Oncogenetic landscape and clinical impact of IDH1 and IDH2 mutations in T-ALL

IDH1 and IDH2 mutations (IDH1/2Mut) are recognized as recurrent genetic alterations in acute myeloid leukemia (AML) and associated with both clinical impact and therapeutic opportunity due to the recent development of specific IDH1/2Mut inhibitors. In T-cell acute lymphoblastic leukemia (T-ALL), their incidence and prognostic implications remain poorly reported. Our targeted next-generation sequencing approach allowed comprehensive assessment of genotype across the entire IDH1 and IDH2 locus in 1085 consecutive unselected and newly diagnosed patients with T-ALL and identified 4% of, virtually exclusive (47 of 49 patients), IDH1/2Mut. Mutational patterns of IDH1/2Mut in T-ALL present some specific features compared to AML. Whereas IDH2R140Q mutation was frequent in T-ALL (25 of 51 mutations), the IDH2R172 AML hotspot was absent. IDH2 mutations were associated with older age, an immature phenotype, more frequent RAS gain-of-function mutations and epigenetic regulator loss-of-function alterations (DNMT3A and TET2). IDH2 mutations, contrary to IDH1 mutations, appeared to be an independent prognostic factor in multivariate analysis with the NOTCH1/FBXW7/RAS/PTEN classifier. IDH2Mut were significantly associated with a high cumulative incidence of relapse and very dismal outcome, suggesting that IDH2-mutated T-ALL cases should be identified at diagnosis in order to benefit from therapeutic intensification and/or specific IDH2 inhibitors. Supplementary Information The online version contains supplementary material available at 10.1186/s13045-021-01068-4.


Introduction
T-cell acute lymphoblastic leukemia (T-ALL) is aggressive neoplasms resulting from the proliferation of T-lymphoid progenitors blocked at thymic stages of differentiation and account for 15% and 25% of pediatric and adult ALLs, respectively [1]. T-ALL is associated with a wide range of acquired genetic abnormalities that contribute to developmental arrest and abnormal proliferation [2]. Although intensive treatment protocols have markedly improved the outcomes of children with T-ALL, cure rates remain below 60% for adults and 85% for children [3][4][5]. The prognosis is particularly poor in relapsing patients, justifying the development of novel targeted therapies [6,7]. For example, alterations affecting epigenetic factors may offer novel targeted therapeutic approaches in high-risk T-ALL [8].
In T-ALL, IDH1/2 Mut have been partially explored and their prognostic impact poorly reported [16,17]. We now provide the first comprehensive analysis and oncogenetic landscape of IDH1/2 Mut in a cohort of 1085 T-ALL patients, when the nearly 4% of IDH1/2 Mut are associated with extremely poor prognosis, specifically in IDH2mutated cases.

Patient's protocol and clinical trials
Diagnostic peripheral blood or bone marrow samples from 1085 adults and children with T-ALL were analyzed after informed consent was obtained at diagnosis according to the Declaration of Helsinki. Among the 1085 T-ALL analyzed, 215 adult patients aged from 16-59 years were included in the GRAALL03/05 trials (details provide in supplementary) which were registered at clinicaltrials.gov (GRAALL-2003, #NCT00222027; GRAALL-2005, #NCT00327678). and 261 pediatric patients aged from 1 to 19 years were treated in 10 French pediatric hematology departments, members of the FRALLE study group, according to the FRALLE 2000 T guidelines (Additional file 2: Fig. S5 and Additional file 1: Table S3).

Gene mutation screening
A custom capture Nextera XT gene panel (Illumina, San Diego, CA) targeting all coding exons and their adjacent splice junctions of 80 genes was designed, based on available evidence in hematological neoplasms (Additional file 1: Table S1). DNA Libraries were prepared using Nextera Rapid Capture Enrichment protocol and underwent 2 × 150 bp paired-end sequencing on Illumina MiSeq sequencing system with MiSeq Reagent Kit v2 (Illumina). Briefly, sequence reads were filtered and mapped to the human genome (GRCh37/hg19) using in-house software (Polyweb, Institut Imagine, Paris). Annotated variants were selected after filtering out calls according to the following criteria: (1) coverage < 30×, < 10 alternative reads or variant allelic fraction (VAF) < 7%; (2) polymorphisms described in dbSNP, 1000Genomes, EVS, Gnomad and EXAC with a calculated mean population frequency > 0.1%. Non-filtered variants were annotated using somatic database COSMIC (version 78) and ProteinPaint (St Jude Children's Research Hospital -Pediatric Cancer data portal). Lollipop plots were generated with ProteinPaint (https:// pecan. stjude. org/#/ prote inpai nt).

Minimal residual disease assessment
Immunoglobulin/T-cell receptor (Ig/TCR) gene rearrangement-based Minimal Residual Disease (MRD) evaluation was centrally assessed for patients who reached complete remission after the first induction cycle, on BM samples after induction (MRD1). MRD was centrally assessed by real-time quantitative allele-specific oligonucleotide PCR and interpreted according to EuroMRD group guidelines [20][21][22].

