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Use of Genome Engineering to Create Patient Specific MLL Translocations in Primary Human Hematopoietic Stem and Progenitor Cells

  • Erin H. Breese ,

    Contributed equally to this work with: Erin H. Breese, Corina Buechele

    Affiliation Division of Pediatric Hematology/Oncology, Department of Pediatrics, Stanford University, Stanford, California, United States of America

  • Corina Buechele ,

    Contributed equally to this work with: Erin H. Breese, Corina Buechele

    Affiliation Department of Pathology, Stanford University, Stanford, California, United States of America

  • Catherine Dawson,

    Affiliation Division of Pediatric Hematology/Oncology, Department of Pediatrics, Stanford University, Stanford, California, United States of America

  • Michael L. Cleary , (MHP); (MLC)

    Affiliation Department of Pathology, Stanford University, Stanford, California, United States of America

  • Matthew H. Porteus (MHP); (MLC)

    Affiliation Division of Pediatric Stem Cell Transplantation and Regenerative Medicine, Department of Pediatrics, Stanford University, Stanford, California, United States of America

Use of Genome Engineering to Create Patient Specific MLL Translocations in Primary Human Hematopoietic Stem and Progenitor Cells

  • Erin H. Breese, 
  • Corina Buechele, 
  • Catherine Dawson, 
  • Michael L. Cleary, 
  • Matthew H. Porteus


One of the challenging questions in cancer biology is how a normal cell transforms into a cancer cell. There is strong evidence that specific chromosomal translocations are a key element in this transformation process. Our studies focus on understanding the developmental mechanism by which a normal stem or progenitor cell transforms into leukemia. Here we used engineered nucleases to induce simultaneous specific double strand breaks in the MLL gene and two different known translocation partners (AF4 and AF9), which resulted in specific chromosomal translocations in K562 cells as well as primary hematopoietic stem and progenitor cells (HSPCs). The initiation of a specific MLL translocation in a small number of HSPCs likely mimics the leukemia-initiating event that occurs in patients. In our studies, the creation of specific MLL translocations in CD34+ cells was not sufficient to transform cells in vitro. Rather, a variety of fates was observed for translocation positive cells including cell loss over time, a transient proliferative advantage followed by loss of the clone, or a persistent proliferative advantage. These studies highlight the application of genome engineering tools in primary human HSPCs to induce and prospectively study the consequences of initiating translocation events in leukemia pathogenesis.


Leukemia is the most common form of childhood cancer, affecting approximately 5.2 per 100,000 children per year [1]. Over the past 60 years, scientific inquiry and advancements in treatment through clinical trials have taken what used to be a uniformly fatal disease and transformed it into a disease in which more than 90% of patients are cured [2, 3]. However, certain subtypes of pediatric leukemia remain difficult to treat and retain a poor prognosis. Many of these, including the majority of cases of infant leukemia and many treatment-related leukemias, are characterized by a translocation within the Mixed Lineage Leukemia (MLL) gene [4].

Aberrations of the MLL gene can be found in both primary and treatment-related acute leukemia in children and adults. However, the highest frequency of MLL rearrangements is seen in infants with acute leukemia [5]. For infants diagnosed with acute lymphoblastic leukemia (ALL), approximately 60–80% have an MLL rearrangement, which has been identified as a molecular feature associated with a very poor prognosis, with overall survival less than 50% [5, 6]. For infants diagnosed with AML (acute myeloid leukemia), approximately 40% are found to have an MLL rearrangement [5]. While over 60 different translocation partners have been identified, the MLL-AF4 and MLL-AF9 translocations account for over half of the MLL rearrangements seen in infant leukemia [5, 6]. Interestingly, the MLL-AF4 translocation is seen almost exclusively in ALL, while the MLL-AF9 translocation is more commonly seen in AML, but can also occur in ALL [7]. Translocations of the MLL gene appear to be a driving force in the pathogenesis of leukemia in these cases, with the resulting fusion protein sustaining aberrant expression of developmental genes critical in hematopoiesis [8]. Many attempts to model this process have involved forced expression of an MLL fusion protein in cells using a retroviral vector [8]. While these models have advanced our understanding of the MLL gene and fusion proteins, they have not fully recapitulated the clinical course seen in pediatric patients [9]. We believe that a system that more accurately models the initiating events that occur in nature will provide insight into the pathogenesis and possible treatments for this disease.

Chromosomal translocations, which are a hallmark of cancer cells, have been shown to result from mis-repair of simultaneous double-strand breaks (DSBs) on two different chromosomes [1012]. The free end of one chromosome is ligated to a portion of a different chromosome either through classic or alternative non-homologous end-joining [13]. The evidence that DSBs on two different chromosomes can cause translocations came from studies in which recognition sites for specific nucleases were introduced into two different chromosomes and then translocations between the two artificial sites measured [10]. In the last ten years, several different platforms for engineering nucleases to induce double strand breaks at specific genome target sites have been developed giving rise to the field of genome editing. These platforms include zinc finger nucleases (ZFNs), TAL effector nucleases (TALENs) and RNA-guided endonucleases of the CRISPR/Cas9 family (RGENs). These new nuclease platforms have been used to engineer translocations and chromosomal rearrangements found in Ewing sarcoma, anaplastic large cell lymphoma, and lung cancer [12, 14].

