Literature DB >> 29305415

Histone modifier gene mutations in peripheral T-cell lymphoma not otherwise specified.

Meng-Meng Ji1, Yao-Hui Huang1, Jin-Yan Huang1, Zhao-Fu Wang2, Di Fu1, Han Liu1, Feng Liu1, Christophe Leboeuf3,4, Li Wang1,3, Jing Ye3, Yi-Ming Lu3, Anne Janin3,4, Shu Cheng5, Wei-Li Zhao5,3.   

Abstract

Due to heterogeneous morphological and immunophenotypic features, approximately 50% of peripheral T-cell lymphomas are unclassifiable and categorized as peripheral T-cell lymphomas, not otherwise specified. These conditions have an aggressive course and poor clinical outcome. Identification of actionable biomarkers is urgently needed to develop better therapeutic strategies. Epigenetic alterations play a crucial role in tumor progression. Histone modifications, particularly methylation and acetylation, are generally involved in chromatin state regulation. Here we screened the core set of genes related to histone methylation (KMT2D, SETD2, KMT2A, KDM6A) and acetylation (EP300, CREBBP) and identified 59 somatic mutations in 45 of 125 (36.0%) patients with peripheral T-cell lymphomas, not otherwise specified. Histone modifier gene mutations were associated with inferior progression-free survival time of the patients, irrespective of chemotherapy regimens, but an increased response to the histone deacetylase inhibitor chidamide. In vitro, chidamide significantly inhibited the growth of EP300-mutated T-lymphoma cells and KMT2D-mutated T-lymphoma cells when combined with the hypomethylating agent decitabine. Mechanistically, decitabine acted synergistically with chidamide to enhance the interaction of KMT2D with transcription factor PU.1, regulated H3K4me-associated signaling pathways, and sensitized T-lymphoma cells to chidamide. In a xenograft KMT2D-mutated T-lymphoma model, dual treatment with chidamide and decitabine significantly retarded tumor growth and induced cell apoptosis through modulation of the KMT2D/H3K4me axis. Our work thus contributes to the understanding of aberrant histone modification in peripheral T-cell lymphomas, not otherwise specified and the stratification of a biological subset that can benefit from epigenetic treatment. Copyright
© 2018 Ferrata Storti Foundation.

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Year:  2018        PMID: 29305415      PMCID: PMC5865443          DOI: 10.3324/haematol.2017.182444

Source DB:  PubMed          Journal:  Haematologica        ISSN: 0390-6078            Impact factor:   9.941


Introduction

Peripheral T-cell lymphomas (PTCL) represent a heterogeneous clinicopathological entity of non-Hodgkin lymphoma with an aggressive disease course and poor clinical outcome. Approximately 50% of PTCL are unclassifiable and categorized as PTCL, not otherwise specified (PTCL-NOS).[1] Using gene expression profiling, PTCL-NOS lymphocytes can be distinguished from normal T lymphocytes, with deregulation of genes involved in apoptosis, proliferation, cell adhesion, and transcription regulation.[2] Two subgroups of PTCL-NOS have been identified, which are characterized by high expression of either GATA3 or TBX21/T-bet transcription factors and downstream target genes.[3] However, actionable biomarkers closely related to the pathogenic mechanism need to be further investigated and may become potential therapeutic targets of PTCL-NOS.[4,5] Epigenetic alterations play a crucial role in tumor progression.[6] Next-generation sequencing technologies have led to the discovery of epigenetic modifier gene mutations in PTCL, such as the DNA methylation genes TET2, TET1 and DNMT3A,[7,8] and chromatin remodeler genes ARID1B and ARID2.[9,10] Meanwhile, genes of histone methylation, such as KMT2D, KMT2A, KDM6A, SETD2 and EZH2, and those of histone acetylation, including CREBBP and EP300, have also been found in PTCL and other T-lymphoid malignancies.[9,11-13] To further determine their prognostic significance and correlation with clinical treatment, here we assessed the mutational pattern of the main epigenetic modifier genes in patients with PTCL-NOS.

Methods

Patients

A total of 239 patients with previously untreated PTCL-NOS were enrolled in this study. The histological diagnosis was established according to the World Health Organization (WHO) classification.[14] The study was approved by the Shanghai Rui Jin Hospital Review Board with informed consent obtained in accordance with the Declaration of Helsinki.

Targeted sequencing

Targeted sequencing was performed on available tumor samples of 125 patients. To determine the mutations of candidate genes, polymerase chain reaction primers were designed by iPLEX Assay Design software (Sequenom, California, USA). Multiplexed libraries of tagged amplicons from patients with PTCL-NOS were generated by the 48×48 Access Array microfluidic platform (Fluidigm, South San Francisco, USA) according to the manufacturer’s protocol. Deep sequencing was performed with established Illumina protocols on the GAIIx and MiSeq platform (Illumina, California, USA). Matched peripheral blood samples were included to exclude germline polymorphisms and the mutations were confirmed by Sanger sequencing.

