Somatic Mutations and Outcomes in CML Adolescent and Young Adults Compared to Children, Adults, and BCR::ABL1-positive ALL Patients

Somatic Mutations and Outcomes in CML Adolescent and Young Adults Compared to Children, Adults, and BCR::ABL1-positive ALL Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Somatic Mutations and Outcomes in CML Adolescent and Young Adults Compared to Children, Adults, and BCR::ABL1-positive ALL Patients Katerina Machova Polakova, Jitka Krizkova, Vaclava Polivkova, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5789724/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Apr, 2025 Read the published version in Leukemia → Version 1 posted 9 You are reading this latest preprint version Abstract Adolescent and young adult (AYA) patients with chronic myeloid leukemia in chronic phase (CML-CP) reportedly fare worse on tyrosine kinase inhibitor (TKIs) than adults. This real-life study compared mutation profiles and outcomes in 80 AYA, 97 adult, and 16 pediatric CML-CP patients, alongside 81 BCR::ABL1 -positive acute lymphoblastic leukemia (ALL) patients. Somatic mutations in cancer-related genes (CRGs) were more frequent in AYAs with CML-CP (25.0%) than in adults (19.6%) or children (12.5%). AYAs with Ph+ ALL also exhibited higher mutational frequencies (53.3%) compared to children (26.7%) and adults (38.9%). Mutation landscapes differed at diagnosis with ASXL1 , DNMT3A , and TET2 dominant in CML-CP and RUNX1 , IKZF1 , and BCR::ABL1 predominated in Ph+ ALL. ASXL1 mutations correlated with reduced progression-free survival (PFS) in AYAs and adults, with adults showing increased BCR::ABL1 mutations during TKI therapy, a trend not observed in AYAs. Nilotinib improved PFS in AYAs with ASXL1 mutations, highlighting the efficacy of higher-generation TKIs. ASXL1 mutations also impaired erythropoiesis, warranting further validation. Despite a higher mutational burden, AYAs did not show worse prognoses than adults, with lower mutation rates at follow-up suggesting better adherence. Mutation profiling and optimized TKI use are crucial to mitigate progression risks in CRG-mutated patients. Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Chronic myeloid leukaemia Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Acute lymphocytic leukaemia AYA CML ASXL1 somatic mutations eryhtropoiesis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Chronic myeloid leukemia (CML) is characterized by a translocation t(9;22)(q34;q11.2), which results in BCR::ABL1 rearrangement. Targeting the BCR::ABL1 protein with tyrosine kinase inhibitors (TKIs) dramatically changed outcome of CML patients. The landscape of TKI therapy has evolved with the introduction of second and third-generation TKIs that have demonstrated enhanced efficacy and a broader spectrum of BCR::ABL1 inhibition compared to their predecessors. 1 , 2 Currently, most patients with chronic phase CML (CML-CP) achieve a normal life expectancy. Factors affecting the efficiency of TKI treatment include the availability of drugs, their tolerability, the emergence of resistance to TKIs, as well as patient compliance, comorbidities, and age-related considerations. 3 , 4 The incidence of CML rises with age, with the median age at diagnosis exceeding 60 years 5 , 6 and the highest occurrence observed in individuals aged 75 and over. Prior to the integration of TKIs into clinical practice, advanced age was regarded as an adverse prognostic factor 7 and was involved in calculation of SOKAL and Euro score. 8 , 9 Despite adolescents and young adults (AYAs), defined by the National Comprehensive Cancer Network (NCCN) Guidelines (Version 2.2024) as patients aged 15–39, accounting for 7–10% of newly diagnosed CML cases, they remain understudied. Several clinical trials have indicated that AYA CML patients present with elevated white blood cell counts, larger spleen sizes, and lower hemoglobin levels at diagnosis compared to their older counterparts. 10 , 11 Additionally, a higher proportion of AYA patients exhibit BCR::ABL1 transcript levels exceeding 10% on the international scale (IS) at 3 months post-TKI initiation. 10 These indicators, reflective of the diseases of potentially aggressive nature in this specific age group, underscore the unique challenges faced by AYA patients in managing CML. However, studies have not consistently demonstrated lower probabilities of achieving major molecular response (MMR) and complete cytogenetic response (CCgR) in AYA patients. Importantly, none of these studies have confirmed the impact of age on overall survival and progression-free survival (PFS). The lack of consistent evidence emphasizes the need for further research and comprehensive investigations of AYA CML patients. Despite the continual improvement in CML patient outcomes, ongoing research has shown that additional genetic abnormalities, including somatic mutations in cancer-related genes (CRGs), were responsible for worse response to TKIs. 12 – 15 Mutations in genes encoding epigenetic modifiers such as ASXL1 , DNMT3A , and TET2 have been shown to elevate the risk of molecular relapse upon treatment discontinuation. 16 Moreover, these mutations are not isolated events but are frequently associated with clonal hematopoiesis, especially in CML patients of advanced age, typically those above 65 years. 17 – 19 On the other hand, patients carrying ASXL1 mutations at the time of diagnosis are often characterized as younger individuals facing a higher risk classification, 13 indicating a role of clonal evolution associated with ASXL1 mutations in CML pathogenesis. This suggests a potential role for these mutations as prognostic markers in guiding treatment decisions and long-term management strategies for CML patients. In this study, our objective was to explore the spectrum of somatic mutations in adolescent and young adult patients with CML in chronic phase (CML-CP) and to compare them with pediatric and adult CML patients, as well as with patients diagnosed with BCR::ABL1 -positive acute lymphoblastic leukemia (Ph + ALL). Materials and Methods Patient cohorts The total cohort of 193 patients diagnosed with chronic myeloid leukemia in chronic phase, classified according to European Leukemia Net (ELN) criteria. 3 Patients were treated at the Institute of Hematology and Blood Transfusion and University Hospital in Motol in Prague, Czech Republic. Detailed clinical information is given in Table 1. The patients were divided into three groups according to age at diagnosis: children (aged 0–17 years), adolescent and young adults (AYAs) (aged 18–39 years), and adult patients (˃40 years). The CML cohort consisted of 16 children (median 12 years; range 2–17 years), 80 AYAs (median 33 years; range 19–39 years), and 97 adults (median 58 years; range 40–79 years). Ph + ALL cohort comprised 30 children, 15 AYAs, and 36 adult patients with median age 10 (range 2–18 years), 33 years (range 18–39 years), 56 years (range 40–77 years), respectively. All patients or their guardians provided written informed consent. The study was approved by the institutional ethical committee and performed in accordance with the Declaration of Helsinki. Primary cell isolation Total leukocytes were isolated from peripheral blood (PB) or bone marrow (BM). Peripheral blood mononuclear cells (PMNCs) were isolated using Lymphoprep density gradient centrifugation (STEMCELL Technologies, Vancouver, Canada) according to the manufacturer´s recommendations. Mutation detection in the kinase domain of BCR::ABL1 BCR::ABL1 kinase domain amplicon libraries were prepared using the Nextera XT DNA Library Prep Kit (Cat. No. FC-131-1096, Illumina, San Diego, CA, USA) as previously reported. 20 Data processing, error filtering, and mutation calling at significant levels were performed using the NextGENe software (Softgenetics, State College, PA, USA) and the in-house bioinformatic tool NextDom. 20 NGS panel sequencing DNA for NGS panel sequencing was isolated from PB/BM using MagCore (RBC Bioscience, New Taipei City, Taiwan) or from TRIzol/ITG lysates by phenol-chloroform extraction. The custom panel sequencing of 22 whole genes and the selected exons of additional 40 genes (Roche, Basel, Switzerland) frequently mutated in myeloid and lymphoid malignancies (Supplementary Table S1 ) was used for the detection of somatic mutations. The library was prepared using KAPA HyperPlus (Roche) according to the protocol of manufacturer and sequenced 2x150-bp on the MiSeq instrument (Illumina, San Diego, CA, USA). Data were evaluated using the NextGENe software (Softgenetics). The clinical relevance of the detected variants with minimal coverage 500x and variant allele frequencies (VAF) > 5% was evaluated using VarSome. 21 The somatic origin of mutations, where the VAF did not correspond to the level of BCR::ABL1 , was confirmed using genomic DNA from buccal swabs. Response and clinical outcomes Total RNA was isolated from PB/BM total leukocytes using standard procedures. BCR::ABL1 transcript levels were quantified using RT-qPCR and expressed on the International Scale (IS). 22 Response definitions and CML phases classifications followed ELN criteria. 