Purpose:

Treatment outcomes for childhood acute lymphoblastic leukemia (ALL) have improved steadily, but a significant proportion of patients still experience relapse due to drug resistance, which is partly explained by inherited and/or somatic genetic alternations. Recently, we and others have identified genetic variants in the ARID5B gene associated with susceptibility to ALL and also with relapse. In this study, we sought to characterize the molecular pathway by which ARID5B affects antileukemic drug response in patients with ALL.

Experimental Design:

We analyzed association of ARID5B expression in primary human ALL blasts with molecular subtypes and treatment outcome. Subsequent mechanistic studies were performed in ALL cell lines by manipulating ARID5B expression isogenically, in which we evaluated drug sensitivity, metabolism, and molecular signaling events.

Results:

ARID5B expression varied substantially by ALL subtype, with the highest level being observed in hyperdiploid ALL. Lower ARID5B expression at diagnosis was associated with the risk of ALL relapse, and further reduction was noted at ALL relapse. In isogenic ALL cell models in vitro, ARID5B knockdown led to resistance specific to antimetabolite drugs (i.e., 6-mercaptopurine and methotrexate), without significantly affecting sensitivity to other antileukemic agents. ARID5B downregulation significantly inhibited ALL cell proliferation and caused partial cell-cycle arrest. At the molecular level, the cell-cycle checkpoint regulator p21 (encoded by CDKN1A) was most consistently modulated by ARID5B, plausibly as its direct transcription regulation target.

Conclusions:

Our data indicate that ARID5B is an important molecular determinant of antimetabolite drug sensitivity in ALL, in part, through p21-mediated effects on cell-cycle progression.

Translational Relevance

The past decades have seen increasing survival in children with acute lymphoblastic leukemia (ALL), but relapse still occurs in approximately 20% of patients, primarily as a result of de novo or acquired drug resistance. ARID5B has been identified by us and others to be associated with susceptibility to ALL and treatment outcomes, although the biological mechanisms by which ARID5B contributes to normal hematopoiesis and leukemogenesis are largely unknown. We found that downregulation of ARID5B led to cell proliferation inhibition, cell-cycle arrest, and resistance to antimetabolite drugs (mercaptopurine and methotrexate). At the molecular level, CDKN1A is a plausible direct transcription regulation target of ARID5B and might be an important mediator of antimetabolite drug sensitivity in ALL. Taken together, our findings point to a new mechanism of drug resistance in ALL and may aid the development of new therapies for this group of patients.

Acute lymphoblastic leukemia (ALL) is the most common cancer in children and a leading cause of disease-related death in childhood (1, 2). Although aggressive and fatal if not treated, ALL responds remarkably well to cytotoxic agents [e.g., glucocorticoids, methotrexate, and 6-mercaptopurine (6-MP)] when compared with other hematologic malignancies and most solid tumors (3). Contemporary combination chemotherapy can induce complete remission in nearly all children with ALL, and more than 85% of patients achieve sustained disease-free survival after approximately 2 years of risk-adapted treatment. Even with the introduction of molecularly targeted agents (e.g., imatinib), conventional chemotherapeutics remain the mainstay of ALL therapy and have proved indispensable for long-term survival (4). However, the exact mechanisms by which these cytotoxic agents exert their antileukemic effects are not completely understood. For example, a significant proportion of patients with ALL respond to initial induction therapy but nevertheless experience relapse (5, 6), and many eventually succumb to their disease (7). The disparity between early response and long-term survival is a significant clinical issue, for which the underlying biology is largely unknown. Identifying genetic factors that drive inherent or acquired drug resistance would not only inform more rationally designed ALL treatment regimens but could also improve fundamental understanding of the biology of leukemia drug sensitivity.

Recent genomic profiling studies have discovered a number of novel pathways involved in leukemia pathogenesis and/or treatment response. For example, genome-wide association studies by us and others have identified ARID5B as one of the top loci associated with susceptibility to ALL in children (8–18). ARID5B variants were particularly overrepresented in patients with hyperdiploid ALL and also correlated with methotrexate metabolism in ALL cells (13, 15). We have subsequently identified additional variants at this locus that influence both ALL risk and treatment outcome (16, 17). ARID5B is a member of the ARID gene family characterized by a shared DNA-interacting motif (19–23). ARID genes are generally described as chromatin-remodeling factors (20, 24, 25), and somatic mutations in these genes have recently been described in multiple solid tumors (e.g., ARID1A; ref. 26), signifying their importance in tumorigenesis. There is a particular paucity of functional studies of ARID5B, although the limited data available suggest that it functions as a transcription factor (19, 22). In liver cells, ARID5B interacts with PHF2 as part of the chromatin-remodeling complex involved in histone methylation at genes related to chondrogenesis and glucogenesis (27). Arid5b-null mice showed signs of defective lymphocyte development, especially during the first 3 months after birth (19). However, the exact role of the ARID5B gene in hematologic malignancy is largely uncharacterized, particularly in the context of antileukemic drug responses.

In this study, we systematically evaluated the expression pattern of ARID5B in pediatric ALL and its relation leukemia relapse. In vitro manipulation of ARID5B expression directly influenced the sensitivity of ALL cells to 6-MP and methotrexate, plausibly via p21-mediated effects on the cell cycle. Collectively, these data point to ARID5B as a potential prognostic factor in ALL and novel mechanisms related to antileukemic drug resistance.

Patients and ALL genomics

The pattern of ARID5B gene expression in newly diagnosed ALL and its variation by molecular subtype were analyzed using two global gene expression profile datasets: 446 children from St. Jude Children's Research Hospital (GSE33315; ref. 28) and 106 patients from the German Cooperative Study Group for Childhood ALL and the Dutch Childhood Oncology Group (DCOG, GSE13351; ref. 29). These patients represent consecutively enrolled cases or were selected to represent the diversity of ALL subtypes (28, 29).

The association of ARID5B expression with ALL relapse was examined first in 59 patients with high-risk B-cell ALL treated on the COG 1961 protocol (GSE7440; ref. 30), of whom 28 experienced complete remission for at least 4 years and 31 experienced a bone marrow relapse within 3 years of diagnosis. In a second cohort of 49 patients with matched diagnosis-relapse ALL pairs (GSE28460; ref. 31), we compared the ARID5B expression in the diagnostic bone marrow with that in relapsed leukemia in the same individual. For these analyses, patients were included primarily on the basis of sample availability (30, 31).