Cell line and reagents

The Jurkat T-leukemia cell line was obtained from the American Type Culture Collection. Cells were grown in RPMI-1640 medium, supplemented with 10% heat-inactivated fetal bovine serum in a humidified atmosphere containing 5% CO2 at 37°C. Valproic acid (VPA, V3640) was from Sigma (San Francisco, USA). Suberoylanilide hydroxamic acid (SAHA, S1047) and romidepsin (ROMI, S3020) were from Selleck (Houston, USA). Chidamide, the histone deacetylase (HDAC) inhibitor clinically available in China, was kindly provided by Chipscreen (shenzhen, China).

Lentivirus packaging and transduction

Purified plasmids pGV365-KMT2D (WT), pGV365-KMT2D (V5486M), pGV365-EP300 (WT) and pGV365-EP300 (H1377R) were transfected with package vectors into HEK-293T cells using lipofectamine 2000 (Invitrogen, California, USA; 11668019) according to the manufacturer’s protocol. The supernatant fraction of HEK-293T cell cultures was then condensed to a viral concentration of approximately 3×108 transducing units/mL. The lentiviral particles were incubated with Jurkat cells for 72 h. The stably transduced cells were selected by EGFP or mCherry fluorescence protein after transduction.

Statistical analysis

Data were calculated as the mean ± standard deviation from three separate experiments. The Student t-test was applied to compare two normally distributed groups and the Mann-Whitney U test to compare two groups which did not conform to normal distribution. The Bonferroni adjustment was used to perform multiple comparisons. Progression-free survival was calculated from the date when treatment began to the date when the disease progression was recognized or the date of the last follow-up. Overall survival time was measured from the date of diagnosis to the date of death or the last follow-up. Univariate hazard estimates were generated with unadjusted Cox proportional hazards models. Covariates demonstrating statistical significance with P values <0.05 on univariate analysis were included in the multivariate model. All statistical procedures were performed with the SPSS version 20.0 statistical software package or GraphPad Prism 5 software. P<0.05 was considered statistically significant.

Online supplementary methods

DNA preparation, western blot, immunofluorescence, immunohistochemistry, isobolographic analysis, mRNA-seq library preparation and sequencing analysis, ChIP-seq library preparation and sequencing analysis, the TUNEL assay, murine model and micro-positron emission tomography and computed tomography imaging are described in the Online Supplementary Methods.

Results

Histone modifier genes were frequently mutated in peripheral T-cell lymphoma not otherwise specified

A total of 91 somatic mutations of epigenetic modifier genes were identified in 60 of 125 (48.0%) patients with PTCL-NOS by targeted sequencing (Figure 1A). Most of the somatic mutations were missense mutations (n=72), followed by nonsense (n=10) and frameshift mutations (n=9) (Figure 1B). We observed a preference for C>T/G>A alterations analogous to the somatic single-nucleotide variation spectrum in other cancers (Figure 1C). No correlation was found in terms of age and gender. Mutations of histone methylation genes (category I) most frequently occurred in KMT2D (encoding H3K4 methyltransferase, 25/125 patients, 20.0%), followed by those in SETD2 (encoding H3K36 methyltransferase, 6/125 patients, 4.8%), KMT2A (encoding H3K4 methyltransferase, 3/125 patients, 2.4%) and KDM6A (encoding H3K27 demethylase, 1/125 patients, 0.8%). No EZH2 mutation was detected. Mutations of histone acetylation genes (category II) were found in EP300 (encoding H3K18 acetyltransferase, 10/125 patients, 8.0%) and in CREBBP (encoding H3K18 acetyltransferase, 5/125 patients, 4.0%). DNA methylation genes TET2, TET1 and DNMT3A (category III), as well as chromatin remodeler genes ARID1B and ARID2 (category IV), were also affected in 12.0%, 3.2%, 3.2%, 4% and 1.6% of the patients, respectively (Figure 1A and Online Supplementary Table S1). In accordance with the conceptual classification of the mutated genes, overlap mutations were seldom present among histone methylation, histone acetylation, DNA methylation or chromatin remodeler genes. In particular, histone methylation gene mutations, such as mutations of histone acetylation genes, were mutually exclusive of each other, suggesting that histone modifying genes might be involved in distinct biological processes (Figure 1D).
Figure 1.

Histone modifier gene mutations in peripheral T-cell lymphoma, not otherwise specified. (A) Gene mutations identified by targeted sequencing in 125 patients with peripheral T-cell lymphomas. The number of patients (N) with mutations is listed on the right. The mutations are classified into the categories indicated on the left: I, histone methylation; II, histone acetylation; III, DNA methylation; IV, chromatin remodeler. (B) Number and type of non-silent somatic mutations. (C) Number and percentage of non-silent somatic single nucleotide variants. (D) Circos diagram according to mutation categories.