3 The probability of progression-free survival (PFS) was estimated from the start of TKI treatment to the date of progression defined as TKI treatment failure, the presence of high-risk additional chromosomal abnormalities, BCR::ABL1 kinase domain mutations, or CML-related death. Colony forming assays Clonogenic assays were conducted using CML progenitor CD34 + or peripheral blood mononuclear cells (PBMCs) from patients with ASXL1 mutation detected at diagnosis (N = 4). Mononuclear cells were isolated using Lymphoprep separation and CD34 + cells were purified by immunomagnetic beads (CD34 MicroBead Kit Human, 130-097-047; Miltenyi Biotec, Bergish Gladbach, Germany). PBMCs were from healthy donor served as a control. CD34+ (1x 10 3 ) or PBMCs (2x 10 5 ) were seeded into methylcellulose MethoCult™ H4435 medium (STEMCELL Technologies, Vancouver, Canada). Samples were analyzed in duplicate, and colonies were enumerated and characterized after 14 days. Colony counts were compared to reference progenitor cell colony frequencies in MethoCult™ of healthy donors, as reported by the manufacturer. Statistical analysis Baseline characteristics and hematological parameters were compared using Fisher´s exact test, Pearson´s Chi-squared or the Kruskal–Wallis tests. PFS was estimated by the Kaplan–Meier method and compared by log-rank test. Univariate and multivariate analyses were performed to evaluate associations between patient characteristics and survival outcomes. All statistical analyses were performed using R 4.3.1. Results Frequency and spectrum of mutations in each age group of CML-CP and Ph + ALL patients To characterize the spectrum of somatic mutations in detail and to clarify the mutation landscape in AYA (N = 80) patients with CML-CP, we compared them with adults (N = 97), and pediatric patients (N = 16). All 193 CML patients (Table 1) in this study were diagnosed at chronic phase and did not progress to the blast phase during TKI treatment. We observed a significantly larger spleen size in AYAs compared to adult patients (p = 0.016). Furthermore, AYAs had significantly higher levels of white blood count (p = 0.019) and platelets (p = 0.007). No significant difference in the percentage of blasts was observed between the two age groups (p = 0.078). Among the AYAs, 76.3% (61/80) patients were treated with imatinib as the first-line therapy, while 23.8% (19/80) patients received nilotinib. In the adult group, 96.9% (94/97) patients were treated with imatinib, and 3.1% (3/97) patients were treated with nilotinib. In the pediatric cohort, all patients received imatinib as the first-line treatment and 56.3% (9/16) of pediatric patients underwent hematopoietic cell transplantation. None of the patients were pretreated with interferon alpha. In total, 42 somatic mutations were identified in CML at diagnosis with a median VAF 32.2% (range 5.0-96.9) across 13 CRGs. These included 16 frameshift, 13 nonsense, 11 missense, and 2 start loss mutations (Supplementary Table S2). Somatic mutations were identified in 25% (20/80) of AYA CML patients, 19.6% (19/97) of adult patients, and 12.5% (2/16) of pediatric patients (Fig. 1 A). The highest frequency of mutations was found also in Ph + ALL AYAs (53.3%; 8/15) followed by adults (38.9%; 14/36) and children (26.7%; 8/30) (Fig. 1 B). Among the 13 CRGs mutated in CML, ASXL1 emerged as the most frequently mutated gene in CML, with mutations observed in 2 pediatric CML patients, 13 AYA patients, and 8 adult patients (Fig. 1 C). Three recurrent mutations in ASXL1 were identified: c.1934dup G646Wfs*12, c.2077C > T R693*, and c.1773C > G Y591* affecting N = 8, 3, and 2 patients, respectively. All frame shift mutations led to premature stop codons with subsequent loss of the c-terminal plant-homeo-domain. Notably, only one AYA patient harbored two somatic CRG mutations. Epigenetic modifiers ASXL1 , DNMT3A , and TET2 were mutated in 18.8% (15/80) AYAs and 14.4% (14/97) of adult patients with median VAFs 31.5% (range 5.4–46.5) and 32.2% (range 5.0–48.0), respectively. No mutation in BCR::ABL1 was detected in CML patients across all age groups at the time of diagnosis. Overall, 35 somatic mutations were identified in Ph + ALL patients with a median VAF of 44.5% (range 11.2–82.5) across 16 CRGs (Supplementary Table S2). Mutations in RUNX1 were the most common events in both Ph + ALL children (N = 3) and AYAs (N = 4), while mutated IKZF1 in the adults (N = 4) (Fig. 1 D). Mutation RUNX1 c.602G > A R201Q was recurrently identified in two patients. Five patients were found to have two distinct somatic mutations at diagnosis. In contrast to CML patients with no BCR::ABL1 kinase domain mutation at diagnosis, two Ph + ALL patients harbored BCR::ABL1 kinase domain mutations at the time of diagnosis. Frequency of CML patients with mutations in relation to TKI response We next analyzed 177 paired samples from 80 AYA and 97 adult CML patients collected during TKI treatment, based on sample availability. At the time of follow-up sample analysis, patients were divided into TKI responders and non-responders according to ELN criteria 3 and analyzed for CRG mutations. Additionally, all the paired samples from the time of non-optimal TKI response (warning and failure) were analyzed for BCR::ABL1 kinase domain mutations. Overall, the frequency of CML patients with CRG mutations, regardless TKI response and age, was 22% (39/177) at diagnosis and 25.4% (45/177) at TKI follow-up (Supplementary Table S3). Contrary to samples at the time of diagnosis, a significantly higher prevalence of CRG mutations was found in adults 32.0% (31/97) compared to AYA patients 17.5% (14/80) in TKI follow-up (p = 0.04). All the detected mutations are listed in Supplementary Table S2. Adult patients developed significantly more de novo mutations (both in BCR::ABL1 and other CRG) during treatment (27.8%) compared to AYA patients (12.5%) (p = 0.02). At diagnosis, CRG mutations in optimal responders were slightly more frequently observed in AYAs (17.1%; 7/41) than in adult patients (12.5%; 6/48). All 13 mutations identified in responders from both age groups except those in EZH2 c.2T > C M1T and DNMT3A c.1609T > C C537R, disappeared during the TKI treatment or were observed at low VAF corresponding to the residual level of BCR::ABL1 transcript. De novo mutations, namely ASXL1 c.1934dup G646Wfs*12, TET2 c.2429del Q810Rfs*3, and DNMT3A c.1591G > A D531N, were found only in adult responders (Supplementary Table S2). In diagnostic samples of TKI non-responders, somatic mutations were detected in 9 different CRGs (Fig. 2 A). All 7 ASXL1 mutations detected in adults at diagnosis and 3/4 in AYAs persisted during TKI treatment and were detectable at TKI failure (Fig. 2 B and 2 C). While mutations in ASXL1 most often appeared at diagnosis, mutations in BCR::ABL1 were the most common genetic alterations acquired during the therapy (Fig. 2 D). The frequency of de novo BCR::ABL1 mutations was higher in adult patients (35.6%) compared to AYAs (24.0%). The treatment failure was also associated with the occurrence of de novo mutations in ASXL1 , TET2 , and RUNX1 in both age groups. Most failures in AYA and adult patients were at the time of follow-up sample analysis treated with imatinib 1st-line (Supplementary Table S4). Impact of somatic mutations on outcomes of CML-CP patients We evaluated the impact of somatic mutations detected in CRGs at diagnosis (20/80 AYA and 19/97 adult patients) and TKI follow-up (14/80 AYA and 31/97 adult patients) on progression free survival (PFS) of CML patients. The presence of any mutation at diagnosis significantly reduced the probability of PFS compared to patients with no mutation both in AYA (p = 0.031; HR = 2.7; Cl 1.09–6.66) and adult (p = 0.003; HR = 2.97; Cl 1.46–6.04) CML patients (Fig. 3 A and 3 B). ASXL1 mutations identified at diagnosis were associated with inferior PFS compared to patients with no mutation in both age groups, AYA (p = 0.094; HR = 2.5; CI 0.86–7.33) and adult (p = 0.009; HR = 3.21; CI 1.34–7.67) patients (Fig. 3 C and 3 D). The most common reason of therapy failure in AYAs was BCR::ABL1 transcript level > 1% at any time after 12 months of TKI treatment (8/80; 10%) and in adult patients the BCR::ABL1 kinase domain mutation acquisition (12/97; 12%). Univariate analysis further revealed that high prognostic scores (SOKAL, EUTOS, ELTS) were predictive of poor outcomes in adult patients but not in AYA patients (Table 2). ELTS and EUTOS scores were highly significant in the adults p < 0.001; HR = 7; CI 3.29–14.89 and p = 0.001; HR = 3.4, CI 1.66–6.98, respectively. In AYAs, the treatment with nilotinib significantly reduced the risk of progression (p = 0.05; HR = 0.23; Cl 0.05–0.98). De novo CRG mutations significantly worsened the PFS in AYA (p = 0.002; HR = 6.1, CI 1.98–18.75), while they showed a trend toward increased risk in adult patients, though not statistically significant (p = 0.07; HR = 2.04, CI 0.95–4.36). Impact of ASXL1 mutations on cumulative incidence of BCR::ABL1 mutations during follow-up on TKI treatment Cumulative incidence of mutations in the kinase domain of BCR::ABL1 acquired during TKI treatment was significantly higher in adult patients with ASXL1 mutation at the time of diagnosis compared to adult patients with no mutation at diagnosis (p < 0.001) (Fig. 4 ). Five of six adult patients with ASXL1 mutation at diagnosis that acquired BCR::ABL1 mutation were treated with imatinib. Contrary to adults, only one AYA patient (Patient #13) with nonsense mutation ASXL1 E773* at diagnosis developed de novo mutations in BCR::ABL1 (F317L and M351T) (Supplementary Table S2). Impact of ASXL1 mutations on clonogenicity Next, we assessed the clonogenic potential of CD34 + cells and PBMCs from three patients with ASXL1 mutations, from whom the cells were available and vital (Supplementary Table S5). Blood count results showed reduced or minimal erythropoiesis at the time of diagnosis and anemia or mild anemia in Pt 2 and Pt 3 (Supplementary Table S6). Impaired erythropoiesis was observed in CD34 + cells, evidenced by a decrease in CFU-GM (Pt 1) of erythroid progenitor colonies (Supplementary Figure S1 , Panel A). In patients 2 and 3, PBMCs were available only for the clonogenicity analysis, which is not ideal sample as isolated CD34+. However, impaired erythropoiesis was noted in PBMCs from a patient with the ASXL1 E877 frameshift mutation (Pt 3), as indicated by a decrease in BFU-E numbers (Supplementary Figure S1 , Panel B). Additionally, we analyzed the blood counts of all AYA patients (N = 11) and all adults (N = 10) with the ASXL1 mutation (Supplementary Table S7). For comparison, we randomly selected 28 AYAs and 28 adults from the studied cohorts without ASXL1 mutations and evaluated their blood counts. Patients with the ASXL1 mutation (n = 20) exhibited a significantly higher platelet count compared to those without the mutation (N = 56) (p < 0.001). This difference remained statistically significant when analyzed within age groups (AYA patients with ASXL1 mutation vs. non-mutated ASXL1 : p = 0.02; adults with ASXL1 mutation vs. non-mutated ASXL1 : p = 0.016). As mentioned above, a higher platelet count was observed in AYA patients compared to adults. Moreover, an even higher platelet level was noted in AYA patients with ASXL1 mutations. Discussion This work focused on AYA CML-CP patients, whose outcome on TKI therapy has been previously reported as worse compared to adult patients. 