ARTICLE - Acute Lymphoblastic Leukemia Genomics improves risk stratification of adults with T-cell acute lymphoblastic leukemia enrolled in measurable residual disease-oriented trials Celia González-Gil,1 Mireia Morgades,2+ Thaysa Lopes,1+ Francisco Fuster-Tormo,1 Jesús García- Chica,1 Ran Zhao,3 Pau Montesinos,4 Anna Torrent,2 Marina Diaz-Beya,5 Rosa Coll,6 Lourdes Correspondence: E.G. Ferrer Hermosín,7 Santiago Mercadal,8 José González-Campos,9 Lurdes Zamora,2 Teresa Artola,10 egenesca@carrerasresearch.org Ferran Vall-Llovera,11 Mar Tormo,12 Cristina Gil-Cortés,13 Pere Barba,14 Andrés Novo,15 Jordi Ribera,1 Received: April 4, 2022. Teresa Bernal,16 Paula López de Ugarriza,16 María-Paz Queipo,17 Pilar Martínez-Sánchez,18 Alicia Accepted: October 14, 2022. Giménez,18 Teresa González-Martínez,19 Antonia Cladera,20 José Cervera,4 Rosa Fernández- Early view: November 3, 2022. Martín,21 María Ángeles Ardaiz,22 María Jesús Vidal,23 Ángela Baena,24 Nuria López-Bigas,25 Anna Bigas,1,26 Jaroslaw Maciejewski,27 Alberto Orfao,28 Josep Maria Ribera1,2 and Eulalia Genescà1 https://doi.org/10.3324/haematol.2022.281196 ©2023 Ferrata Storti Foundation 1 Institut d’Investigació contra la Leucemia Josep Carreras (IJC), Campus ICO-Germans Trias i Published under a CC BY-NC license Pujol, Universitat Autònoma de Barcelona, Barcelona, Spain; 2Departament d’Hematologia Clínica, ICO-Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Barcelona, Spain; 3Department of Quantitative Health Sciences and Leukemia Program, Department of Hematology and Medical Oncology, Cleveland Clinic, Cleveland, OH, USA; 4Hospital Universitari i Politècnic La Fe, Valencia, Spain; 5Servei d’Hematologia Clínica, Hospital Clínic de Barcelona, Barcelona, Spain; 6Institut Català d’Oncologia (ICO), Hospital Josep Trueta, Girona, Spain; 7 Servicio Hematología Clínica, Hospital de Jerez, Jerez de la Frontera, Spain; 8Servei d’Hematologia Clínica, Hospital Duran i Reynals-ICO, Hospitalet del Llobregat, Spain; 9Servicio Hematología Clínica, Hospital Vírgen del Rocío, Sevilla, Spain; 10Servicio Hematología Clínica, Hospital Universitario de Donostia, Donostia, Spain; 11Servicio Hematología Clínica, Hospital Mútua de Terrassa, Terrassa, Spain; 12Hospital Clínico Universitario, Instituto de Investigación INCLIVA, Valencia, Spain; 13Servicio Hematología Clínica, Hospital General de Alicante, Alicante, Spain; 14Servicio Hematología Clínica, Hospital Universitari de la Vall d’Hebron, Barcelona, Spain; 15Servicio Hematología Clínica, Hospital Son Espases, Palma de Mallorca, Spain; 16 Servicio Hematología Clínica, Hospital Central de Asturias, Instituto de Investigación Sanitario del Principado de Asturias (ISPA), Instituto Oncológico Universitario del Principado de Asturias (IUOPA), Oviedo, Spain; 17Servicio Hematología Clínica, Hospital Virgen de la Victoria, Málaga, Spain; 18Servicio Hematología Clínica, Hospital 12 de Octubre, Madrid, Spain; 19Servicio Hematología Clínica, Hospital Universitario de Salamanca, Salamanca, Spain; 20Servicio Hematología Clínica, Hospital Son LLátzer, Palma de Mallorca, Spain; 21Servicio Hematología Clínica, Hospital Insular de Gran Canarias, Las Palmas de Gran Canaria, Spain; 22Servicio Hematología Clínica, Complejo Hospitalario de Navarra, Pamplona, Spain; 23Servicio Hematología Clínica, Complejo Hospitalario de León, León, Spain; 24Servicio Hematología Clínica, Complejo Hospitalario de Jaén, Jaén, Spain; 25Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain; 26Program in Cancer Research, Institut-Hospital del Mar d’Investigacions Mèdiques, CIBERONC, Barcelona, Spain; 27Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA and 28Centro de Investigación del Cáncer (IBMCC-CSIC/USAL), Departamento de Medicina, Universidad de Salamanca, Instituto Biosanitario de Salamanca, CIBERONC, Salamanca, Spain + MM and TL contributed equally. Abstract Genetic information has been crucial to understand the pathogenesis of T-cell acute lymphoblastic leukemia (T-ALL) at diagnosis and at relapse, but still nowadays has a limited value in a clinical context. Few genetic markers are associated with the outcome of T-ALL patients, independently of measurable residual disease (MRD) status after therapy. In addition, the prognostic relevance of genetic features may be modulated by the specific treatment used. We analyzed the genetic profile of 145 T-ALL patients by targeted deep sequencing. Genomic information was integrated with the clinical- biological and survival data of a subset of 116 adult patients enrolled in two consecutive MRD-oriented trials of the Haematologica | 108 - April 2023 969 ARTICLE - Genomics improves risk stratification in T-ALL C. González-Gil et al. Spanish PETHEMA (Programa Español de Tratamientos en Hematología) group. Genetic analysis revealed a mutational profile defined by DNMT3A/ N/KRAS/ MSH2/ U2AF1 gene mutations that identified refractory/resistant patients. Mutations in the DMNT3A gene were also found in the non-leukemic cell fraction of patients with T-ALL, revealing a possible mutational-driven clonal hematopoiesis event to prime T-ALL in elderly. The prognostic impact of this adverse genetic profile was independent of MRD status on day +35 of induction therapy. The combined worse-outcome genetic signature and MRD on day +35 allowed