The NSD2 P.E1099K Mutation Is Enriched at Relapse and Confers

Published OnlineFirst April 24, 2020; DOI: 10.1158/1541-7786.MCR-20-0092

MOLECULAR CANCER RESEARCH | CANCER “-OMICS”

The NSD2 p.E1099K Mutation Is Enriched at Relapse and Confers Drug Resistance in a Cell Context–Dependent Manner in Pediatric Acute Lymphoblastic Leukemia Joanna Pierro1,2, Jason Saliba1, Sonali Narang1, Gunjan Sethia1, Shella Saint Fleur-Lominy1,3, Ashﬁyah Chowdhury1, Anita Qualls1, Hannah Fay1, Harrison L. Kilberg1, Takaya Moriyama4, Tori J. Fuller5, David T. Teachey5, Kjeld Schmiegelow6, Jun J. Yang4, Mignon L. Loh7, Patrick A. Brown8, Jinghui Zhang4, Xiaotu Ma4, Aristotelis Tsirigos1, Nikki A. Evensen1, and William L. Carroll1,2

ABSTRACT ◥ The NSD2 p.E1099K (EK) mutation is observed in 10% of and REIIBP EK isoforms had a greater impact than knockdown acute lymphoblastic leukemia (ALL) samples with enrichment at of Type II alone, suggesting that both SET containing EK relapse indicating a role in clonal evolution and drug resistance. To isoforms contribute to phenotypic changes driving relapse. discover mechanisms that mediate clonal expansion, we engineered Furthermore, in vivo models using both cell lines and patient B-precursor ALL (B-ALL) cell lines (Reh, 697) to overexpress samples revealed dramatically enhanced proliferation of NSD2 wildtype (WT) and EK NSD2, but observed no differences in EK compared with WT and reduced sensitivity to 6-mercapto- proliferation, clonal growth, or chemosensitivity. To address purine in the relapse sample relative to diagnosis. Finally, whetherNSD2EKactscollaborativelywithotherpathways,we EK-mediated changes in chromatin state and transcriptional used short hairpin RNAs to knockdown expression of NSD2 in output differed dramatically among cell lines further supporting B-ALL cell lines heterozygous for NSD2 EK (RS4;11, RCH-ACV, a cell context–specificroleofNSD2EK.Theseresultsdemon- SEM). Knockdown resulted in decreased proliferation in all lines, strate a unique role of NSD2 EK in mediating clonal fitness decreased clonal growth in RCH-ACV, and increased sensitivity through pleiotropic mechanisms dependent on the genetic and to cytotoxic chemotherapeutic agents, although the pattern of epigenetic landscape. drug sensitivity varied among cell lines implying that the oncogenic properties of NSD2 mutations are likely cell context specific Implications: NSD2 EK mutation leads to drug resistance and a and rely on cooperative pathways. Knockdown of both Type II clonal advantage in childhood B-ALL.

Introduction relapse remains a major cause of death related to cancer in children (2, 3). While new immunologic approaches are quite promising, While 5-year survival rates for newly diagnosed pediatric acute leukemia subclones continue to emerge through the selective pressures lymphoblastic leukemia (ALL) now approach 90%, up to 20% of of therapy (4). Therefore, targeting the underlying biological pathways children will suffer relapse and face a poor prognosis (1). Thus, ALL of therapy resistance is crucial for preventing and treating relapse. Comprehensive genomic profiling of diagnosis/relapse pairs from patients with B-precursor ALL (B-ALL) has identified relapse- 1 Departments of Pediatrics and Pathology, Perlmutter Cancer Center, NYU enriched mutations and copy-number changes that confer drug 2 Langone Health, New York, New York. Division of Pediatric Hematology/ resistance (5–9). Mutations in epigenetic regulators are among the Oncology, Hassenfeld Children's Hospital at NYU Langone Health, New York, fi New York. 3Division of Medical Hematology/Oncology, NYU Langone Health, most commonly seen alterations at relapse and have been identi ed in New York, New York. 4Department of Pharmaceutical Sciences, St. Jude Chil- almost two-thirds of cases (10). We have previously demonstrated the dren's Research Hospital, Memphis, Tennessee. 5Department of Pediatrics and vital role of epigenetic changes in mediating drug sensitivity making the Center for Childhood Cancer Research, Children's Hospital of Philadelphia targeting such lesions a promising therapeutic strategy (11). and The Perelman School of Medicine at The University of Pennsylvania, NSD2 (MMSET, WHSC1) encodes a histone 3 lysine 36 (H3K36) Philadelphia, Pennsylvania. 6Department of Pediatrics and Adolescent Medicine, 7 methyltransferase that catalyzes the monomethylation and dimethy- The University Hospital Rigshospitalet, Copenhagen, Denmark. Department of fi Pediatrics, Benioff Children's Hospital and The Helen Diller Family Comprehen- lation of H3K36. NSD2 alterations have been identi ed in a variety of sive Cancer Center University of California, San Francisco, San Francisco, cancers, most notably the t(4;14) translocation in multiple myeloma, California. 8The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, which confers a poor prognosis (12). The substitution of glutamic acid Johns Hopkins University School of Medicine, Baltimore, Maryland. to lysine at residue 1099 (p.E1099K, EK) within the conserved SET Note: Supplementary data for this article are available at Molecular Cancer domain occurs in up to 10% of ALL patients (13, 14). NSD2 EK results Research Online (http://mcr.aacrjournals.org/). in increased methyltransferase activity leading to a global increase in J. Pierro and J. Saliba contributed equally to this article. H3K36me2 levels and stereotactic inhibition of EZH2-mediated H3K27 trimethylation. This has also been observed in t(4;14) multiple Corresponding Author: William L. Carroll, New York University Langone Medical Center, 522 First Avenue, Smilow Building, New York, NY 10016. Phone: 212-263- myeloma and has been shown to lead to increased proliferation, 2327; Fax: 212-263-9190; E-mail: [email protected] enhanced DNA damage repair, and resistance to DNA damaging agents (13–16). Mol Cancer Res 2020;18:1153–65 NSD2 consists of three distinct isoforms associated with oncogen- doi: 10.1158/1541-7786.MCR-20-0092 esis: Type I, Type II, and response element II–binding protein (REIIBP; 2020 American Association for Cancer Research. Supplementary Fig. S1; refs. 17, 18). The canonical isoform, Type II, is

AACRJournals.org | 1153

Pierro et al.