23 The CML-CP cohort consisted of 80 AYAs, 97 adults and 16 pediatric patients. At diagnosis, AYAs exhibited significantly larger spleen sizes and higher levels of white blood cells and platelets compared to adult patients. This is consistent with studies reporting that younger CML patients often present more risk factors compared to older patients. 10 , 11 There were also differences in baseline characteristics and treatment regimens; a greater proportion of AYA patients received the second-generation TKI nilotinib as a first-line treatment compared to adult patients, aligning with the observations of, 11 who noted age-based variations in TKI usage. Altogether, 42 somatic mutations in 13 CRGs were identified, with a higher mutation frequency in AYA CML patients (25.0%) compared to adults (19.6%) and pediatric (12.5%) patients treated in real-clinical practice. Additionally, among Ph + ALL patients, AYA individuals were diagnosed with CRG mutations more frequently (53.3%) than children (26.7%) and adult patients (38.9%). The elevated mutational burden in AYAs in both diseases is notable. However, the landscape of mutated genes at diagnosis differed between CML-CP patients and Ph + ALL with ASXL1 , DNMT3A and TET2 as the three most frequently mutated genes among 193 CML-CP patients, while RUNX1 , IKZF1 and BCR::ABL1 were the most mutated genes in 81 Ph + ALL patients. ASXL1 was the most frequently mutated gene at diagnosis across pediatric, AYA and adult CML patients. Importantly, mutated ASXL1 was significantly associated with cumulative incidence of BCR::ABL1 mutations acquisition on TKI therapy in adult CML patients, which was not observed in AYAs. CML patients with significantly lower probability of PFS were those who carried mutated ASXL1 in both AYAs and adult patients in comparison with patients without mutations supporting the assumption that ASXL1 is the CML-related oncogene. 13 Furthermore, ASXL1 mutations appeared to contribute to impaired erythropoiesis, as evidenced by blood count abnormalities and reduced colony formation from erythroid progenitors, consistent with findings from previous studies. 24 , 25 This observation should be validated in a larger cohort of CML patients with ASXL1 mutations. Although CRG mutations were detected at a lower frequency, their presence correlated with reduced PFS and enhanced the level of significance. Together, these findings support emerging evidence that mutations in CRGs detected at the time of diagnosis in CML-CP patients represent risk factors for disease progression. Based on BCR::ABL1 transcript kinetics and variant allele frequency (VAF) of mutations in CRGs, it is presumed that these mutations are present in CML cells, which is in line with previous works. 19 , 26 BCR::ABL1 was the most frequent gene with mutation acquisition during TKI therapy with a markedly higher prevalence in adult patients, suggesting age-related susceptibility to additional mutations under TKI treatment pressure. This pattern aligns with, 26 who reported higher rates of new mutations in older CML patients during TKI therapy. ASXL1 was the second most frequently mutated gene on TKI therapy, albeit at a much lower frequency than BCR::ABL1 . Univariate analysis revealed that high SOKAL, EUTOS and ELTS scores along with ASXL1 mutations were significantly associated with reduced PFS in adult patients. This pattern was not observed in AYAs, where nilotinib therapy showed significant association with PFS. Specifically, nilotinib was administered to 50% (6/12) of AYA patients with ASXL1 mutations, highlighting that more potent TKIs than imatinib, when used as first-line therapy in patients with ASXL1 mutations, may improve PFS. As this study is based on real-world data, this hypothesis requires validation in larger cohorts of patients treated with higher-generation TKIs as a first-line approach. Conversely, previous work based on clinical trial data indicated that patients with ASXL1 mutations had inferior probability to achieve MMR on nilotinib as first-line therapy. 13 However, this study did not compare outcomes in patients treated with imatinib to evaluate the MMR rates in patients with ASXL1 mutations. In conclusion, this comparative study on mutation frequency and mutational landscapes in AYA, pediatric, and adult patients with CML-CP and Ph + ALL revealed that CRG mutations were more frequently detected in AYA patients at the time of diagnosis. However, our findings did not support the initial hypothesis that AYA CML-CP patients might carry oncogenic mutations commonly observed in Ph + ALL. This study demonstrated that mutations in CRGs in CML-CP patients (both AYA and adults) represent a risk factor for disease progression during TKI therapy. Generally, CML-CP patients who responded optimally to TKI therapy showed lower mutation rates at diagnosis and follow-up, particularly among AYA patients, suggesting good adherence, better disease control, and fewer emergent mutations during therapy (with a higher proportion of AYA patients receiving nilotinib). Patients who did not respond to TKI therapy (treatment failures) exhibited higher mutation rates both at diagnosis and during follow-up. Nevertheless, adult patients generally showed higher mutation rates at follow-up, irrespective of response, suggesting a potential age-related factor. ASXL1 mutations and other CRG mutations serve as risk factors for progression during TKI therapy in both AYA and adult CML-CP patients. Although overall, AYA do not seem to have a worse prognosis than others, despite having more mutations. Using higher generations of TKIs at diagnosis that effectively target CML cells with ASXL1 mutations and possibly other CRGs could potentially reduce disease progression risk. Declarations Acknowledgements This work was supported by MHCZ NU21-07-00225 and DRO (IHBT, 00023736). Samples collection was supported by grant no. LM2023033 (BBMRI.cz). Computational resources were provided by the e-INFRA CZ project (ID:90254), supported by the Ministry of Education, Youth and Sports of the Czech Republic. Author Contributions JK performed experiments and data analyses and wrote the manuscript; VP, AL, AB, NC, TS performed experiments and data analyses; PS performed bioinformatic and statistical analyses; VV, DM, HK, MMS, DS, CS provided samples and clinical data from the adult patients; MZ, JZ, JT provided samples and patients characteristics; KMP designed the study, supervised the study, interpreted the data, and wrote the manuscript All authors revised and approved the final version of the manuscript. Competing Interests KMP- Novartis - advisory board; support by Novartis through the European Treatment and Outcome Study (EUTOS) for CML. The remaining authors declare no competing financial interests. Data Availability Statement The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. References Cortes JE, Jones D, O’Brien S, Jabbour E, Ravandi F, Koller C et al. Results of dasatinib therapy in patients with early chronic-phase chronic myeloid leukemia. J Clin Oncol 2010; 28 : 389–404. Saglio G, Kim D-W, Issaragrisil S, le Coutre P, Etienne G, Lobo C et al. Nilotinib versus imatinib for newly diagnosed chronic myeloid leukemia. N Engl J Med 2010; 362 : 2251–2259. Hochhaus A, Baccarani M, Silver RT, Schiffer C, Apperley JF, Cervantes F et al. European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. Leukemia 2020; 34 : 966–984. Jabbour E, Kantarjian HM, O’Brien S, Shan J, Quintás-Cardama A, Garcia-Manero G et al. Front-line therapy with second-generation tyrosine kinase inhibitors in patients with early chronic phase chronic myeloid leukemia: what is the optimal response? J Clin Oncol 2011; 29 : 4260–4265. National Cancer Institute SEER USA. SEER USA. https://seer.cancer.gov/statfacts/html/cmyl.html (accessed 18 Dec2024). Cancer Research UK. Cancer Research UK. https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/leukaemia-cml/incidence#heading-One (accessed 18 Dec2024). Cortes J, Talpaz M, O’Brien S, Giles F, Rios MB, Shan J et al. Effects of age on prognosis with imatinib mesylate therapy for patients with Philadelphia chromosome-positive chronic myelogenous leukemia. Cancer 2003; 98 : 1105–1113. Hasford J, Pfirrmann M, Hehlmann R, Allan NC, Baccarani M, Kluin-Nelemans JC et al. A New Prognostic Score for Survival of Patients With Chronic Myeloid Leukemia Treated With Interferon Alfa Writing Committee for the Collaborative CML Prognostic Factors Project Group. JNCI: Journal of the National Cancer Institute 1998; 90 : 850–859. Sokal JE, Cox EB, Baccarani M, Tura S, Gomez GA, Robertson JE et al. Prognostic discrimination in ‘good-risk’ chronic granulocytic leukemia. Blood 1984; 63 : 789–99. Kalmanti L, Saussele S, Lauseker M, Proetel U, Müller MC, Hanfstein B et al. Younger patients with chronic myeloid leukemia do well in spite of poor prognostic indicators: results from the randomized CML study IV. Ann Hematol 2014; 93 : 71–80. Castagnetti F, Gugliotta G, Baccarani