risk stratification of T-ALL into standard or high-risk groups with significantly different 5- year overall survival (OS) of 52% (95% confidence interval: 37-67) and 17% (95% confidence interval: 1-33), respectively. These results confirm the relevance of the tumor genetic profile in predicting patient outcome in adult T-ALL and highlight the need for novel gene-targeted chemotherapeutic schedules to improve the OS of poor-prognosis T-ALL patients. Introduction genetic profiles associated with patient outcome within specific clinical trials is essential for improved risk stratifi- Acute lymphoblastic leukemia (ALL) is an infrequent ag- cation and to move towards more personalized medicine. gressive cancer being more common in children.1 ALL in- In the study reported here, we screened DNA from 145 T- cludes B- and T-cell lineage subtypes. T-cell acute ALL patients, based on a custom-built T-ALL-oriented lymphoblastic leukemia (T-ALL) accounts for 10–15% of next-generation sequencing panel (NGSp). Of these, 116 pediatric and 20–25% of adult cases.2,3 B-cell precursor ALL were adult patients treated as part of two consecutive and T-ALL share some genetic features4 and are considered high-risk MRD-oriented trials by the Spanish PETHEMA together for treatment in many trials. The classical prog- (Programa Español para el Tratamiento de Hemopatías Ma- nostic factors such as age, white blood cell (WBC) count, lignas) group. Our goal was to identify gene-mutational pro- measurable residual disease (MRD) and some genetic fea- files (point mutations, small insertions and deletions and tures have been used to predict outcome and stratify the indels) at diagnosis that could help to predict response to therapy in both types of ALL.2,5-7 Although treatment re- therapy and outcome. sponse via MRD monitoring represents a milestone in vir- tually all ALL trials, MRD is not available at diagnosis and might not finely predict relapse in adult ALL patients,6-8 emphasizing the need for additional prognostic markers Methods that may be readily available for these patients at diagnosis. Targeted deep sequencing Studies by the cooperative Group for Research in Adult DNA samples or cryopreserved leukemic cells from T-ALL Acute Lymphoblastic Leukemia (GRAALL) demonstrated patients (n=145) were collected from different national bio- the prognostic relevance of some genetic markers in adult banks (see the Online Supplementary Appendix for informa- T-ALL.7,9 The combination of mutations in the tion). The mutational profile was obtained employing a NOTCH1/FBXW7 signaling pathway, in the absence of custom gene panel (SureSelectXT HS Target Enrichment N/KRAS gene mutations and alterations in PTEN, together System for Illumina Multiplexed Sequencing Platforms, Agi- with adequate MRD clearance, identified a group of adult lent Technologies, Santa Clara, CA, USA) and sequencing in T-ALL patients with a good prognosis, who might not bene- a MiSeq instrument (Illumina, San Diego, CA, USA). Muta- fit from further intensification treatment by allogeneic tions were retrieved applying a home-made standard gold stem cell transplantation (allo-SCT).7 MRD and the onco- pipeline analysis (see detailed methods section in the On- genetic pattern were independent prognostic factors used line Supplementary Appendix). Final selected variants were for patient stratification in the current protocols of the classified as pathogenic, benign or of uncertain significance GRAALL Group. if the majority (≥6/10), final version of the in silico predictors It is well established that genetics plays a key role in the identified the variant as being in one of the categories. In- development and progression of T-ALL. The disease is sus- formation about predictors was extracted from dbNSFP18 tained by genetic abnormalities that often determine the via ANNOVAR annotation. Benign variants were excluded stage of maturation arrest (e.g., MLL-r, CALM::AFA10, HOXA- from further analyses. Information of genes and regions in- r, TLX1-r, TLX3-r, SIL::TAL), and/or the proliferation and/or cluded in the panel has been previously described19 and it survival rate of leukemic cells (e.g., CDKN2A/B, K/NRAS, is shown in an Excel file in the Online Supplementary Ap- NOTCH1/FBXW7, NUP214::ABL1, JAK/STAT).10,11 However, the pendix. prognostic relevance of a genetic profile identified in a group of T-ALL patients may be influenced by the treat- Patients and treatment protocols ment protocol used, since several gene mutations generate For clinical and outcome correlations, 29 patients from our resistance to treatment.12–17 Therefore, assessment of the initial cohort were excluded (see the Online Supplementary Haematologica | 108 - April 2023 970 ARTICLE - Genomics improves risk stratification in T-ALL C. González-Gil et al. Appendix). Thus, a representative cohort of 116 adult T-ALL variants were observed in nine (6%) patients (Figure 1A). patients were studied. The diagnosis of T-ALL was made Of patients with variants, 92% (125/136) carried missense according to the World Health Organization criteria20 and mutations and 32% (44/136) had nonsense mutations. the cytogenetic classification was based on the Genesca Genes with predominate missense variants were JAK3 et al.19 study, instead of the classical cut-off