{"doi":"10.1002/ctm2.1491","title":"Mutations of epigenetic genes and correlation with treatment response in peripheral T‐cell lymphoma","abstract":null,"journal":"Clinical and Translational Medicine","year":2024,"id":607888,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":542963,"name":"Wei Wang","orcid":"0000-0001-8676-1190","position":1,"is_corresponding":false},{"id":171430,"name":"Wanying Li","orcid":null,"position":2,"is_corresponding":false},{"id":530284,"name":"Yan Zhang","orcid":"0000-0003-0244-218X","position":3,"is_corresponding":false},{"id":1560996,"name":"Danqing Zhao","orcid":null,"position":4,"is_corresponding":false},{"id":830037,"name":"Wei Zhang","orcid":"0000-0002-3575-6225","position":5,"is_corresponding":false},{"id":1203871,"name":"Daobin Zhou","orcid":"0000-0002-1592-1932","position":6,"is_corresponding":false},{"id":1560993,"name":"Chong Wei","orcid":"0000-0001-9690-8555","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Mutations of epigenetic genes and correlation with treatment response in peripheral T‐cell lymphoma","abstract":"Peripheral T-cell lymphomas (PTCLs) are heterogeneous and relatively rare diseases, which account for 20% to 30% of non-Hodgkin's lymphoma in China.1, 2 Due to a lack of prospective studies and targeted therapeutic drugs, the treatment of PTCL is still disappointing. Long-term survival of most types of PTCLs were around 30%–40%.3 Recent molecular studies revealed that PTCL with T-follicular helper (TFH) origin including angioimmunoblastic T-cell lymphoma (AITL) and nodal PTCL with TFH phenotype (nTFHL) share recurrent mutations in epigenetic regulating genes, including TET2, DNMT3A and IDH2.4, 5 Therapies targeting epigenetic changes, such as demethylation drugs and histone deacetylase (HDAC) inhibitors, are being investigated.6, 7 However, there is still a lack of evidence to determine the correlation between epigenetic mutations and the efficacy of epigenetic targeting drugs. In this prospective study, we aimed to evaluate the correlation between epigenetic mutations and treatment response and their prognostic value. This was a prospective single-center study. Key eligibility criteria included the following: (1) newly diagnosed PTCLs with pathological findings consistent with PTCL, not otherwise specified (PTCL-NOS), AITL, and nTFHL based on the 4th edition of World Health Organization classification2; (2) enough formalin fixed paraffin embedded (FFPE) samples available for next-generation sequencing (NGS); (3) enrolled in one of the two prospective trials: the first was the phase 1/2 trial of chidamide (also known as tucidinostat) combined with cyclophosphamide, vincristine, doxorubicin, etoposide and prednisone regimen (CHOEP), so-called C-CHOEP regimen in newly diagnosed PTCLs (NCT02987244)8; The second was the phase 3 trial of chidamide, azacitidine combined with cyclophosphamide, vincristine, doxorubicin and prednisone regimen (AC-CHOP) versus CHOP regimen in newly diagnosed PTCLs (NCT05075460).9 Between January 2016 and April 2023, 38 patients were prospectively enrolled, including 15 patients in the phase 1/2 trial of C-CHOEP regimen and 23 patients in the experiential arm of the phase 3 trial of AC-CHOP regimen. A flowchart of patients from screening to analysis is shown in Figure S1. The base-line clinical characteristics of the 38 patients are shown in Table 1. NGS of the 38 patients was performed on FFPE tissue samples using 1 of the 2 custom panels. The first custom panel included 413 lymphoma-associated genes (Oncolym Panel, Geneplus-Beijing, Beijing, China). The other custom panel included 84 genes that are frequently mutated in PTCLs (PTCL Panel, Yuanqi Bio, Shanghai, China). Gene lists of the two panels are provided in the supplementary materials (Tables S1 and S2). Both two panels included genes involved in DNA methylation (TET2, IDH2 and DNMT3A), histone methylation (KMT2A, KMT2C, KMT2D, EZH2, BCOR and SETD2), histone acetylation (EP300 and CREBBP) and also other recurrent mutations in PTCLs (including RHOA, PLCG, CD28, VAV1, FYN, STAT3 and TP53). Sequencing was performed on the HiSeq 3000 system. The average sequencing depth was 1153.6 ± 570.3. Buccal mucosa was obtained and sequenced to filter out germline mutations. Only mutations with variant allele frequencies of ≥1% were included in our analysis. Other statistical methods were