M, Breccia M, Specchia G, Levato L et al. Differences among young adults, adults and elderly chronic myeloid leukemia patients. Ann Oncol 2015; 26 : 185–192. Schmidt M, Rinke J, Schäfer V, Schnittger S, Kohlmann A, Obstfelder E et al. Molecular-defined clonal evolution in patients with chronic myeloid leukemia independent of the BCR-ABL status. Leukemia 2014; 28 : 2292–2299. Schönfeld L, Rinke J, Hinze A, Nagel SN, Schäfer V, Schenk T et al. ASXL1 mutations predict inferior molecular response to nilotinib treatment in chronic myeloid leukemia. Leukemia 2022; 36 : 2242–2249. Branford S, Kim DDH, Apperley JF, Eide CA, Mustjoki S, Ong ST et al. Laying the foundation for genomically-based risk assessment in chronic myeloid leukemia. Leukemia 2019; 33 : 1835–1850. Shanmuganathan N, Wadham C, Shahrin N, Feng J, Thomson D, Wang P et al. Impact of additional genetic abnormalities at diagnosis of chronic myeloid leukemia for first-line imatinib-treated patients receiving proactive treatment intervention. Haematologica 2023. doi:10.3324/haematol.2022.282184. Adnan Awad S, Kankainen M, Ojala T, Koskenvesa P, Eldfors S, Ghimire B et al. Mutation accumulation in cancer genes relates to nonoptimal outcome in chronic myeloid leukemia. Blood Adv 2020; 4 : 546–559. Midic D, Rinke J, Perner F, Müller V, Hinze A, Pester F et al. Prevalence and dynamics of clonal hematopoiesis caused by leukemia-associated mutations in elderly individuals without hematologic disorders. Leukemia 2020; 34 : 2198–2205. Branford S, Wadham C, Shanmuganathan N, Fernandes A, Shahrin NH, Feng J et al. Age-Related Clonal Hematopoiesis Mutations Detected at the Time of Stopping Tyrosine Kinase Inhibitor Therapy Predict the Achievement of Treatment-Free Remission for Patients with CML. Blood 2023; 142 : 447–447. Ernst T, Busch M, Rinke J, Ernst J, Haferlach C, Beck JF et al. Frequent ASXL1 mutations in children and young adults with chronic myeloid leukemia. Leukemia 2018; 32 : 2046–2049. Benesova A, De Santis S, Polivkova V, Pecherkova P, Krizkova J, Suchankova P et al. Unstable major molecular response as a trigger for next generation sequencing‐based BCR::ABL1 mutation testing in chronic myeloid leukemia. Am J Hematol 2024; 99 : 759–762. Kopanos C, Tsiolkas V, Kouris A, Chapple CE, Albarca Aguilera M, Meyer R et al. VarSome: the human genomic variant search engine. Bioinformatics 2019; 35 : 1978–1980. Cross NCP, White HE, Müller MC, Saglio G, Hochhaus A. Standardized definitions of molecular response in chronic myeloid leukemia. Leukemia 2012; 26 : 2172–2175. Pemmaraju N, Kantarjian H, Shan J, Jabbour E, Quintas-Cardama A, Verstovsek S et al. Analysis of outcomes in adolescents and young adults with chronic myelogenous leukemia treated with upfront tyrosine kinase inhibitor therapy. Haematologica 2012; 97 : 1029–1035. Shi H, Yamamoto S, Sheng M, Bai J, Zhang P, Chen R et al. ASXL1 plays an important role in erythropoiesis. Sci Rep 2016; 6 : 28789. Yamamoto S, Shi H, Chen S, Zhang P, Zhou Y, Xu M et al. ASXL1 Is a Key Regulator for Erythroid Development and Asxl1 Loss Impairs Erythropoiesis In Vivo. Blood 2015; 126 : 3644–3644. Kim T, Tyndel MS, Kim HJ, Ahn J-S, Choi SH, Park HJ et al. Spectrum of somatic mutation dynamics in chronic myeloid leukemia following tyrosine kinase inhibitor therapy. Blood 2017; 129 : 38–47. Tables Tables 1 to 2 are available in the Supplementary Files section Additional Declarations Yes there is potential conflict of interest. Supplementary Files Table1.xlsx Table2.xlsx SupplementaryInformation.docx Supplementary Information Cite Share Download PDF Status: Published Journal Publication published 28 Apr, 2025 Read the published version in Leukemia → Version 1 posted Editorial decision: revise 27 Jan, 2025 Review # 1 received at journal 27 Jan, 2025 Review # 2 received at journal 23 Jan, 2025 Reviewer # 2 agreed at journal 09 Jan, 2025 Reviewer # 1 agreed at journal 09 Jan, 2025 Reviewers invited by journal 09 Jan, 2025 Editor assigned by journal 09 Jan, 2025 Submission checks completed at journal 09 Jan, 2025 First submitted to journal 08 Jan, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5789724","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":399953010,"identity":"30d1e5ba-6977-4000-b4bb-6e0d125640be","order_by":0,"name":"Katerina Machova Polakova","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIiWNgGAWjYBACCTBpAOEwgwh+Bh5mAlqY0bRINgC1HCCohQFJi8EBAlok288ffFxRcEeeQezww88FFYfljW/kHjb+wGBnj0uLNE8ys+EZg2eGDdJpxtIzzhw23HYjLznhAEMyTg/JMSSzSTYYHGZskE4wY+ZtS2PcdiPH+MABhgNsOLXwP2b/CdRi3yCd/g2kxX7zDIgWHpwOk0hmYwRqSWyQzgHZYpO4QSLHGOiwAxI4vT/jsTHIYclt0jnF0jxnbJJnnHljbHDGINkAlxaJ84kPPzb8OWzbL52+8TNPhYRtf3uOsURFBe4QgwM03+K0YxSMglEwCkYBMQAAb7BPYGpf1BsAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-7398-5555","institution":"Institute of Hematology and Blood Transfusion","correspondingAuthor":true,"prefix":"","firstName":"Katerina","middleName":"Machova","lastName":"Polakova","suffix":""},{"id":399953011,"identity":"4638b49e-9300-4692-8a36-02d4edc28e0a","order_by":1,"name":"Jitka Krizkova","email":"","orcid":"","institution":"Institute of Hematology and Blood Transfusion","correspondingAuthor":false,"prefix":"","firstName":"Jitka","middleName":"","lastName":"Krizkova","suffix":""},{"id":399953012,"identity":"aff7eab7-3560-4573-a451-2ebea57a4f7b","order_by":2,"name":"Vaclava Polivkova","email":"","orcid":"","institution":"Institute of Hematology and Blood Transfusion","correspondingAuthor":false,"prefix":"","firstName":"Vaclava","middleName":"","lastName":"Polivkova","suffix":""},{"id":399953013,"identity":"9beb93f0-8b5e-4bcf-8094-0e7029163281","order_by":3,"name":"Adam Laznicka","email":"","orcid":"","institution":"Institute of Hematology and Blood Transfusion","correspondingAuthor":false,"prefix":"","firstName":"Adam","middleName":"","lastName":"Laznicka","suffix":""},{"id":399953014,"identity":"47a8453e-766f-47da-aa78-0ce9f405a175","order_by":4,"name":"Nikola Curik","email":"","orcid":"","institution":"Institute of Hematology and Blood 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Transfusion","correspondingAuthor":false,"prefix":"","firstName":"Tomas","middleName":"","lastName":"Smazik","suffix":""},{"id":399953018,"identity":"5cdb2269-b5ff-4c41-8bca-c452a2a85962","order_by":8,"name":"Veronika Vysinova","email":"","orcid":"","institution":"Institute of Hematology and Blood Transfusion","correspondingAuthor":false,"prefix":"","firstName":"Veronika","middleName":"","lastName":"Vysinova","suffix":""},{"id":399953019,"identity":"19944625-cb23-41f6-8733-9d4be041bf70","order_by":9,"name":"Dana Mikulenkova","email":"","orcid":"","institution":"Institute of Hematology and Blood Transfusion","correspondingAuthor":false,"prefix":"","firstName":"Dana","middleName":"","lastName":"Mikulenkova","suffix":""},{"id":399953020,"identity":"257d15bb-18e2-4b6c-8b84-f51c78926b21","order_by":10,"name":"Hana Klamova","email":"","orcid":"https://orcid.org/0009-0000-5020-7040","institution":"Institute of Hematology and Blood Transfusion","correspondingAuthor":false,"prefix":"","firstName":"Hana","middleName":"","lastName":"Klamova","suffix":""},{"id":399953021,"identity":"c4cbd9db-de0d-4e3a-a2da-2d7d78394d40","order_by":11,"name":"Marketa Stastna Markova","email":"","orcid":"","institution":"Institute of Hematology and Blood Transfusion","correspondingAuthor":false,"prefix":"","firstName":"Marketa","middleName":"Stastna","lastName":"Markova","suffix":""},{"id":399953022,"identity":"575097a7-24b0-4ed4-8427-e2ad6025f4e0","order_by":12,"name":"Dana Srbova","email":"","orcid":"","institution":"Institute of Hematology and Blood Transfusion","correspondingAuthor":false,"prefix":"","firstName":"Dana","middleName":"","lastName":"Srbova","suffix":""},{"id":399953023,"identity":"86873cf8-b48e-436f-b819-da820b68f4f3","order_by":13,"name":"Jan Zuna","email":"","orcid":"https://orcid.org/0000-0002-0887-3709","institution":"CLIP, Second Faculty of Medicine, Charles University and University Hospital Motol","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"","lastName":"Zuna","suffix":""},{"id":399953024,"identity":"a480741f-bd8c-4531-ba4b-8878a8283ee4","order_by":14,"name":"Marketa Zaliova","email":"","orcid":"https://orcid.org/0000-0002-1639-7124","institution":"2nd Faculty of Medicine, Charles University Prague","correspondingAuthor":false,"prefix":"","firstName":"Marketa","middleName":"","lastName":"Zaliova","suffix":""},{"id":399953025,"identity":"e5ed59b0-3905-4b6e-9dd5-b41782b946d6","order_by":15,"name":"Jan Trka","email":"","orcid":"https://orcid.org/0000-0002-9527-8608","institution":"2nd Faculty of Medicine, Charles University and University Hospital Motol","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"","lastName":"Trka","suffix":""},{"id":399953026,"identity":"473e0a88-700e-4df4-a45d-a55ebae40c37","order_by":16,"name":"Cyril Salek","email":"","orcid":"https://orcid.org/0000-0002-0021-3247","institution":"Institute of Hematology and Blood Transfusion","correspondingAuthor":false,"prefix":"","firstName":"Cyril","middleName":"","lastName":"Salek","suffix":""}],"badges":[],"createdAt":"2025-01-08 14:06:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5789724/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5789724/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41375-025-02609-3","type":"published","date":"2025-04-28T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":73702432,"identity":"15d1c59a-e418-4bce-a68c-af27dabd2589","added_by":"auto","created_at":"2025-01-13 17:34:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":242382,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAge- and disease-related spectrum of somatic mutations at diagnosis.\u003c/strong\u003eThe frequency of patients with mutations according to age and disease (A) CML and (B) Ph+ ALL. Spectrum of somatic mutations in (C) CML and (D) Ph+ ALL patients according to age subgroups. The total number of mutations identified is shown in tables.