the largest, spanning 1365 amino acids with Type I representing the In vivo xenograft experiments N-terminus and REIIBP the C-terminus of the full-length isoform. Patient-derived xenograft (PDX) models using nonobese diabetic/ While Type I results from alternative splicing, REIIBP is transcribed severe combined immunodeficiency (NOD/SCID/Il2rgtm1wjl/SzJ) from a separate internal transcription start site. Type II and REIIBP mice were generated from a diagnostic (NSD2 WT) and relapse contain the conserved SET domain responsible for methyltransferase (NSD2 EK) pair as described previously (22). Mice (4–5/treatment activity and regulation of gene expression through histone methyla- arm/sample) were randomized to receive 6-mercaptopurine (6-MP; tion (19). Type I can also alter gene expression; however, the mech- 25 mg/kg/day by gavage) or vehicle control following the detection of þ þ anism(s) remains poorly understood (17). Notably, Type I and II at least 1% peripheral blood (PB) blasts (defined as CD19 /CD45 by localize to the nucleus, whereas REIIBP localizes to the cytoplasm and flow cytometry) for 5 days per week until sacrifice. Average disease nucleolus. Unlike Type II, the impact of EK on REIIBP function has yet burden at the time of treatment initiation was not different between to be fully categorized. treatment and control arms. Disease burden was assessed weekly by Herein, we provide further evidence to support the role of NSD2 EK flow cytometric measurement of PB and splenic and bone marrow in pediatric B-ALL disease progression and now demonstrate under- blasts were compared at sacrifice using published techniques (8). lying cellular context has a vital impact on the epigenetic and phenotypic alterations mediated by NSD2 EK. Our data suggest NSD2 EK RNA-seq requires cooperative pathways to exert its pleiotropic effects on cell Gene expression was assessed by RNA-seq according to standard cycle, proliferation, clonogenicity, and drug response. Our results also protocols (20). RNA was extracted using the QIAGEN RNeasy Mini suggest that both NSD2 Type II and REIIBP contribute to these effects. Kit and quality was verified by an Agilent Bioanalyzer 2100 (PICO chip). RNA-seq libraries were sequenced using 54 base pair reads on the Illumina Genome Analyzer GAIIx. Image collection and analysis Materials and Methods was completed using the Illumina CASAVA pipeline. Adapters from Cell culture, drug preparation, viral preparation, immunoblotting, RNA-seq paired-end reads were trimmed and low-quality bases (<30) phenotypic assays, and mouse xenografts were performed according to were removed using Trimmomatic (v0.33; ref. 23). Alignment was methods published previously (7, 8, 20) and additional information performed using STAR (v2.5.3a; ref. 24) to human genome (hg19) and can be found in Supplementary Information. bases with mapping quality <30 were removed. Raw counts of sequencing reads were obtained from HTseq2. Normalized genome Cells and reagents browser tracks were generated using BEDTools (v2.26.0; ref. 25). The B-lineage leukemia cell lines RS4;11, Reh (ATCC), KOPN8, Differential gene expression analysis was performed using 697, RCH-ACV (DSMZ), and SEM (kindly gifted by Jun Yang, St. Jude DESeq2 (26). For each gene, a two-sample t test was applied to obtain Children's Hospital) were grown in RPMI1640 medium. HEK293T the P value for significance of differential expression between test and (ATCC) cells were grown in DMEM. All media were supplemented control. Genes detected as differentially expressed (P < 0.002) were fi with 10% FBS, 1% penicillin/streptomycin under 5% CO2 at 37 C. No de ned as upmodulated or downmodulated according to the sign of cell lines were used beyond passage 20. Each leukemia line was t-statistics. All other genes were classified as “not changed” in expres- validated by short tandem repeat analysis through ATCC except for sion. Genes with absolute fold change ≥1.5 and P ≤ 0.05 were selected RCH-ACV which was purchased from DSMZ directly. DSMZ rou- for pathway analysis with Enrichr and KEGG 2016 to determine tinely verifies cell lines and provides authentication information with pathways significantly altered as indicated by combined scores each order. Cell lines were routinely monitored for Mycoplasma (P value and z-score; refs. 27, 28). contamination by PCR using ATCC Universal Mycoplasma Detection Kit (20-1012K). ChIP-seq Cells were cross-linked in 1% formaldehyde, lysed and then sheared Primary patient sample gene expression analysis chromatin was immunoprecipitated with antibodies targeting histone Primary patient samples were obtained from the Children's Oncol- marks [H3K36me2 (Abcam, ab9049), H3K27me3 (Abcam, ab6002), ogy Group (COG) Biobank. All subjects provided consent for banking H3K27ac (Abcam, ab4729), and H3K9ac (Millipore, 06-942)]. A small and future research use of these specimens in accordance with the aliquot was set aside prior to immunoprecipitation as input DNA. regulations of the institutional review boards of all participating Quality control was performed using an Agilent Technologies 2100 institutions. Whole-genome sequencing and/or whole-exome Bioanalyzer prior to library preparation. ChIP-seq libraries were sequencing was performed as described previously (9). Data were generated using KAPA HyperPrep kit, quantified using KAPA qPCR aggregated for somatic single-nucleotide variants/indels detected in kit, and sequenced using the HiSeq 2500 for paired-end 50-bp reads. diagnosis/relapse tumors of each case to generate two-dimensional ChIP-seq paired-end reads were trimmed and low-quality bases (<30) scatter plots to visualize variant allele frequency (VAF) between were removed using Trimmomatic (v0.33; ref. 23). Reads were mapped diagnosis and relapse tumors. A small number of somatic variants, to the hg19 using bowtie2 and bases with mapping quality <30 were including NSD2 EK, were subject to ultradeep targeted resequencing removed. Due to the broad/diffuse peaks created by H3K36me2 and (>500,000)todefine their preexistence status in diagnosis tumors. H3K27me3, peaks for these marks were called by SICER that uses a CleanDeepSeq was used to obtain allele counts of corresponding cluster enrichment–based analysis (29). H3K27ac and H3K9ac peaks markers (21). To detect somatic mutations with very low frequency, were called using MACS2 (–broad; ref. 30). Differential binding wildtype (WT) genomic sites flanking the designed amplicons with analysis of peak data was performed using DiffBind (31) and nearest same genotype as the marker of interest were used to derive a genes were annotated using ChIPseeker (32). H3K27ac-promoter background error-rate histogram of corresponding mutation type and regions, H3K9ac-promoter regions, H3K36me2-promoter, and gene the VAF of the marker of interest was compared against the back- body regions (exclude intergenic regions) were selected for further ground error-rate histogram by using Z-test (two-sided). Markers with downstream analysis. RNA-seq heatmaps were aligned with the P < 0.001 were called somatic in the corresponding sample. histone mark called for each gene from DiffBind output files to assess

1154 Mol Cancer Res; 18(8) August 2020 MOLECULAR CANCER RESEARCH

NSD2 p.E1099K in Relapsed B-ALL

effect of the mark on gene expression. Bigwig files and profile plots Results were generated using deepTools2 (v2.3.3) using RPGC normalization NSD2 EK is detected at diagnosis as a minor subclone in a (–smoothLength 2500 –binSize 500; ref. 33). Profile plots were gen- majority of patients who harbor dominant EK mutations at erated across significantly upregulated and downregulated genes and relapse immediate upstream and downstream 10-kb regions were divided into In a recently collected cohort of matched diagnosis/remission/ 50 bins of 200 bp each to compare knockdown (KD; NSD2-low) lines relapse samples from patients enrolled on COG relapse B-ALL trial against the NT control (NSD2-high). If the closest upstream gene was (AALL1331), NSD2 EK was present at relapse in 7 of 82 trios. A at least 30 kb away from the transcription start site (TSS) of the current previously published analysis of 20 trios also harbored NSD2 EK at gene, the intergenic region was visualized to detect profile patterns in relapse (9) resulting in an overall frequency at relapse of 12%. Among those regions using the first and last 10 kb of each intergenic region. For all 10 NSD2 EK relapse cases (Fig. 1), three cases had similar VAFs at distribution analysis regions were defined in mutually exclusive manor diagnosis and relapse while four cases revealed NSD2 EK as part of a as promoter ¼ plus/minus 5 kb from TSS, gene body ¼ exon þ intron þ minor subclone at diagnosis (VAF < 0.1) that evolved into the major utr, and intergenic ¼ intergenic þ downstream regions. clone at relapse (VAF, 0.49–0.72). Similarly, 3 patients harbored NSD2 ChIP-seq and RNA-seq data were then integrated to determine EK solely at relapse suggesting that these mutations were acquired or whether the observed epigenetic changes were associated with com- that a minor clone may have been present at diagnosis but below mensurate changes in transcriptional output. The log2 fold changes in sensitivity of detection. The enrichment of NSD2 EK at relapse in 7 of histone peaks at promoters (for activation marks) and promoter/gene 10 patients implies a role in shaping clonal evolution and drug body (repressive marks) were then compared with the log2 fold resistance. changes in gene expression. Box plots were generated to display changes in marks relative to gene expression. A similar approach was Overexpression of NSD2 WT and EK in leukemia cell lines has no performed for enhancers and superenhancers which were associated impact on tumor phenotype with the nearest neighboring gene. To determine the role of NSD2 EK in clonal evolution, B-ALL cell lines (Reh and 697) were engineered to overexpress c-myc–tagged ATAC-seq Type II WT or EK NSD2. As a control, both cell lines were stably ATAC libraries were generated on the basis of the protocol by infected with the empty destination vector (EV). Overexpression of Buenrostro and colleagues (34) with one modification. Cells were lysed both WT and EK resulted in increased H3K36me2 and decreased via centrifugation for 1 minute at 500 g. Nuclei were tagmented using H3K27me3 consistent with enzymatic hyperactivity (Supplementary Nextera (Illumina) Tagmentation DNA buffer and enzyme. PCR Fig. S2A). However, overexpression of either WT or EK did not affect amplification was performed as described in protocol. Reads were clonogenicity, cell proliferation, or drug sensitivity (Supplementary mapped to the hg19 using Bowtie2(v2.3.4.1) and those with a mapping Fig. S2B–S2D). Furthermore, we overexpressed either the WT or quality <30 were removed. Duplicated reads were removed using EK REIIBP isoform in Reh cells. Like Type II overexpression, Sambamba (v0.6.8). Peaks were called using MACS2(v2.1.1). Differ- REIIBP overexpression was insufficient to impart oncogenic propert- ential binding analysis of peaks was performed using DiffBind. Peaks ies in a NSD2 WT background B-ALL cell line (Supplementary were assigned to nearest neighboring gene. Fig. S3A–S3C).