This study was approved by the Institutional Review Board at St. Jude Children's Research Hospital. Informed consent was obtained from parents, guardians, or patients as appropriate. This study was conducted in accordance with the U.S. Common Rule and all applicable legal regulatory requirements.

ALL cell culture and ARID5B knockdown

ALL cell lines (Nalm6, SEM, and UOC-B1 cells) were grown in culture in RPMI1640 medium (GIBCO, Life Technologies) supplemented with 10% heat-inactivated FBS and 2 mmol/L l-glutamine, at 37°C in 5% CO2. Stable knockdown of ARID5B was performed using lentiviral short hairpin RNAs (shRNA) cloned on the pLKO backbone (Sigma-Aldrich): shRNAs TRCN0000151040, TRCN0000155854, TRCN0000151281, TRCN0000152535, and TRCN0000155468 were used to target ARID5B, with shRNA SHC016 as the nontarget control. Lentiviral particles containing shRNAs were produced by transient transfection of HEK293T cells with calcium phosphate (32). ALL cells were incubated with lentiviral supernatants for 48 hours and then subjected to selection with puromycin (2 μg/mL) for 3 days. Two-hundred transduced leukemia cells were plated in methylcellulose colony-selection medium (Stemcell Technologies) and incubated for 10–20 days to form single-cell colonies. Clones with shRNAs TRCN0000151040 [targeting the 3′ untranslated region (UTR)] and TRCN0000155854 (targeting the coding region) exhibited the strongest ARID5B knockdown and remained stable for at least 10 passages (Supplementary Fig. S1) and were thus selected for use in the subsequent experiments. For ARID5B reexpression, we ectopically expressed the ARID5B coding sequence in knockdown clones with shRNA TRCN0000151040 only (targeting the 3′ UTR), such that knockdown was restricted to endogenous AIRD5B with no effect on ectopic ARID5B expression. For inducible knockdown of ARID5B, shRNA TRCN0000151040 was cloned into the pLKO-Tet-On Vector (Sigma-Aldrich), and transduced ALL cells were exposed to doxycycline (2 μg/mL) for ARID5B downregulation.

The efficacy of ARID5B knockdown was determined by qPCR and Western blot analysis. qPCR assays were performed using the SYBR Reagent (Roche Diagnostics) and an Applied Biosystems 7900 Fast Real-Time PCR System (Applied Biosystems). The primer sequences for ARID5B were AAGGTTGCCATTGGTGAAGAGTGC and GACGGCGGGCTGTTATTGTTTCAT, and the human β-actin gene was used as internal control (primer sequences: GTTGTCGACGACGAGCG and GCACAGAGCCTCGCCTT). An anti-ARID5B antibody was purchased from Sigma-Aldrich (HPA015037) and used at a 1:1,000 dilution.

Orthogonally, we also performed ARID5B knockdown using the CRISPR-dCas9-KRAB system, following previously published CRISPRi method (33). Nalm6 cells were first lentivirally transduced with the dCas9-KRAB-Blast plasmid (#89567, Addgene) to establish stable expression of dCas9 fusion protein. Single-guide RNA (sgRNA) specifically targeting ARID5B promotor (TAGAAAGAGGAGCAGCGCCC) was then introduced by a second lentiviral transduction. After selection with blasticidin and puromycin, expression of ARID5B was determined by RT-PCR described above.

Nalm6, SEM, and UOC-B1 cells were obtained from the ATCC or the German Collection of Microorganisms and Cell Cultures in 2012, respectively. Cells were authenticated by short tandem repeat profiling regularly tested for Mycoplasma contamination by using MycoAlert Mycoplasma Detection Kit (Lonza #LT07-118). All cell line–based experiments were completed within 3 weeks after thawing.

Antileukemic drug sensitivity assay and drug metabolite measurement

Antileukemic drug sensitivity was tested in ALL cells, using the MTT assay (34). Briefly, cells were seeded in 96-well plates at a density of 2 × 104 cells/well then treated with different concentrations of drugs (i.e., prednisone, dexamethasone, vincristine, daunorubicin, asparaginase, methotrexate, or 6-MP) in triplicate. After 48 hours of incubation, cell viability was quantified using the MTT assay and the LC50 (concentration at which drugs kill 50% of leukemia cells) was estimated using the Prism Software (GraphPad Software).

Methotrexate and 6-MP metabolite assays were performed in accordance with our established high-performance liquid chromatography (HPLC)-based procedures (35, 36). Briefly, cells were plated at a density of 0.5 × 106 cells/mL and incubated at 37°C with methotrexate (1 μmol/L) in the presence of glycine (670 μmol/L), adenosine (37 μmol/L), and thymidine (41 μmol/L) for 24 hours. A total of 5 × 106 cells were washed twice with ice-cold PBS, resuspended in water, and boiled for 5 minutes. The cell pellets were then analyzed and quantified for polyglutamated methotrexate (MTXPG) by using HPLC (35). For 6-MP metabolites, cells were incubated with 6-MP (10 μmol/L) for 24 hours, after which lysates were prepared by sonication. Intracellular thioguanine nucleotides were dephosphorylated, and thioguanine ribonucleosides were measured by HPLC (36).

ALL cell proliferation and cell-cycle analysis

ALL cell proliferation (for Nalm6, SEM, and UOC-B1 cells) was monitored by daily viable cell counts during a 4-day culture period. Cell growth was also examined by using the BrdU assay: cells were pulsed with 10 μmol/L bromodeoxyuridine (BrdU) for 10 hours, then BrdU uptake was quantified using flow cytometry. Cell-cycle analysis was performed by using propidium iodide staining. For each experiment, at least 10,000 events per sample were recorded by flow cytometry and data analysis was performed using FlowJo software.

Western blot analysis was performed to quantify the levels of p53, p21, p27, cyclin D, cyclin E, CDK2, and phosphorylated Rb in ALL cells under various conditions, with GAPDH as the loading control. All antibodies were purchased from Cell Signaling Technology and were diluted at 1:1,000 or according to the manufacturer's instructions.

Gene expression profiling of ARID5B-knockdown ALL cells

Total RNA was extracted using an RNA Isolation Kit (Qiagen). cDNA was synthesized from mRNA with Superscript III Reverse Transcriptase (Invitrogen, Life Technologies). Microarray experiments were performed by the Hartwell Center at St. Jude Children's Research Hospital, using the Affymetrix Human GeneChip 1.0 ST Array (Thermo Fisher Scientific). The expression of each probe-tagged gene was determined by Affymetrix Expression Console software, and pathway analyses were performed using the Gene set enrichment analysis algorithm (37).