of five genetic (96.3%), FBXW7 (92.3%), FAT1 (100%), JAK1 (100%) and NRAS alteration21 (see the Online Supplementary Appendix). Pa- (100%). In turn, insertions, deletions, and indels of up to tients were treated with two consecutive MRD-oriented 50 nucleotides, were identified in 67% (91/136) of the high-risk adult ALL protocols. Detailed information of both cases. Of these, 81% (74/91) presented short insertions (52 trials is shown in the Online Supplementary Appendix and frameshift and 38 non-frameshift); 42% (38/91) had short the Online Supplementary Figure S1. In order to homogen- deletions (28 frameshift and 11 non-frameshift); and 12% ize patient allocation according MRD levels at the end of (11/91) had frameshift indels (small insertions or deletions). induction treatment, we established a MRD cut-off of 0.1 PTEN (71·4%) and IL7R (80%) were the two genes with the to define a patient as good responder (≤ 0.1%) in the ALL- highest percentage of indels. Globally, combinations of AR [Ph-]-03 trial (clinicaltrials gov. Identifier: point mutations and indels were observed in 60% (81/136) NCT00853008), similarly as it was established for the ALL- of patients, whereas isolated indels mutations were de- HR [Ph-]-11 trial (clinicaltrials gov. Identifier: NCT01540812). tected in 4% (6/136) of cases. According to the functional Informed consent was obtained from all patients. Samples impact assigned to each variant, 89% (121/136) of patients and clinical data were stored in accordance with the dec- presented pathogenic variants and 83% (113/136) had vari- laration of Helsinki. The study was approved by the Insti- ants of uncertain significance, and only 15 of them exclus- tutional Review Board of the Hospital Germans Trias i Pujol. ively presented variants of uncertain significance. Almost all pathogenic variants (98%) were missense mutations, Statistical analyses whereas most variants of uncertain significance were non- Genes mutated in at least five patients were included in sense variants (16%) or indels (53%) (Online Supplementary the initial screening for impact on OS and cumulative inci- Figure S2). dence of relapse (CIR), as individual genes, except for Recurrently mutated genes found in at least five patients N/KRAs and JAK1/JAK3 mutations that were assessed to- are listed in Figure 1B and all had been previously reported gether since are isoforms, respectively. OS curves were in T-ALL. Mutations were found in: i) transcription factor plotted using the Kaplan–Meier method and compared by tumor suppressor genes (PTEN, BCL11B, RUNX1, GATA3, the log-rank test. CIR was estimated by competing risks ETV6)23–27; ii) epigenetic regulators (PHF6, DNMT3A, EP300, analysis using cumulative incidence functions. Gray’s test KMT2C)27–29; iii) DNA mismatch repair genes (MSH2)30; iv) was used to compare CIR curves. A Cox proportional ha- genes expressing ribosomal protein (RPL5)31; v) genes in- zard regression model was used to identify predictive fac- volved in RNA splicing (U2AF1)32; and vi) signaling pathways tors for OS. Statistical significance was concluded for that regulate T-cell development, such as the RAS/MAPK two-sided values of P<0.05. All statistical analyses were signaling (NRAS)33 WNT (FAT1, FAT3),34,35 IL7R-JAK-STAT performed using SPSS version 24 (IBM Corp. Armonk, NY, (JAK3, JAK1, IL7R, DNM2)36-39 and the NOTCH1/FBXW7 sig- USA), GraphPad Prism® version 8 (GraphPad Software Inc., nalling.40,41 The latter was found in 71% (97/136) of patients La Jolla, CA, USA) and R version 4.1.0. (NOTCH1 and FBXW7), confirming the importance of this Combinations of mutations (affecting ≥12 patients) and signaling pathway in the development of T-ALL. biological traits at the time of diagnosis were pairwise as- sessed using Fisher’s exact test. Multiple associations Genetic-biological associations were corrected using a Benjamini-Hochberg q test, with Major biological features at diagnosis were available for significance concluded for co-existence for values of 143/145 patients and their data were used to classify them q<0.05. by: i) age group: <18, 18-35, 36-60 and >60 years; ii) im- munophenotype: ETP-ALL, pre-T, cortical, mature T-ALL and not determined immunophenotype (NDI); and iii) cyto- genetic groups: 0-2 abnormalities, a complex karyotype Results with at least three abnormalities (CK ≥3) and non-evalu- Somatic mutational landscape of T-cell acute able (NE) cases.19 Previously reported correlations between lymphoblastic leukemia genetic variants occurring in genes mutated in ≥12 patients The presence of point mutations and insertions and dele- and diagnostic traits included a direct association between tions (indels) was investigated in 145 T-ALL patients by TDS the presence of variants in DNMT3A gene and both ETP- using a customized NGSp. Overall, genetic variants were ALL (OR=8.56; q= 0.02)42,43 and advanced age.43 In our detected in 136 of 145 patients (94%) for a median of four analysis, however, DNMT3A mutations were restricted to genetic variants and three mutated genes per patient. No the oldest patients (>60 years [y]) (OR=9.6; q= 0.08) and Haematologica | 108 - April 2023 971 ARTICLE - Genomics improves risk stratification in T-ALL C. González-Gil et al. A B C Figure 1. Genetic profile of T-cell acute lymphoblastic