Data deposition NSD2 EK requires cooperating oncogenic pathways to impact All raw data files generated through high-throughput sequencing tumorigenicity and drug resistance discussed in this publication have been deposited in the National Due to the lack of an oncogenic phenotype in our overexpression Center for Biotechnology Information Gene Expression Omnibus experiments, we hypothesized NSD2 EK might require other coop- (GEO; http://www.ncbi.nlm.nih.gov/geo) and are accessible through erating pathways to endow leukemic cells with a clonal advantage. GEO Series accession number GSE149159. Therefore, we generated NSD2 KD cell lines using short-hairpin (sh) RNAs targeting different NSD2 isoforms in B-ALL cell lines that Statistical analysis naturally harbor a heterozygous NSD2 EK mutation (RS4;11, Statistical significance was calculated using unpaired t test or one- RCH-ACV, and SEM; Fig. 2A; Supplementary Fig. S1). RS4;11 and way ANOVA with post hoc Tukey test for IC50 significance. SEM both contain KMT2A-AFF1 translocations but SEM also contains

Figure 1. A 1.0 B Patients harboring NSD2 EK at relapse in COG PAVETT diagnosis/relapse paired cohorts. A and B, Enrichment of NSD2 EK mutation at relapse is observed in 7 of 10 patients. VAF at diagnosis 0.6 and relapse for 10 B-ALL patient samples. PAWWLL PAVYIB PAPEFH PARFTR PARIAD PAXMYE 0.4 PAVIXG

PAUZSK VAF (Relapse) PAVSUA 0.2

0.0 0.0 0.2 0.4 0.6 1.0 VAF (Diagnosis)

AACRJournals.org Mol Cancer Res; 18(8) August 2020 1155

Pierro et al.

A RS4;11 RCH-ACV SEM Figure 2. NT sh2 sh5 NT sh2 sh5NT sh2 sh5 KD of NSD2 in B-ALL cell lines harboring EK mutations leads to decreased prolif- 140 NSD2 Type II eration and colony formation in a cell context–dependent manner. A, Western blot analysis of whole cell lysates from NSD2 Type I 72 RS4;11, RCH-ACV, and SEM NSD2 KD cell lines. B, Proliferation curves of RS4;11, RCH-ACV, and SEM NDS2 KD cell lines as 55 Tubulin counted by trypan blue over 7–10 days. Each cell line was plated in triplicate with 17 H3K36me2 bars representing the mean SD. A statistical signiﬁcance of <0.001 for all lines was determined by nonlinear 17 H3K27me3 regression exponential growth. C, Meth- oCult colony forming assay in RCH-ACV NSD2 KD cell lines plated at 1,000 cells/ 17 H3 400 mL in duplicate per cell line. Colonies were stained with MTT and counted after 14 days in culture. Statistical significance determined by unpaired t test BC25 RS4;11 RCH-ACV ( P < 0.05, P < 0.01). ) 6 20

r (10 NT 15 **

10 sh2 *

5 sh5 Total cell numbe

0 035710 050100150200250 Days Total number of colonies 20 RCH-ACV ) 6 15 r (10

10 NT

5 Total cell numbe 0 0 3 5 710 Days sh2 20 SEM ) 6 15 r (10

10 NT sh5 5 sh2 sh5 Total cell numbe 0 0357 Days

a CDKN2a deletion and a TP53 mutation. RCH-ACV harbors a expression was also knocked down in WT NSD2 cell lines (Reh, 697, TCF3-PBX1 translocation and mutations in EGFR, HRAS, and NRAS. and KOPN8; Supplementary Fig. S4A). No differences in growth or For a full list of all mutations in each cell line, please refer to clonogenic survival were found upon NSD2 KD in any of the WT cell the Broad Institute's Cancer Cell Line Encyclopedia (https://portals. lines, suggesting the phenotypic changes were due to reduction of broadinstitute.org/ccle). NSD2 EK specifically (Supplementary Fig. S4B and S4C). NSD2 KD in cell lines harboring the heterozygous NSD2 EK Notably, NSD2 KD in heterozygous EK lines also resulted in mutation resulted in decreased proliferation compared with nontar- increased chemosensitivity (Fig. 3; Supplementary Table S1). The geting (NT) controls (Fig. 2B). NSD2 KD in RCH-ACV demonstrated RS4;11 NSD2 KD lines were significantly more sensitive to mercap- < decreased colony formation (Fig. 2C) similar to what was reported topurine (6-MP; sh2: 3.4-fold lower IC50; P 0.0001, sh5: 1.3-fold; previously in RS4;11(35). To determine whether the observed phe- P < 0.003), but not to other agents, including thioguanine notypes was due to reduced expression of mutant NSD2 specifically, (6-TG; Fig. 3A). The impact of decreased NSD2 expression in

1156 Mol Cancer Res; 18(8) August 2020 MOLECULAR CANCER RESEARCH

NSD2 p.E1099K in Relapsed B-ALL

ABCRS4;11 RCH-ACV SEM

- - -5.5 5.5 5 125

- -6 ** 6 ] [M [M] *** 100 [M] *** ***

-7 -6 75 -7

50 NT sh2

% Cell viability 25 sh5 0 −7.0 −6.5 −6.0 −5.5 −5.0 −7.0 −6.5 −6.0 −5.5 −5.0 −6.5 −6.0 −5.5 −5.0 6-MP (M) 6-MP (M) 6-MP (M)

-6 -6 125 ** [M] ** 100 [M]

- 75 7 -7

-6 50 [M] 25 % Cell viability -7 0 −7.5 −7.0 −6.5 −6.0 −5.5 −5.0 −7.5 −7.0 −6.5 −6.0 −5.5 −5.0 −8.0 −7.5 −7.0 −6.5 −6.0 −5.5 6-TG (M) 6-TG (M) 6-TG (M)

-5 -7 125 *** ** [M] -8 [M] -6 100 **

-9 -7 75

-7 50 ] M [ 25 % Cell viability

-8 0 −9.0 −8.5 −8.0 −7.5 −9.0 −8.5 −8.0 −7.5 −7.0 −7 −6 −5 −4 −3 Pred (M) Pred (M) Pred (M)

-7 -7 -7 125 ] ] [M - M -8 8 [ [M] 100 **

- -8 -9 9 75

25 % Cell viability

0 −9.0 −8.5 −8.0 −7.5 −7.0 −9.0 −8.5 −8.0 −7.5 −7.0 −8.5 −8.0 −7.5 −7.0 Dox (M) Dox (M) Dox (M)

Figure 3. KD of NSD2 in B-ALL cell lines harboring EK mutations leads to changes in drug response in a cell context–dependent manner. Representative cytotoxicity curves assessed by CellTiter-Glo of RS4;11 (A), RCH-ACV (B), and SEM (C) NSD2 KD cell lines exposed to various chemotherapy agents, each plated in triplicate and bars represent mean SD. All experiments were repeated at least three times. IC50 dot plots are shown as insets. Dots represent mean from individual experiments. Bar represents median. Statistical signiﬁcance determined by one-way ANOVA (P < 0.05, P < 0.01, P < 0.001).

RCH-ACV cells created a more diverse chemotherapy response P < 0.005), prednisolone (Pred; sh2: 2.6-fold, P < 0.001; sh5: 2.3-fold, proﬁle with increased sensitivity to 6-MP (sh2: 4.0-fold, P < 0.0001; P < 0.003), and doxorubicin (sh2: 1.9-fold, P < 0.007; sh5: 1.2-fold, n.s.) sh5: 2.4-fold, P < 0.0001), 6-TG (sh2: 1.4-fold, P < 0.01; sh5 1.5-fold, relative to NT (Fig. 3B). No difference was observed with methotrexate

AACRJournals.org Mol Cancer Res; 18(8) August 2020 1157

Pierro et al.