Histone modifier gene mutations in peripheral T-cell lymphoma, not otherwise specified. (A) Gene mutations identified by targeted sequencing in 125 patients with peripheral T-cell lymphomas. The number of patients (N) with mutations is listed on the right. The mutations are classified into the categories indicated on the left: I, histone methylation; II, histone acetylation; III, DNA methylation; IV, chromatin remodeler. (B) Number and type of non-silent somatic mutations. (C) Number and percentage of non-silent somatic single nucleotide variants. (D) Circos diagram according to mutation categories. Alterations of histone modifier genes were primarily located at well-conserved amino acid positions across distinct species (Online Supplementary Figure S1). Typically, KMT2D/KMT2A mutations affected the PHD domain (e.g. residues 134–320, 1378–1556, 5032–5138, and 1433–1624, 1871–1983), HMG domain (residues 2021–2072), undetermined domain (e.g. residues 2487–4658) and SET domain (e.g. residues 5397–5519 and 3825–3969). EP300/CREBBP mutations affected the HAT domain (e.g. residues 1306–1612 and 1342–1649).

Histone modifier gene mutations were associated with disease progression in peripheral T-cell lymphoma not otherwise specified

One hundred and forty patients were treated with CHOP-based chemotherapy in a historical cohort of Shanghai Ruijin Hospital from 1997 to 2011, and referred to as the training cohort. The validation cohort consisted of 99 patients enrolled in two prospective studies (NCT 01746992 and NCT 02533700, randomized trials to compare CHOP-based chemotherapy with sequential chemotherapy with CEOP/IVE/GDP or CTOP/ITE/MTX). Since 2012, 49 and 50 patients have been randomized to CHOP-based or sequential chemotherapy, respectively. No obvious differences in clinical and pathological characteristics or treatment response were observed either between the training and the validation cohort, or between the two arms within the validation cohort (Online Supplementary Table S2). Gene mutation data were available for 73 and 52 patients of the training and validation cohorts with available tissue samples, respectively (Figure 1A). In the training cohort, the median follow-up time was 29.1 months (range, 0.5–162.0 months). The 2-year progression-free and overall survival rates of the patients were 36.7% and 47.1%, respectively. In the univariate analysis, the International Prognostic Index was a significant prognostic factor for both progression-free survival and overall survival (both P<0.001), but histone modifier mutations were only prognostic for progression-free survival and not overall survival (P=0.012 and P=0.095, respectively) (Figure 2A,B). In the multivariate analysis, when the International Prognostic Index was controlled for, the presence of a histone modifier gene mutation was an independent prognostic factor for progression-free survival (P<0.001) (Table 1). The 2-year progression-free and overall survival rates were 26.4% and 56.6% for patients with histone modifier gene mutations and 49.6% and 63.3% for patients without mutations (Figure 2A,B). In the validation cohort, the median follow-up time was 19.5 months (range, 2.1–43.0 months). Histone modifier gene mutations were associated with shorter progression-free survival in multivariate analysis (P=0.049) (Table 1). The 2-year progression-free and overall survival rates were 22.2% and 24.2% for patients with histone modifier gene mutations and 41.1% and 57.5% for patients without mutations (P=0.045 and P=0.224) (Figure 2C,D). Overall, these data expand the prognostic role of histone modification in disease progression in PTCL-NOS.
Figure 2.

Progression-free survival and overall survival curves of patients with peripheral T-cell lymphoma not otherwise specified according to histone modifier gene mutations. (A) Progression-free survival and (B) overall survival curves of the training cohort. (C) Progression-free survival and (D) overall survival curves of the validation cohort.

Table 1.

Multivariate analysis of predictors of progression-free survival in patients with PTCL-NOS controlled by International Prognostic Index.

Progression-free survival and overall survival curves of patients with peripheral T-cell lymphoma not otherwise specified according to histone modifier gene mutations. (A) Progression-free survival and (B) overall survival curves of the training cohort. (C) Progression-free survival and (D) overall survival curves of the validation cohort. Multivariate analysis of predictors of progression-free survival in patients with PTCL-NOS controlled by International Prognostic Index.

Histone modifier gene mutations sensitized T-lymphoma cells to the histone deacetylase inhibitor chidamide and/or the hypomethylating agent decitabine

A possible structure-function relationship of the mutants was addressed using the crystal structure of the proteins encoded by KMT2D (PDB4Z4P) and EP300 (PDB4PZR), the two most frequently mutated histone modifier genes. As shown in Figure 3A, KMT2D R5389W, E5444K and V5486M might destabilize the SET domain and reduce histone methylation activity, EP300 E1377R, W1466_ and E1515V might disrupt the acetyl-CoA binding pocket, destabilize the HAT domain and reduce histone acetylation activity. Next, representative missense mutants KMT2D (V5486M) and EP300 (H1377R), as well as WT KMT2D and EP300, were established and transfected into Jurkat cells. Compared with WT protein, while KMT2D mutant reduced the level of H3K4me3, this reduction was restored by the HDAC inhibitors romidepsin and chidamide (Figure 3B and Online Supplementary Figure S2). On the other hand, the level of H3K18ac was reduced in EP300 mutant, but this effect was restored by the HDAC inhibitors valproic acid, suberoylanilide hydroxamic acid, or romidepsin and chidamide (Figure 3C). These results were observed by western blot and by immunofluorescence assay (Figure 3B,C).
Figure 3.