ARID5B binding to the CDKN1A cis-regulatory element

ARID5B chromatin immunoprecipitation (ChIP) assay was performed using the ChIP-IT High Sensitivity Kit (53040; Active Motif) according to the manufacturer's instructions. A total of 2 × 107 Nalm6 cells were fixed with formaldehyde, and sonicated chromatin was incubated with anti-ARID5B antibody (NBP1-83622; Novus Biologicals) or anti-IgG antibody (3900S; Cell Signaling Technology) overnight at 4°C. This was followed by immunoprecipitation with Protein G agarose beads for 3 hours at 4°C. Precipitated DNA was analyzed by qRT-PCR with the following primers: CDKN1A forward primer 1: CACACTGCTCTATGCCAGATAC, CDKN1A reverse primer 1: CCTTAACAAGTCGGCCTGAA; CDKN1A forward primer 2: GCCTGGCTTTGAAGGTTATTG, CDKN1A reverse primer 2: AGTCATTGCTTTCCCTCAACTA; and CDKN1A forward primer 3: GCACTCATGGATTCTCTCCTTTA, CDKN1A reverse primer 3: TGATCCCAGGCAAGTTGTTTA.

In addition, we also performed CRISPRi experiments to specifically disrupt the purported interaction of ARID5B with the CDKN1A cis-regulatory element (33). Briefly, Nalm6 cells with stable dCas9-KRAB expression were lentivirally infected with a sgRNA plasmid (TTTAATCACCTTGGCCCCCG). CDKN1A expression was then quantified by RT-PCR (primer sequences: TGTCCGTCAGAACCCATGC and AAAGTCGAAGTTCCATCGCTC).

Statistical analysis

Variation in ARID5B expression across subtypes was significant in both cohorts (St. Jude and DCOG), as evaluated using the ANOVA test (38). ARID5B expression association with relapse in the COG P1961 cohort was tested using the logistic regression model, after adjusting covariables as needed. Analysis of ARID5B level in diagnosis-relapse ALL pairs was performed using paired t test.

ARID5B expression in ALL and its association with treatment outcome

In an unselected cohort of 446 children with newly diagnosed ALL from St. Jude Children's Research Hospital, ARID5B expression was highly variable by molecular subtype, with the highest level observed in patients with a hyperdiploid karyotype and the lowest level in patients with T-cell ALL (T-ALL, Fig. 1A; ref. 28). This subtype-dependent ARID5B expression pattern was also confirmed in an independent cohort of 106 pediatric patients with ALL from the DCOG (Fig. 1B; ref. 29). ARID5B expression differed by age at leukemia diagnosis (P = 0.001 for comparing age groups <10 years vs. ≥10 years; P = 5.5 × 10−6 for age treated as a continuous variable; ARID5B expression was higher in younger patients) and by gender (P = 0.02; ARID5B expression was higher in female patients), but was not related to genetic ancestry (P > 0.05). Of interest, the frequency of germline ALL risk variant in ARID5B also varies greatly by subtype, highest in the hyperdiploid subtype and least common in T-ALL (15, 1739).

Figure 1.

ARID5B expression varies significantly by ALL subtype. Gene expression was estimated by Affymetrix U133A (for the St. Jude cohort; A) or U133-plus 2.0 (for the Dutch cohort; ref. 25; B) chips. ARID5B expression was consistently highest in hyperdiploid B-ALL subtypes and lowest in T-ALL than in other subtypes in both cohorts. P values were estimated by using the ANOVA test.

Figure 1.

ARID5B expression varies significantly by ALL subtype. Gene expression was estimated by Affymetrix U133A (for the St. Jude cohort; A) or U133-plus 2.0 (for the Dutch cohort; ref. 25; B) chips. ARID5B expression was consistently highest in hyperdiploid B-ALL subtypes and lowest in T-ALL than in other subtypes in both cohorts. P values were estimated by using the ANOVA test.

Close modal

To examine the relation between ARID5B and ALL relapse, we first evaluated its expression in diagnostic leukemia blasts in 59 patients on the Children's Oncology Group CCG1961 trial who had different treatment outcomes. The ARID5B transcript level in ALL cells was significantly lower in patients who experienced relapse than in those who remained in complete remission (P = 0.01), and this difference was significant even after adjusting for ALL molecular subtype, age at diagnosis, and sex (P = 0.04; Fig. 2A). Furthermore, in a cohort of 49 patients who experienced ALL relapse, we observed significant downregulation of ARID5B transcription at disease recurrence compared with the levels in matched ALL blasts at diagnosis (P = 0.0009; Fig. 2B). Taken together, these results show that ARID5B expression varied by ALL subtypes and was associated with relapse.

Figure 2.

Low ARID5B expression is related to ALL relapse. A,ARID5B expression was significantly lower (P = 0.01 by logistic regression test) in diagnostic leukemia cells of patients who experienced relapse than in cells from relapse-free patients enrolled on the CCG1961 protocol (26). B,ARID5B expression levels were significantly decreased (P = 0.0009 by paired t test) in leukemia cells at relapse compared with matched diagnostic leukemia cells from the same individual.

Figure 2.

Low ARID5B expression is related to ALL relapse. A,ARID5B expression was significantly lower (P = 0.01 by logistic regression test) in diagnostic leukemia cells of patients who experienced relapse than in cells from relapse-free patients enrolled on the CCG1961 protocol (26). B,ARID5B expression levels were significantly decreased (P = 0.0009 by paired t test) in leukemia cells at relapse compared with matched diagnostic leukemia cells from the same individual.