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5789724/v1/b8c82773508f0c29c0c8b3dc.png"},{"id":73702437,"identity":"2081fa0a-5c71-48e7-a6ad-5f43beb3fb03","added_by":"auto","created_at":"2025-01-13 17:34:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":208237,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpectrum of somatic mutations observed in AYA and adult TKI non-responders.\u003c/strong\u003eThe bars represent the frequency of patients with somatic mutations at diagnosis (A), TKI follow-up (B), mutations persisting during TKI treatment (C), and those acquired \u003cem\u003ede novo\u003c/em\u003e during TKI treatment (D). The tables below indicate the total number of mutations detected.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5789724/v1/f2d63ece47c62883c288b4c6.png"},{"id":73702444,"identity":"d1912cee-0d3a-4b08-bab8-96d84ebadfd7","added_by":"auto","created_at":"2025-01-13 17:34:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":174203,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImpact of somatic mutations identified at diagnosis on PFS according to type of mutations and age groups.\u003c/strong\u003e PFS of (A) AYA and (B) adult CML patients with any mutation identified at diagnosis compared to patients with no mutation. Effect of \u003cem\u003eASXL1\u003c/em\u003e mutations observed at diagnosis on PFS in (C) AYA and (D) adult patients. Hazard R (95%CI) derived from Cox proportional hazard regression models and the \u003cem\u003ep\u003c/em\u003e-value calculated by the Log-rank test are shown. Number of patients at risk are shown in tables below. Allmut – patients with any mutation at diagnosis; wt - patients with no mutation during the whole TKI follow-up\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5789724/v1/d274d3af0d9697dbdab7ffb9.png"},{"id":73702443,"identity":"05929d05-338b-4092-bc14-b0cf7c064c60","added_by":"auto","created_at":"2025-01-13 17:34:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":56882,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCumulative incidence of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eBCR::ABL1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003emutations in adult CML patients according to the presence of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eASXL1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003emutation at the time of diagnosis.\u003c/strong\u003eThe number of patients at risk is shown in the table below. ASXL1 – \u003cem\u003eASXL1\u003c/em\u003emutation at diagnosis; wt – no mutation at diagnosis\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5789724/v1/cf5aefc00971c00eff5abfb3.png"},{"id":81610618,"identity":"826bc54b-9d8f-411f-a53d-53788454df29","added_by":"auto","created_at":"2025-04-29 07:08:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1734675,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5789724/v1/80d918ce-a676-4a35-b265-7b552979c4ab.pdf"},{"id":73702442,"identity":"06871d62-2fcf-48ae-985d-203df5398afd","added_by":"auto","created_at":"2025-01-13 17:34:01","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11280,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5789724/v1/671339fc0619de952d77feb6.xlsx"},{"id":73702436,"identity":"ef842d91-9f77-4cd3-b57d-c9ee1bf044fd","added_by":"auto","created_at":"2025-01-13 17:34:00","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10627,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5789724/v1/2db1fa21c108559b8423a237.xlsx"},{"id":73702435,"identity":"0cb1f806-2add-4b28-afe7-77d7699678cb","added_by":"auto","created_at":"2025-01-13 17:34:00","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":96055,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Information\u003c/p\u003e","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-5789724/v1/20f1150af1cf7331db960f7d.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential conflict of interest.","formattedTitle":"Somatic Mutations and Outcomes in CML Adolescent and Young Adults Compared to Children, Adults, and BCR::ABL1-positive ALL Patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic myeloid leukemia (CML) is characterized by a translocation t(9;22)(q34;q11.2), which results in \u003cem\u003eBCR::ABL1\u003c/em\u003e rearrangement. Targeting the BCR::ABL1 protein with tyrosine kinase inhibitors (TKIs) dramatically changed outcome of CML patients. The landscape of TKI therapy has evolved with the introduction of second and third-generation TKIs that have demonstrated enhanced efficacy and a broader spectrum of \u003cem\u003eBCR::ABL1\u003c/em\u003e inhibition compared to their predecessors. \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Currently, most patients with chronic phase CML (CML-CP) achieve a normal life expectancy. Factors affecting the efficiency of TKI treatment include the availability of drugs, their tolerability, the emergence of resistance to TKIs, as well as patient compliance, comorbidities, and age-related considerations. \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe incidence of CML rises with age, with the median age at diagnosis exceeding 60 years\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e and the highest occurrence observed in individuals aged 75 and over. Prior to the integration of TKIs into clinical practice, advanced age was regarded as an adverse prognostic factor\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e and was involved in calculation of SOKAL and Euro score.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Despite adolescents and young adults (AYAs), defined by the National Comprehensive Cancer Network (NCCN) Guidelines (Version 2.2024) as patients aged 15\u0026ndash;39, accounting for 7\u0026ndash;10% of newly diagnosed CML cases, they remain understudied.\u003c/p\u003e \u003cp\u003eSeveral clinical trials have indicated that AYA CML patients present with elevated white blood cell counts, larger spleen sizes, and lower hemoglobin levels at diagnosis compared to their older counterparts. \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Additionally, a higher proportion of AYA patients exhibit \u003cem\u003eBCR::ABL1\u003c/em\u003e transcript levels exceeding 10% on the international scale (IS) at 3 months post-TKI initiation. \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e These indicators, reflective of the diseases of potentially aggressive nature in this specific age group, underscore the unique challenges faced by AYA patients in managing CML. However, studies have not consistently demonstrated lower probabilities of achieving major molecular response (MMR) and complete cytogenetic response (CCgR) in AYA patients. Importantly, none of these studies have confirmed the impact of age on overall survival and progression-free survival (PFS). The lack of consistent evidence emphasizes the need for further research and comprehensive investigations of AYA CML patients.\u003c/p\u003e \u003cp\u003eDespite the continual improvement in CML patient outcomes, ongoing research has shown that additional genetic abnormalities, including somatic mutations in cancer-related genes (CRGs), were responsible for worse response to TKIs. \u003csup\u003e\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Mutations in genes encoding epigenetic modifiers such as \u003cem\u003eASXL1\u003c/em\u003e, \u003cem\u003eDNMT3A\u003c/em\u003e, and \u003cem\u003eTET2\u003c/em\u003e have been shown to elevate the risk of molecular relapse upon treatment discontinuation. \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Moreover, these mutations are not isolated events but are frequently associated with clonal hematopoiesis, especially in CML patients of advanced age, typically those above 65 years. \u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e On the other hand, patients carrying \u003cem\u003eASXL1\u003c/em\u003e mutations at the time of diagnosis are often characterized as younger individuals facing a higher risk classification, \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e indicating a role of clonal evolution associated with \u003cem\u003eASXL1\u003c/em\u003e mutations in CML pathogenesis. This suggests a potential role for these mutations as prognostic markers in guiding treatment decisions and long-term management strategies for CML patients.\u003c/p\u003e \u003cp\u003eIn this study, our objective was to explore the spectrum of somatic mutations in adolescent and young adult patients with CML in chronic phase (CML-CP) and to compare them with pediatric and adult CML patients, as well as with patients diagnosed with \u003cem\u003eBCR::ABL1\u003c/em\u003e-positive acute lymphoblastic leukemia (Ph\u0026thinsp;+\u0026thinsp;ALL).\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient cohorts\u003c/h2\u003e \u003cp\u003eThe total cohort of 193 patients diagnosed with chronic myeloid leukemia in chronic phase, classified according to European Leukemia Net (ELN) criteria. \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Patients were treated at the Institute of Hematology and Blood Transfusion and University Hospital in Motol in Prague, Czech Republic. Detailed clinical information is given in Table\u0026nbsp;1. The patients were divided into three groups according to age at diagnosis: children (aged 0\u0026ndash;17 years), adolescent and young adults (AYAs) (aged 18\u0026ndash;39 years), and adult patients (˃40 years). The CML cohort consisted of 16 children (median 12 years; range 2\u0026ndash;17 years), 80 AYAs (median 33 years; range 19\u0026ndash;39 years), and 97 adults (median 58 years; range 40\u0026ndash;79 years). Ph\u0026thinsp;+\u0026thinsp;ALL cohort comprised 30 children, 15 AYAs, and 36 adult patients with median age 10 (range 2\u0026ndash;18 years), 33 years (range 18\u0026ndash;39 years), 56 years (range 40\u0026ndash;77 years), respectively. All patients or their guardians provided written informed consent. The study was approved by the institutional ethical committee and performed in accordance with the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePrimary cell isolation\u003c/h3\u003e\n\u003cp\u003eTotal leukocytes were isolated from peripheral blood (PB) or bone marrow (BM). Peripheral blood mononuclear cells (PMNCs) were isolated using Lymphoprep density gradient centrifugation (STEMCELL Technologies, Vancouver, Canada) according to the manufacturer\u0026acute;s recommendations.