Effect of histone deacetylase inhibitor in KMT2D-mutated and EP300-mutated T-lymphoma. (A) Structure prediction of the missense mutations. The crystal structure of the complex of KMT2D and EP300 is PDB: 4Z4P and PDB: 4PZR, respectively. SAM, S-adenosyl-L-methionine. (B and C) Western blot and immunofluoresence assay of Jurkat cells transfected with wild-type (WT), KMT2D mutants (V5486M) (B) and EP300 mutants (H1377R) (C) upon treatment with different HDAC inhibitors. Jurkat cells were treated for 48 h at IC50. Histone 3 (H3) was used as a loading control. VPA, valproic acid, 3.7 mm; SAHA, suberoylanilide hydroxamic acid, 10 μm; ROMI, romidepsin, 5 nm; CHID, chidamide, 5 μm (48 h). Bar=10 μm. (D) Immunostaining of H3K4me3 and H3K18ac in tumor samples of PTCL-NOS patients with or without KMT2D or EP300 mutations. Bar=20 μm. (E) Response rate in relapsed PTCL-NOS patients treated with CHID according to the mutation status of histone modifier genes.

Effect of histone deacetylase inhibitor in KMT2D-mutated and EP300-mutated T-lymphoma. (A) Structure prediction of the missense mutations. The crystal structure of the complex of KMT2D and EP300 is PDB: 4Z4P and PDB: 4PZR, respectively. SAM, S-adenosyl-L-methionine. (B and C) Western blot and immunofluoresence assay of Jurkat cells transfected with wild-type (WT), KMT2D mutants (V5486M) (B) and EP300 mutants (H1377R) (C) upon treatment with different HDAC inhibitors. Jurkat cells were treated for 48 h at IC50. Histone 3 (H3) was used as a loading control. VPA, valproic acid, 3.7 mm; SAHA, suberoylanilide hydroxamic acid, 10 μm; ROMI, romidepsin, 5 nm; CHID, chidamide, 5 μm (48 h). Bar=10 μm. (D) Immunostaining of H3K4me3 and H3K18ac in tumor samples of PTCL-NOS patients with or without KMT2D or EP300 mutations. Bar=20 μm. (E) Response rate in relapsed PTCL-NOS patients treated with CHID according to the mutation status of histone modifier genes. In tumor samples from PTCL-NOS patients, a significantly lower fraction of nuclear H3K4me3 positivity (+++~++++, 30%) was observed in cases with the KMT2D mutation than in those without mutations. Similarly, a lower fraction of nuclear H3K18ac positivity (+++~++++, 17%) was present in cases with EP300/CREBBP mutations than in those without mutations (Figure 3D). Interestingly, upon treatment with chidamide (administered orally at a dose of 30 mg twice per week), relapsed patients with a histone modifier gene mutation showed a remarkably increased response rate (complete or partial remission), as compared to those without mutations (Figure 3E and Online Supplementary Table S3). Thus, such mutations might alter the protein function on chromatin state regulation, sensitizing PTCL-NOS patients to HDAC inhibitors. In vitro, Jurkat cells bearing the KMT2D V5486M or EP300 H1377R mutant were treated with different concentrations of chidamide and/or the hypomethylating agent decitabine for 48 h. The combination index (CI) curve yielded most of the data points to the area <1, denoting synergistic interactions in KMT2D V5486M mutated cells. Meanwhile, the inhibitory effect on EP300 H1377R mutated cells was achieved by chidamide alone (Figure 4A). Flow cytometry revealed that chidamide and decitabine synergistically induced KMT2D V5486M mutated cell apoptosis and G0/G1 arrest (Figure 4B). The in vivo anti-tumor activity of dual treatment on T-cell lymphoma was further evaluated in a murine xenograft model in which KMT2D V5486M mutated Jurkat cells subcutaneously injected into nude mice. The tumors formed in mice co-treated with chidamide and decitabine were significantly smaller than those that formed in untreated animals or those treated with the single agents, starting from 15 days of treatment (Figure 4C, left panel), as visualized by 18F-fluorodeoxyglucose small-animal positron emission tomography – computed tomography at 21 days of treatment (Figure 4C, right panel). To search for more evidence of tumor cell apoptosis, a TUNEL assay was performed on mice tumor sections. Compared with the untreated group and the groups treated with single agents, the number of apoptotic tumor cells was increased following combined treatment (Figure 4D). In accordance with in vitro data, upregulation of H3K4me3 was more significant in the combination treatment group than in the single-agent and the untreated group (Figure 4E).
Figure 4.