(MTX; Supplementary Table S1). Activated caspase 3 levels were A major mechanism of cell death mediated by both 6-MP and 6-TG measured using flow cytometry after 120 hours of exposure to 6-MP, relates to incorporation of thioguanine nucleotides (TGN) into DNA 6-TG, and doxorubicin in RS4;11 and RCH-ACV NT and KD cells leading to double-stranded breaks, cell-cycle arrest, and apoptosis (7). (Supplementary Fig. S5A and S5B). A significantly greater percentage Thus, the impact of NSD2 KD on 6-MP, but not 6-TG sensitivity seen of cells had activated caspase 3 in 6-MP–treated RS4;11 sh2 and 6-MP, in RS4;11, was unexpected. To investigate this selectivity, cell-cycle 6-TG, and doxorubicin-treated RCH-ACV sh2 lines versus their NT progression and DNA-TG incorporation were measured following controls, which verified the cytotoxicity results across cell types. In thiopurine treatment. Over the course of 6-MP treatment, the RS4;11 addition, like Swaroop and colleagues, we observed increased apo- KD cells demonstrated a greater degree of cell-cycle arrest, as dem- ptosis in RCH-ACV NSD2 KD cells at baseline; however, caspase onstrated by a decrease in cells actively cycling (P < 0.01), compared activation following treatments were significantly higher than baseline with the NT cells. However, following 6-TG treatment, NT and sh2- levels (Supplementary Fig. 5B; ref. 36). SEM KD and NT cells had expressing cells displayed an equivalent drop in the percentage of cells similar responses to 6-MP, 6-TG, MTX, and doxorubicin treatment cycling (Fig. 5A). These data support our cytotoxicity results that (Fig. 3C). Paradoxically, in SEM, only sh5 showed increased sensitivity revealed increased sensitivity to 6-MP but not 6-TG. In contrast, KD in to Pred (7.8-fold; P < 0.009; Fig. 3C), suggesting a role for Type I in RCH-ACV cells led to a significantly greater decrease in cycling cells glucocorticoid resistance, consistent with a recent report demonstrat- over time compared with NT upon treatment with both 6-MP ing Type I can modulate gene expression (17). (P < 0.01) and 6-TG (P < 0.01; Fig. 5B). Furthermore, RCH-ACV Overall, sh2, which targets both EK containing isoforms, had a KD cells showed increased DNA-TG levels over time after 6-MP more dramatic impact on the cellular phenotypes than sh5. To treatment compared with NT (P < 0.001), consistent with increased address whether these findings were due to the greater degree of KD sensitivity through the DNA-TG–induced nucleotide mismatching observed with sh2 (Fig. 2A), a third shRNA, sh1 (which also targets and futile mismatch repair attempts. In contrast, while RS4;11 KD Type II and REIIBP) was tested (Supplementary Fig. S1). This showed slower accumulation of DNA-TGs, presumably due to slower resulted in less of a reduction in NSD2 expression compared with proliferation, by 120 hours of exposure to 6-MP, NT, and KD cells sh2, yet also showed analogous 6-MP sensitivity (Supplementary exhibited no significant difference of DNA-TGs (Fig. 5C). SEM NT Fig. S6). These findings suggest that both isoforms may be involved and KD cell lines did not reveal significant differences in cell-cycle in mediating the impact of NSD2 EK. Furthermore, in contrast to progression or TGN incorporation upon treatment with 6-MP, as mutant lines, NSD2 KD of SET containing isoforms in WT lines expected on the basis of the cell viability data (data not shown). (Reh, 697, and KOPN8) failed to show any impact on response to However, this short-term exposure may not reliably mimic the 6-MP, 6-TG, doxorubicin, or MTX compared with NT controls long-term maintenance therapy of ALL. Still, these data indicate NSD2 (Supplementary Fig. S7; Supplementary Table S1). Collectively, EK can impart thiopurine resistance through alternative mechanisms these results again indicate NSD2 EK has a pleiotropic impact on in addition to circumventing the canonical thiopurine-induced mis- drug resistance that is dependent on cell context. The one exception match repair–dependent process. was KD in 697 and KOPN8 (NSD2 WT) cells which led to a paradoxical increase in resistance to Pred (1.9-fold, P < 0.0003; NSD2 EK activates unique transcriptional programs that are cell 58.6-fold, P < 0.005, respectively), suggesting expression of NSD2 context dependent WT actually sensitizes these cells to glucocorticoids. To determine the downstream transcriptional program mediated by To assess potential oncogenic properties of NSD2 EK in vivo, NSD2 EK, RNA-seq was performed on Reh and 697 cells overexpres- xenograft models were generated from isogenic cell lines and a sing either WT or EK NSD2, and EV controls (Supplementary diagnostic and relapse primary B-ALL patient sample (PAWWLL) Table S3). Interestingly, in both Reh and 697, the WT and EK lines that harbored NSD2 EK only at relapse (PDX). Importantly, the effects (relative to EV controls) shared approximately 50% of upregulated and on growth were supported by significantly decreased tumor burden in 35% of downregulated genes (Supplementary Fig. S8A) suggesting that mice injected with RS4;11 cells expressing sh2 compared with NT while WT and EK NSD2 do share some transcriptional targets, EK may (Fig. 4A). However, we were not able to recapitulate the response to modulate a unique set of genes. Furthermore, when comparing EK 6-MP treatment likely due to the much slower growth of EK KD cells overexpression in Reh cells to 697 cells, only 5 upregulated genes in vivo (sh2 2-fold lower in vitro vs. >10-fold lower in vivo). Likewise, (ADAP2, PCNXL2, PLXNA2, SCBA, and NSD2) and one suppressed the relapse patient sample harboring EK resulted in more aggressive gene (FLRT3) were shared with similar results noted between Reh and disease compared with the diagnosis sample as evidenced by com- 697 WT cell lines (Supplementary Fig. S8B). The limited overlap in paring absolute splenic blast count at sacrifice in both relapse and differentially regulated genes and pathways modulated by overex- diagnostic samples treated with vehicle controls (Fig. 4B). While both pressed EK and WT NSD2 between cell lines implies the transcrip- the relapse and diagnostic samples retained sensitivity to 6-MP, the tional programs modulated by NSD2 are quite dependent on cell relative reduction in absolute blast count was far greater at diagnosis context (Supplementary Fig. S8C). (25-fold) compared with relapse (11-fold decrease; Fig. 4B). Further- To determine the extent to which NSD2-mediated epigenetic more, bone marrow blast percentage was dramatically reduced with changes play a role in gene expression, we performed ChIP-seq on 6-MP treatment in the diagnosis sample relative to vehicle control Reh WT and EK NSD2 overexpression lines. As expected, we saw a whereas the relapse sample showed no difference posttreatment global increase in the H3K36me2 mark across the genome as well as a (Fig. 4C). Western blot analysis demonstrates increased H3K36me2 global decrease in the H3K27me3 mark. When aligning the signifi- in a sample from the relapse-derived mice, suggesting hyperactivation cantly differentially expressed up and downregulated genes from of NSD2 (Fig. 4D). While this in vivo model supports the role of NSD2 RNA-seq alongside the respective ChIP-seq data, we observed a strong EK in proliferation and resistance to 6-MP, it is difficult to ascertain correlation between gain of H3K36me2 and loss of H3K27me3 with whether these findings are solely due to the gain of NSD2 EK because increased gene expression, indicating NSD2-mediated epigenetic additional mutations are acquired at relapse (Supplementary changes drive gene expression in cells with hyperactivated NSD2 Table S2). (Supplementary Fig. S9).

1158 Mol Cancer Res; 18(8) August 2020 MOLECULAR CANCER RESEARCH

NSD2 p.E1099K in Relapsed B-ALL

Figure 4. A 1011 NSD2 EK leads to significant impact on NT Vehicle in vivo fi 10 tumor growth . A, Quanti cation 10 NT 6-MP fl * of average ux determined by analyzing * BLI of mice injected with RS4;11 NT or 109 ns sh2 Vehicle sh2-expressing cells treated with vehicle or 6-MP. Bars represent mean SD. N ¼ 108 sh2 6-MP 4 per condition. Quantification of absolute splenic blast count as calculated by 107 6 spleen cell number (10 ) percentage Average flux of blasts in spleen (B) and bone marrow 106 blast percent (C) at sacrifice from PDX generated from diagnosis (NSD2 WT)/ 105 relapse (NSD2 EK) patient pair. Mice 0 4 8 12 16 20 24 were treated with vehicle (n ¼ 5for Days both diagnosis and relapse) or 6-MP (25 mg/kg/day; n ¼ 4 for diagnosis, n ¼ 5 for relapse) 5 days a week until BD** DR sacrifice. Bars represent mean SD. D, *** Western blot analysis of whole cell 800 NSD2 Type II lysate from cells taken from spleen 140 of mice showing increased H3K36me2 s) 600 in mouse from relapse sample (R) compared with mouse from diagnosis (D) *** NSD2 Type I 400 72 sample. 17 200 H3K36me2

0 55 Tubulin

(cell count × % blast -200 icle

Spleen absolute blast count e 6-MP vehicle s veh e si laps Re gno elaps Diagnosis 6-MP R Dia