Close modal

ARID5B influences ALL sensitivity to antimetabolite drugs

Given the observed downregulation of ARID5B expression at relapse, we hypothesized that loss of ARID5B may render ALL cells resistant to chemotherapeutic agents. To determine the effects of ARID5B on sensitivity to specific antileukemic drugs, we first established stable knockdown of this gene in a panel of human ALL cell lines, with which we tested the dose-dependent cytotoxicity of antimetabolite drugs (6-MP and methotrexate), glucocorticoids (prednisone and dexamethasone), daunorubicin, vincristine, and asparaginase (Fig. 3; Supplementary Table S1). In Nalm6 cells (DUX4 rearranged with ERG alternation), a 60% downregulation of ARID5B expression led to 19.4- and 30.2-fold increases in the LC50 of methotrexate and 6-MP, respectively (Fig. 3A), with only modest effects on the sensitivity to other chemotherapeutic agents (Supplementary Table S1). In a series of Nalm6 clones with varying degrees of ARID5B knockdown, we observed a gradual increase in drug resistance as ARID5B expression decreased, with an inverse correlation between ARID5B expression and the LC50s of methotrexate and 6-MP (r2 = 0.5 and 0.64, respectively; Supplementary Fig. S2). Furthermore, the resistance of ARID5B-knockdown cells to methotrexate and 6-MP was reversed by reexpressing ARID5B (Supplementary Fig. S3), indicating that the effects on drug sensitivity were specifically driven by ARID5B. Both methotrexate and 6-MP needs to be activated intracellularly to exert cytotoxic effects. Therefore, we also examined the effects of ARID5B on drug metabolism. Upon ARID5B knockdown, the levels of methotrexate and 6-MP active metabolites (MTXPG and thioguanine nucleotides, respectively) were reduced significantly (Supplementary Fig. S4), consistent with ALL cell resistance to these two drugs. Similar patterns of drug sensitivity and resistance were observed when ARID5B was knocked down in two other ALL cell lines (Fig. 3B and C), namely SEM (MLL-rearranged) and UOC-B1 (TCF3-HLF fusion) cells. These results suggest that ARID5B selectively regulates antimetabolite drug sensitivity in ALL, with lower expression of this gene directly linked to resistance to methotrexate and 6-MP. The selective effects of ARID5B on 6-MP and methotrexate sensitivity are highly relevant because prolonged exposure to these antimetabolite drugs is indispensable to the cure of ALL, and 6-MP resistance in particular is a major cause of ALL relapse (40, 41).

Figure 3.

ARID5B and antimetabolite drug sensitivity in ALL cells. A–C, Stable knockdown of ARID5B was established using shRNA in Nalm6, SEM, and UOC-B1 cells, and its expression level was determined by Western blot analysis (top). GAPDH was used as a loading control. Drug sensitivity was determined using the MTT assay for methotrexate (MTX, middle) and 6-MP (bottom). Each experiment was performed at least three times in triplicate.

Figure 3.

ARID5B and antimetabolite drug sensitivity in ALL cells. A–C, Stable knockdown of ARID5B was established using shRNA in Nalm6, SEM, and UOC-B1 cells, and its expression level was determined by Western blot analysis (top). GAPDH was used as a loading control. Drug sensitivity was determined using the MTT assay for methotrexate (MTX, middle) and 6-MP (bottom). Each experiment was performed at least three times in triplicate.

Close modal

To further validate these findings, we also performed ARID5B knockdown in Nalm6 cells using the CRISPR-dCas9 system (33), in which gene transcription was inhibited by sgRNA-mediated targeting of suppressor protein KRAB to the ARID5B promoter. Again, resistance to antimetabolite drugs was observed in ALL cells with ARID5B downregulation (Supplementary Fig. S5).

ARID5B regulates the cell cycle and p21 signaling

Because the cytotoxic effects of methotrexate and 6-MP are highly dependent on cell proliferation, we postulated that ARID5B expression affected cell cycle. Across three ALL cell lines, cell growth was significantly impeded upon ARID5B knockdown (Fig. 4, top). The decrease of cell growth was also confirmed by the BrdU-uptake assay (Supplementary Fig. S6). When ARID5B expression was repressed, we observed partial but consistent blockade of cell cycling, with a significant increase in cells in the G0–G1-phase and a concurrent reduction of the S and G2–M population (Fig. 4, middle). At the molecular level, the cellular machinery involved in cell-cycle checkpoint control was affected in ARID5B-knockdown cells, particularly those related to G1/S transition (Fig. 4, bottom). For example in Nalm6 cells, ARID5B knockdown led to a dramatic upregulation of p21 and had a modest effect on p27; both of these proteins are master regulators of cyclin/CDKs during G1/S transition. Cyclin D and E levels were only modestly affected, but a reduction in CDK2 and phosphorylated Rb was readily detectable, consistent with the partial blockade of S-phase entry. The profound change in p21 and phosphorylated Rb levels following ARID5B knockdown was also confirmed in SEM and UOC-B1 cells.

Figure 4.

ARID5B as a regulator of cell-cycle progression. A–C, The proliferation of ALL cells was monitored by counting viable cells daily (top), and the cell-cycle distribution was determined by propidium iodide staining and flow cytometry (middle). Compared with nontarget control cells, ARID5B-knockdown (KD) cells had higher percentages of cells in the G0–G1-phases but lower percentages in the S and G2–M-phases. At the molecular level, ARID5B knockdown led to consistent upregulation of p53 and p21 and downregulation of phosphorylated Rb in ALL cell lines (bottom). Experiments were performed in Nalm6, SEM, and UOC-B1 cells (A, B, and C, respectively).

Figure 4.

ARID5B as a regulator of cell-cycle progression. A–C, The proliferation of ALL cells was monitored by counting viable cells daily (top), and the cell-cycle distribution was determined by propidium iodide staining and flow cytometry (middle). Compared with nontarget control cells, ARID5B-knockdown (KD) cells had higher percentages of cells in the G0–G1-phases but lower percentages in the S and G2–M-phases. At the molecular level, ARID5B knockdown led to consistent upregulation of p53 and p21 and downregulation of phosphorylated Rb in ALL cell lines (bottom). Experiments were performed in Nalm6, SEM, and UOC-B1 cells (A, B, and C, respectively).

Close modal

To test the hypothesis that p21 was a direct transcription target of ARID5B, we established cell line models with inducible ARID5B knockdown. Upon the addition of doxycycline, the ARID5B level started to decline within 7 hours, at which time p21 expression increased slightly. By 24 hours, ARID5B was knocked down by 58% and p21 was upregulated 2.4-fold, as compared with the levels at time zero. Between 24 and 48 hours, the level of p21 continued to increase and that of ARID5B remained low (Fig. 5A). When doxycycline was removed from the culture medium, ARID5B expression recovered within 24 hours and, consequently, the p21 level largely returned to that seen in the parental cells (Fig. 5B). Subcellularly, ARID5B was restricted to the nuclei of ALL cells, but its downregulation led to an increase in both nuclear and cytoplasmic p21 (Fig. 5C). When ALL cells were treated with increasing concentrations of methotrexate or 6-MP, the p21 level decreased gradually and became undetectable once the cells had entered apoptosis (as indicated by the cleavage of PARP; Supplementary Fig. S7). Therefore, p21 upregulation (as seen in ARID5B-knockdown cells) might directly antagonize methotrexate/6-MP–induced apoptosis in ALL.