Effect of chidamide and decitabine in KMT2D-mutated and EP300-mutated T-lymphoma. (A) Combination index (CI) curve calculated by Compusyn software in KMT2D-mutated and EP300-mutated Jurkat cells treated with chidamide (CHID, 5 μm) and/or decitabine (DECI, 5 μm) for 48 h. (B) KMT2D-mutated Jurkat cell apoptosis and cell cycle determined by flow cytometry of cells treated with CHID and/or DECI for 48 h. *P<0.05, **P<0.01 compared with the untreated cells. (C) In vivo effect of the CHID and DECI combination in a murine T-lymphoma xenograft model. Tumor volume (left panel) and standardized uptake value (SUV) intensity of micro-positron emission tomograpy-computed tomography (right panel) of xenograft nude mice injected subcutaneously with KMT2D V5486-mutated Jurkat cells treated with CHID (12.5 mg/kg, twice weekly for 3 weeks), DECI (0.5 mg/kg, twice weekly for 3 weeks), either alone or in combination. **P<0.01 compared with the untreated group that received RPMI1640. (D) Apoptotic cells detected by the TUNEL assay (×400). Bar=20 μm. (E) Immunohistochemical assay of H3K4me3 in murine tumor samples treated with CHID and/or DECI. **P<0.01 compared with the untreated group. Bar=50 μm.

Effect of chidamide and decitabine in KMT2D-mutated and EP300-mutated T-lymphoma. (A) Combination index (CI) curve calculated by Compusyn software in KMT2D-mutated and EP300-mutated Jurkat cells treated with chidamide (CHID, 5 μm) and/or decitabine (DECI, 5 μm) for 48 h. (B) KMT2D-mutated Jurkat cell apoptosis and cell cycle determined by flow cytometry of cells treated with CHID and/or DECI for 48 h. *P<0.05, **P<0.01 compared with the untreated cells. (C) In vivo effect of the CHID and DECI combination in a murine T-lymphoma xenograft model. Tumor volume (left panel) and standardized uptake value (SUV) intensity of micro-positron emission tomograpy-computed tomography (right panel) of xenograft nude mice injected subcutaneously with KMT2D V5486-mutated Jurkat cells treated with CHID (12.5 mg/kg, twice weekly for 3 weeks), DECI (0.5 mg/kg, twice weekly for 3 weeks), either alone or in combination. **P<0.01 compared with the untreated group that received RPMI1640. (D) Apoptotic cells detected by the TUNEL assay (×400). Bar=20 μm. (E) Immunohistochemical assay of H3K4me3 in murine tumor samples treated with CHID and/or DECI. **P<0.01 compared with the untreated group. Bar=50 μm. To determine KMT2D-H3K4me3 DNA binding targets, ChIP-seq was performed using H3K4me3 antibody in KMT2D V5486M mutated Jurkat cells treated with chidamide (5 μm) alone or in combination with decitabine (5 μm) for 48 h. Presentation of the data in a Venn diagram identified a significant non-overlapping portion of H3K4me3 binding promoters in the combination group, excluding 663 promoters overlapping with the chidamide group and 17 with the decitabine group (Figure 5A,B). Consistent with previous studies, H3K4me3 peaks were found at gene promoters. The group of promoters, whose H3K4me3 levels were affected by combined chidamide and decitabine treatment, but not by either chidamide or decitabine treatment alone, was enriched with binding site motifs for PU.1, a transcription factor that activates gene expression during myeloid and B-cell lymphoid cell development[15,16] (Figure 5C). Furthermore, RNA sequencing analysis indicated that, in comparison with the untreated group and the single-agent groups, combined treatment led to significant modulation of multiple signaling pathways associated with cancer, including those of apoptosis, cell cycle progression, cell adhesion, and transcriptional regulation (Figure 5D). Particularly, PU.1 was included in both the cancer pathway and the transcriptional pathway in the combined treatment group. Pathway enrichment analysis of the overlapping genes of the RNA-Seq and ChIP-Seq in the combination group was then performed. Significant pathways relevant to T-cell biology are shown in Figure 5E. As revealed by gene set enrichment analysis, the MAPK pathway was inactivated in the combination treatment group compared with the untreated group. Accordingly, p-ERK upregulation was observed not only in tumor samples of PTCL-NOS patients with KMT2D mutations, but also in those of xenografted T-lymphoma mice bearing KMT2D V5486M mutants, the latter being inhibited by combined treatment with chidamide and decitabine (Figure 5F,G).
Figure 5.