Statistical analysis
Comparisons for categorical and continues variables between IDH1 Mut or IDH2 Mut and IDH WT subgroups were performed with Fisher's exact test and Mann-Whitney test, respectively. Overall survival (OS) was calculated from the date of diagnosis to the last follow-up date censoring patients alive. The cumulative incidence of relapse (CIR) was calculated from the complete remission date to the date of relapse censoring patients alive without relapse at the last follow-up date. Relapse and death in complete remission were considered as competitive events. Univariate and multivariate analyses assessing the impact of categorical and continuous variables were performed with a Cox model. Proportional-hazards assumption was checked before conducting multivariate analyses. In univariate and multivariate analyses, age and log10(WBC) were considered as continuous variables. All analyses were stratified on the trial. Variables with a p value less than 0.1 in univariate analysis were included in the multivariable models. Statistical analyses were performed with STATA software (STATA 12.0 Corporation, College Station, TX). All p-values were two-sided, with p < 0.05 denoting statistical significance. Circos plots were generated using R software.

Incidence of IDH1 and IDH2 mutations in 1085 T-ALL
A total of 51 (4%) mutations, mainly clonal, in either IDH1 or IDH2 were apparent in 49 cases ( Fig. 1a and Additional file 1: Table S2 . IDH1 mutations were identified in 19 T-ALL cases (2%) and IDH2 mutations in 32 cases (3%). IDH1/2 Mut were mutually exclusive except in 2 cases. The IDH2 R140Q mutation was the most prevalent mutation affecting IDH2 (n = 25, 78%). We identified 7 IDH1 mutations located in the R132 hotspot (37% of IDH1 mutations), 3 cases with IDH1 R132C mutation, 2 with IDH1 R132S , 1 with IDH1 R132H and IDH1 R132G mutation. The most common IDH2 mutations in AML occur at R140 followed by residue IDH2 R172 . The latter mutation is virtually the only IDH mutation found in angio-immunoblastic T cell lymphoma, reported in about 30% of cases (Additional file 2: Fig. S1) [23]. IDH2 R172 mutation has also been rarely and inconsistently described in peripheral T-cell lymphoma not otherwise specified (NOS) with T-follicular helper (T FH ) phenotype [24,25]. In striking contrast, IDH2 R172 was not reported in our series of T-ALL. IDH1 R132 , the most frequent IDH1 mutation reported in our cohort, has recently been recognized to cooperate with NOTCH1 activation in a T-ALL mouse model [26]. These results highlight the specific consequence associated with IDH1/2 Mut subtype during immature T-cell development.
Interestingly, contrary to IDH2-mutated cases, IDH1 Mut did not statistically differ from IDH WT patient regarding age, immunophenotype or mutational co-occurrence.
In multivariate analysis considering variables associated with CIR and OS in univariate analyses as covariates, IDH2 Mut predicted a trend for lower OS (HR: 1.98, 95%CI (0.86-4.57); p = 0.11) and statistically higher CIR (SHR, 4.06, 95%CI (1.84-8.96), p = 0.001) even after adjustment on the 4-gene NOTCH1/FBXW7/RAS/PTEN (NFRP) classifier which identified poor prognosis patients in both GRAALL and FRALLE trials [3,4]. Conversely to IDH-2 Mut , IDH1 Mut was not associated with poor prognostic impact in T-ALL (4y-CIR: 25% vs 29%, p = 0.75 and 4y-OS: 80% vs 71%, p = 0.61). We provide the largest comprehensive analysis of IDH1 and IDH2 mutations in T-ALL and highlight for the first time both their clinical profile and, most importantly, the extremely poor prognosis impact associated with IDH-2 Mut . We describe the specific oncogenetic landscape of IDH1/2 Mut and interestingly report that IDH2 Mut T-ALL conversely to IDH1 Mut were associated with an immature phenotype and alterations such as RAS mutations, transcription factors alterations (ETV6, IKZF1) and epigenetic regulators alterations (TET2, DNMT3A).
Recent studies have shed light on new prognostic factor in T-ALL allowing sharper prediction of the risk of relapse (e.g., NFRP classifier, level of MRD1, IKZF1 alterations) [3,4,27]. Despite this, a significant number of T-ALL relapses remain unpredicted, so new predictive markers are needed, given the extremely poor prognosis associated with T-ALL relapse. We therefore consider that IDH2 Mut T-ALL cases should be identified at diagnosis to benefit from therapeutic intensification and/or specific IDH2 Mut inhibitors [15]. Table 1 Clinico-biological and outcome characteristics of adult and pediatric T-ALL (GRAALL and FRALLE protocols) according to IDH1/2 status p-values < 0.05 are indicated in bold MRD1 correspond to MRD evaluation after induction and was performed by allele-specific oligonucleotides polymerase chain reaction. T-cell receptor status and oncogenic were performed as described in supplemental methods. IDH1 Mut and IDH2 Mut were statistically compared to IDH1 WT and IDH2 WT patients, respectively T-ALL: T-cell acute lymphoblastic leukemia; WBC, white blood count; CNS, central nervous system; ETP, early thymic precursor; High Risk classifier, NOTCH1/FBXW7-RAS/ PTEN classifier as previously described [3,4]; CR, complete remission; MRD, minimal residual disease; Allo-HSCT, allogenic hematopoietic stem cell transplantation; CIR, cumulative incidence of relapse; OS, overall survival; HR: hazard ratio, SHR: specific hazard ratio, CI: confidence interval 1