Here we designed TALENs, which consist of a fusion of a sequence specific TAL effector DNA binding domain to the nuclease domain from FokI, to specifically engineer chromosomal translocations involving the MLL gene in both K562 cells and primary hematopoietic stem and progenitor cells (HSPCs). We found that the frequency of translocations is higher in K562 cells than in HSPCs. Interestingly, the creation of MLL translocations in HSPCs was not sufficient to fully transform the cells in vitro into leukemia. Instead we found that there is a heterogeneous response to the creation of an MLL translocation whereby some cells develop a clear proliferative advantage, others develop a clear proliferative disadvantage, while still others develop a transient proliferative advantage that then disappears. These studies, which model how leukemia might occur in humans through the generation of patient specific translocations involving the endogenous genes in a small number of cells, provide the genetic foundation for studying leukemogenesis.

Materials and Methods

TALEN construction and validation

MLL, AF4, and AF9 cleavage sites were designed based on patient specific translocation breakpoints available through GenBank using the TAL Effector Nucleotide Targeter 2.0 [15]. Three pairs of TALENs were created for each cleavage site using the Golden Gate TALEN Assembly Method [16] and inserted into the MR015 vector. Each pair was then tested for cutting efficiency using the surveyor assay [17]. Briefly, K562 cells were nucleofected with a combination of TALEN pairs. Genomic DNA was isolated using the Qiagen DNeasy DNA isolation system and the region of interest (MLL, AF4, or AF9 cut sites) was amplified by PCR with the following primers: MLLAF4 5’GGTTTGACCAATTGTCCCAATAAT3’, 5’TCTGGTTTGTCCTTTCCATTTGTA3’; AF4 5’TTTGGGAGACACTGGGGTAACAAT3’, 5’CCCACCTGAGGAATTTCACCTTCT3’; MLLAF9: 5’AGCAATCTCACAGGGTTCCT3’, 5’TGGGACAATTGGTCAAACCT3’; AF9 5’ATCTTGTTCCAGTAGAAGGCTGTTTC3’, 5’AACTCATGAATGATAAGGAAGCAAAA3’. Following isolation by gel extraction, the PCR products were heated to 95°C to denature DNA and then cooled slowly to allow the strands to re-anneal. The samples were incubated for 1h at 37°C with the T7 endonuclease, which cleaves at sites of DNA mismatches. The samples were then run on a 10% polyacrylamide gel and stained with ethidium bromide for visualization showing the expected cleaved products according to the TALENs cut sites (MLLAF4: ~402 bp + 68 bp; AF4: ~383 bp + 260bp; MLLAF9: ~240bp + 198bp; AF9: ~240bp + 112bp).

Cell culture and nucleofection

K562 (ATCC CCL-243) cells were cultured in RPMI + 10% BGS supplemented with penicillin/streptomycin and L-glutamine and maintained at 37°C throughout the experiment. K562 cells were nucleofected using the Amaxa Nucleofector II (program T-016). Primary human CD34+ cells were isolated from fresh umbilical cord blood obtained from the maternity ward of Stanford Hospital which was approved by (Stanford University Research Compliance Office Human Subjects Research and Institutional Review Board (IRB) protocol 23665 and Stem Cell Research Oversight (SCRO) Compliance Panel protocol 401) using Ficoll-Paque plus (GE Healthcare Life Sciences) followed by Miltenyi CD34 MicroBead Kit or autoMACS cell separation. Written informed consent was obtained for use of these samples in research. They were not procured from a tissue bank or donation center. When fresh umbilical cord blood was not available, commercially available frozen human CD34+ cells isolated from umbilical cord blood were used (AllCells LLC or StemCell Technologies). Following isolation, CD34+ cells were maintained in serum free X-Vivo15 media (Lonza) supplemented with cytokines (PeproTech: SCF 100 ng/ml, TPO 100 ng/ml, Flt3L 100 ng/ml, IL-6 100 ng/ml; Cellagen Technology: SR1 0.75 μM) overnight at low oxygen tension. The following day, CD34+ cells were nucleofected using the Lonza 4-D Nucleofector System (program EO-100). Cells were incubated at 37°C, 5% CO2 in serum free media + cytokines + 20 μM Z-Vad-FMK (Enzo Life Sciences) to inhibit apoptosis for 48 hours following nucleofection. After 48 hours, CD34+ cell cultures were maintained in media + cytokines + 10% filtered umbilical cord blood plasma. Viability of cells was determined by flow cytometry based on FSC and SSC characteristics using the BD Accuri C6 flow cytometer and further confirmed by staining of Trypan blue (Life technologies) at indicated time points.

Ethics Statement

The use of human cord blood derived CD34+ cells was approved by the Stanford University Research Compliance Office Human Subjects Research and Institutional Review Board (IRB) protocol 23665 and Stem Cell Research Oversight (SCRO) Compliance Panel protocol 401. Written informed consent was obtained for use of these samples in research. They were not procured from a tissue bank or donation center.

Translocation PCR and Sequencing

MLL translocations were assayed using semi-quantitative PCR. For each PCR, 150 ng genomic DNA was used with translocation specific primers: MLL-AF4 (MLL primer: 5’GGTTTGACCAATTGTCCCAATAAT3’; AF4 primer: 5’CCCACCTGAGGAATTTCACCTTCT3’; annealing temp 60°C), AF4-MLL (AF4 primer: 5’TTTGGGAGACACTGGGGTAACAAT3’; MLL primer: 5’TCTGGTTTGTCCTTTCCATTTGTA3’; annealing temp 59°C), MLL-AF9 (MLL primer: 5’TGTTGACATGATTTCAGACTTACAAA3’; AF9 primer: 5’GGAAAAGTTCTTGAATGGAATTAAAA3’; annealing temp 61°C), AF9-MLL (AF9 primer: 5’AAGGCTGTTTCGTCTACATAGAAAAT3’; MLL primer: 5’TAGGATAATCCAGAATTTTCTTTTGC3’; annealing temp 61°C). PCR parameters: denature at 95°C for 5 min, [denature at 95°C for 30 sec, anneal at primer specific temp for 45 sec, extension at 72°C for 1 min] for 38–40 cycles depending on primer set, and final extension at 72°C for 1 min. PCR products were visualized on a 1% agarose gel with ethidium bromide. PCR products were extracted from the gel (Qiagen), cloned into the pCRII-Blunt-TOPO vector (Invitrogen), transformed into competent cells. After incubation at 37°C overnight colonies were isolated and enriched in liquid culture. Plasmid DNA of the transformed competent cells was purified (Qiagen Miniprep) and submitted for Sanger Sequencing using the M13 forward and M13 reverse primers.