Chip-seq and RNA sequencing data of KMT2D-mutated T-lymphoma cells treated with chidamide and/or decitabine. (A) Venn diagram depicting the overlap between transcription factors bound by H3K4me3 ChIP-seq in the combination group, as compared to the chidamide (CHID)-treated group and the decitabine (DECI)-treated group in KMT2D V5486-mutated Jurkat cells. (B) The top significant transcription factors bound by H3K4me3 in the combination group. (C) ChIP-seq analysis of transcription factors bound by H3K4me3. Enriched H3K4me3-binding motifs for PU.1 analyzed by KMT2D V5486-mutated Jurkat cells treated with CHID and DECI relative to genomic background (upper panel). Genomic snapshots of PU.1 peaks bound by H3K4me3 in different groups (lower panel). (D) Cellular and genetic information processing revealed by RNA-seq on the combination group in KMT2D V5486-mutated Jurkat cells. (E) Pathway analysis of the most differentially expressed genes that overlapped in both RNA-Seq and ChIP-Seq analysis in the combination group (upper panel). Gene-set enrichment analysis of the MAPK pathway (lower panel). (F) Immunohistochemical assay of p-ERK in tumor samples of PTCL-NOS patients with or without KMT2D mutations. (G) Immunostaining of p-ERK in tumor samples of xenografted murine models bearing KMT2D V5486 mutants treated with CHID and/or DECI. **P<0.01 compared with the untreated group. Bar=20 μm.

Chip-seq and RNA sequencing data of KMT2D-mutated T-lymphoma cells treated with chidamide and/or decitabine. (A) Venn diagram depicting the overlap between transcription factors bound by H3K4me3 ChIP-seq in the combination group, as compared to the chidamide (CHID)-treated group and the decitabine (DECI)-treated group in KMT2D V5486-mutated Jurkat cells. (B) The top significant transcription factors bound by H3K4me3 in the combination group. (C) ChIP-seq analysis of transcription factors bound by H3K4me3. Enriched H3K4me3-binding motifs for PU.1 analyzed by KMT2D V5486-mutated Jurkat cells treated with CHID and DECI relative to genomic background (upper panel). Genomic snapshots of PU.1 peaks bound by H3K4me3 in different groups (lower panel). (D) Cellular and genetic information processing revealed by RNA-seq on the combination group in KMT2D V5486-mutated Jurkat cells. (E) Pathway analysis of the most differentially expressed genes that overlapped in both RNA-Seq and ChIP-Seq analysis in the combination group (upper panel). Gene-set enrichment analysis of the MAPK pathway (lower panel). (F) Immunohistochemical assay of p-ERK in tumor samples of PTCL-NOS patients with or without KMT2D mutations. (G) Immunostaining of p-ERK in tumor samples of xenografted murine models bearing KMT2D V5486 mutants treated with CHID and/or DECI. **P<0.01 compared with the untreated group. Bar=20 μm.

Discussion

First observed in B-cell lymphoma, recurrent mutations of epigenetic modifier genes have recently been identified in PTCL-NOS.[9] In the present study, we performed targeted sequencing of the main epigenetic modifier genes in a large cohort of Chinese PTCL-NOS patients. The results showed that the mutational spectrum of these genes in PTCL-NOS was similar to that in B-cell lymphoma, in which predominantly missense mutations were found.[17,18] Importantly, our study provided clinical evidence that histone modifier gene mutations, particularly those involved in histone methylation and acetylation, are significantly associated with tumor chemoresistance and disease progression of PTCL-NOS. The adverse prognostic effect of histone modifier gene mutations was further proven in a chemotherapy-independent manner, prompting us to explore bio-therapeutic agents that can overcome chemoresistance in PTCL-NOS patients. It is well known that HDAC inhibitors are potent anticancer drugs in hematopoietic malignancies, including lymphoma.[19-21] The aim of using HDAC inhibitors is to restore normal histone modification patterns through inhibition of various components of the epigenetic machinery.[22,23] In B-cell lymphoma, HDAC inhibitors can rescue deficits in histone acetylation induced by EP300/CREBBP mutations,[24] rendering tumor cells more sensitive to suberoylanilide hydroxamic acid.[25] This can explain why chidamide also has favorable efficacy on PTCL-NOS patients bearing EP300/CREBBP mutations. Moreover, KMT2D-mutated PTCL-NOS patients responded to chidamide. Both in vitro and in vivo, the combination of decitabine and chidamide induced apoptosis of Jurkat cells bearing the KMT2D mutant. This is in accordance with previous reports that decitabine and 5-azacytidine produce a marked synergistic effect in combination with suberoylanilide hydroxamic acid and romidepsin in T-lymphoma cell lines by modulating cell cycle arrest and apoptosis.[26,27] As a mechanism of action, KMT2D mutations of B-lymphoma cells promote malignant outgrowth by perturbing methylation of H3K4 that affect the JAK-STAT, Toll-like receptor, or B-cell receptor pathway.[28,29] Here our study indicated that dual treatment with chidamide and decitabine enhanced the interaction of KMT2D with the transcription factor PU.1, thereby inactivating the H3K4me-associated signaling pathway MAPK, which is constitutively activated in T-cell lymphoma.[13,30,31] The transcription factor PU.1 is involved in the development of all hematopoietic lineages[32] and regulates lymphoid cell growth and transformation.[33] Aberrant PU.1 expression promotes acute myeloid leukemia and is related to the pathogenesis of multiple myeloma via the MAPK pathway.[34,35] On the other hand, PU.1 is also shown to interact with chromatin remodeler and DNA methyltransferease to control hematopoiesis and suppress leukemia.[36] Our data thus suggested that the combined action of chidamide and decitabine may interfere with the differentiation and/or viability of PTCL-NOS through a PU.1-dependent gene expression program. In conclusion, histone modifier genes indicate clinical progression of PTCL-NOS and may represent a group of actionable biomarkers of this disease subtype. Characterized as a biological subset of PTCL-NOS, patients with dysregulation of the histone modification machinery may be amenable to therapeutic intervention with HDAC inhibitors, given either alone or in combination with hypomethylating agents.
  36 in total