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMutation detection in the kinase domain of\u003c/b\u003e \u003cb\u003eBCR::ABL1\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eBCR::ABL1\u003c/em\u003e kinase domain amplicon libraries were prepared using the Nextera XT DNA Library Prep Kit (Cat. No. FC-131-1096, Illumina, San Diego, CA, USA) as previously reported. \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Data processing, error filtering, and mutation calling at significant levels were performed using the NextGENe software (Softgenetics, State College, PA, USA) and the in-house bioinformatic tool NextDom. \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003eNGS panel sequencing\u003c/h3\u003e\n\u003cp\u003eDNA for NGS panel sequencing was isolated from PB/BM using MagCore (RBC Bioscience, New Taipei City, Taiwan) or from TRIzol/ITG lysates by phenol-chloroform extraction. The custom panel sequencing of 22 whole genes and the selected exons of additional 40 genes (Roche, Basel, Switzerland) frequently mutated in myeloid and lymphoid malignancies (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) was used for the detection of somatic mutations. The library was prepared using KAPA HyperPlus (Roche) according to the protocol of manufacturer and sequenced 2x150-bp on the MiSeq instrument (Illumina, San Diego, CA, USA). Data were evaluated using the NextGENe software (Softgenetics). The clinical relevance of the detected variants with minimal coverage 500x and variant allele frequencies (VAF)\u0026thinsp;\u0026gt;\u0026thinsp;5% was evaluated using VarSome. \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e The somatic origin of mutations, where the VAF did not correspond to the level of \u003cem\u003eBCR::ABL1\u003c/em\u003e, was confirmed using genomic DNA from buccal swabs.\u003c/p\u003e\n\u003ch3\u003eResponse and clinical outcomes\u003c/h3\u003e\n\u003cp\u003eTotal RNA was isolated from PB/BM total leukocytes using standard procedures. \u003cem\u003eBCR::ABL1\u003c/em\u003e transcript levels were quantified using RT-qPCR and expressed on the International Scale (IS). \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Response definitions and CML phases classifications followed ELN criteria. \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e The probability of progression-free survival (PFS) was estimated from the start of TKI treatment to the date of progression defined as TKI treatment failure, the presence of high-risk additional chromosomal abnormalities, \u003cem\u003eBCR::ABL1\u003c/em\u003e kinase domain mutations, or CML-related death.\u003c/p\u003e\n\u003ch3\u003eColony forming assays\u003c/h3\u003e\n\u003cp\u003eClonogenic assays were conducted using CML progenitor CD34\u0026thinsp;+\u0026thinsp;or peripheral blood mononuclear cells (PBMCs) from patients with \u003cem\u003eASXL1\u003c/em\u003e mutation detected at diagnosis (N\u0026thinsp;=\u0026thinsp;4). Mononuclear cells were isolated using Lymphoprep separation and CD34\u0026thinsp;+\u0026thinsp;cells were purified by immunomagnetic beads (CD34 MicroBead Kit Human, 130-097-047; Miltenyi Biotec, Bergish Gladbach, Germany). PBMCs were from healthy donor served as a control. CD34+ (1x 10\u003csup\u003e3\u003c/sup\u003e) or PBMCs (2x 10\u003csup\u003e5\u003c/sup\u003e) were seeded into methylcellulose MethoCult\u0026trade; H4435 medium (STEMCELL Technologies, Vancouver, Canada). Samples were analyzed in duplicate, and colonies were enumerated and characterized after 14 days. Colony counts were compared to reference progenitor cell colony frequencies in MethoCult\u0026trade; of healthy donors, as reported by the manufacturer.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eBaseline characteristics and hematological parameters were compared using Fisher\u0026acute;s exact test, Pearson\u0026acute;s Chi-squared or the Kruskal\u0026ndash;Wallis tests. PFS was estimated by the Kaplan\u0026ndash;Meier method and compared by log-rank test. Univariate and multivariate analyses were performed to evaluate associations between patient characteristics and survival outcomes. All statistical analyses were performed using R 4.3.1.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eFrequency and spectrum of mutations in each age group of CML-CP and Ph\u0026thinsp;+\u0026thinsp;ALL patients\u003c/h2\u003e \u003cp\u003eTo characterize the spectrum of somatic mutations in detail and to clarify the mutation landscape in AYA (N\u0026thinsp;=\u0026thinsp;80) patients with CML-CP, we compared them with adults (N\u0026thinsp;=\u0026thinsp;97), and pediatric patients (N\u0026thinsp;=\u0026thinsp;16). All 193 CML patients (Table\u0026nbsp;1) in this study were diagnosed at chronic phase and did not progress to the blast phase during TKI treatment.\u003c/p\u003e \u003cp\u003eWe observed a significantly larger spleen size in AYAs compared to adult patients (p\u0026thinsp;=\u0026thinsp;0.016). Furthermore, AYAs had significantly higher levels of white blood count (p\u0026thinsp;=\u0026thinsp;0.019) and platelets (p\u0026thinsp;=\u0026thinsp;0.007). No significant difference in the percentage of blasts was observed between the two age groups (p\u0026thinsp;=\u0026thinsp;0.078).\u003c/p\u003e \u003cp\u003eAmong the AYAs, 76.3% (61/80) patients were treated with imatinib as the first-line therapy, while 23.8% (19/80) patients received nilotinib. In the adult group, 96.9% (94/97) patients were treated with imatinib, and 3.1% (3/97) patients were treated with nilotinib. In the pediatric cohort, all patients received imatinib as the first-line treatment and 56.3% (9/16) of pediatric patients underwent hematopoietic cell transplantation. None of the patients were pretreated with interferon alpha.\u003c/p\u003e \u003cp\u003eIn total, 42 somatic mutations were identified in CML at diagnosis with a median VAF 32.2% (range 5.0-96.9) across 13 CRGs. These included 16 frameshift, 13 nonsense, 11 missense, and 2 start loss mutations (Supplementary Table S2). Somatic mutations were identified in 25% (20/80) of AYA CML patients, 19.6% (19/97) of adult patients, and 12.5% (2/16) of pediatric patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The highest frequency of mutations was found also in Ph\u0026thinsp;+\u0026thinsp;ALL AYAs (53.3%; 8/15) followed by adults (38.9%; 14/36) and children (26.7%; 8/30) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong the 13 CRGs mutated in CML, \u003cem\u003eASXL1\u003c/em\u003e emerged as the most frequently mutated gene in CML, with mutations observed in 2 pediatric CML patients, 13 AYA patients, and 8 adult patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Three recurrent mutations in \u003cem\u003eASXL1\u003c/em\u003e were identified: c.1934dup G646Wfs*12, c.2077C\u0026thinsp;\u0026gt;\u0026thinsp;T R693*, and c.1773C\u0026thinsp;\u0026gt;\u0026thinsp;G Y591* affecting N\u0026thinsp;=\u0026thinsp;8, 3, and 2 patients, respectively. All frame shift mutations led to premature stop codons with subsequent loss of the c-terminal plant-homeo-domain. Notably, only one AYA patient harbored two somatic CRG mutations. Epigenetic modifiers \u003cem\u003eASXL1\u003c/em\u003e, \u003cem\u003eDNMT3A\u003c/em\u003e, and \u003cem\u003eTET2\u003c/em\u003e were mutated in 18.8% (15/80) AYAs and 14.4% (14/97) of adult patients with median VAFs 31.5% (range 5.4\u0026ndash;46.5) and 32.2% (range 5.0\u0026ndash;48.0), respectively. No mutation in \u003cem\u003eBCR::ABL1\u003c/em\u003e was detected in CML patients across all age groups at the time of diagnosis.\u003c/p\u003e \u003cp\u003eOverall, 35 somatic mutations were identified in Ph\u0026thinsp;+\u0026thinsp;ALL patients with a median VAF of 44.5% (range 11.2\u0026ndash;82.5) across 16 CRGs (Supplementary Table S2). Mutations in \u003cem\u003eRUNX1\u003c/em\u003e were the most common events in both Ph\u0026thinsp;+\u0026thinsp;ALL children (N\u0026thinsp;=\u0026thinsp;3) and AYAs (N\u0026thinsp;=\u0026thinsp;4), while mutated \u003cem\u003eIKZF1\u003c/em\u003e in the adults (N\u0026thinsp;=\u0026thinsp;4) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Mutation \u003cem\u003eRUNX1\u003c/em\u003e c.602G\u0026thinsp;\u0026gt;\u0026thinsp;A R201Q was recurrently identified in two patients. Five patients were found to have two distinct somatic mutations at diagnosis. In contrast to CML patients with no BCR::ABL1 kinase domain mutation at diagnosis, two Ph\u0026thinsp;+\u0026thinsp;ALL patients harbored BCR::ABL1 kinase domain mutations at the time of diagnosis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFrequency of CML patients with mutations in relation to TKI response\u003c/h2\u003e \u003cp\u003eWe next analyzed 177 paired samples from 80 AYA and 97 adult CML patients collected during TKI treatment, based on sample availability. At the time of follow-up sample analysis, patients were divided into TKI responders and non-responders according to ELN criteria \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e and analyzed for CRG mutations. Additionally, all the paired samples from the time of non-optimal TKI response (warning and failure) were analyzed for \u003cem\u003eBCR::ABL1\u003c/em\u003e kinase domain mutations.