100 C **

20 BM Blast percent (%) 0

e 6-MP vehicle s vehicle e aps osi Rel gn elaps Diagnosis 6-MP R Dia

We next examined gene expression in our NSD2 KD cell lines lated by sh2 (Type II and REIIBP) and sh5 (Type I and II). Interest- naturally harboring the EK mutation by RNA-seq (Supplementary ingly, reduction of Type II/REIIBP resulted in a greater impact on gene Table S3). We ﬁrst compared transcriptional programs between expression compared with reduction of Type I/II further supporting a NT (NSD2high) and sh2 (NSD2low) lines. We observed only 4.4% possible role of REIIBP in NSD2-mediated oncogenesis (Fig. 6B). (143/3,257) of upregulated genes and 1.7% (39/2,319) of downregu- Notably, the majority of genes modulated by sh5 are a subset of those lated genes were shared between all three cell lines (Fig. 6A) indicating modulated by sh2, again suggesting REIIBP may modulate gene signiﬁcant diversity in transcriptional reprogramming by NSD2 expression and impact the phenotype of NSD2 EK cancer cells. between cell types. Pathway analysis on genes modulated by NSD2 To examine the impact of NSD2 on chromatin accessibility, we also reduction in each cell line revealed few common pathways shared performed ATACseq in our NSD2 KD cell lines naturally harboring among cell lines (focal adhesion and cell adhesion molecules), some of NSD2 EK (Supplementary Fig. S11B). Similar to RNA-seq analysis, we which are in agreement with previously published data (Supplemen- compared open and closed chromatin regions between NT (NSD2high) tary Fig. S10; ref. 36). As our functional assays implied a possible role and sh2 (NSD2low) lines. The most variable region of peak alterations for REIIBP, we also examined differences in gene expression modu- was within the intergenic space (Fig. 6C). Interestingly, RCH-ACV

AACRJournals.org Mol Cancer Res; 18(8) August 2020 1159

Pierro et al.

A RS4;11 NT sh2

1 NT sh2 0.9 ** 6-MP 0.8 ** 0.7 0.6 0.5

0.4 EdU 0.3 0.2 6-TG 0.1 0

% Cycling normalized to untreated 96 120 96 120 6-MP 6-TG PI B RCH-ACV NT sh2

6-MP 1.4 NT sh2

1.2 *** **

0.8 ** ** EdU 0.6

0.4 6-TG

0.2

0 96 120 96 120 % Cycling normalized to untreated 6-MP 6-TG PI

C RS4;11 RCH-ACV

15,000 15,000 NT sh2

10,000 * 10,000 ** *** ***

5,000 5,000

0 0 DNA-TGN Levels (fmol/ m g DNA) 0 72 96 120 0 72 96 120 Hours Hours

Figure 5. NSD2 EK mediates resistance to 6-MP through multiple mechanisms. Cell-cycle analysis measured by EdU incorporation for RS4;11 (A) and RCH-ACV (B) cell lines.

Percentage of cell cycling was normalized to untreated controls at each time point. The IC50 of the more sensitive line (sh2) was chosen for this analysis. Representative ﬂow cytometry images at 120 hours shown on right. Rectangle represents EdU positive (cycling) cells. C, DNA-TGN incorporation was measured using LC/MS-MS following 6-MP treatment of RS4;11 (left) and RCH-ACV (right) lines. Bars represent mean SD. Statistical signiﬁcance determined by unpaired t test ( P < 0.05, P < 0.01, P < 0.001).

1160 Mol Cancer Res; 18(8) August 2020 MOLECULAR CANCER RESEARCH

NSD2 p.E1099K in Relapsed B-ALL

A B Upregulated in NSD2High NSD2 sh2 vs. sh5 Upregulated genes RS4;11 SEM

518 292 1132

143 45 225

714

RCH-ACV NSD2 sh2 vs. sh5 Downregulated in NSD2High Downregulated genes RS4;11 SEM

175 85 535

39 59 117

1309

RCH-ACV

C Gains D Promoters 5,000 Gains Losses

4,000 RS4;11 SEM RS4;11 SEM 152 0 30 10 0 69 3,000 1 0 2,000 70 0 1 0 Peak number 1,000 656 26 0 RS4;11 SEM RCH-ACV RCH-ACV RCH-ACV

Losses Nonpromoters

1,000 Gains Losses Intergenic RS4;11 SEM RS4;11 SEM Promoter 750 Gene body 864 25 168 44 3 891

50 0 500 1180 17 1 1

Peak number 250 1671 101

0 RS4;11 SEM RCH-ACV RCH-ACV RCH-ACV

Figure 6. KD of NSD2 in NSD2 EK B-ALL cell lines reveals distinct genetic signatures and chromatin accessibility. A, Overlap of differentially expressed genes, assessed by RNA-seq, in RS4;11, RCH-ACV, and SEM NT (NSD2high) relative to each cell line's sh2 KD using an absolute fold change of 1.5, P < 0.05. B, Overlap of shared upregulated (top) and downregulated (bottom) genes in NT versus sh2 against NT versus sh5 in RS4;11, RCH-ACV, and SEM. C, Quantification of peaks gained or lost, as assessed by ATACseq, in RS4;11, RCH-ACV, and SEM NT relative to each cell line's sh2 KD using an absolute fold change of 1.5, P < 0.05. D, Overlap of nearest genes to peaks gained or lost among the three lines. Promoters defined as 5 kb from TSS, nonpromoters defined as all other regions excluding promoters. and RS4;11 NSD2high lines each had significant gains of open whereas SEM displayed the most peak losses. Gains and losses of chromatin within their intergenic regions, whereas SEM NSD2high ATAC promoter peaks correlated with increases and decreases displayed marked peak loss within their intergenic regions indicating in transcript expression as assessed by RNA-seq in RS4:11 and a decrease in accessible chromatin. Within promoter regions, RCH-ACV but no correlation was observed in the SEM cell line RCH-ACV and RS4;11 showed modest increases in peak gains, (Supplementary Fig. S11A). Gene bodies were the least variable region

AACRJournals.org Mol Cancer Res; 18(8) August 2020 1161

Pierro et al.