RNA was isolated from CD34+ cell cultures using the RNeasy Mini Kit (Qiagen). 500 ng of RNA from each sample was used to generate cDNA using the RevertAid First Strand DNA Synthesis Kit (Thermo Scientific). PCR was subsequently performed for the MLL-AF4 transcript [MLL primer: 5’CAGGAGGATTGTGAAGCAGAAAA3’; AF4 primer: 5’TAGGGAAAGGAAACTTGGATGG3’] using the following cycling parameters: denature at 95°C for 5 min, [denature at 95°C for 30 sec, anneal at 58°C for 45 sec, extension at 72°C for 1 min] for 36 cycles, and final extension at 72°C for 1 min. PCR products were visualized, gel extracted, and prepared for Sanger sequencing as noted above. Primers used for real-time analysis of MLL-AF4 fusion transcript were previously described by Siraj et al. [18] qPCR using Luminaris HiGreen qPCR Master Mix (Thermo Scientific) or iTaq Universal SYBR Green Supermix (BioRad) was performed using the following parameters: 95°C for 5 min, [95°C for 15 sec, 57°C for 30 sec, 72°C for 45 sec] for 40 cycles in, followed by melting curve analysis in the BioRad CFX384 C1000 Real-Time System. For real-time analysis of the genomic MLL-AF4 translocation, the MLL-AF4 primers described above were used using the following cycling parameters: 95°C for 5 min, [95°C for 30 sec, 60°C for 45 sec, 72°C for 1 min] for 39 cycles, followed by melting curve analysis. GAPDH amplification was used for normalization for all experiments. The ddCt method (Applied Biosystems) with expression levels compared relative to threshold of detection.

Fluorescence In Situ Hybridization analysis

Live cultures of the indicated populations were submitted for FISH analysis to the Cytogenetics Laboratory of Stanford Hospital and Clinics on a fee for service basis. Cells were fixed and hybridized with the Vysis MLL Dual Color Break Apart Rearrangement Probe (5’ green, 3’ red). Two hundred cells were analyzed per sample for the presence or absence of an MLL rearrangement. A representative image was obtained for each sample.

Colony-forming cell (CFC) assays

CD34+ cells were nucleofected with MLL and AF4 or AF9 TALENs or control (GFP) and were seeded in triplicate (10,000cells/dish) at days 25 and 39 of extended liquid culture in Methocult H4230 methylcellulose medium (StemCell Technologies Inc., Vancouver) supplemented with the same cytokines used in liquid cultures. Cultures were incubated at 37°C, 5% CO2, and colonies were scored after 12–14 days. Secondary CFC assays were performed by harvesting all cells from the primary cultures after colony enumeration, and replating them into new assays under identical conditions. Morphology of the colonies was determined as previously described [19]. All statistical analyses were performed with the Student’s t test. P<0.05 was considered statistically significant.


Generation of TALENs that create specific double strand breaks within the MLL, AF4, and AF9 genes

Previous studies have identified hot spots within the MLL, AF4, and AF9 genes, known as breakpoint cluster regions, that are frequently the sites of chromosomal translocations in patients with leukemia [7]. To design TALENs for the MLL and AF4 genes, we chose a specific patient translocation sequence (UPN010) that is available through the GenBank database (AJ408902.1) and is representative of the most common site of translocations in patients with infant leukemia [20]. The Golden Gate assembly method [16] was used to create pairs of TALENs that induce a specific double strand break within the breakpoint cluster regions of MLL and AF4 corresponding to the UPN010 translocation (Fig 1A). Following nucleofection with the MLL and AF4 TALENs, respectively, resultant double strand breaks within the MLL and AF4 genes were detected using the surveyor assay, which results in cleavage of PCR products at sites of DNA mismatch that result from the creation of indels at sites of double strand breaks (Fig 1B) [17]. A second set of TALENs was designed to create double strand breaks in the MLL and AF9 genes within the breakpoint cluster regions typically seen in patients with MLL-AF9 leukemia (Fig 1C). This design was based on the specific translocation sequence found in a child with AML (P1) that was characterized by Langer et al. [21]. The surveyor assay confirmed activity of both the MLL and AF9 TALENs (Fig 1D).

Fig 1. MLL, AF4, and AF9 TALEN design.

(A, C) TALEN pairs (bold sequence) were designed to target known translocation break points (underlined) within the MLL, AF4, and AF9 genes. (B, D) Following nucleofection into K562 cells, cutting by each TALEN pair was measured using the surveyor assay, which detects indels within the target region that result from imprecise repair of a DNA double strand break. Asterisks denote cleaved PCR products.