Figure 5.

ARID5B is a direct transcriptional regulator of p21. To identify whether p21 was a transcription regulation target of ARID5B, we established doxycycline (dox)-dependent inducible knockdown of ARID5B in Nalm6 cells. The levels of ARID5B and p21 at different time points after doxycycline treatment were determined by Western blot analysis. A, The ARID5B level decreased steadily as a function of time, with a concomitant increase in p21. B, The removal of doxycycline led to the recovery of ARID5B expression and consequently a decrease in p21. C, Both nuclear and cytoplasmic p21 were affected by ARID5B knockdown. LaminB and β-actin were used as loading controls for nuclear and cytoplasmic proteins, respectively. Direct binding of ARID5B to a potential regulatory element 25 kb upstream of CDKN1A was confirmed by ARID5B ChIP-qPCR in Nalm6 cells. D, The ChIP assays were performed three times. The results are shown as the percentage of the input. E, To directly examine the effects of ARID5B binding, Nalm6 cells were transduced with CRISPR/dCas9-KRAB (CRISPRi) with sgRNA targeting ARID5B-binding site. CDKN1A expression was subsequently determined by RT-PCR. *, P < 0.05 by t test.

Figure 5.

ARID5B is a direct transcriptional regulator of p21. To identify whether p21 was a transcription regulation target of ARID5B, we established doxycycline (dox)-dependent inducible knockdown of ARID5B in Nalm6 cells. The levels of ARID5B and p21 at different time points after doxycycline treatment were determined by Western blot analysis. A, The ARID5B level decreased steadily as a function of time, with a concomitant increase in p21. B, The removal of doxycycline led to the recovery of ARID5B expression and consequently a decrease in p21. C, Both nuclear and cytoplasmic p21 were affected by ARID5B knockdown. LaminB and β-actin were used as loading controls for nuclear and cytoplasmic proteins, respectively. Direct binding of ARID5B to a potential regulatory element 25 kb upstream of CDKN1A was confirmed by ARID5B ChIP-qPCR in Nalm6 cells. D, The ChIP assays were performed three times. The results are shown as the percentage of the input. E, To directly examine the effects of ARID5B binding, Nalm6 cells were transduced with CRISPR/dCas9-KRAB (CRISPRi) with sgRNA targeting ARID5B-binding site. CDKN1A expression was subsequently determined by RT-PCR. *, P < 0.05 by t test.

Close modal

Querying the CDKN1A locus for an ARID motif (42), we identified a potential ARID5B binding site 25 kb distal to the transcription start site of CDKN1A. Interestingly, this locus overlaps with an open chromatin segment in a number of hematopoietic cells (lymphoid-primed multipotential progenitors, granulocyte–monocyte progenitors, monocytes, and B cells) on the basis of ATAC-seq signal (43) and histone modification marks (H3K27Ac, H3K4me1, and H3K4me3; Supplementary Fig. S8). Using ARID5B ChIP-qPCR, we experimentally verified ARID5B binding to this putative cis-regulatory element (Fig. 5D). More importantly, targeting dCas9-KRAB to interrupt ARID5B binding at this site, using the CRISPRi method (33), resulted in a 1.58-fold change in CDKN1A expression (Fig. 5E). Collectively, our results suggest that ARID5B is a putative transcription suppressor of CDKN1A.

ARID5B was first linked to ALL in a series of reports in which germline intronic variants of the ARID5B gene were identified as modifying the risk of developing leukemia (13, 15). Despite repeated validation in independent studies across diverse populations (8, 9, 11, 12, 14, 16–18, 44–46), the exact effects of these genetic polymorphisms on ARID5B activity and more importantly the biological processes by which this protein regulates normal and malignant hematopoiesis remain largely unknown. Our current study, therefore, represents one of the first attempts to characterize ARID5B signaling in ALL. ARID5B appeared to be abundantly expressed in ALLs, with the exception of T-ALL. Its particularly elevated transcription in hyperdiploid ALL is consistent with the observation that children with ARID5B risk alleles were most likely to develop this specific subtype of ALL.

When we downregulated ARID5B in a panel of ALL cells of diverse subtypes, there was a consistent decrease in proliferation, partly due to cell-cycle blockade at the G1/S checkpoint. This is relevant because multiple therapeutic agents for ALL (e.g., methotrexate and 6-MP) target DNA synthesis and nucleotide metabolism with cell-cycle–dependent cytotoxic effects. For example, reduced cell cycling would decrease the incorporation of 6-MP metabolites into DNA, leading to lower levels of DNA damage and subsequent apoptosis (47). Indeed, it has long been postulated that the remarkable response of ALL to methotrexate/6-MP–based therapy is at least partly due to the rapid cycling of ALL cells. Because prolonged exposure to these chemotherapeutic agents is essential for long-term remission in children with ALL, genetic factors modulating their sensitivity are likely to influence ALL relapse, as seen in the case of ARID5B. Interestingly, low expression of ARID5B was associated with high rates of relapse, and ARID5B expression was also downregulated at relapse, suggesting that ARID5B suppression may confer inherent drug resistance at ALL diagnosis and may also be responsible for acquired drug resistance at ALL relapse. It should be noted, however, that the exact degree to which ARID5B contributes to methotrexate and 6-MP resistance in ALL remains unclear, and it is plausible that this gene represents a component of a larger network or pathway of genes governing ALL sensitivity to the antimetabolite drugs.

Our results also shed important light on possible functions of ARID5B in hematopoietic tissue, particularly the effects of this gene on cell-cycle regulation. Although the expression of several cell cycle and checkpoint genes changed significantly upon ARID5B knockdown, the most consistent alteration across ALL cell lines of different subtypes was the upregulation of p21. As a master regulator of both G1/S and G2–M checkpoints, p21 expression is itself tightly regulated via p53-dependent mechanisms and also via pathways that do not involve p53 (48–50). Upregulation of p21 occurs rapidly upon exposure to chemotherapeutics as a means of delaying the initiation of apoptosis, and it may be involved in the decision between cell-cycle arrest and apoptosis (51). Inducible ARID5B knockdown in ALL cell lines led to p21 suppression in a time-dependent fashion within 24 hours, suggesting a possible direct link. It is, therefore, reasonable to hypothesize that the downregulation of ARID5B activates p21 expression, which in turn blocks cyclin and CDK signaling and eventually triggers cell-cycle arrest. There is some evidence that the AT-rich interactive (ARID) domain in ARID5B possesses sequence-specific DNA-binding affinity and can interact with and guide epigenetic regulators (e.g., PHF2; ref. 19, 21–23, 27). Combining motif analysis, histone modification, ATAC-seq data, and ChIP-qPCR, we indeed identified an ARID5B binding site within a putative cis-regulatory element upstream of CDKN1A (Fig. 5D; Supplementary Fig. S8), and the disruption of which altered CDKN1A transcription.