1.  CREBBP Inactivation Promotes the Development of HDAC3-Dependent Lymphomas.

Authors:  Yanwen Jiang; Ana Ortega-Molina; Huimin Geng; Hsia-Yuan Ying; Katerina Hatzi; Sara Parsa; Dylan McNally; Ling Wang; Ashley S Doane; Xabier Agirre; Matt Teater; Cem Meydan; Zhuoning Li; David Poloway; Shenqiu Wang; Daisuke Ennishi; David W Scott; Kristy R Stengel; Janice E Kranz; Edward Holson; Sneh Sharma; James W Young; Chi-Shuen Chu; Robert G Roeder; Rita Shaknovich; Scott W Hiebert; Randy D Gascoyne; Wayne Tam; Olivier Elemento; Hans-Guido Wendel; Ari M Melnick
Journal:  Cancer Discov       Date:  2016-10-12       Impact factor: 39.397

Review 2.  Histone deacetylases and their inhibitors in cancer, neurological diseases and immune disorders.

Authors:  Katrina J Falkenberg; Ricky W Johnstone
Journal:  Nat Rev Drug Discov       Date:  2014-08-18       Impact factor: 84.694

Review 3.  New molecular insights into peripheral T cell lymphomas.

Authors:  Stefano A Pileri; Pier Paolo Piccaluga
Journal:  J Clin Invest       Date:  2012-10-01       Impact factor: 14.808

Review 4.  The 2016 revision of the World Health Organization classification of lymphoid neoplasms.

Authors:  Steven H Swerdlow; Elias Campo; Stefano A Pileri; Nancy Lee Harris; Harald Stein; Reiner Siebert; Ranjana Advani; Michele Ghielmini; Gilles A Salles; Andrew D Zelenetz; Elaine S Jaffe
Journal:  Blood       Date:  2016-03-15       Impact factor: 22.113

5.  Exome sequencing identifies somatic mutations of DDX3X in natural killer/T-cell lymphoma.

Authors:  Lu Jiang; Zhao-Hui Gu; Zi-Xun Yan; Xia Zhao; Yin-Yin Xie; Zi-Guan Zhang; Chun-Ming Pan; Yuan Hu; Chang-Ping Cai; Ying Dong; Jin-Yan Huang; Li Wang; Yang Shen; Guoyu Meng; Jian-Feng Zhou; Jian-Da Hu; Jin-Fen Wang; Yuan-Hua Liu; Lin-Hua Yang; Feng Zhang; Jian-Min Wang; Zhao Wang; Zhi-Gang Peng; Fang-Yuan Chen; Zi-Min Sun; Hao Ding; Ju-Mei Shi; Jian Hou; Jin-Song Yan; Jing-Yi Shi; Lan Xu; Yang Li; Jing Lu; Zhong Zheng; Wen Xue; Wei-Li Zhao; Zhu Chen; Sai-Juan Chen
Journal:  Nat Genet       Date:  2015-07-20       Impact factor: 38.330

6.  PU.1 is a major downstream target of AML1 (RUNX1) in adult mouse hematopoiesis.

Authors:  Gang Huang; Pu Zhang; Hideyo Hirai; Shannon Elf; Xiaomei Yan; Zhao Chen; Steffen Koschmieder; Yutaka Okuno; Tajhal Dayaram; Joseph D Growney; Ramesh A Shivdasani; D Gary Gilliland; Nancy A Speck; Stephen D Nimer; Daniel G Tenen
Journal:  Nat Genet       Date:  2007-11-11       Impact factor: 38.330

Review 7.  Emerging epigenetic targets and therapies in cancer medicine.

Authors:  Relja Popovic; Jonathan D Licht
Journal:  Cancer Discov       Date:  2012-04-23       Impact factor: 39.397

8.  Dynamic regulation of PU.1 expression in multipotent hematopoietic progenitors.

Authors:  Stephen L Nutt; Donald Metcalf; Angela D'Amico; Matthew Polli; Li Wu
Journal:  J Exp Med       Date:  2005-01-17       Impact factor: 14.307

9.  Targeted mutational profiling of peripheral T-cell lymphoma not otherwise specified highlights new mechanisms in a heterogeneous pathogenesis.