Induction of double strand breaks within the breakpoint cluster region of MLL and its fusion partner is sufficient to generate MLL translocations

To test whether the simultaneous induction of two double strand breaks is sufficient to induce a specific chromosomal translocation, we nucleofected K562 cells with either the MLL and AF4 TALENs, or the MLL and AF9 TALENs. Genomic DNA isolated on day 3 post-nucleofection demonstrated both the primary MLL translocation (MLL-AF4; MLL-AF9) and the reciprocal translocation (AF4-MLL; AF9-MLL) (Fig 2A and 2B). Translocations were not detected when the MLL TALENs were expressed alone. TALEN transfected cells appeared to have a survival disadvantage in the K562 cultures as the relative intensity of the translocation product within the cell populations was significantly decreased after 14 days in culture. Resultant PCR products were isolated, and genomic rearrangements confirmed by Sanger sequencing (Fig 2C and 2D). A sub-culturing strategy was used to quantify the MLL-AF4 translocation frequency in K562 cells, which was approximately 1 in 1100 cells (8.9 x 10−4). These studies demonstrate that TALENs specifically targeted to the respective breakpoint cluster regions are capable of generating MLL chromosomal translocations.

Fig 2. Co-expression of MLL and AF4 or AF9 TALENs in K562 cells induces MLL translocations.

(A, B) MLL and AF4 or AF9 TALENs were transiently expressed in K562 cells. Genomic DNA was isolated at the indicated time point and used for PCR analysis for MLL translocations. (C, D) PCR products were isolated and sequenced to confirm translocation products. Data shown are a composite alignment of PCR products from multiple experiments showing a variety of distinct translocations. Underlines denote TALEN binding sites.

TALENs targeted to breakpoint cluster regions are sufficient to generate MLL translocations in human primary hematopoietic stem and progenitor cells

Since K562 cells have significant chromosomal abnormalities at baseline and likely do not recapitulate what would be observed in primary cells, we explored the feasibility of inducing translocations in human primary HSPCs. After isolation of human primary CD34+ cells from fresh umbilical cord blood, the indicated TALENs were introduced by nucleofection. Cells were maintained in culture and monitored over time for the appearance of an MLL translocation. After 1–2 weeks following nucleofection, MLL-AF4 or MLL-AF9 translocations and the respective reciprocal translocations (AF4-MLL; AF9-MLL) were detected (Fig 3A and 3B). The resultant PCR products were isolated and the translocations confirmed by Sanger sequencing (Fig 3C and 3D). In order to assess the frequency of induction of MLL-AF4 translocations by TALENs, human CD34+ cells were subdivided into a 96 well plate immediately following nucleofection with MLL and AF4 TALENs (50,000 cells per well). Parallel cultures were maintained over time and monitored by PCR for the presence of the MLL-AF4 as well as the reciprocal AF4-MLL translocation. The estimated MLL-AF4 translocation frequency following nucleofection with TALENs was 2.6–4.0 x 10−5. The reciprocal AF4-MLL translocation was found to have a lower frequency of 1.3–2 x 10−5. Taken together, these data demonstrate the induction of MLL chromosomal translocations by TALEN-mediated genome engineering of primary human HSPCs.

Fig 3. Co-expression of MLL and AF4 or AF9 TALENs in primary human CD34+ cells induces MLL translocations.

(A, B) Primary human CD34+ cells isolated from umbilical cord blood were nucleofected with MLL and AF4 or AF9 TALENs. Genomic DNA was isolated at the indicated time point and used for PCR analysis for MLL translocations. (C, D) PCR products were isolated and sequenced to confirm translocation products. Nucleotide sequences shown are a composite alignment of PCR products from multiple experiments showing a variety of distinct translocations. Underlines denote TALEN binding sites.

MLL translocations in primary CD34+ cells confer a survival advantage in extended culture and induce clonal expansion in colony-forming cell assays

To assess whether de novo MLL translocations result in a survival advantage in primary cells, human CD34+ cells were nucleofected with MLL and AF4 or AF9 TALENs or GFP and maintained in culture. Cell viability was determined by flow cytometry over time (S1 Fig). Whereas the control sample died out after 2 months in culture, the MLL-AF4 and MLL-AF9 samples continued to proliferate until approximately day 100–120. We did not see a difference in the proliferation capacity between the MLL-AF4 and MLL-AF9 samples.

Further analysis of the subcultures revealed a variable pattern on a clonal level. We used both semi-quantitative PCR (MLL-AF4 and AF4-MLL; Fig 4A) and qPCR (MLL-AF4; Fig 4B) to track the kinetics of a given clone over time. Seventeen out of the 20 subcultures had a detectable MLL-AF4 translocation one week following nucleofection. Many of these clones persisted for 14–21 days in culture, but disappeared between days 21–41. However, a number of subcultures contained a clone with an MLL-AF4 translocation that appeared to have a significant survival advantage as demonstrated by the increased prominence of the translocation product over time. While some of these clones displayed a rapid early expansion and subsequently disappeared after day 21, four clones remained prominent thru days 41–57. FISH analysis was performed on subcultures 9 and 20 at day 41 to better quantify the percentage of cells with an MLL translocation (Fig 5). Using an MLL break apart probe, an MLL translocation was detected in 49.5% (99/200) of cells in subculture 9, 17.5% (35/200) of cells in subculture 20, and 0% (0/200) of cells in the GFP control culture. Interestingly, the four subcultures that demonstrated the most significant expansion and prolonged survival in extended culture also had a detectable reciprocal AF4-MLL translocation by PCR (S2 Fig) and the reciprocal translocation was detected in subculture 9 by FISH analysis. Additionally, expression of the MLL-AF4 fusion product transcript was confirmed by RT-PCR in subcultures 3, 9, 16, and 20 (S3 Fig). In order to further understand the clonal dynamics of the MLL translocations in these subcultures, MLL-AF4 and AF4-MLL PCRs were repeated with genomic DNA from subcultures 3, 9, 16, and 20 and the PCR products analyzed by Sanger sequencing (S2 Fig). Sequencing confirmed 1–2 initial clones (tracked by unique translocation sequence) with one clone becoming dominant over time in each subculture.