It is entirely plausible that p21 is one of many ARID5B target genes and thus is only partially responsible for the effects of ARID5B knockdown on cell cycle and drug resistance. In fact, our global expression profiling studies in ALL cell lines identified other genes that were differentially expressed upon ARID5B knockdown, with an enrichment of components of the p53 signaling pathway (Supplementary Fig. S9). These results provide interesting leads for further mechanistic studies in the future. Leung and colleagues recently reported that ARID5B is a direct target of TAL1 and functions as an activator of MYC transcription in T-ALL (52). Interestingly, ARID5B knockdown also led to significant delay in cell growth in T-ALL, but this was primarily the result of increased apoptosis, with only modest effects on the cell-cycle distribution.

There is still much to learn about the functions of ARID5B in blood cell development and diseases, especially the functional consequences of disease-related genetic variants in this gene. In addition to ALL, ARID5B variants have also been implicated in genetic susceptibility to autoimmune diseases (e.g., lupus, rheumatoid arthritis, type 2 diabetes, and Graves' disease; ref. 53–56). Elucidating ARID5B biology may therefore have significance in improving our understanding of immune regulation in general.

No potential conflicts of interest were disclosed.

Conception and design: H. Xu, S. E, J.J. Yang

Development of methodology: X. Zhao, S. E, H. Zhang

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): X. Zhao, D. Bhojwani, S. E, H. Zhang, N.L. Seibel, W.L. Carroll, W.E. Evans

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): H. Xu, X. Zhao, D. Bhojwani, S. E, W. Yang, C. Li, W.E. Evans, J.J. Yang

Writing, review, and/or revision of the manuscript: H. Xu, X. Zhao, D. Bhojwani, C. Goodings, W.L. Carroll, W.E. Evans, J.J. Yang