patients at diagnosis. (A) Frequency of variants per patient in the cohort (n=145). (B) Frequency of patients showing recurrently mutated genes (cut-off of ≥5 mutations/gene). (C) Pairwise associations observed between the recurrently mutated genes and the biological characteristics of the disease at presentation. Positive and negative correlations are depicted as magenta and green circles, respectively. Circle diameters indicate the degree of significance. Y: years; ETP-ALL: early T-cell precursor acute lymphoblastic leukemia; NDI: not determined immunophenotype; abn: abnormal- ities; CK: complex karyotype; NE: non-evaluable karyotype. were not associated to adolescents and young adults (AYA, and mutational profiles identified by TDS on patient out- 18-35 y) (OR=0.09; q=0.07). Other new significant associ- come was restricted to 116 patients homogeneously ations included a lower incidence of FBXW7 variants in treated in two high-risk consecutive MRD-oriented ETP-ALL (OR=0; q=0.07), higher frequency of FAT1 gene PETHEMA trials whose clinical, biological and outcome variants in patients with an NE karyotype (OR=6.36; data were complete. Comparison of the outcome of the q=0.07) at the expense of a negative association between sequenced (n=116) versus non-sequenced patients (n=116) this gene and patients with 0-2 abnormalities (OR=0.09; did not reach significant differences in terms of OS. Thus, q=0.02), and association of NRAS mutations with and ETP- our cohort was representative of the patients included in ALL immunophenotype (OR=6.13; q=0.07) that contrasts both trials. Like other adult T-ALL cohorts, this was mainly with the negative association of these mutations with the composed of males of median age (37 y). Overall, CR rate cortical subtype (OR=0; q=0.07) (Figure 1C). (Induction-1 + Induction-2) for the whole series was 88%, being 83% for cases who achieved MRD levels <0.1% at the Prognostic significance of gene mutations and end of Induction-1. Most patients (72%) were treated ac- mutational profiles cording to the chemotherapy schedules proposed in the The analysis of the clinical impact of the genetic variants trials. The remaining patients were assigned to allo-SCT. Haematologica | 108 - April 2023 972 ARTICLE - Genomics improves risk stratification in T-ALL C. González-Gil et al. Table 1. Prognostic impact of genes found to be recurrently mutated in the PETHEMA T-cell acute lymphoblastic leukemia Number of patients OS 5 years, CIR 5 years, (N=116) % (95% CI) % (95% CI) Gene Patients Patients Patients Patients with Patients with Patients with without without P without mutations mutations mutations mutations mutations mutations FBXW7 20 96 62 (36-88) 32 (21-43) 0.032 - - DNMT3A 10 106 13 (0-37) 38 (27-49) 0.001 - - N/KRAS 13 103 21 (0-45) 39 (28-50) 0.023 85 (37-97) 50 (39-61) MSH2 5 111 20 (0-55) 37 (26-48) 0.036 - - U2AF1* 5 111 20 (0-55) 50 (40-60) 0.003 - - results expressed as 2-year overall survival (OS) probability. CI: confidence interval; CIR: cumulative incidence of relapse. * The 5 year CIR and OS probabilities for the whole series hematopoiesis of indeterminate potential (CHIP).45–47 We was 54% (95% confidence interval [CI]: 43%-64%) and 36% grouped mutations in these two genes into the aging- (95% CI: 26-46), respectively. genes cluster. In turn, N/KRAS, or MSH2 gene mutations In order to identify mutations in genes affecting patient have previously been described as being involved in gen- outcome, we first assessed the impact on OS and CIR of erating resistance to ALL treatment.13,14,16 We named this each individual gene mutated in at least five patients. group of gene mutations as treatment-resistance-gene Strikingly, we could not confirm the previously reported cluster. Both clusters identified patients with a similarly association between NOTCH1 mutations and prolonged OS poor response to treatment (Online Supplementary Table (Online Supplementary Figure S3A), or the lower CIR rate S1). Overall, 25% (29/116) of patients harbored mutations (data not shown).9,44 A more in-depth analysis of the dis- in genes conferring a worse outcome with more frequent tinct NOTCH1 gene variants identified with respect to their slow response to initial treatment, high toxicity and early functional impact (pathogenic vs. uncertain significance) death (Figure 2). Of note, OS of patients with co-occur- (Online Supplementary Figure S3B) and according to the rence of more than one worse prognosis mutation was variant allele frequency (VAF) with a cut-off of 25% to de- similar to that of patients carrying on only one worse out- fine a variant as clonal (Online Supplementary Figure S3C), come mutation (P=0.750). Therefore, we subsequently as- confirmed the lack of prognostic impact of NOTCH1 vari- sessed the global prognostic impact of all adverse gene ants on OS in our T-ALL patients. In contrast, patients mutations collectively as a variable named worse-outcome carrying FBXW7 mutations, were associated with a better genetics (WOG) by univariable and multivariable analyses. OS (Table 1). Sixty-five percent of patients carrying muta- Similarly, patients carrying mutations in FBXW7 were also tions in FBXW7 (13/20) also presented a mutation in the included as a variable named good-outcome genetics NOTCH1 gene, with no differences