Fig 4. Survival advantage for CD34+ cells containing an MLL-AF4 translocation.

Primary human CD34+ cells isolated from umbilical cord blood were nucleofected with MLL and AF4 TALENs. The population was immediately divided into 20 subcultures (50,000 cells per well), which were maintained over time. Genomic DNA was isolated at the indicated time points and used for semi-quantitative PCR analysis for MLL translocations (A) and qPCR for the MLL-AF4 translocation (B). (-- indicates subcultures nucleofected with GFP as negative control)

Fig 5. FISH analysis shows MLL translocations in human CD34+ cells induced by MLL and AF4 TALENs.

(A-D) FISH analysis using an MLL break apart probe was performed on cells from subcultures 9 (A, B) and 20 (C) as well as a negative control culture (D) to evaluate the presence of MLL chromosomal translocations. Two hundred cells were analyzed for each sample. Representative images are shown. Red arrows indicate cells positive for an MLL translocation. Panel B shows a cell from subculture 9 in metaphase that was noted to have an MLL translocation.

We next performed colony-forming assays to further assess the clonal expansion and transformative potential of the translocated cells. For this purpose, we plated 10,000 cells of the MLL translocated samples (both AF4 and AF9) or control samples each on day 25 and 39 of the extended culture in semisolid medium supplemented with the same cytokines that were used during the extended cultures. All three cultures generated colonies after 12–14 days, but the MLL-AF4 and MLL-AF9 samples displayed significantly higher clonogenic potential after the second round of replating as compared to the control samples (Fig 6A). Remarkably, approximately 20% of the colonies in the experimental samples containing the translocated cells, but not the control sample, demonstrated a compact morphology consistent with more immature cells [19] (Fig 6B). However, the colony forming assays confirmed that the translocated cells were not fully transformed since further replating resulted in decreasing cell numbers comparable to what was observed in our extended in vitro cultures.

Fig 6. CD34+ cells nucleofected with MLL and AF4 or AF9 TALENs display enhanced replating potential in semi-solid medium.

Colony forming assays were performed to assess the effect of MLL and AF4 or AF9 TALENs on the replating efficiency of CD34+ cells in semi-solid medium. The bars in Panel A represent the mean number of colonies generated per 104 seeded cells. Panel B shows the morphology of secondary colonies generated by CD34+ cells nucleofected with MLL and AF4 or AF9 TALENs: diffuse colony representing ~80% (left) and compact colony representing ~20% (right) of all colonies.


Using tools developed for genome editing/engineering, we induced patient specific MLL chromosomal translocations in primary human hematopoietic stem and progenitor cells (freshly isolated CD34+ cells), and prospectively investigated what happened to the cells as a result of the initiating event. We believe that this is the first example in which TALEN nucleases have induced the relevant translocation in primary human HSPCs, a critically important milestone in using engineered nucleases to study the ontogeny of translocation associated leukemia.

MLL-rearranged leukemia presents a unique opportunity to explore leukemia pathogenesis in a prospective manner. We know from infant studies that MLL rearrangements are an initiating event that occurs in utero in infants who develop MLL-rearranged leukemia [22, 23]. Other chromosomal translocations such as TEL-AML1 and BCR-ABL have been shown to occur in utero, but demonstrate more twin discordance, longer latency, and are thought to require subsequent mutations for leukemia development [24, 25]. Epidemiologic studies suggest that an MLL translocation alone may be sufficient for leukemogenesis given the high penetrance and short latency seen in twin studies [26]. MLL translocations also occur in therapy related leukemias in which a secondary leukemia usually occurs 1–3 years after exposure to topoisomerase inhibitors such as etoposide and teniposide [2729]. Thus, the latency in infant leukemia and therapy related leukemia both highlight the importance of understanding the developmental period between the occurrence of the translocation and the appearance of overt leukemia.

Despite extensive investigations over the past 20 years, our understanding of the role of MLL translocations in the pathogenesis of acute leukemia is still not complete. Many animal models have been developed and helped to define MLL fusion proteins as key transcriptional and epigenetic regulators that lead to leukemia pathogenesis [7, 9, 3034]. However, current animal models have failed to fully recapitulate the role of MLL fusion proteins, especially in the case of the MLL-AF4 translocation. The MLL-AF4 translocation has been difficult to model in mice due both to the size of the MLL-AF4 translocation product and its chromosomal orientation [8]. Additionally, mouse models that develop leukemia by forced expression of an MLL-AF4 fusion product have not fully recapitulated the clinical phenotype seen in infants and are complicated by potential effects related to retroviral insertion. There is ongoing debate as to whether the MLL-AF4 fusion protein alone is sufficient to induce leukemogenesis or whether subsequent mutations are required [35]. Previous studies have demonstrated MLL-AF4 leukemias to have fewer additional mutations as compared to other leukemias, but have identified N-Ras, K-Ras, and Flt-3 as a source of potential cooperating mutations [3640]. Additionally, it remains unclear whether there is a role for the reciprocal AF4-MLL translocation product, as only a fraction of patients have a detectable reciprocal translocation; however one report has demonstrated leukemia development in a mouse model by enforced expression of the reciprocal AF4-MLL fusion product alone [41]. The genome engineering approach developed in our studies provides a novel approach to more fully explore the role of various initiating events in leukemia pathogenesis in a prospective, physiologic manner using primary HSPCs.