\u003c/p\u003e \u003cp\u003eOverall, the frequency of CML patients with CRG mutations, regardless TKI response and age, was 22% (39/177) at diagnosis and 25.4% (45/177) at TKI follow-up (Supplementary Table S3). Contrary to samples at the time of diagnosis, a significantly higher prevalence of CRG mutations was found in adults 32.0% (31/97) compared to AYA patients 17.5% (14/80) in TKI follow-up (p\u0026thinsp;=\u0026thinsp;0.04). All the detected mutations are listed in Supplementary Table S2. Adult patients developed significantly more \u003cem\u003ede novo\u003c/em\u003e mutations (both in \u003cem\u003eBCR::ABL1\u003c/em\u003e and other CRG) during treatment (27.8%) compared to AYA patients (12.5%) (p\u0026thinsp;=\u0026thinsp;0.02).\u003c/p\u003e \u003cp\u003eAt diagnosis, CRG mutations in optimal responders were slightly more frequently observed in AYAs (17.1%; 7/41) than in adult patients (12.5%; 6/48). All 13 mutations identified in responders from both age groups except those in \u003cem\u003eEZH2\u003c/em\u003e c.2T\u0026thinsp;\u0026gt;\u0026thinsp;C M1T and \u003cem\u003eDNMT3A\u003c/em\u003e c.1609T\u0026thinsp;\u0026gt;\u0026thinsp;C C537R, disappeared during the TKI treatment or were observed at low VAF corresponding to the residual level of \u003cem\u003eBCR::ABL1\u003c/em\u003e transcript. \u003cem\u003eDe novo\u003c/em\u003e mutations, namely \u003cem\u003eASXL1\u003c/em\u003e c.1934dup G646Wfs*12, \u003cem\u003eTET2\u003c/em\u003e c.2429del Q810Rfs*3, and \u003cem\u003eDNMT3A\u003c/em\u003e c.1591G\u0026thinsp;\u0026gt;\u0026thinsp;A D531N, were found only in adult responders (Supplementary Table S2).\u003c/p\u003e \u003cp\u003eIn diagnostic samples of TKI non-responders, somatic mutations were detected in 9 different CRGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). All 7 \u003cem\u003eASXL1\u003c/em\u003e mutations detected in adults at diagnosis and 3/4 in AYAs persisted during TKI treatment and were detectable at TKI failure (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). While mutations in \u003cem\u003eASXL1\u003c/em\u003e most often appeared at diagnosis, mutations in \u003cem\u003eBCR::ABL1\u003c/em\u003e were the most common genetic alterations acquired during the therapy (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). The frequency of \u003cem\u003ede novo BCR::ABL1\u003c/em\u003e mutations was higher in adult patients (35.6%) compared to AYAs (24.0%). The treatment failure was also associated with the occurrence of \u003cem\u003ede novo\u003c/em\u003e mutations in \u003cem\u003eASXL1\u003c/em\u003e, \u003cem\u003eTET2\u003c/em\u003e, and \u003cem\u003eRUNX1\u003c/em\u003e in both age groups. Most failures in AYA and adult patients were at the time of follow-up sample analysis treated with imatinib 1st-line (Supplementary Table S4).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eImpact of somatic mutations on outcomes of CML-CP patients\u003c/h2\u003e \u003cp\u003eWe evaluated the impact of somatic mutations detected in CRGs at diagnosis (20/80 AYA and 19/97 adult patients) and TKI follow-up (14/80 AYA and 31/97 adult patients) on progression free survival (PFS) of CML patients. The presence of any mutation at diagnosis significantly reduced the probability of PFS compared to patients with no mutation both in AYA (p\u0026thinsp;=\u0026thinsp;0.031; HR\u0026thinsp;=\u0026thinsp;2.7; Cl 1.09\u0026ndash;6.66) and adult (p\u0026thinsp;=\u0026thinsp;0.003; HR\u0026thinsp;=\u0026thinsp;2.97; Cl 1.46\u0026ndash;6.04) CML patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). \u003cem\u003eASXL1\u003c/em\u003e mutations identified at diagnosis were associated with inferior PFS compared to patients with no mutation in both age groups, AYA (p\u0026thinsp;=\u0026thinsp;0.094; HR\u0026thinsp;=\u0026thinsp;2.5; CI 0.86\u0026ndash;7.33) and adult (p\u0026thinsp;=\u0026thinsp;0.009; HR\u0026thinsp;=\u0026thinsp;3.21; CI 1.34\u0026ndash;7.67) patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). The most common reason of therapy failure in AYAs was \u003cem\u003eBCR::ABL1\u003c/em\u003e transcript level\u0026thinsp;\u0026gt;\u0026thinsp;1% at any time after 12 months of TKI treatment (8/80; 10%) and in adult patients the \u003cem\u003eBCR::ABL1\u003c/em\u003e kinase domain mutation acquisition (12/97; 12%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUnivariate analysis further revealed that high prognostic scores (SOKAL, EUTOS, ELTS) were predictive of poor outcomes in adult patients but not in AYA patients (Table\u0026nbsp;2). ELTS and EUTOS scores were highly significant in the adults p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; HR\u0026thinsp;=\u0026thinsp;7; CI 3.29\u0026ndash;14.89 and p\u0026thinsp;=\u0026thinsp;0.001; HR\u0026thinsp;=\u0026thinsp;3.4, CI 1.66\u0026ndash;6.98, respectively. In AYAs, the treatment with nilotinib significantly reduced the risk of progression (p\u0026thinsp;=\u0026thinsp;0.05; HR\u0026thinsp;=\u0026thinsp;0.23; Cl 0.05\u0026ndash;0.98). \u003cem\u003eDe novo\u003c/em\u003e CRG mutations significantly worsened the PFS in AYA (p\u0026thinsp;=\u0026thinsp;0.002; HR\u0026thinsp;=\u0026thinsp;6.1, CI 1.98\u0026ndash;18.75), while they showed a trend toward increased risk in adult patients, though not statistically significant (p\u0026thinsp;=\u0026thinsp;0.07; HR\u0026thinsp;=\u0026thinsp;2.04, CI 0.95\u0026ndash;4.36).\u003c/p\u003e \u003cp\u003e \u003cb\u003eImpact of\u003c/b\u003e \u003cb\u003eASXL1\u003c/b\u003e \u003cb\u003emutations on cumulative incidence of\u003c/b\u003e \u003cb\u003eBCR::ABL1\u003c/b\u003e \u003cb\u003emutations during follow-up on TKI treatment\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCumulative incidence of mutations in the kinase domain of \u003cem\u003eBCR::ABL1\u003c/em\u003e acquired during TKI treatment was significantly higher in adult patients with \u003cem\u003eASXL1\u003c/em\u003e mutation at the time of diagnosis compared to adult patients with no mutation at diagnosis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Five of six adult patients with \u003cem\u003eASXL1\u003c/em\u003e mutation at diagnosis that acquired \u003cem\u003eBCR::ABL1\u003c/em\u003e mutation were treated with imatinib. Contrary to adults, only one AYA patient (Patient #13) with nonsense mutation \u003cem\u003eASXL1\u003c/em\u003e E773* at diagnosis developed \u003cem\u003ede novo\u003c/em\u003e mutations in \u003cem\u003eBCR::ABL1\u003c/em\u003e (F317L and M351T) (Supplementary Table S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eImpact of\u003c/b\u003e \u003cb\u003eASXL1\u003c/b\u003e \u003cb\u003emutations on clonogenicity\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNext, we assessed the clonogenic potential of CD34\u0026thinsp;+\u0026thinsp;cells and PBMCs from three patients with \u003cem\u003eASXL1\u003c/em\u003e mutations, from whom the cells were available and vital (Supplementary Table S5). Blood count results showed reduced or minimal erythropoiesis at the time of diagnosis and anemia or mild anemia in Pt 2 and Pt 3 (Supplementary Table S6). Impaired erythropoiesis was observed in CD34\u0026thinsp;+\u0026thinsp;cells, evidenced by a decrease in CFU-GM (Pt 1) of erythroid progenitor colonies (Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, Panel A). In patients 2 and 3, PBMCs were available only for the clonogenicity analysis, which is not ideal sample as isolated CD34+. However, impaired erythropoiesis was noted in PBMCs from a patient with the \u003cem\u003eASXL1\u003c/em\u003e E877 frameshift mutation (Pt 3), as indicated by a decrease in BFU-E numbers (Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, Panel B).\u003c/p\u003e \u003cp\u003eAdditionally, we analyzed the blood counts of all AYA patients (N\u0026thinsp;=\u0026thinsp;11) and all adults (N\u0026thinsp;=\u0026thinsp;10) with the \u003cem\u003eASXL1\u003c/em\u003e mutation (Supplementary Table S7). For comparison, we randomly selected 28 AYAs and 28 adults from the studied cohorts without \u003cem\u003eASXL1\u003c/em\u003e mutations and evaluated their blood counts. Patients with the \u003cem\u003eASXL1\u003c/em\u003e mutation (n\u0026thinsp;=\u0026thinsp;20) exhibited a significantly higher platelet count compared to those without the mutation (N\u0026thinsp;=\u0026thinsp;56) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This difference remained statistically significant when analyzed within age groups (AYA patients with \u003cem\u003eASXL1\u003c/em\u003e mutation vs. non-mutated \u003cem\u003eASXL1\u003c/em\u003e: p\u0026thinsp;=\u0026thinsp;0.02; adults with \u003cem\u003eASXL1\u003c/em\u003e mutation vs. non-mutated \u003cem\u003eASXL1\u003c/em\u003e: p\u0026thinsp;=\u0026thinsp;0.016). As mentioned above, a higher platelet count was observed in AYA patients compared to adults. Moreover, an even higher platelet level was noted in AYA patients with \u003cem\u003eASXL1\u003c/em\u003e mutations.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis work focused on AYA CML-CP patients, whose outcome on TKI therapy has been previously reported as worse compared to adult patients.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e The CML-CP cohort consisted of 80 AYAs, 97 adults and 16 pediatric patients. At diagnosis, AYAs exhibited significantly larger spleen sizes and higher levels of white blood cells and platelets compared to adult patients. This is consistent with studies reporting that younger CML patients often present more risk factors compared to older patients.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e There were also differences in baseline characteristics and treatment regimens; a greater proportion of AYA patients received the second-generation TKI nilotinib as a first-line treatment compared to adult patients, aligning with the observations of,\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e who noted age-based variations in TKI usage.