in OS between both (GOG). Basal characteristics at the time of diagnosis and groups (FBXW7 only vs. FBXW7 and NOTCH1) (data not treatment response of patients belonging to the WOG- and shown), suggesting that the good outcome observed in WOG+ groups are shown in Table 2 (Online Supplementary patients carrying FBXW7 mutations could be attributed to Table S2 for patients GOG+ and GOG-). Importantly, only a specific dysfunction of the FBXW7 protein (Online Sup- one patient presented mutations in FBXW7 (GOG) and plementary Figure S3D). In addition, patients showing U2AF1 (WOG), whose death was associated to transplant- DNMT3A, N/KRAS, MSH2 and/or U2AF1 mutations had a related mortality. This patient was included in the WOG lower OS than patients with no mutations in these genes group, to maintain both variables independent. Age, WBC (Table 1). It is of note that only patients with mutations in count, central nervous system (CNS) infiltration, ETP-ALL N/KRAS genes showed a high probability of CIR (Table 1). phenotype, CK ≥3 alterations, MRD level at the 0.1% cut- Based on these results, we grouped mutations in genes off, WOG and GOG were included in the univariable analy- associated with a worse outcome according to the same sis (Table 3). The two treatment protocols were also homeostatic processes affected and basal biologic char- included in the analysis to exclude any possible protocol- acteristics. Thus, patients with mutations in DNMT3A and dependent bias. By multivariable analysis, MRD level ≥0.1% U2AF1 were older (median age 54 y, P<0.001) and more fre- after induction-1 (day +35) and the WOG cluster were in- quently showed an ETP-ALL immunophenotype (P<0.001). dependently associated with shorter OS rates with hazard Mutations in these two genes were consistent with clonal ratios (HR) of 2.187 (range, 1.087-4.400) and 3.040 (range, Haematologica | 108 - April 2023 973 ARTICLE - Genomics improves risk stratification in T-ALL C. González-Gil et al. Figure 2. Scheme of the genetic profile of each T-cell acute lymphoblastic patient, its response and evolution during treatment. Only genes recurrently mutated in ≥5 patients are shown. Each mutation is indicated by a square: brown squares correspond to genes contained in the worse-outcome genetics (WOG) signature; dark green squares correspond to mutations in the FBXW7 gene (good-outcome genetics [GOG] signature) and pink squares correspond to other mutated genes. Treatment response and patient evolution data are shown at the bottom. Induction + 14d indicates the percentage of blast cells in bone marrow 14 days after starting induction therapy; induction + 35d corresponds to measurable residual disease (MRD) values at the end of the first induction blocks (induction 1); induction-2 indicates patients that received or not an Induction-2 treatment block. Consolidation corresponds to MRD values at the end of consolidation chemo-block. Post-consolidation indicates treatment choice (allogeneic stem cell transplantation or chemotherapy) based on MRD values at the end of the consolidation treatment. On the right, the percentage of cases mutated in the different genes are indicated. NA: not available. 1.531-6.035) respectively (Table 3). The multivariable analysis clonal hematopoiesis of indeterminate potential (CHIP), we for CIR, did not validate the predictive role of N/KRAS mu- investigated those variants in the non-leukemic fraction of tations observed in the univariable analysis (Online Supple- peripheral blood cells of the same patients. For this pur- mentary Table S3). In fact, we could not identify any variable pose, genomic DNA from purified polymorphonuclear cells to predict CIR risk in our adult T-ALL cohort. of nine patients carrying mutations in these two genes was Based on these results, we re-stratified our patients ac- sequenced. However, no genetic variants of the U2AF1 gene cording to their MRD level on day +35 after induction-1 and were identified in the polymorphonuclear cell fraction of the presence or absence of WOG mutations. Two groups of the two patients with mutations in this gene in their leu- patients were identified: standard-risk patients with MRDlow kemic cells. By contrast, identical DNMT3A mutations were plus WOG- (5-y OS of 52 %, 95% CI: 37-67, n=65); and high- found at lower or similar (VAF) in the polymorphonuclear risk patients that included MRDhigh and WOG- (n=11), MRDlow fraction of seven of seven cases whose leukemic cells had plus WOG+(n=9) and MRDhigh plus WOG+ (n=4) patients re- mutations in this gene (Table 4), suggesting that these mu- spectively, with a 5-y OS of 17% (95% CI: 1-33) (Figure 3). tations were already present in a common lympho-myeloid early stem cell precursor and appear before the leukemia Tracking aging cluster mutations in non-leukemic cells arises. Moreover, in two patients, copy number alterations In order to determine whether the DNMT3A and U2AF1 gen- and mutations in the DNMT3 gene were apparent in the etic variants associated with the aging-genes cluster ident- blast cells, highlighting the importance of this gene in the ified in our adult T-ALL patient cohort were related to development of their leukemia. Further analysis of non- Haematologica | 108 - April 2023 974 ARTICLE - Genomics improves risk stratification