as follows. Differences of continuous variable and categorical variable were estimated using the Mann–Whitney U test and the Fisher's exact test. Progression-free survival (PFS) and overall survival (OS) were analyzed using the Kaplan-Meier method. Survival rates differenced were compared using the Log-rank test. Univariate analysis was performed using Cox regression for PFS and OS. In total, 253 somatic mutations involving 109 genes were identified. The average number of mutations was 6.7 (range: 1–21) per sample. Mutational profile revealed from the 38 PTCL tumour samples were shown in Figure 1. Widespread mutations in epigenetic modifying genes were identified in this cohort. In line with previous studies, the most frequent epigenetic mutations were TET2 mutations identified in 27/38 (71.1%) of the patients, DNMT3A mutations in 9/38 (23.6%) of the patients, IDH2 mutations in 8/38 (21.0%) of the patients and KMT2C mutations in 6/38 (15.8%) of the patients. Among other recurrent mutations in PTCLs, RHOA mutations were identified in 20/38 (52.6%) of the patients and PLCG1 identified in 5/38 (13.2%) of the patients. A total of 47 TET2 mutations were identified in the 38 PTCL tumour samples (Figure 2A). All of the IDH2 mutations occurred in the hotspot point (p.R172M/G/S/K) (Figure 2B). Most of the RHOA mutations occurred in the hotspot point (c.50G > T, p.G17V) except for two missense mutations (c.482C > T and c.358G > T) identified in one patient (ID32) (Figure 2C). AITL and nTFHL have higher frequency of TET2, IDH2, and RHOA mutations than in PCTL-NOS (TET2: 80.8% vs. 50.0%, p = .052; IDH2: 30.8% vs. .0%, p = .039; RHOA:69.2% vs. 16.7%, p = .008). Mutations of TET2, RHOA and IDH2 showed strong correlations. All but two RHOA-mutated cases also harbored TET2 mutations, and all of the IDH2 mutations were identified exclusively in samples that also harbor RHOA mutations (Figure 2E). We next evaluated the impact of individual epigenetic mutations on treatment response. Responses were evaluable in 36 of the 38 patients. Among the epigenetic genes evaluated, only DNMT3A mutation was found to be associated with an adverse response rate. The mutation frequency of DNMT3A mutation was significantly higher in the non-responder group than that in the responder group (mutation frequency of 41.2% vs. 5.3%, p = .016) (Figure 3A). Similarly, patients with mutated DNMT3A had significantly lower responses rate than those with wild-type DNMT3A (ORR, 12.5% vs. 64.3%, p = .016; CR rate, .0% vs.57.1%, p = .005). In subgroup analysis stratified by treatment modalities (C-CHOEP or AC-CHOP), none of the epigenetic regulators showed significant association with the response with a small sample size in each subgroup (Figure 3B). Further, in subgroup analysis stratified by pathological subtypes (PTCL-NOS or AITL/nTFHL), DNMT3A mutation maintained the prognostic value of poor response rate in the AITL/nTFHL subgroup (Figure 3C). The frequency of DNMT3A mutation was still significantly higher in the non-responder than in the responder group (mutation frequency of 46.2% vs. 0%, p = .015) among patients with AITL and nTFHL. In previous studies, the correlation between TET2 mutation status and the response to epigenetic treatment was the most studied and showed controversial results.10, 7 However, TET2 mutation did not show a significant correlation with treatment response in the analysis of the entire group and subgroup analyses stratified by treatment modalities and pathological subtypes in our study. Different types of epigenetic mutations may reshape the epigenome globally. To test this hypothesis, we further evaluated the correlation of the number of epigenetic mutations with treatment response. We found that non-responding patients exhibited a higher average number of epigenetic mutations compared with the responders (2.6 vs. 1.6, p = .008), which suggests that a high mutation burden of epigenetic genes may predict a low response rate (Figure 3D). Additionally, the number of total somatic mutations between the responder and non-responders was not significantly different, which indicated that response rates were truly associated with epigenetic mutational burden instead of global mutational burden (Figure 3E). When excluding patients with the DNMT3A mutations from analysis, a higher average number of epigenetic mutations was also found among