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Intraclonal heterogeneity in CMML
modifier, splicing factor and signaling genes.6 Mapping of CMML clonal architecture identified early clonal domi- nance, intratumor heterogeneity in the hematopoietic stem and progenitor cell compartment in which mutations accumulate mostly linearly, and growth advantage to the most mutated cells.7 Hypomethylating agents, which are commonly used in severe dysplastic forms of the disease, can restore a balanced hematopoiesis.8 The response to these drugs, which correlates with DNA demethylation, can occur in the absence of any decrease in mutation allele burden measured in circulating monocytes,6 arguing for a role of epigenetic alterations in disease expression and outcome.9
One of the main limitations in studying CMML patho- physiology is the lack of appropriate models, either patient-derived cell lines or genetically modified animals, which faithfully reproduce disease features. Currently, the best available CMML preclinical model is xenotransplan- tation of CMML cells in immunocompromised mice, especially those with transgenic expression of human cytokines including granulocyte-macrophage colony-stim- ulating factor.10,11 The modeling of myeloid malignancies by generating patient-derived induced pluripotent stem cells (iPSC) recently appeared as another opportunity to model these diseases and, although challenging, capture their genetic heterogeneity.12–15 In CMML, we previously demonstrated that intraclonal heterogeneity was rarely detected in mature cells of the clone as a consequence of a growth advantage to most mutated cells with differentia- tion but was preserved in stem and progenitor cells.6,7 Therefore, we sorted CD34+ cells from a CMML patient and reprogrammed these cells to capture some intraclonal genetic heterogeneity and characterize hematopoiesis derived from genetically close but distinct iPSC.
Methods
Generation, characterization and maintenance of induced pluripotent stem cells
CD34+ cells collected from a healthy donor and a CMML patient, with informed consent and approval of the Ethics Committee (DC-2014-209), were infected with non-integrated Sendai virus encoding Klf4, Oct4, Sox2 and c-Myc to generate iPSC. An additional iPSC (Co6) was kindly provided by Dr Weiss.16 iPSC were passaged once a week to yield a cell suspen- sion of small colonies (3-10 cells). Intracellular and extracellular pluripotency markers were detected by flow cytometry and ter- atoma formation was evaluated by intramuscular injection of iPSC into NOD/SCID/IL2rγ−/− mice. Karyotyping and comparative genomic hybridization were performed. The procedures are detailed in the Online Supplementary Material.
Hematopoietic cell differentiation
A two-dimensional monolayer system was used to differentiate iPSC into CD34+CD43+ hematopoietic progenitor cells (HPC). Clonogenic assays were performed by mixing HPC in serum-free medium with MethoCult H4434 classic (Stem Cell Technologies, Grenoble, France) before plating the cell suspension in 35-mm dishes. Colonies were scored after 14 days and analyzed on a BD LSRFortessa X-20. HPC mixed with serum-free fibrin clots were seeded for 10 days in the presence of thrombopoietin and stem cell factor before measuring colony-forming unit-megakaryocyte (CFU-Mk) colonies. HPC were also suspended in serum-free liquid medium with growth factors for 10 days before flow analysis of
cell surface markers and May-Grünwald-Giemsa staining of cytospins. More details are provided in the Online Supplementary Material.
Flow cytometry and cell sorting
The antibodies used are listed in Online Supplementary Table S1. Cells were analyzed using a BD LSRFortessaTM X-20 and Kaluza analysis software. HPC, monocytes and megakaryocytes were sorted on a BD InfluxTM Cell sorter. Details are provided in the Online Supplementary Material.
Whole exome sequencing
We collected genomic DNA from sorted monocytes and CD3+ T cells and iPSC to perform whole exome sequencing. Raw reads were aligned to the reference human genome hg19 (Genome Reference Consortium GRCh37) using BWA 0.5.9 (Burrows– Wheeler Aligner) backtrack algorithm with default parameters. A mutation was reported as present if the variant allele frequency was ≥4%. More details are provided in the Online Supplementary Material.
Genome-wide DNA methylation detected by enhanced reduced representation bisulfite sequencing
High-molecular weight DNA was sequenced on a HiSeq3000 Illumina sequencer and 50 bp reads were aligned against a bisul- fite-converted human genome (hg19). Differentially methylated regions (DMR) identified an absolute methylation difference ≥40% with a false discovery rate <5% and were annotated using the ChIPenrich R package,17 which was also used for gene ontol- ogy and pathway analysis. For correspondence analysis and hier- archical clustering, tiles with the highest standard deviation (SD >0.03) were used. More details are provided in the Online Supplementary Material.
Statistical analysis
Statistical analysis was performed with GraphPad Prism soft- ware, using an unpaired t test and Mann-Whitney test, depending on distribution, similarity of variance, and sample number. The Kruskal-Wallis test was used for multiple comparisons.
Data availability
Accession numbers for enhanced reduced representation bisul- fite sequencing, whole exome sequencing and RNA sequencing data are GSE114115, E-MTAB-7917 and E-MTAB-7850, respec- tively.
Results
Reprogramming of CD34+ cells from a patient with chronic monomyelocytic leukemia captures a part of the disease’s genetic heterogeneity
We reprogrammed CD34+ cells collected from a CMML patient whose monocyte DNA whole exome sequencing had identified 12 mutations, including two mutations in TET2 (S1691fs and R1516X) and heterozygous mutations in KRAS(G12D) and KDM6A(R61X). The clinical and bio- logical features of the patient’s disease are depicted in the Online Supplementary Material. Reprogramming of CD34+ cells collected from an age-matched healthy donor gener- ated control clones (Figure 1A, B). We selected nine clones (5 from the patient; 4 from the healthy donor) demonstrat- ing pluripotency features, including morphology (Online Supplementary Figure S1A), expression of markers (Online Supplementary Figure S1B) and formation of teratomas in
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