in T-ALL C. González-Gil et al. hematopoietic cells would be needed to rule out a germinal response to initial chemotherapy treatment and low CR basis for these alterations, although the in silico predictors rates. These patients more often needed two induction indicated that those variants had an actual or potential im- cycles to achieve a good MRD response which could also pact on the function of the DNMT3A protein, which argues account for the higher rate of early deaths, due to toxicity, in favor of them being of non-germinal origin (Table 4). observed at the end of induction treatment, and thereby their shorter OS. However, our WOG signature did not have an impact on the CIR, since did not identify patients at high versus low risk of relapse. This may be due to the very poor Discussion clinical outcome of the patients with a WOG mutational This study describes a gene mutational signature, named profile, yet observed at early stages of the treatment, that WOG, that identifies high-risk T-ALL patients with a slow would eliminate the possibility of a higher rate of sub- Table 2. Clinical-biological characteristics and response to treatment of T-cell acute lymphoblastic leukemia patients grouped according to their gene mutational profile. Genetic group P Total (N=116) WOG- (N=87) WOG+ (N=29) Patient-related features Median age, years (range) 34 (16-61) 44 (19-60) 0.068 37 (16-61) Sex, M/F 71/16 15/14 0.001 86/30 Disease-related features Median WBC, x109/L (range) 66.3 (0.5-525.4) 23.4 (0.6-495) ECOG, N (%) 0 31/83 (37) 12/29 (41) 43/112 (38) 1 42/83 (51) 11/29 (38) 0.546 53/112 (47) 2 9/83 (11) 5/29(17) 14/112 (13) ≥3 1/83 (1) 1/29 (4) 2/112 (2) Adenopathies, N (%) 37/72 (51) 18/26 (69) 0.116 55/98 (56) Splenomegaly, N (%) 30/83 (36) 9/28 (32) 0.701 39/111 (35) Hepatomegaly, N (%) 20/82 (24) 5/28 (18) 0.476 25/110 (23) Mediastinal mass, N (%) 41/84 (49) 8/29 (28) 0.047 49/113 (43) CNS involvement, N (%) 10/83 (12) 4/27 (15) 0.743 14/110 (13) Immunophenotype, N (%) ETP-ALL 8/81 (10) 14/29 (48) 22/110 (19) Pre-T 15/81 (18) 4/29 (14) <0.001 19/110 (16) Cortical 42/81 (52) 5/29 (17) 47/110 (41) Mature 16/81 (20) 6/29 (21) 22/110 (19 Cytogenetics, N (%) 0-2 abn 49/87 (56) 17/29 (59) 66 (57) 0.926 CK ≥3 8/87 (9) 2/29 (7) 10 (9) NE 30/87 (35) 10/29 (34) 40 (34) Response-related features Slow response at day +14, N (%) 26/72 (36) 22/27 (82) <0.001 48/99 (48) Induction cycles to CR, N (%) 1 77/87 (89) 16/29 (55) <0.001 93 (80) 2 10/87 (11) 13/29 (45) 23 (20) CR post Ind-1, N (%) 81/87 (93) 14/29 (48) <0.001 95 (82) CR (Ind-1 + Ind-2), N (%) 82/87 (94) 20/29 (69) <0.001 102 (88) MRD <0.1% at day +35, N (%) 65/76 (86) 9/13 (69) 0.221 74/89 (83) Treatment Chemotherapy, N (%) 54/70 (77) 5/12 (42) 59/82 (72) 0.031 Allo-SCT, N (%) 16/70 (23) 7/12 (58) 23/82 (28) Results expressed as number of cases/total cases (percentage). WOG: worse-outcome genetics; measurable residual disease (MRD) values were considered for those patients that reach complete remission (CR); M: male; F: female; WBC: white blood cells; ECOG: Eastern Cooperative Oncology Group; CNS: central nervous system; ETP-ALL: early T-cell precursor acute lymphoblastic leukemia; abn: abnormalities; CK: complex karyotype; day +14: 14 days after induction treatment; day +35: 35 days after induction treatment; allo-SCT: allogeneic stem cell transplan- tation. Ind: induction. Haematologica | 108 - April 2023 975 ARTICLE - Genomics improves risk stratification in T-ALL C. González-Gil et al. sequent relapses. Thus, the WOG mutational signature mediate-risk group (those with MRDhighplus WOG- and allows to identify at diagnosis those patients who will be MRDlow plus WOG+) within the high-risk group. In addition, resistant and refractory to conventional frontline treatment. other genes that did not reach statistical significance The WOG signature was an independent risk factor for OS, when analyzed individually for OS impact, due to the li- together with the end-induction MRD levels (0.1% cut-off) mited number of mutated patients for the specific gene indicating that the two parameters cooperate to confer a assessed (i.e., patients with JAK3 and JAK1 mutations), poor outcome to T-ALL patients. Thus, we demonstrated could also impair the selection of a very low-risk group of that the WOG signature contributes to the improved risk- patients. The assessment of the WOG genetics in the cur- stratification of adult T-ALL patients, confirming the rel- rent ALL-PETHEMA trial (ALL19), in which a more sensitive evance of genetic data in this clinical setting. The lack of MRD cut-off is employed, will help to corroborate the util- co-occurrence observed in the genes included in the WOG ity of these genetic marker to stratify adult T-ALL patients signature (Online Supplementary Figure S4) highlights the within PETHEMA trials. importance of the contribution of each individual gene in The WOG signature identified here is defined by the mu- the outcome significance of the WOG signature, although tational status of genes known to be involved in ALL treat- we could not demonstrate its individual contribution in ment resistance.13-16 These included activating mutations the multivariable analysis except for patients with in the N/KRAS genes (n=13). The two G-proteins (N/KRAS) DNMT3A mutations (data not