the non-responders than among the responders (2.1 vs. 1.4, p = .078) (Figure 3F). However, the difference did not approach statistical significance. This result was inconsistent with a previously published study by Falchi et al, in which responders harbored a higher average number of epigenetic mutations. However, the treatment modalities and treatment histories of enrolled patients were clearly different between this previous study and our study. In this sense, we still should be cautious against broad generalization of conclusions drawn from our study until they can be validated in larger-scale controlled studies. Finally, we assessed the correlation between epigenetic mutations and survival. The median follow-up time was 16 (range: 1 - 56) months. The median PFS and OS time were 7 and 50 months for the whole cohort (Figure 3G). The 1-year and 2-year PFS rates were 33.3% and 24.9%, respectively. The 1-year and 2-year OS rates were both 56.4%. In univariate analysis for PFS, established risk factors for PTCL including age, LDH level, ECOG status, Ann Arbor stage, extranodal sites involvement, bone marrow involvement along with epigenetic mutations of TET2, IDH2, DNMT3A, KMT2A, KMT2C, KMT2D, SETD2 and EP300 were incorporated. Only DNMT3A mutation was identified as an independent adverse prognostic factors for PFS in univariate analysis (HR = 2.928, 95% CI: 1.229-6.974, p = .015) (Figure 3I). Patients with mutant DNMT3A showed significantly inferior 1- and 2-year PFS rates compared with those with wild type (0% and 0% vs. 42.4% and 31.8%) (Figure 3H). In univariate analysis for OS, none of the above factors showed significant prognostic value. These results were consistent with a recently published study by Ruan J et al, in which DNMT3A mutation was also reported to be associated with adverse PFS for patients with PTCLs and treated with oral azacitidine plus CHOP.7 In another study evaluating histone modifier gene mutations in PTCL-NOS, Ji et al reported that mutations of histone modifier genes were associated with inferior PFS for patients with PTCL-NOS.11 However, in our study, both PFS and OS showed no significant differences between patients with or without histone modifier gene mutations (Figure S2) This study, like many other studies on this relatively rare disease, the limitations included the small sample size, the heterogeneity of treatment modalities, and the usage of different NGS panels. Clonal hematopoiesis was not evaluated which may further influence the treatment efficacy and survival. Findings in our preliminary study can serve as a reference for large scale multicenter studies in the future. In conclusion, widespread epigenetic mutations were identified in patients with PTCLs. DNMT3A mutation may serve as a potential biomarker in predicting resistance to chemotherapies priming with epigenetic targeting drugs and adverse PFS in patients with PTCLs. A high mutation burden of epigenetic genes may also predict poor treatment responses. CW, DBZ, and WZ designed the study. CW, WW, YZ, and DQZ performed the experiment. CW and WYL analyzed all the data. WZ and DBZ helped perform the analysis with constructive discussions. CW wrote the main manuscript. DBZ and WZ reviewed and revised the manuscript. All authors read and approved the final manuscript. The authors thank all investigators, coordinators and the patients and their families for participating in this study. They would like to acknowledge Beijing-Geneplus Technology Limited Company and Shanghai Rightongene Biotechnology Limited Company for their work on NGS sequencing. This work was supported by National Natural Science Foundation of China (NSFC) (grant number: 81970188), National High Level Hospital Clinical Research Funding (grant numbers: 2022-PUMCH-A-261, 2022-PUMCH-C-056, and 2022-PUMCH-B-134). National Natural Science Foundation of China (NSFC), Grant Number: 81970188; National High Level Hospital Clinical Research Funding, Grant Numbers: 2022-PUMCH-A-261, 2022-PUMCH-C-056, and 2022-PUMCH-B-134 The authors declare no potential conflict of interest. This study was approved by the institutional review board of Peking Union Medical College Hospital and the study was conducted in accordance with the Declaration of Helsinki. Not applicable. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. 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