as chromatin accessibility was unchanged across all three NSD2high cell among cell lines in these properties and, importantly, a highly variable types. Interestingly, only 0.11% of promoter region gains and 1.3% of impact on chemosensitivity to individual agents used in ALL treat- intergenic regions with peak gains were shared among all three cell ment. Moreover, the impact of NSD2 EK on proliferation and drug lines (Fig. 6D), consistent with our RNA-seq data showing very little resistance was confirmed using in vivo models. overlap of changes in transcriptional output across cell lines. Overall, While we and others have shown relapse enriched somatic altera- the data indicate NSD2 EK effects chromatin accessibility in a cell tions result in either pan-resistance (6, 8) or resistance to a single class context–dependent manner with the most profound impact on of agents such as glucocorticoids or thiopurines (20, 40–42), remark- accessibility within intergenic regions. ably, our data show that NSD2 EK imparts resistance to a variety of Finally, to examine changes in the epigenetic landscape driven by agents depending on cell type. KD of NSD2 EK in RS4;11 resulted in NSD2 EK, we performed ChIP-seq on our RS4;11 NT and KD lines. increased sensitivity to 6-MP and in RCH-ACV, widespread sensitivity We saw a dramatic increase in the H3K36me2 mark across intergenic to 6-MP, 6-TG, doxorubicin, and Pred. Li and colleagues also observed regions (Fig. 7A and B) with a pronounced decrease in H3K27me3 increased glucocorticoid sensitivity in RCH-ACV (43). No alteration evenly across the genome (data not shown) in NT (NSD2high) com- in drug sensitivity was seen in SEM mediated by the KD of both SET pared with KD (NSD2low), which coincides with dramatic changes in containing isoforms. This varied pattern of resistance further supports chromatin accessibility within the intergenic regions as well as pre- a model where NSD2 EK collaborates with other oncogenic programs vious data reported in multiple myeloma (36). We noted a strong to impart a clonal advantage. correlation of increased gene expression with an increase in the Unexpectedly, NSD2 EK confers resistance to 6-MP exclusively H3K36me2 at promoters and gene bodies as well as an increase in in RS4;11 and significantly more resistance to 6-MP versus 6-TG in promoter distribution of the activating H3K9ac and H3K27ac marks RCH-ACV. Generally, both prodrugs manifest cell death through the (Fig. 7C). Despite the genome-wide heightened H3K36me2, a subset generation and incorporation of TGNs into DNA, but we validated a of genes displayed a decrease in expression along with loss of novel mechanism of resistance in RS4;11 by demonstrating no differ- H3K36me2 in RS4;11 NT relative to the KD (Fig. 7D). Likewise, in ence in DNA-TG levels between NT and NSD2 KD cells. Unlike 6-TG, spite of the genome wide loss of H3K27me3, a small subset of genes 6-MP may impact cellular metabolism by inhibition of de novo purine maintained this repressive mark and lost expression compared with synthesis and GTP homeostasis (44, 45). Elucidating the exact mech- the KD line (Fig. 7D). These findings suggest that NDS2 EK-mediated anism(s) by which NSD2 EK mediates 6-MP resistance is critical, as epigenetic changes that contribute to gene expression are due to direct 6-MP is a backbone of ALL maintenance therapy. histone methyltransferase activity of NSD2 as well as downstream The phenotypic diversity among cell lines was also seen when effects on the epigenetic landscape. examining changes in chromatin state and transcriptional output across cell lines. Similar to previous work in t(4;14) multiple myeloma by Popovic and colleagues, our ChIP-seq analysis of RS4;11 showed Discussion EK-mediated H3K36me2 enrichment was distributed widely across Relapsed B-ALL remains a leading cause of cancer mortality in the genome and not confined to promoters and gene bodies (15). Upon children. The outgrowth of preexisting intrinsic or secondary drug- further analysis of changes in chromatin structure mediated by resistant subclones under the selective pressures of chemotherapy modulation of NSD2 in the three cell lines containing NSD2 EK accounts for the majority of disease recurrences (37, 38). Mutations in alleles, we demonstrate diversity in the amount and location of epigenetic modifiers are found in a majority of patients at relapse, differential peaks yet, within all lines, most changes occurred in suggesting a role for the epigenome in mediating clonal evolution. intergenic regions, an observation also seen in multiple myeloma (15). NSD2 EK occurs in up to 10% of B-ALL and appears to be particularly Interestingly, RS4;11 NT displays a majority of peak gains in the enriched in ETV6/RUNX1 and TCF3/PBX1 biological sub- intergenic region that complements our ChIP-seq findings, which types (9, 14, 35). Furthermore, a recent publication identified NSD2 demonstrated gains of H3K36me2 in intergenic regions. Presence of mutations were enriched at relapse in B-ALL, all of which were early NSD2 EK impacted chromatin accessibility in RCH-ACV and SEM relapses (<36 months from diagnosis) further supporting a role in drug lines mostly in the intergenic regions as well. However, cell context resistance (39). Our analysis of relapse samples with NSD2 EK clearly has a role because the activating mutation conveys a variable mutations shows that in the majority of cases (7/10), either the signature in each cell line as overlap of peaks between cell types is mutation was not detected at diagnosis or was present in a very minor limited. subclone indicating a role in clonal evolution. The importance of cell context was reinforced by RNA-seq In our aim to discover the underlying mechanism(s) that drive analysis of KD of NSD2 in heterozygous EK cell lines where little NSD2 EK-mediated clonal evolution, we utilized two preclinical overlap was seen in transcriptome changes. Minimal overlap was models. Unlike previous studies in multiple myeloma and ALL that also observed between the NSD2 EK upregulated and downregu- modulated endogenous expression in cell lines harboring a NSD2 EK lated pathways seen in each individual cell type. Interestingly, allele (16, 36), we demonstrate that overexpression of WT NSD2 changes in chromatin accessibility determined by ATACseq did (mimicking multiple myeloma) or EK NSD2 (mimicking B-ALL) in not always correlate with the magnitude of changes measured by WT B-ALL lines do not lead to enhanced oncogenic properties, despite RNA-seq. For example, SEM NSD2high possessed the largest set of increased H3K36me2 and decreased H3K27me3. Conversely, KD of upregulated genes, but displayed the greatest loss of chromatin NSD2 in cell lines that harbor heterozygous NSD2 EK resulted in accessibility at the promoter and the intergenic regions. Conversely, diminished oncogenic properties, which was not observed upon NSD2 RCH-ACV NSD2high possessed the largest number of downregu- KD in WT lines, implying that NSD2 EK requires collaborative lated genes, but displayed the greatest gains of accessibility at the pathways to exert oncogenic properties. These results agree with promoter and the intergenic regions. Taken together, the greatest previous work where KD of NSD2 in individual cell lines harboring influence of NSD2 EK may not be related to proximal transcription the mutation resulted in decreased proliferation and clonal elements, but rather on distal regulatory regions that impact growth (14, 35, 36), but herein we demonstrate significant differences transcriptional reprogramming (46).

1162 Mol Cancer Res; 18(8) August 2020 MOLECULAR CANCER RESEARCH

NSD2 p.E1099K in Relapsed B-ALL

A H3K27me3 H3K36me2 B H3K36me2 Intergenic 11.5 NSD2-high NSD2-low NT 11.0

10.5 Gene body Intergenic Promoter 10.0

sh2 9.5 Gene 1 10 Kb 10 Kb Gene 2

NSD2 High

NSD2 Low RS4;11 NT vs. sh2 5.0 C 2.5 K27me3 Chr.8 0.0 **** −2.5 −5.0 5.0 2.5 K36me2 **** H3K36me2 Intragenic 0.0 −2.5 18 NSD2-high −5.0 NSD2-low 5.0 16

2.5 K27 Ac 0.0 **** 14 −2.5 −5.0 12 5.0 Down Up 10 2.5 **** K9Ac 0.0 8 −2.5 −5.0 −10.0 Kb TSS TES 10.0 Kb 5.0 Histone mark [log2(NT/sh2)]

K27 Ac.Ech 2.5 NSD2 High 0.0 **** NSD2 Low −2.5 −5.0 5.0

K27 Ac.SE 2.5 Chr.8 0.0 ** −2.5 −5.0 Down Up Gene expression [log2(NT/sh2)]

H3K27Ac D RNAseq H3K36me2 H3K27me3 Promoters Enhancers H3K9Ac

−1

NT sh2 NT sh2 NT sh2 NT sh2 NT sh2 NT sh2

Figure 7. KD of NSD2 in NSD2 EK B-ALL cell lines leads to a unique epigenetic signature that modulates gene expression. A, Pie chart of distribution of histone marks as assessed by ChIP-seq. B, Proﬁle plots of distribution of H3K36me2 in RS4;11 NT and sh2 in intergenic (top) and intragenic (bottom) regions of the genome. Underneath each are IGV genome browser views of H3K36me2 distribution within a representative locus on chromosome 8. C, Box plot of changes in histone marks as assessed by ChIP-seq analysis in RS4;11 NT (relative to NSD2 sh2) aligned with gene expression data (P < 0.01, P < 0.001, P < 0.0001). D, Heatmaps of top differentially expressed genes aligned with histone marks between RS4;11 NT and sh2.

AACRJournals.org Mol Cancer Res; 18(8) August 2020 1163

Pierro et al.