In vitro, we observed that many cells with an induced MLL translocation do not persist in culture. This is likely a result of an intact apoptotic response in primary cells. However, a subset of cells that acquired an MLL translocation persisted over time, appeared to have a selective advantage in extended culture, and demonstrated a higher clonogenic potential in colony forming assays. While this effect was not as robust as that seen in previous studies when the fusion product has been introduced with retroviral vectors, this is likely related to lower expression of the fusion product under the control of the endogenous promoter. Interestingly, the clones that demonstrated the most robust survival advantage either in subculture analysis or colony forming assay contained the reciprocal translocation product. This further suggests that the reciprocal translocation may play an active role in leukemia pathogenesis. While the MLL-rearranged cells demonstrated a selective advantage, which may represent a pre-leukemic clone, our studies would suggest that they were not fully transformed as these cells eventually died out in culture as well as with serial replating in colony forming assays. This is consistent with other studies showing that enforced expression of an MLL-AF4 transgene in primary HSPCs conveys a proliferative advantage but is insufficient to generate leukemia [9, 38]. An alternative explanation for the enhanced proliferation followed by disappearance is that the culture conditions do not support immortalized growth of transformed cells since it is widely known that primary ALL, including those with MLL translocations, are extremely difficult to grow in culture. Finally, it could also be that the clones were pre-leukemic but also died out because they retained some of the characteristics of their cell of origin (an early progenitor) and had a defined but limited replicative lifespan. Further studies are required to address these hypotheses. Nevertheless, this model system presents a unique opportunity, as we typically do not have access to pre-leukemic clones in order to explore the steps necessary to transform into leukemia. We are currently using this system both in vitro and in vivo to explore the immunophenotypic, gene expression and epigenetic changes that occur in cells over time as a result of the MLL translocation. Additionally, we are using this system to generate MLL translocations in CD34+ cells freshly isolated from umbilical cord blood followed by transplantation into immunocompromised (NSG) mice in order to develop a novel mouse model of MLL-rearranged leukemia. We believe this system will allow us to more fully and accurately answer whether or not MLL translocations are sufficient for leukemogenesis or whether they require cooperating events. It will also allow exploration of the relationship between the MLL translocation partner as well as cell of origin in relation to disease phenotype.

Supporting Information

S1 Fig. MLL translocations confer a survival advantage in primary human CD34+ cells.

CD34+ cells were nucleofected with MLL and AF4 or AF9 TALENs or GFP (control) and maintained in culture in vitro. Cell viability was monitored over time by flow cytometry.


S2 Fig. Clonal expansion of CD34+ cells containing an MLL translocation.

Human CD34+ cells were nucleofected with MLL and AF4 TALENs to induce MLL translocations. Subpopulations were sampled over time for the presence of the MLL-AF4 and AF4-MLL translocations. PCR products were isolated and sequenced to evaluate evolution of sequence specific clones.


S3 Fig. RT-PCR shows expression of MLL-AF4 fusion transcripts in CD34+ cells induced by TALENs.

(A) RNA was isolated at day 42 for each subculture showing a prominent MLL-AF4 translocation as well as the negative control cultures. RT-PCR detected the MLL-AF4 transcript expressed in subcultures 9 and 20. The PCR products were isolated and sequenced for confirmation. (B) Real-time RT-PCR confirmed MLL-AF4 transcript expression in subcultures 3, 9, 16, and 20 above the threshold limit of detection.



We thank Dan Voytas at University of Minnesota for generously providing the TALEN Golden Gate library. We also thank Dana Bangs from the Stanford Hospital and Clinics Cytogenetics Laboratory for his assistance with the MLL FISH analysis, and Will Wagstaff and Joseph Clark for technical assistance with CD34+ cell isolation.

Author Contributions

Conceived and designed the experiments: EHB CB MLC MHP. Performed the experiments: EHB CB CD. Analyzed the data: EHB CB MLC MHP. Contributed reagents/materials/analysis tools: EHB CB MLC MHP. Wrote the paper: EHB CB CD MLC MHP.