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): D. Bhojwani

Study supervision: J.J. Yang

The authors thank the patients and parents who participated in the clinical trials included in this study. The authors thank Keith A. Laycock, PhD, ELS, for scientific editing of the article. This work was supported by the NIH (GM118578, CA021765, and GM115279), the American Lebanese Syrian Associated Charities of St. Jude Children's Research Hospital, and the Specialized Center of Research of Leukemia and Lymphoma Society (7010-14).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Pui
CH
,
Robison
LL
,
Look
AT
. 
Acute lymphoblastic leukaemia
.
Lancet
2008
;
371
:
1030
43
.
2.
Greaves
M
. 
Infection, immune responses and the aetiology of childhood leukaemia
.
Nat Rev Cancer
2006
;
6
:
193
203
.
3.
Pui
CH
,
Evans
WE
. 
Drug therapy - treatment of acute lymphoblastic leukemia
.
New Engl J Med
2006
;
354
:
166
78
.
4.
Schultz
KR
,
Bowman
WP
,
Aledo
A
,
Slayton
WB
,
Sather
H
,
Devidas
M
, et al
Improved early event-free survival with imatinib in Philadelphia chromosome-positive acute lymphoblastic leukemia: a Children's Oncology Group study
.
J Clin Oncol
2009
;
27
:
5175
81
.
5.
Borowitz
MJ
,
Wood
BL
,
Devidas
M
,
Loh
ML
,
Raetz
EA
,
Salzer
WL
, et al
Prognostic significance of minimal residual disease in high risk B-ALL: a report from Children's Oncology Group study AALL0232
.
Blood
2015
;
126
:
964
71
.
6.
Borowitz
MJ
,
Devidas
M
,
Hunger
SP
,
Bowman
WP
,
Carroll
AJ
,
Carroll
WL
, et al
Clinical significance of minimal residual disease in childhood acute lymphoblastic leukemia and its relationship to other prognostic factors: a Children's Oncology Group study
.
Blood
2008
;
111
:
5477
85
.
7.
Nguyen
K
,
Devidas
M
,
Cheng
SC
,
La
M
,
Raetz
EA
,
Carroll
WL
, et al
Factors influencing survival after relapse from acute lymphoblastic leukemia: a Children's Oncology Group study
.
Leukemia
2008
;
22
:
2142
50
.
8.
Bhandari
P
,
Ahmad
F
,
Mandava
S
,
Das
BR
. 
Association of genetic variants in ARID5B, IKZF1 and CEBPE with risk of childhood de novo B-Lineage acute lymphoblastic leukemia in India
.
Asian Pac J Cancer Prev
2016
;
17
:
3989
95
.
9.
Chokkalingam
AP
,
Hsu
LI
,
Metayer
C
,
Hansen
HM
,
Month
SR
,
Barcellos
LF
, et al
Genetic variants in ARID5B and CEBPE are childhood ALL susceptibility loci in Hispanics
.
Cancer Cause Control
2013
;
24
:
1789
95
.
10.
Gharbi
H
,
Ben Hassine
I
,
Soltani
I
,
Safra
I
,
Ouerhani
S
,
Othmen
HBH
, et al
Association of genetic variation in IKZF1, ARID5B, CDKN2A, and CEBPE with the risk of acute lymphoblastic leukemia in Tunisian children and their contribution to racial differences in leukemia incidence
.
Pediatr Hematol Oncol
2016
;
33
:
157
67
.
11.
Hsu
LI
,
Chokkalingam
AP
,
Briggs
FB
,
Walsh
K
,
Crouse
V
,
Fu
C
, et al
Association of genetic variation in IKZF1, ARID5B, and CEBPE and surrogates for early-life infections with the risk of acute lymphoblastic leukemia in Hispanic children
.
Cancer Cause Control
2015
;
26
:
609
19
.
12.
Migliorini
G
,
Fiege
B
,
Hosking
FJ
,
Ma
Y
,
Kumar
R
,
Sherborne
AL
, et al
Variation at 10p12.2 and 10p14 influences risk of childhood B-cell acute lymphoblastic leukemia and phenotype
.
Blood
2013
;
122
:
3298
307
.
13.
Papaemmanuil
E
,
Hosking
FJ
,
Vijayakrishnan
J
,
Price
A
,
Olver
B
,
Sheridan
E
, et al
Loci on 7p12.2, 10q21.2 and 14q11.2 are associated with risk of childhood acute lymphoblastic leukemia
.
Nat Genet
2009
;
41
:
1006
10
.
14.
Prasad
RB
,
Hosking
FJ
,
Vijayakrishnan
J
,
Papaemmanuil
E
,
Koehler
R
,
Greaves
M
, et al
Verification of the susceptibility loci on 7p12.2, 10q21.2, and 14q11.2 in precursor B-cell acute lymphoblastic leukemia of childhood
.
Blood
2010
;
115
:
1765
7
.
15.
Trevino
LR
,
Yang
W
,
French
D
,
Hunger
SP
,
Carroll
WL
,
Devidas
M
, et al
Germline genomic variants associated with childhood acute lymphoblastic leukemia
.
Nat Genet
2009
;
41
:
1001
5
.
16.
Xu
H
,
Cheng
C
,
Devidas
M
,
Pei
DQ
,
Fan
YP
,
Yang
WJ
, et al
ARID5B genetic polymorphisms contribute to racial disparities in the incidence and treatment outcome of childhood acute lymphoblastic leukemia
.
J Clin Oncol
2012
;
30
:
751
7
.
17.
Xu
H
,
Yang
WJ
,
Perez-Andreu
V
,
Devidas
M
,
Fan
YP
,
Cheng
C
, et al
Novel susceptibility variants at 10p12.31–12.2 for childhood acute lymphoblastic leukemia in ethnically diverse populations
.
J Natl Cancer Inst
2013
;
105
:
733
42
.
18.
Yang
W
,
Trevino
LR
,
Yang
JJ
,
Scheet
P
,
Pui
CH
,
Evans
WE
, et al
ARID5B SNP rs10821936 is associated with risk of childhood acute lymphoblastic leukemia in blacks and contributes to racial differences in leukemia incidence
.
Leukemia
2010
;
24
:
894
6
.
19.
Lahoud
MH
,
Ristevski
S
,
Venter
DJ
,
Jermiin
LS
,
Bertoncello
I
,
Zavarsek
S
, et al
Gene targeting of Desrt, a novel ARID class DNA-binding protein, causes growth retardation and abnormal development of reproductive organs
.
Genome Res
2001
;
11
:
1327
34
.
20.
Lin
C
,
Song
W
,
Bi
X
,
Zhao
J
,
Huang
Z
,
Li
Z
, et al
Recent advances in the ARID family: focusing on roles in human cancer
.
Onco Targets Ther
2014
;
7
:
315
24
.
21.
Patsialou
A
,
Wilsker
D
,
Moran
E
. 
DNA-binding properties of ARID family proteins
.
Nucleic Acids Res
2005
;
33
:
66
80
.
22.
Whitson
RH
,
Huang
T
,
Itakura
K
. 
The novel Mrf-2 DNA-binding domain recognizes a five-base core sequence through major and minor-groove contacts
.
Biochem Biophys Res Commun
1999
;
258
:
326
31
.
23.
Wilsker
D
,
Patsialou
A
,
Dallas
PB
,
Moran
E
. 
ARID proteins: a diverse family of DNA binding proteins implicated in the control of cell growth, differentiation, and development
.
Cell Growth Differ
2002
;
13
:
95
106
.
24.
Guan
B
,
Wang
TL
,
Shih
IeM
. 
ARID1A, a factor that promotes formation of SWI/SNF-mediated chromatin remodeling, is a tumor suppressor in gynecologic cancers
.
Cancer Res
2011
;
71
:
6718
27
.
25.
Wang
X
,
Nagl
NG
,
Wilsker
D
,
Van Scoy
M
,
Pacchione
S
,
Yaciuk
P
, et al
Two related ARID family proteins are alternative subunits of human SWI/SNF complexes
.
Biochem J
2004
;
383
:
319
25
.
26.
Bitler
BG
,
Fatkhutdinov
N
,
Zhang
R
. 
Potential therapeutic targets in ARID1A-mutated cancers
.
Expert Opin Ther Targets
2015
;
19
:
1419
22
.
27.
Baba
A
,
Ohtake
F
,
Okuno
Y
,
Yokota
K
,
Okada
M
,
Imai
Y