Our study provided additional novel insights related to the biolog- Disclosure of Potential Conflicts of Interest ical properties of the NSD2 EK mutation in ALL. First, by comparing D.T. Teachey is a consultant/advisory board member for La Roche, Amgen, the impact of overexpressed WT NSD2 (mimicking multiple myelo- Janssen, and Sobi. No potential conflicts of interest were disclosed by the other ma) versus NSD2 EK (mimicking B ALL), we are able to show that authors. despite some overlap in changes in the transcriptional output within Authors’ Contributions the same cell line, a remarkable degree of diversity exists. The EK substitution occurs within the SET domain in a loop proximal to the Conception and design: J. Pierro, J. Saliba, N.A. Evensen, W.L. Carroll Development of methodology: J. Pierro, J. Saliba, S. Saint Fleur-Lominy, substrate binding pocket which may contribute to alterations in NSD2 N.A. Evensen, W.L. Carroll substrate binding. This hypothesis is supported by a recent report that Acquisition of data (provided animals, acquired and managed patients, provided showed NSD2 EK has greater affinity for chromatin and enhanced facilities, etc.): J. Pierro, J. Saliba, S. Saint Fleur-Lominy, A. Chowdhury, A. Qualls, nucleosome complex stability (36), which may explain the transcrip- H. Fay, H.L. Kilberg, T.J. Fuller, D.T. Teachey, J.J. Yang, P.A. Brown, N.A. Evensen tional diversity observed between our NSD2 WT and EK overexpres- Analysis and interpretation of data (e.g., statistical analysis, biostatistics, sion lines. A second unique aspect of our study is our ability to assess computational analysis): J. Pierro, J. Saliba, S. Narang, G. Sethia, S. Saint Fleur- Lominy, A. Chowdhury, H. Fay, H.L. Kilberg, T. Moriyama, T.J. Fuller, D.T. Teachey, the possible contribution of both SET containing isoforms in trans- J.J. Yang, P.A. Brown, J. Zhang, X. Ma, A. Tsirigos, N.A. Evensen, W.L. Carroll formation and clonal evolution. In RS4;11 and RCH-ACV, combined Writing, review, and/or revision of the manuscript: J. Pierro, J. Saliba, G. Sethia, KD of Type II and REIIBP (sh2) demonstrated a greater reduction in H. Fay, D.T. Teachey, K. Schmiegelow, J.J. Yang, M.L. Loh, P.A. Brown, N.A. Evensen, cell proliferation and more pronounced effect on chemosensitivity W.L. Carroll compared with cells with simultaneous KD of Type I and Type II (sh5). Administrative, technical, or material support (i.e., reporting or organizing data, In a t(4;14) multiple myeloma cell model, the concurrent reduction of constructing databases): J. Pierro, J. Saliba, N.A. Evensen, W.L. Carroll Study supervision: W.L. Carroll both SET domain containing isoforms also imparted the most drastic impact on cell phenotypes (47). While both SET isoforms have been Acknowledgments implicated in the methylation of many histone substrates and play We gratefully acknowledge the funding received to complete this work. roles in transcriptional regulation, DNA repair, and RNA processing, W.L. Carroll has received grants from the NCI of Health (R01 CA140729-05), The the major contribution of Type II to oncogenic programming appears Leukemia and Lymphoma Society Specialized Center for Research (7010-14), to be related to generation of H3K36me2 (48). Studies have demon- Perlmutter Cancer Center Arline and Norman M. Feinberg Pilot Grant for Lymphoid strated REIIBP has H3K27 methyltransferase activity resulting in Malignancies, and the Perlmutter Cancer Center (P30 CA016087). J. Pierro receives funding from the St. Baldrick's Foundation (Fellowship Award, 524986), Alex's transcriptional repression (49), H3K79 methyltransferase activity Lemonade Stand Foundation (Young Investigator Grant), and Pediatric Cancer resulting in transcriptional activation (50), and a role in RNA proces- Foundation (Fellowship Training Grant). We gratefully acknowledge the support sing (18). Therefore, distinct aspects of both the EK activating muta- of the NYU School of Medicine Cytometry and Cell Sorting Laboratory and the tion and differences in the function and transcriptional reprogram- Genome Technology Center, which are supported by the NYU Langone Health ming of Type II and REIIBP may account for some of the cell context– Perlmutter Cancer Center Support Grant (P30 CA016087). We would like to thank specific differences noted. the laboratory of Kenneth Scott (Baylor College of Medicine) for the lentiviral destination overexpression vector and the laboratory of Sang-Boem Seo (Chung- Overall, our data indicate NSD2 EK can endow B-ALL cells with a Ang University) for the REIIBP cDNA sequence. clonal advantage through divergent mechanisms depending on the cell context, mediated by unique genetic or epigenetic signatures. In this regard, the mechanism of action of NSD2 EK is significantly different The costs of publication of this article were defrayed in part by the payment of page from other relapse-enriched alterations that are associated with spe- charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. cific resistance to individual agents used in therapy such as thiopurines or glucocorticoids. The pleotropic effect mediated by NSD2 EK may provide tumor cells with even greater plasticity to respond to the Received January 27, 2020; revised March 10, 2020; accepted April 17, 2020; selective pressures of therapy. published first April 24, 2020.

References 1. Hunger SP, Lu X, Devidas M, Camitta BM, Gaynon PS, Winick NJ, et al. thiopurine resistance in pediatric B-lymphoblastic leukemia. Haematologica Improved survival for children and adolescents with acute lymphoblastic 2018;103:830–9. leukemia between 1990 and 2005: a report from the children's oncology group. 8. Jones CL, Gearheart CM, Fosmire S, Delgado-Martin C, Evensen NA, Bride K, J Clin Oncol 2012;30:1663–9. et al. MAPK signaling cascades mediate distinct glucocorticoid resistance 2. Nguyen K, Devidas M, Cheng SC, La M, Raetz EA, Carroll WL, et al. Factors mechanisms in pediatric leukemia. Blood 2015;126:2202–12. influencing survival after relapse from acute lymphoblastic leukemia: a 9. Ma X, Edmonson M, Yergeau D, Muzny DM, Hampton OA, Rusch M, et al. Rise Children's Oncology Group study. Leukemia 2008;22:2142–50. and fall of subclones from diagnosis to relapse in pediatric B-acute lymphoblastic 3. Carroll WL, Raetz EA. Clinical and laboratory biology of childhood acute leukaemia. Nat Commun 2015;6:6604. lymphoblastic leukemia. J Pediatr 2012;160:10–8. 10. MarBG,BullingerLB,McLeanKM,GraumanPV,HarrisMH,StevensonK, 4. Park JH, Riviere I, Gonen M, Wang X, Senechal B, Curran KJ, et al. Long-term et al. Mutations in epigenetic regulators including SETD2 are gained during follow-up of CD19 CAR therapy in acute lymphoblastic leukemia. N Engl J Med relapse in paediatric acute lymphoblastic leukaemia. Nat Commun 2014;5: 2018;378:449–59. 3469. 5. Yang JJ, Bhojwani D, Yang W, Cai X, Stocco G, Crews K, et al. Genome-wide 11. Bhatla T, Wang J, Morrison DJ, Raetz EA, Burke MJ, Brown P, et al. Epigenetic copy number profiling reveals molecular evolution from diagnosis to relapse in reprogramming reverses the relapse-specific gene expression signature and childhood acute lymphoblastic leukemia. Blood 2008;112:4178–83. restores chemosensitivity in childhood B-lymphoblastic leukemia. Blood 6. Hogan LE, Meyer JA, Yang J, Wang J, Wong N, Yang W, et al. Integrated genomic 2012;119:5201–10. analysis of relapsed childhood acute lymphoblastic leukemia reveals therapeutic 12. Hudlebusch HR, Santoni-Rugiu E, Simon R, Ralfkiær E, Rossing HH, Johansen strategies. Blood 2011;118:5218–26. JV, et al. The histone methyltransferase and putative oncoprotein MMSET is 7. Evensen NA, Madhusoodhan PP, Meyer J, Saliba J, Chowdhury A, Araten DJ, overexpressed in a large variety of human tumors. Clin Cancer Res 2011;17: et al. MSH6 haploinsufficiency at relapse contributes to the development of 2919–33.