  1. 1. Howlader N, Noone A, Krapcho M, Garshell J, Miller D, Altekruse S, et al. SEER Cancer Statistics Review, 1975–2011 Bethesda, MD: National Cancer Institute, 2014 based on November 2013 SEER data submission, posted to the SEER web site, April 2014. Report No.
  2. 2. Piller G. Leukaemia—a brief historical review from ancient times to 1950. Br J Haematol. 2001;112(2):282–92. Epub 2001/02/13. pmid:11167820.
  3. 3. Hunger SP, Lu X, Devidas M, Camitta BM, Gaynon PS, Winick NJ, et al. Improved survival for children and adolescents with acute lymphoblastic leukemia between 1990 and 2005: a report from the children's oncology group. J Clin Oncol. 2012;30(14):1663–9. Epub 2012/03/14. pmid:22412151; PubMed Central PMCID: PMC3383113.
  4. 4. Chowdhury T, Brady HJ. Insights from clinical studies into the role of the MLL gene in infant and childhood leukemia. Blood Cells Mol Dis. 2008;40(2):192–9. Epub 2007/10/02. pmid:17905612.
  5. 5. Sam TN, Kersey JH, Linabery AM, Johnson KJ, Heerema NA, Hilden JM, et al. MLL gene rearrangements in infant leukemia vary with age at diagnosis and selected demographic factors: a Children's Oncology Group (COG) study. Pediatr Blood Cancer. 2012;58(6):836–9. Epub 2011/07/30. pmid:21800415; PubMed Central PMCID: PMC3208122.
  6. 6. Jansen MW, Corral L, van der Velden VH, Panzer-Grumayer R, Schrappe M, Schrauder A, et al. Immunobiological diversity in infant acute lymphoblastic leukemia is related to the occurrence and type of MLL gene rearrangement. Leukemia. 2007;21(4):633–41. Epub 2007/02/03. pmid:17268512.
  7. 7. Meyer C, Hofmann J, Burmeister T, Groger D, Park TS, Emerenciano M, et al. The MLL recombinome of acute leukemias in 2013. Leukemia. 2013;27(11):2165–76. Epub 2013/05/01. pmid:23628958; PubMed Central PMCID: PMC3826032.
  8. 8. Liu H, Cheng EH, Hsieh JJ. MLL fusions: pathways to leukemia. Cancer Biol Ther. 2009;8(13):1204–11. Epub 2009/09/05. pmid:19729989; PubMed Central PMCID: PMC3289713.
  9. 9. Montes R, Ayllon V, Gutierrez-Aranda I, Prat I, Hernandez-Lamas MC, Ponce L, et al. Enforced expression of MLL-AF4 fusion in cord blood CD34+ cells enhances the hematopoietic repopulating cell function and clonogenic potential but is not sufficient to initiate leukemia. Blood. 2011;117(18):4746–58. Epub 2011/03/11. pmid:21389315.
  10. 10. Weinstock DM, Brunet E, Jasin M. Induction of chromosomal translocations in mouse and human cells using site-specific endonucleases. J Natl Cancer Inst Monogr. 2008;(39):20–4. Epub 2008/07/24. pmid:18647997; PubMed Central PMCID: PMC3261771.
  11. 11. Brunet E, Simsek D, Tomishima M, DeKelver R, Choi VM, Gregory P, et al. Chromosomal translocations induced at specified loci in human stem cells. Proceedings of the National Academy of Sciences of the United States of America. 2009;106(26):10620–5. Epub 2009/06/25. pmid:19549848; PubMed Central PMCID: PMC2700748.
  12. 12. Piganeau M, Ghezraoui H, De Cian A, Guittat L, Tomishima M, Perrouault L, et al. Cancer translocations in human cells induced by zinc finger and TALE nucleases. Genome Res. 2013;23(7):1182–93. Epub 2013/04/10. pmid:23568838; PubMed Central PMCID: PMC3698511.
  13. 13. Iliakis G, Wang H, Perrault AR, Boecker W, Rosidi B, Windhofer F, et al. Mechanisms of DNA double strand break repair and chromosome aberration formation. Cytogenet Genome Res. 2004;104(1–4):14–20. Epub 2004/05/27. pmid:15162010.
  14. 14. Choi PS, Meyerson M. Targeted genomic rearrangements using CRISPR/Cas technology. Nat Commun. 2014;5:3728. Epub 2014/04/25. pmid:24759083.
  15. 15. Doyle EL, Booher NJ, Standage DS, Voytas DF, Brendel VP, Vandyk JK, et al. TAL Effector-Nucleotide Targeter (TALE-NT) 2.0: tools for TAL effector design and target prediction. Nucleic acids research. 2012;40(Web Server issue):W117–22. Epub 2012/06/14. pmid:22693217; PubMed Central PMCID: PMC3394250.
  16. 16. Cermak T, Doyle EL, Christian M, Wang L, Zhang Y, Schmidt C, et al. Efficient design and assembly of custom TALEN and other TAL effector-based constructs for DNA targeting. Nucleic acids research. 2011;39(12):e82. Epub 2011/04/16. pmid:21493687; PubMed Central PMCID: PMC3130291.
  17. 17. Qiu P, Shandilya H, D'Alessio JM, O'Connor K, Durocher J, Gerard GF. Mutation detection using Surveyor nuclease. Biotechniques. 2004;36(4):702–7. Epub 2004/04/20. pmid:15088388.
  18. 18. Siraj A, Ozbek U, Sazawal S, Sirma S, Timson G, Al-Nasser A, et al. Preclinical validation of a monochrome real-time multiplex assay for translocations in childhood acute lymphoblastic leukemia. Clinical Cancer Research. 2002;8:3832–40. pmid:12473597
  19. 19. Lavau C, Szilvassy SJ, Slany R, Cleary ML. Immortalization and leukemic transformation of a myelomonocytic precursor by retrovirally transduced HRX-ENL. EMBO J. 1997;16(14):4226–37. Epub 1997/07/16. pmid:9250666; PubMed Central PMCID: PMC1170048.
  20. 20. Reichel M, Gillert E, Angermuller S, Hensel J, Heidel F, Lode M, et al. Biased distribution of chromosomal breakpoints involving the MLL gene in infants versus children and adults with t(4;11) ALL. Oncogene. 2001;20:2900–7. pmid:11420702
