: (1) leukemic *Hif-1α*^--/--^ cells are less sensitive to the chemotherapy, which would be in contrast to our original expectation; and/or (2) leukemic *Hif-1α*^--/--^ cells expand faster than *Hif-1α*^+/+^ cells after chemotherapy. To discriminate between these two options and unveil possible mechanisms leading to this effect, we conducted a single-cell transcriptome analysis.

We found that chemotherapy-treated cells displayed a distinct transcriptomic profile when compared with PBS-treated cells, but with fewer differences when comparing *Hif-1α*^--/--^ and *Hif-1α*^+/+^ cells. Still, of the significantly overexpressed genes specific for each group, we identified an increment in genes involved in translation (PBS-*Hif-1α*^--/--^ cells) and in mRNA processing, DNA replication, and protein folding (CTX-*Hif-1α*^--/--^ cells). Overall, this is in line with a more active proliferative status of *Hif-1α*^--/--^ cells and suggests that deletion of *Hif-1α* is transcriptionally deregulating these aforementioned specific pathways. Chemotherapy-depleted cells with an immune-related phenotype represent the cells expanded in leukemia. As expected, *Hif-1α*^--/--^ cells were depleted in expression of *Hif-1α* targets, and *Hif-1α* deletion leads to an enhanced transcription of genes involved mainly in replication, mRNA processing, and translation.

These results are in accordance with the described effect of *Hif-1α*, inhibiting cell cycle and promoting quiescence, actions attributed to blockage of c-MYC and enhancement of cyclin-dependent kinase inhibitors such as p21/CDKN1A ([@bib11]). Since we are deleting only one member of a multigene family, it remains a possibility that other members, i.e., *Hif-2*α, could have a compensatory effect. Future work could benefit from an increased understanding of both gene redundancy and potential hypoxia-independent effects of *Hif-1α*.

Overall, our data suggest that *Hif-1α* inhibition failed to improve the outcome of chemotherapy in MLL-AF9-driven AML and, in contrast, led to a faster progression of disease upon withdrawal of the treatment. Further investigations are needed to extend these conclusions to other genetic subtypes of AML.

Deletion of *Hif-1α* in our setting was permanent, which would be a different scenario than in a clinical setting where administration of *Hif-1α* inhibitors would be transient. Our results nevertheless emphasize that the effects of HIF inhibition have to be further investigated before this strategy can be applied in a clinical setting.

Experimental Procedures {#sec4}
=======================

Mice {#sec4.1}
----

*Hif-1α*^lox^ mice ([@bib18]) (JAX 007561) were crossed with the tamoxifen-inducible Rosa26Cre-ER^T2^ mice ([@bib27]) (JAX 008463) to generate a combined conditional knockout (KO) model. Mice were maintained at the animal facility of the Biomedical Center at Lund University (Sweden) and all experiments were performed with consent from a local ethics committee.

Statistical Analysis {#sec4.2}
--------------------

All data are expressed as the mean ± SEM. Differences between groups were assessed using unpaired Student\'s t tests. All analyses were performed with Prism software, version 7.0 (GraphPad Software).

Detailed descriptions of experiments can be found in [Supplemental Experimental Procedures](#mmc1){ref-type="supplementary-material"}.

Author Contributions {#sec5}
====================

T.V.-H. designed the study, performed experiments, analyzed data, and wrote the manuscript; S.S. performed bioinformatics analysis; I.H. and E.E. performed experiments; and J.C and D.B. designed the study and wrote the manuscript. All authors revised the manuscript and approved the final version of this study.

Accession Numbers {#app1}
=================

The accession number for transcriptomic data is GEO: [GSE119484](ncbi-geo:GSE119484){#intref0010}.

Supplemental Information {#app3}
========================

Document S1. Supplemental Experimental Procedures and Figures S1--S4Document S2. Article plus Supplemental Information

We thank Dr. Göran Karlsson and Parashar Dhapola for helpful discussions on data analysis. This work was supported with a project grant to T.V.-H. from the Sigurd och Elsa Goljes Minne Memorial Foundation, to J.C. from The Swedish Cancer Society (Cancerfonden) and Barncancerfonden, and to D.B. from The Swedish Cancer Society, The Swedish Medical Research Council, ERC (Leukemiabarrier 615068), The Knut and Alice Wallenberg Foundation, and the Tobias Foundation.

Supplemental Information includes Supplemental Experimental Procedures and four figures and can be found with this article online at [https://doi.org/10.1016/j.stemcr.2018.11.023](10.1016/j.stemcr.2018.11.023){#intref0015}.