, et al
PKA-dependent regulation of the histone lysine demethylase complex PHF2-ARID5B
.
Nat Cell Biol
2011
;
13
:
668
75
.
28.
Zhang
JH
,
Ding
L
,
Holmfeldt
L
,
Wu
G
,
Heatley
SL
,
Payne-Turner
D
, et al
The genetic basis of early T-cell precursor acute lymphoblastic leukaemia
.
Nature
2012
;
481
:
157
63
.
29.
Den Boer
ML
,
van Slegtenhorst
M
,
De Menezes
RX
,
Cheok
MH
,
Buijs-Gladdines
JG
,
Peters
ST
, et al
A subtype of childhood acute lymphoblastic leukaemia with poor treatment outcome: a genome-wide classification study
.
Lancet Oncol
2009
;
10
:
125
34
.
30.
Bhojwani
D
,
Kang
H
,
Menezes
RX
,
Yang
W
,
Sather
H
,
Moskowitz
NP
, et al
Gene expression signatures predictive of early response and outcome in high-risk childhood acute lymphoblastic leukemia: a children's oncology group study [corrected]
.
J Clin Oncol
2008
;
26
:
4376
84
.
31.
Hogan
LE
,
Meyer
JA
,
Yang
J
,
Wang
J
,
Wong
N
,
Yang
W
, et al
Integrated genomic analysis of relapsed childhood acute lymphoblastic leukemia reveals therapeutic strategies
.
Blood
2011
;
118
:
5218
26
.
32.
Xu
H
,
Zhang
H
,
Yang
WJ
,
Yadav
R
,
Morrison
AC
,
Qian
MX
, et al
Inherited coding variants at the CDKN2A locus influence susceptibility to acute lymphoblastic leukaemia in children
.
Nat Commun
2015
;
6
:
7553
.
33.
Gilbert
LA
,
Larson
MH
,
Morsut
L
,
Liu
ZR
,
Brar
GA
,
Torres
SE
, et al
CRISPR-mediated modular RNA-guided regulation of transcription in eukaryotes
.
Cell
2013
;
154
:
442
51
.
34.
Evans
WE
,
Relling
MV
,
Rodman
JH
,
Crom
WR
,
Boyett
JM
,
Pui
CH
. 
Conventional compared with individualized chemotherapy for childhood acute lymphoblastic leukemia
.
New Engl J Med
1998
;
338
:
499
505
.
35.
French
D
,
Yang
W
,
Cheng
C
,
Raimondi
SC
,
Mullighan
CG
,
Downing
JR
, et al
Acquired variation outweighs inherited variation in whole genome analysis of methotrexate polyglutamate accumulation in leukemia
.
Blood
2009
;
113
:
4512
20
.
36.
Dervieux
T
,
Chu
Y
,
Su
Y
,
Pui
CH
,
Evans
WE
,
Relling
MV
. 
HPLC determination of thiopurine nucleosides and nucleotides in vivo in lymphoblasts following mercaptopurine therapy
.
Clin Chem
2002
;
48
:
61
8
.
37.
Subramanian
A
,
Tamayo
P
,
Mootha
VK
,
Mukherjee
S
,
Ebert
BL
,
Gillette
MA
, et al
Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles
.
Proc Natl Acad Sci U S A
2005
;
102
:
15545
50
.
38.
R Core Team
.
R: a language and environment for statistical computing
; 
2013
.
Available from:
https://www.gbif.org/tool/81287/r-a-language-and-environment-for-statistical-computing.
39.
Perez-Andreu
V
,
Roberts
KG
,
Xu
H
,
Smith
C
,
Zhang
H
,
Yang
W
, et al
A genome-wide association study of susceptibility to acute lymphoblastic leukemia in adolescents and young adults
.
Blood
2015
;
125
:
680
6
.
40.
Li
BS
,
Li
H
,
Bai
Y
,
Kirschner-Schwabe
R
,
Yang
JJ
,
Chen
Y
, et al
Negative feedback-defective PRPS1 mutants drive thiopurine resistance in relapsed childhood ALL
.
Nat Med
2015
;
21
:
563
71
.
41.
Meyer
JA
,
Wang
JH
,
Hogan
LE
,
Yang
JJ
,
Dandekar
S
,
Patel
JP
, et al
Relapse-specific mutations in NT5C2 in childhood acute lymphoblastic leukemia
.
Nat Genet
2013
;
45
:
290
4
.
42.
Bailey
TL
,
Gribskov
M
. 
Combining evidence using p-values: application to sequence homology searches
.
Bioinformatics
1998
;
14
:
48
54
.
43.
Corces
MR
,
Buenrostro
JD
,
Wu
B
,
Greenside
PG
,
Chan
SM
,
Koenig
JL
, et al
Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution
.
Nat Genet
2016
;
48
:
1193
203
.
44.
Ross
JA
,
Linabery
AM
,
Blommer
CN
,
Langer
EK
,
Spector
LG
,
Hilden
JM
, et al
Genetic variants modify susceptibility to leukemia in infants: a Children's Oncology Group report
.
Pediatr Blood Cancer
2013
;
60
:
31
4
.
45.
Vijayakrishnan
J
,
Kumar
R
,
Henrion
MY
,
Moorman
AV
,
Rachakonda
PS
,
Hosen
I
, et al
A genome-wide association study identifies risk loci for childhood acute lymphoblastic leukemia at 10q26.13 and 12q23.1
.
Leukemia
2017
;
31
:
573
9
.
46.
Healy
J
,
Richer
C
,
Bourgey
M
,
Kritikou
EA
,
Sinnett
D
. 
Replication analysis confirms the association of ARID5B with childhood B-cell acute lymphoblastic leukemia
.
Haematologica
2010
;
95
:
1608
11
.
47.
Panetta
JC
,
Evans
WE
,
Cheok
MH
. 
Mechanistic mathematical modelling of mercaptopurine effects on cell cycle of human acute lymphoblastic leukaemia cells
.
Br J Cancer
2006
;
94
:
93
100
.
48.
Aliouat-Denis
CM
,
Dendouga
N
,
Van den Wyngaert
I
,
Goehlmann
H
,
Steller
U
,
van de Weyer
I
, et al
p53-independent regulation of p21Waf1/Cip1 expression and senescence by Chk2
.
Mol Cancer Res
2005
;
3
:
627
34
.
49.
Kim
WH
,
Kang
KH
,
Kim
MY
,
Choi
KH
. 
Induction of p53-independent p21 during ceramide-induced G1 arrest in human hepatocarcinoma cells
.
Biochem Cell Biol
2000
;
78
:
127
35
.
50.
Macleod
KF
,
Sherry
N
,
Hannon
G
,
Beach
D
,
Tokino
T
,
Kinzler
K
, et al
p53-dependent and independent expression of p21 during cell growth, differentiation, and DNA damage
.
Genes Dev
1995
;
9
:
935
44
.
51.
Karimian
A
,
Ahmadi
Y
,
Yousefi
B
. 
Multiple functions of p21 in cell cycle, apoptosis and transcriptional regulation after DNA damage
.
DNA Repair
2016
;
42
:
63
71
.
52.
Leong
WZ
,
Tan
SH
,
Ngoc
PCT
,
Amanda
S
,
Yam
AWY
,
Liau
WS
, et al
ARID5B as a critical downstream target of the TAL1 complex that activates the oncogenic transcriptional program and promotes T-cell leukemogenesis
.
Genes Dev
2017
;
31
:
2343
60
.
53.
Wang
G
,
Watanabe
M
,
Imai
Y
,
Hara
K
,
Manabe
I
,
Maemura
K
, et al
Associations of variations in the MRF2/ARID5B gene with susceptibility to type 2 diabetes in the Japanese population
.
J Hum Genet
2012
;
57
:
727
33
.
54.
Okada
Y
,
Terao
C
,
Ikari
K
,
Kochi
Y
,
Ohmura
K
,
Suzuki
A
, et al
Meta-analysis identifies nine new loci associated with rheumatoid arthritis in the Japanese population
.
Nat Genet
2012
;
44
:
511
6
.
55.
Yang
W
,
Tang
H
,
Zhang
Y
,
Tang
X
,
Zhang
J
,
Sun
L
, et al
Meta-analysis followed by replication identifies loci in or near CDKN1B, TET3, CD80, DRAM1, and ARID5B as associated with systemic lupus erythematosus in Asians
.
Am J Hum Genet
2013
;
92
:
41
51
.
56.
Tomer
Y
,
Hasham
A
,
Davies
TF
,
Stefan
M
,
Concepcion
E
,
Keddache
M
, et al
Fine mapping of loci linked to autoimmune thyroid disease identifies novel susceptibility genes
.
J Clin Endocrinol Metab
2013
;
98
:
E144
52
.