Authors:  J H Schatz; S M Horwitz; J Teruya-Feldstein; M A Lunning; A Viale; K Huberman; N D Socci; N Lailler; A Heguy; I Dolgalev; J C Migliacci; M Pirun; M L Palomba; D M Weinstock; H-G Wendel
Journal:  Leukemia       Date:  2014-09-03       Impact factor: 11.528

10.  Disruption of KMT2D perturbs germinal center B cell development and promotes lymphomagenesis.

Authors:  Jiyuan Zhang; David Dominguez-Sola; Shafinaz Hussein; Ji-Eun Lee; Antony B Holmes; Mukesh Bansal; Sofija Vlasevska; Tongwei Mo; Hongyan Tang; Katia Basso; Kai Ge; Riccardo Dalla-Favera; Laura Pasqualucci
Journal:  Nat Med       Date:  2015-09-14       Impact factor: 53.440

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  21 in total

Review 1.  Advances in targeted therapy for malignant lymphoma.

Authors:  Li Wang; Wei Qin; Yu-Jia Huo; Xiao Li; Qing Shi; John E J Rasko; Anne Janin; Wei-Li Zhao
Journal:  Signal Transduct Target Ther       Date:  2020-03-06

Review 2.  Chromatin-Remodeled State in Lymphoma.

Authors:  Yuxuan Liu; Yulissa Gonzalez; Jennifer E Amengual
Journal:  Curr Hematol Malig Rep       Date:  2019-10       Impact factor: 3.952

3.  The genomic landscape of canine diffuse large B-cell lymphoma identifies distinct subtypes with clinical and therapeutic implications.

Authors:  Diana Giannuzzi; Laura Marconato; Antonella Fanelli; Luca Licenziato; Raffaella De Maria; Andrea Rinaldi; Luca Rotta; Nicole Rouquet; Giovanni Birolo; Piero Fariselli; Afua A Mensah; Francesco Bertoni; Luca Aresu
Journal:  Lab Anim (NY)       Date:  2022-06-20       Impact factor: 12.625

4.  Nodal cytotoxic peripheral T-cell lymphoma occurs frequently in the clinical setting of immunodysregulation and is associated with recurrent epigenetic alterations.

Authors:  Laurence de Leval; Philippe Gaulard; Alina Nicolae; Justine Bouilly; Diane Lara; Virginie Fataccioli; François Lemonnier; Fanny Drieux; Marie Parrens; Cyrielle Robe; Elsa Poullot; Bettina Bisig; Céline Bossard; Audrey Letourneau; Edoardo Missiaglia; Christophe Bonnet; Vanessa Szablewski; Alexandra Traverse-Glehen; Marie-Hélène Delfau-Larue
Journal:  Mod Pathol       Date:  2022-03-17       Impact factor: 8.209

Review 5.  The pleiotropic roles of EZH2 in T-cell immunity and immunotherapy.

Authors:  Ying Wang; Tien Bui; Yi Zhang
Journal:  Int J Hematol       Date:  2022-10-21       Impact factor: 2.319

Review 6.  Advances in targeted therapy for malignant lymphoma.

Authors:  Li Wang; Wei Qin; Yu-Jia Huo; Xiao Li; Qing Shi; John E J Rasko; Anne Janin; Wei-Li Zhao
Journal:  Signal Transduct Target Ther       Date:  2020-03-06

7.  Targeting epigenetic regulators in the treatment of T-cell lymphoma.

Authors:  Nada Ahmed; Andrew L Feldman
Journal:  Expert Rev Hematol       Date:  2020-01-22       Impact factor: 2.929

Review 8.  The interplay between DNA and histone methylation: molecular mechanisms and disease implications.

Authors:  Yinglu Li; Xiao Chen; Chao Lu
Journal:  EMBO Rep       Date:  2021-04-12       Impact factor: 8.807

9.  Circular RNA regulatory network reveals cell-cell crosstalk in acute myeloid leukemia extramedullary infiltration.

Authors:  Chengfang Lv; Lili Sun; Zhibo Guo; Huibo Li; Desheng Kong; Bingqi Xu; Leilei Lin; Tianjiao Liu; Dan Guo; Jin Zhou; Yinghua Li
Journal:  J Transl Med       Date:  2018-12-17       Impact factor: 5.531

10.  Comprehensive analysis of circRNA expression profiles and circRNA-associated competing endogenous RNA networks in the development of mouse thymus.

Authors:  Wenting Li; Nana Ma; Ting Yuwen; Bo Yu; Yao Zhou; Yufei Yao; Qi Li; Xiaofan Chen; Jun Wan; Yu Zhang; Wei Zhang
Journal:  J Cell Mol Med       Date:  2020-04-19       Impact factor: 5.310

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