showed), probably due to are involved in the RAF/MEK/ERK signaling pathway48 and the limited number of patients included in each individual have been identified as being responsible for steroid re- gene-group. Here also, the impact of WOG variable was sistance.12,13 Importantly, these mutations are associated probably underestimated since the MRD threshold em- with poor prognosis in both pediatric and adult T-ALL.9,49 ployed in the two retrospective trials to discriminate pa- The WOG signature described here also included MSH2 tients with good versus worse response was not sensitive gene mutations (n=5) that affected the interaction with enough. With a more sensitive MRD cut-off, the number MSH3 and MSH6 proteins, respectively, and the formation of patients with MRDhigh would be higher and therefore the of MSH3-MSH2 and MSH6-MSH2 heterodimers, two com- WOG signature could contribute to discriminate an inter- ponents of the post-replicative DNA mismatch repair sys- Table 3. Prognostic factors for overall survival identified in the univariable and multivariable analyses in the PETHEMA adult T- cell acute lymphoblastic cohort. Univariable analyses Multivariable analyses Disease/patient feature N HR (95% CI) P N HR (95% CI) P Age* 95 1.007 (0.984–1.031) 0.540 - - - WBC count* 93 1.001 (0.999–1.003) 0.440 - - - CNS involvement No 82 Reference 0.391 - - - Yes 8 0.598 (0.185–1.937) ETP-ALL No ETP-ALL 77 Reference 0.168 - - - ETP-ALL 11 1.687 (0.803–3.544) Karyotype 0-2 abn. 59 Reference 0.052 - - - CK ≥3 6 2.623 (0.993–6.928) PETHEMA treatment protocol ALL-HR-11 69 Reference 0.633 - - - ALL-AR-03 26 1.162 (0.628–2.148) GOG Non-mutated 77 Reference 0.046 - - - Mutated 18 0.343 (0.120–0.981) WOG 76 Non-mutated 81 Reference 0.004 Reference 0.028 13 Mutated 14 2.636 (1.363 – 5.095) 2.187 (1.087 –4.400) MRD at day +35 <0.1% 74 Reference 0.001 74 Reference 0.001 ≥0.1% 15 3.339 (1.691 – 6.592) 15 3.040 (1.531 –6.035) Age and white blood cell (WBC) count were considered as continuous variables. N: number of cases; HR: hazard ratio; CI: confidence interval; * OS: overall survival; ETP-ALL: early T-cell precursor acute lymphoblastic leukemia; abn: abnormalities; CK: complex karyotype; CNS: central nervous system; GOG: good-outcome genetics; WOG: worse-outcome genetics; MRD: measurable residual disease. Haematologica | 108 - April 2023 976 ARTICLE - Genomics improves risk stratification in T-ALL C. González-Gil et al. tem (MMR).50 Under defective MMR function conditions, immature leukemic subtypes42,54-56 and like other epigen- blasts may lack the capacity to recognize mismatched etic regulators, they are thought to be an early event in DNA pairs, leading to the generation of chemoresis- leukemogenesis, conferring self-renewal properties on tance.14,15 Despite the pathogenic role of mutations in this uncommitted hematopoietic progenitors, facilitating the gene, limited information is available about its clinical rel- subsequent acquisition of secondary mutations.57,58 Im- evance, probably due to the low frequency of these mu- portantly, most DNMT3A mutations observed in the blast tations in adult T-ALL. Nevertheless, leukemic cells from cells were also present in the non-leukemic cell fraction of relapsed pediatric cases are enriched in MSH2 gene mu- polymorphonucleated cells of the same patients at lower tations, suggesting that relapse in these patients may be or similar VAF. It is of particular interest that the genetic sig- due to a drug resistance mechanism driven by MSH2 mu- nature that defines CHIP includes mutations in these two tations.17,51 The two other genetic components of WOG are genes at very low VAF.45,46 These genes have also been de- the DNMT3A (n=10) and U2AF1 (n=5) genes. U2AF1 gene scribed in AML at higher VAF.59,60 Together, these observa- mutations have been previously identified in adult and tions favor an explanation of a DNMT3A mutation-driven childhood T-ALL32,52 and predict poorer prognosis in de clonal hematopoiesis event in a common lymphoid-myeloid novo acute myeloid leukemia (AML) patients.53 However, as early progenitor that, together with other alterations, could far as we know, no data are available concerning the con- determine the transformation into AML or T-ALL. In contrast, sequences of this mutation in T-ALL. DMNT3A mutations we did not find U2AF1 mutations in non-leukemic cells, al- have previously been identified in older patients and in though we were able to investigate only a few T-ALL cases. A B C Figure 3. Prognostic stratification of adult T-cell acute lym- phoblastic patients according to overall survival defined by the presence of worse-outcome genetic mutations and measur- able residual disease status 35 days after starting therapy. (A) Overall survival (OS) according to measurable residual disease (MRD) levels at 4 years (y) showed rates of (95% confidence in- terval [CI]: 35-63) in patients with MRDlow (<0.1%) and 8% (95% CI: 0-23) for those with MRDhigh (≥0.1%). (B) OS according to worse-outcome genetics (WOG) mutational status at 5 y showed rates of 13% (95% CI: 0-26) in the WOG-mutated pa- tients (WOG+) and 45% (95% CI: 32-58) in non-mutated patients (WOG-). (C) OS according to WOG mutational status and MRD values (d+35) at 5 y was 52% (95% CI: 37-67) for patients with MRDlow (<0.1%) and