  21. 21. Langer T, Metzler M, Reinhardt D, Viehmann S, Borkhardt A, Reichel M, et al. Analysis of t(9;11) chromosomal breakpoint sequences in childhood acute leukemia: almost identical MLL breakpoints in therapy-related AML after treatment without etoposides. Genes Chromosomes Cancer. 2003;36(4):393–401. Epub 2003/03/06. pmid:12619163.
  22. 22. Greaves M. Molecular Genetics, Natural History and the Demise of Childhood Leukaemia. European Journal of Cancer. 1999;35(14):1941–53. pmid:10711237
  23. 23. Greaves MF, Maia AT, Wiemels JL, Ford AM. Leukemia in twins: lessons in natural history. Blood. 2003;102(7):2321–33. Epub 2003/06/07. pmid:12791663.
  24. 24. Borst L, Wesolowska A, Joshi T, Borup R, Nielsen FC, Andersen MK, et al. Genome-wide analysis of cytogenetic aberrations in ETV6/RUNX1-positive childhood acute lymphoblastic leukaemia. Br J Haematol. 2012;157(4):476–82. Epub 2012/03/13. pmid:22404039.
  25. 25. Mullighan CG, Goorha S, Radtke I, Miller CB, Coustan-Smith E, Dalton JD, et al. Genome-wide analysis of genetic alterations in acute lymphoblastic leukaemia. Nature. 2007;446(7137):758–64. Epub 2007/03/09. pmid:17344859.
  26. 26. Cowell IG, Austin CA. Mechanism of generation of therapy related leukemia in response to anti-topoisomerase II agents. Int J Environ Res Public Health. 2012;9(6):2075–91. Epub 2012/07/26. pmid:22829791; PubMed Central PMCID: PMC3397365.
  27. 27. Super HJ, McCabe NR, Thirman MJ, Larson RA, Le Beau MM, Pedersen-Bjergaard J, et al. Rearrangements of the MLL gene in therapy-related acute myeloid leukemia in patients previously treated with agents targeting DNA- topoisomerase II. Blood. 1993;82(12):3705–11. pmid:8260707
  28. 28. Libura J, Slater DJ, Felix CA, Richardson C. Therapy-related acute myeloid leukemia-like MLL rearrangements are induced by etoposide in primary human CD34+ cells and remain stable after clonal expansion. Blood. 2005;105(5):2124–31. Epub 2004/11/06. pmid:15528316.
  29. 29. Cowell IG, Sondka Z, Smith K, Lee KC, Manville CM, Sidorczuk-Lesthuruge M, et al. Model for MLL translocations in therapy-related leukemia involving topoisomerase IIbeta-mediated DNA strand breaks and gene proximity. Proceedings of the National Academy of Sciences of the United States of America. 2012;109(23):8989–94. Epub 2012/05/23. pmid:22615413; PubMed Central PMCID: PMC3384169.
  30. 30. Wei J, Wunderlich M, Fox C, Alvarez S, Cigudosa JC, Wilhelm JS, et al. Microenvironment determines lineage fate in a human model of MLL-AF9 leukemia. Cancer Cell. 2008;13(6):483–95. Epub 2008/06/10. S1535-6108(08)00155-4 [pii] pmid:18538732; PubMed Central PMCID: PMC2486365.
  31. 31. Barabe F, Kennedy JA, Hope KJ, Dick JE. Modeling the initiation and progression of human acute leukemia in mice. Science. 2007;316(5824):600–4. Epub 2007/04/28. pmid:17463288.
  32. 32. Moriya K, Suzuki M, Watanabe Y, Takahashi T, Aoki Y, Uchiyama T, et al. Development of a multi-step leukemogenesis model of MLL-rearranged leukemia using humanized mice. PloS one. 2012;7(6):e37892. Epub 2012/06/30. pmid:22745659; PubMed Central PMCID: PMC3380045.
  33. 33. Chen W, Li Q, Hudson WA, Kumar A, Kirchhof N, Kersey JH. A murine Mll-AF4 knock-in model results in lymphoid and myeloid deregulation and hematologic malignancy. Blood. 2006;108(2):669–77. Epub 2006/03/23. pmid:16551973; PubMed Central PMCID: PMC1895483.
  34. 34. Chen W, O'Sullivan MG, Hudson W, Kersey J. Modeling human infant MLL leukemia in mice: leukemia from fetal liver differs from that originating in postnatal marrow. Blood. 2011;117(12):3474–5. Epub 2011/03/26. pmid:21436082; PubMed Central PMCID: PMC3069683.
  35. 35. Stam RW. The ongoing conundrum of MLL-AF4 driven leukemogenesis. Blood. 2013;121(19):3780–1. Epub 2013/05/11. pmid:23660854.
  36. 36. Dobbins SE, Sherborne AL, Ma YP, Bardini M, Biondi A, Cazzaniga G, et al. The silent mutational landscape of infant MLL-AF4 pro-B acute lymphoblastic leukemia. Genes Chromosomes Cancer. 2013;52(10):954–60. Epub 2013/07/31. pmid:23893660.
  37. 37. Liang DC, Shih LY, Fu JF, Li HY, Wang HI, Hung IJ, et al. K-Ras mutations and N-Ras mutations in childhood acute leukemias with or without mixed-lineage leukemia gene rearrangements. Cancer. 2006;106(4):950–6. Epub 2006/01/13. pmid:16404744
  38. 38. Montes R, Ayllon V, Prieto C, Bursen A, Prelle C, Romero-Moya D, et al. Ligand-independent FLT3 activation does not cooperate with MLL-AF4 to immortalize/transform cord blood CD34+ cells. Leukemia. 2014;28(3):666–74. Epub 2013/11/19. pmid:24240202.
  39. 39. Prelle C, Bursen A, Dingermann T, Marschalek R. Secondary mutations in t(4;11) leukemia patients. Leukemia. 2013;27(6):1425–7. Epub 2012/12/18. pmid:23242105; PubMed Central PMCID: PMC3677139.
  40. 40. Taketani T, Taki T, Sugita K, Furuichi Y, Ishii E, Hanada R, et al. FLT3 mutations in the activation loop of tyrosine kinase domain are frequently found in infant ALL with MLL rearrangements and pediatric ALL with hyperdiploidy. Blood. 2004;103(3):1085–8. pmid:14504097
  41. 41. Bursen A, Schwabe K, Ruster B, Henschler R, Ruthardt M, Dingermann T, et al. The AF4.MLL fusion protein is capable of inducing ALL in mice without requirement of MLL.AF4. Blood. 2010;115(17):3570–9. Epub 2010/03/03. pmid:20194896.