1164 Mol Cancer Res; 18(8) August 2020 MOLECULAR CANCER RESEARCH

NSD2 p.E1099K in Relapsed B-ALL

13. Oyer JA, Huang X, Zheng Y, Shim J, Ezponda T, Carpenter Z, et al. Point 33. Ramírez F, Ryan DP, Gruning€ B, Bhardwaj V, Kilpert F, Richter AS, et al. mutation E1099K in MMSET/NSD2 enhances its methyltranferase activity and deepTools2: a next generation web server for deep-sequencing data analysis. leads to altered global chromatin methylation in lymphoid malignancies. Nucleic Acids Res 2016;44:W160–5. Leukemia 2014;28:198–201. 34. Buenrostro JD, Wu B, Chang HY, Greenleaf WJ. ATAC-seq: a method for 14. Jaffe JD, Wang Y, Chan HM, Zhang J, Huether R, Kryukov GV, et al. Global assaying chromatin accessibility genome-wide. Curr Protoc Mol Biol 2015;109: chromatin profiling reveals NSD2 mutations in pediatric acute lymphoblastic 21 29 1–9. leukemia. Nat Genet 2013;45:1386–91. 35. Ding LW, Sun QY, Tan KT, Chien W, Mayakonda A, Yeoh AEJ, et al. Mutational 15. Popovic R, Martinez-Garcia E, Giannopoulou EG, Zhang Q, Zhang Q, Ezponda landscape of pediatric acute lymphoblastic leukemia. Cancer Res 2017;77:390– T, et al. Histone methyltransferase MMSET/NSD2 alters EZH2 binding and 400. reprograms the myeloma epigenome through global and focal changes in H3K36 36. Swaroop A, Oyer JA, Will CM, Huang X, Yu W, Troche C, et al. An activating and H3K27 methylation. PLoS Genet 2014;10:e1004566. mutation of the NSD2 histone methyltransferase drives oncogenic reprogram- 16. Shah MY, Martinez-Garcia E, Phillip JM, Chambliss AB, Popovic R, Ezponda T, ming in acute lymphocytic leukemia. Oncogene 2019;38:671–86. et al. MMSET/WHSC1 enhances DNA damage repair leading to an increase in 37. Mallory N, Pierro J, Raetz E, Carroll WL. The potential of precision medicine for resistance to chemotherapeutic agents. Oncogene 2016;35:5905–15. childhood acute lymphoblastic leukemia: opportunities and challenges. Exp Rev 17. Xie Z, Chooi JY, Toh SHM, Yang D, Basri NB, Ho YS, et al. MMSET I acts as an Precis Med Drug Dev 2018;3:343–56. oncoprotein and regulates GLO1 expression in t(4;14) multiple myeloma cells. 38. Pierro J, Hogan LE, Bhatla T, Carroll WL. New targeted therapies for relapsed Leukemia 2019;33:739–48. pediatric acute lymphoblastic leukemia. Expert Rev Anticancer Ther 2017;17: 18. Mirabella F, Murison A, Aronson LI, Wardell CP, Thompson AJ, Hanrahan SJ, 725–36. et al. A novel functional role for MMSET in RNA processing based on the link 39. Li B, Brady SW, Ma X, Shen S, Zhang Y, Li Y, et al. Therapy-induced mutations between the REIIBP isoform and its interaction with the SMN complex. drive the genomic landscape of relapsed acute lymphoblastic leukemia. Blood PLoS One 2014;9:e99493. 2020;135:41–55. 19. Lauring J, Abukhdeir AM, Konishi H, Garay JP, Gustin JP, Wang Q, et al. The 40. Li B, Li H, Bai Y, Kirschner-Schwabe R, Yang JJ, Chen Y, et al. Negative feedback- multiple myeloma associated MMSET gene contributes to cellular adhesion, defective PRPS1 mutants drive thiopurine resistance in relapsed childhood ALL. clonogenic growth, and tumorigenicity. Blood 2008;111:856–64. Nat Med 2015;21:563–71. 20. Meyer JA, Wang J, Hogan LE, Yang JJ, Dandekar S, Patel JP, et al. Relapse-specific 41. Tzoneva G, Perez-Garcia A, Carpenter Z, Khiabanian H, Tosello V, Allegretta M, mutations in NT5C2 in childhood acute lymphoblastic leukemia. Nat Genet et al. Activating mutations in the NT5C2 nucleotidase gene drive chemotherapy 2013;45:290–4. resistance in relapsed ALL. Nat Med 2013;19:368–71. 21. Ma X, Shao Y, Tian L, Flasch DA, Mulder HL, Edmonson MN, et al. Analysis of 42. Jones CL, Bhatla T, Blum R, Wang J, Paugh SW, Wen X, et al. Loss of TBL1XR1 error profiles in deep next-generation sequencing data. Genome Biol 2019;20:50. disrupts glucocorticoid receptor recruitment to chromatin and results in glu- 22. Maude SL, Dolai S, Delgado-Martin C, Vincent T, Robbins A, Selvanathan A, cocorticoid resistance in a B-lymphoblastic leukemia model. J Biol Chem 2014; et al. Efficacy of JAK/STAT pathway inhibition in murine xenograft models of 289:20502–15. early T-cell precursor (ETP) acute lymphoblastic leukemia. Blood 2015;125: 43. Li J, Catalina T, Swaroop A, Kulis M, Oyer J, Will C, Dupere-Richer D, et al. A 1759–67. Gain of Function Mutation in the NSD2 Histone Methyltransferase Drives 23. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina Glucocorticoid Resistance of Acute Lymphoblastic Leukemia; 2018 Nov. San sequence data. Bioinformatics 2014;30:2114–20. Diego, CA: ASH Publications; 2018. p. 653. 24. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: 44. Coulthard SA, McGarrity S, Sahota K, Berry P, Redfern CPF. Three faces of ultrafast universal RNA-seq aligner. Bioinformatics 2013;29:15–21. mercaptopurine cytotoxicity in vitro: methylation, nucleotide homeostasis, and 25. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing deoxythioguanosine in DNA. Drug Metab Dispos 2018;46:1191–9. genomic features. Bioinformatics 2010;26:841–2. 45. Coulthard SA, Redfern CP, Vikingsson S, Lindqvist-Appell M, Skoglund K, 26. Love MI, Huber W, Anders S. Moderated estimation of fold change and Jakobsen-Falk I, et al. Increased sensitivity to thiopurines in methylthioadeno- dispersion for RNA-seq data with DESeq2. Genome Biol 2014;15:550. sine phosphorylase-deleted cancers. Mol Cancer Ther 2011;10:495–504. 27. Chen EY, Tan CM, Kou Y, Duan Q, Wang Z, Meirelles GV, et al. Enrichr: 46. Jing D, Huang Y, Liu X, Sia KCS, Zhang JC, Tai X, et al. Lymphocyte-specific interactive and collaborative HTML5 gene list enrichment analysis tool. chromatin accessibility pre-determines glucocorticoid resistance in acute lym- BMC Bioinformatics 2013;14:128. phoblastic leukemia. Cancer Cell 2018;34:906–21. 28. Kuleshov MV, Jones MR, Rouillard AD, Fernandez NF, Duan Q, Wang Z, et al. 47. Martinez-Garcia E, Popovic R, Min DJ, Sweet SM, Thomas PM, Zamdborg L, Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. et al. The MMSET histone methyl transferase switches global histone methyl- Nucleic Acids Res 2016;44:W90–7. ation and alters gene expression in t(4;14) multiple myeloma cells. Blood 2011; 29. Xu S, Grullon S, Ge K, Peng W. Spatial clustering for identification of ChIP- 117:211–20. enriched regions (SICER) to map regions of histone methylation patterns in 48. Kuo AJ, Cheung P, Chen K, Zee BM, Kioi M, Lauring J, et al. NSD2 links embryonic stem cells. Methods Mol Biol 2014;1150:97–111. dimethylation of histone H3 at lysine 36 to oncogenic programming. Mol Cell 30. Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, et al. Model- 2011;44:609–20. based analysis of ChIP-Seq (MACS). Genome Biol 2008;9:R137. 49. Kim JY, Kee HJ, Choe NW, Kim SM, Eom GH, Baek HJ, et al. Multiple-myeloma- 31. Ross-Innes CS, Stark R, Teschendorff AE, Holmes KA, Ali HR, Dunning MJ, related WHSC1/MMSET isoform RE-IIBP is a histone methyltransferase with et al. Differential oestrogen receptor binding is associated with clinical outcome transcriptional repression activity. Mol Cell Biol 2008;28:2023–34. in breast cancer. Nature 2012;481:389–93. 50. Woo Park J, Kim KB, Kim JY, Chae YC, Jeong OS, Seo SB. RE-IIBP methylates 32. Yu G, Wang LG, He QY. ChIPseeker: an R/Bioconductor package for ChIP peak H3K79 and induces MEIS1-mediated apoptosis via H2BK120 ubiquitination by annotation, comparison and visualization. Bioinformatics 2015;31:2382–3. RNF20. Sci Rep 2015;5:12485.

AACRJournals.org Mol Cancer Res; 18(8) August 2020 1165

The NSD2 p.E1099K Mutation Is Enriched at Relapse and Confers Drug Resistance in a Cell Context−Dependent Manner in Pediatric Acute Lymphoblastic Leukemia

Joanna Pierro, Jason Saliba, Sonali Narang, et al.

Mol Cancer Res 2020;18:1153-1165. Published OnlineFirst April 24, 2020.

Updated version Access the most recent version of this article at: doi:10.1158/1541-7786.MCR-20-0092

Supplementary Access the most recent supplemental material at: Material http://mcr.aacrjournals.org/content/suppl/2020/04/24/1541-7786.MCR-20-0092.DC1

Cited articles This article cites 49 articles, 15 of which you can access for free at: http://mcr.aacrjournals.org/content/18/8/1153.full#ref-list-1

E-mail alerts Sign up to receive free email-alerts related to this article or journal.

Reprints and To order reprints of this article or to subscribe to the journal, contact the AACR Publications Department at Subscriptions [email protected].

Permissions To request permission to re-use all or part of this article, use this link http://mcr.aacrjournals.org/content/18/8/1153. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC) Rightslink site.