WOG- (standard-risk-patients), compared with 17% (95% CI: 1-33) for high-risk patients including MRDhigh plus WOG-, MRDlow plus WOG+ and MRDhigh plus WOG+. Haematologica | 108 - April 2023 977 ARTICLE - Genomics improves risk stratification in T-ALL C. González-Gil et al. Table 4. DNMT3A genetic variants identified in patients associated with the aging cluster in the non-leukemic and leukemic cell. Functional impact of DNMT3A aa VAF VAF CNA DNMT3A mutations Patient ID Age, years Immunophenotype change leukemic cells non-leukemic cells status In silico COSMIC predictors Uncertain p.F827fs 28% 34% 2 .. significance TALL91 64 ETP-ALL Uncertain p.R771X 59% 3.6% 3 Pathogenic significance TALL95 61 ETP-ALL p.F732V 88% 38% 1 Pathogenic .. TALL93 78 ETP-ALL p.R882H 43% 3.5% .. Pathogenic Pathogenic TALL50 60 ETP-ALL p.R882H 48% 46% .. Pathogenic Pathogenic TALL101 48 Cortical p.R882C 50% 21% .. Pathogenic Pathogenic TALL46 57 ETP-ALL p.R882H 51% 40% .. Pathogenic Pathogenic p.D876E 41% 30% 2 Pathogenic .. TALL8 51 ETP-ALL Uncertain p.I715fs 45% 31% 2 .. significance ID: identifier; aa: amino acid; VAF: variant allelic frequency; CNA: copy number alteration; ETP-ALL: early T-cell precursor acute lymphoblastic leukaemia. RefSeq ID DNMT3A: NM_022552. The incidence of NOTCH1 and FBXW7 mutations in our pa- ing the induction or late intensification stages of the tients was similar to that reported in other adult and treatment). pediatric cohorts,40,44,61-63 but we found no association be- In conclusion, we describe a WOG mutational signature, tween mutations in NOTCH1 gene and patient outcome. In which identifies older, refractory/resistant high-risk T-ALL fact, the clinical impact of NOTCH1/FBXW7 mutations in patients with a poorer OS due to the suboptimal response adult T-ALL is still a matter of debate. Here we have to induction therapy. Patients in this group emerge as shown that patients with mutations in FBXW7, including candidates for novel, personalized frontline therapeutic or not mutations in NOTCH1, have a better outcome com- schedules. paring with patients carrying on only mutations in NOTCH1 gene, but this association do not reach statistical signifi- Disclosures cance in the multivariable analysis. The GRAALL group No conflicts of interest to disclose. showed that mutations in NOTCH1, together with FBXW7, identified patients with better event-free survival and OS, Contributions with an independent predictive value.44,61 They also CG-G performed the experiments and analyzed the data, showed that the combination of low-risk genetics (de- produced the figures and contributed to the writing process. fined by the presence of mutations in the NOTCH1 signal- MM did the statistical analyses. TL performed library prep- ing pathway [NOTCH1 and FBXW7] and wild-type N/KRAS arations; FF-T analyzed the sequencing data. JG-C devel- or PTEN) and MRD negativity, allowed identification of a oped the initial NGSp design. PM, AT, MD-B, RC, JR, LH, SM, fraction of adult T-ALL patients with a very good out- JG-C, LZ, TA, FV-L, MT, CG-C, PB, AN, TB, PLdU, M-PQ, PM-S, come7. However, the same cooperative group also showed AG, TG, AC, JC, RF, MAA, MJV and ÁB provided clinical data. that the favorable prognostic impact of NOTCH1/FBXW7 N-LB and AB provided support for the project through the mutations was influenced by the treatment protocol AECC T-ALL consortium. RZ and JM created Figure 1C. AO and used.61 Other studies in adult T-ALL cohorts have not been JMR contributed to the study conceptualization, data analy- able to confirm this benefit,62,64 whereas the large differ- sis and reviewed the manuscript. EG designed the study, re- ences in the prevalence of NOTCH1/FBXW7 mutations re- viewed the data, and wrote and reviewed the manuscript. All ported in other series may compromise the clinical impact authors have read and approved the manuscript. of these mutations in the studied cohort.65 Compared with the GRAALL trials,7,9 patients from the PETHEMA trials6,22 Acknowledgements included in this study are older, and were treated slightly We would like to thank Carmen Benet, Maria Paz Garrasta- different (i.e., they did not receive cyclophosphamide dur- zul, Irene García-Cadenas, Gemma Azaceta, Beatriz Soria, Haematologica | 108 - April 2023 978 ARTICLE - Genomics improves risk stratification in T-ALL C. González-Gil et al. Silvia Monsalvo, María Lourdes Amador, Xavier Ortín, Jesús ISCIII (PI19/01828 and PI19/01183), co-funded by ERDF/ESF, "A Feliu, Carlos Rodríguez, Irene Romero, María-Paz Martínez, way to make Europe"/"Investing in your future", CERCA/Gen- Mª Jesús Peñarrubia and Alberto Gimenez for providing eralitat de Catalunya SGR 2017 288 (GRC)/ “La Caixa”. C Gon- retrospective clinical data for this study. We would also like zález-Gil was supported by AGAUR grant (ref: 2020 FI_B2 to thank to Dr. Dr. Yasunobu Nagata and Dr. Brian P. Hobbs 00210). for help with the design of the morphological-genetic as- sociations analysis pipeline. Data-sharing statement The datasets used and/or analysed during the current Funding study are available from the corresponding author on rea- This project was supported by the AECC (GC16173697BIGA); sonable request. References 1. Yi M, Zhou L, Li A, Luo S, Wu K. 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