\u003c/p\u003e \u003cp\u003eAltogether, 42 somatic mutations in 13 CRGs were identified, with a higher mutation frequency in AYA CML patients (25.0%) compared to adults (19.6%) and pediatric (12.5%) patients treated in real-clinical practice. Additionally, among Ph\u0026thinsp;+\u0026thinsp;ALL patients, AYA individuals were diagnosed with CRG mutations more frequently (53.3%) than children (26.7%) and adult patients (38.9%). The elevated mutational burden in AYAs in both diseases is notable. However, the landscape of mutated genes at diagnosis differed between CML-CP patients and Ph\u0026thinsp;+\u0026thinsp;ALL with \u003cem\u003eASXL1\u003c/em\u003e, \u003cem\u003eDNMT3A\u003c/em\u003e and \u003cem\u003eTET2\u003c/em\u003e as the three most frequently mutated genes among 193 CML-CP patients, while \u003cem\u003eRUNX1\u003c/em\u003e, \u003cem\u003eIKZF1\u003c/em\u003e and \u003cem\u003eBCR::ABL1\u003c/em\u003e were the most mutated genes in 81 Ph\u0026thinsp;+\u0026thinsp;ALL patients.\u003c/p\u003e \u003cp\u003e \u003cem\u003eASXL1\u003c/em\u003e was the most frequently mutated gene at diagnosis across pediatric, AYA and adult CML patients. Importantly, mutated \u003cem\u003eASXL1\u003c/em\u003e was significantly associated with cumulative incidence of \u003cem\u003eBCR::ABL1\u003c/em\u003e mutations acquisition on TKI therapy in adult CML patients, which was not observed in AYAs. CML patients with significantly lower probability of PFS were those who carried mutated \u003cem\u003eASXL1\u003c/em\u003e in both AYAs and adult patients in comparison with patients without mutations supporting the assumption that \u003cem\u003eASXL1\u003c/em\u003e is the CML-related oncogene.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Furthermore, \u003cem\u003eASXL1\u003c/em\u003e mutations appeared to contribute to impaired erythropoiesis, as evidenced by blood count abnormalities and reduced colony formation from erythroid progenitors, consistent with findings from previous studies.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e This observation should be validated in a larger cohort of CML patients with \u003cem\u003eASXL1\u003c/em\u003e mutations.\u003c/p\u003e \u003cp\u003eAlthough CRG mutations were detected at a lower frequency, their presence correlated with reduced PFS and enhanced the level of significance. Together, these findings support emerging evidence that mutations in CRGs detected at the time of diagnosis in CML-CP patients represent risk factors for disease progression. Based on \u003cem\u003eBCR::ABL1\u003c/em\u003e transcript kinetics and variant allele frequency (VAF) of mutations in CRGs, it is presumed that these mutations are present in CML cells, which is in line with previous works. \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eBCR::ABL1\u003c/em\u003e was the most frequent gene with mutation acquisition during TKI therapy with a markedly higher prevalence in adult patients, suggesting age-related susceptibility to additional mutations under TKI treatment pressure. This pattern aligns with, \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e who reported higher rates of new mutations in older CML patients during TKI therapy. \u003cem\u003eASXL1\u003c/em\u003e was the second most frequently mutated gene on TKI therapy, albeit at a much lower frequency than \u003cem\u003eBCR::ABL1\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eUnivariate analysis revealed that high SOKAL, EUTOS and ELTS scores along with \u003cem\u003eASXL1\u003c/em\u003e mutations were significantly associated with reduced PFS in adult patients. This pattern was not observed in AYAs, where nilotinib therapy showed significant association with PFS. Specifically, nilotinib was administered to 50% (6/12) of AYA patients with \u003cem\u003eASXL1\u003c/em\u003e mutations, highlighting that more potent TKIs than imatinib, when used as first-line therapy in patients with \u003cem\u003eASXL1\u003c/em\u003e mutations, may improve PFS.\u003c/p\u003e \u003cp\u003eAs this study is based on real-world data, this hypothesis requires validation in larger cohorts of patients treated with higher-generation TKIs as a first-line approach. Conversely, previous work based on clinical trial data indicated that patients with \u003cem\u003eASXL1\u003c/em\u003e mutations had inferior probability to achieve MMR on nilotinib as first-line therapy. \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e However, this study did not compare outcomes in patients treated with imatinib to evaluate the MMR rates in patients with \u003cem\u003eASXL1\u003c/em\u003e mutations.\u003c/p\u003e \u003cp\u003eIn conclusion, this comparative study on mutation frequency and mutational landscapes in AYA, pediatric, and adult patients with CML-CP and Ph\u0026thinsp;+\u0026thinsp;ALL revealed that CRG mutations were more frequently detected in AYA patients at the time of diagnosis. However, our findings did not support the initial hypothesis that AYA CML-CP patients might carry oncogenic mutations commonly observed in Ph\u0026thinsp;+\u0026thinsp;ALL. This study demonstrated that mutations in CRGs in CML-CP patients (both AYA and adults) represent a risk factor for disease progression during TKI therapy. Generally, CML-CP patients who responded optimally to TKI therapy showed lower mutation rates at diagnosis and follow-up, particularly among AYA patients, suggesting good adherence, better disease control, and fewer emergent mutations during therapy (with a higher proportion of AYA patients receiving nilotinib). Patients who did not respond to TKI therapy (treatment failures) exhibited higher mutation rates both at diagnosis and during follow-up. Nevertheless, adult patients generally showed higher mutation rates at follow-up, irrespective of response, suggesting a potential age-related factor. \u003cem\u003eASXL1\u003c/em\u003e mutations and other CRG mutations serve as risk factors for progression during TKI therapy in both AYA and adult CML-CP patients. Although overall, AYA do not seem to have a worse prognosis than others, despite having more mutations. Using higher generations of TKIs at diagnosis that effectively target CML cells with \u003cem\u003eASXL1\u003c/em\u003e mutations and possibly other CRGs could potentially reduce disease progression risk.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by MHCZ NU21-07-00225 and DRO (IHBT, 00023736). Samples collection was supported by grant no. LM2023033 (BBMRI.cz). Computational resources were provided by the e-INFRA CZ project (ID:90254), supported by the Ministry of Education, Youth and Sports of the Czech Republic.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJK performed experiments and data analyses and wrote the manuscript; VP, AL, AB, NC, TS performed experiments and data analyses; PS performed bioinformatic and statistical analyses; VV, DM, HK, MMS, DS, CS provided samples and clinical data from the adult patients; MZ, JZ, JT provided samples and patients characteristics; KMP designed the study, supervised the study, interpreted the data, and wrote the manuscript\u003c/p\u003e\n\u003cp\u003eAll authors revised and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKMP- Novartis - advisory board; support by Novartis through the European Treatment and Outcome Study (EUTOS) for CML.\u003c/p\u003e\n\u003cp\u003eThe remaining authors declare no competing financial interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eCortes JE, Jones D, O\u0026rsquo;Brien S, Jabbour E, Ravandi F, Koller C \u003cem\u003eet al.\u003c/em\u003e Results of dasatinib therapy in patients with early chronic-phase chronic myeloid leukemia. \u003cem\u003eJ Clin Oncol\u003c/em\u003e 2010; \u003cstrong\u003e28\u003c/strong\u003e: 389\u0026ndash;404.\u003c/li\u003e\n \u003cli\u003eSaglio G, Kim D-W, Issaragrisil S, le Coutre P, Etienne G, Lobo C \u003cem\u003eet al.\u003c/em\u003e Nilotinib versus imatinib for newly diagnosed chronic myeloid leukemia. \u003cem\u003eN Engl J Med\u003c/em\u003e 2010; \u003cstrong\u003e362\u003c/strong\u003e: 2251\u0026ndash;2259.\u003c/li\u003e\n \u003cli\u003eHochhaus A, Baccarani M, Silver RT, Schiffer C, Apperley JF, Cervantes F \u003cem\u003eet al.\u003c/em\u003e European LeukemiaNet 2020 recommendations for treating chronic myeloid leukemia. \u003cem\u003eLeukemia\u003c/em\u003e 2020; \u003cstrong\u003e34\u003c/strong\u003e: 966\u0026ndash;984.\u003c/li\u003e\n \u003cli\u003eJabbour E, Kantarjian HM, O\u0026rsquo;Brien S, Shan J, Quint\u0026aacute;s-Cardama A, Garcia-Manero G \u003cem\u003eet al.\u003c/em\u003e Front-line therapy with second-generation tyrosine kinase inhibitors in patients with early chronic phase chronic myeloid leukemia: what is the optimal response? \u003cem\u003eJ Clin Oncol\u003c/em\u003e 2011; \u003cstrong\u003e29\u003c/strong\u003e: 4260\u0026ndash;4265.\u003c/li\u003e\n \u003cli\u003eNational Cancer Institute SEER USA. SEER USA. https://seer.cancer.gov/statfacts/html/cmyl.html (accessed 18 Dec2024).\u003c/li\u003e\n \u003cli\u003eCancer Research UK. Cancer Research UK. https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/leukaemia-cml/incidence#heading-One (accessed 18 Dec2024).\u003c/li\u003e\n \u003cli\u003eCortes J, Talpaz M, O\u0026rsquo;Brien S, Giles F, Rios MB, Shan J \u003cem\u003eet al.\u003c/em\u003e Effects of age on prognosis with imatinib mesylate therapy for patients with Philadelphia chromosome-positive chronic myelogenous leukemia. \u003cem\u003eCancer\u003c/em\u003e 2003; \u003cstrong\u003e98\u003c/strong\u003e: 1105\u0026ndash;1113.\u003c/li\u003e\n \u003cli\u003eHasford J, Pfirrmann M, Hehlmann R, Allan NC, Baccarani M, Kluin-Nelemans JC \u003cem\u003eet al.\u003c/em\u003e A New Prognostic Score for Survival of Patients With Chronic Myeloid Leukemia Treated With Interferon Alfa Writing Committee for the Collaborative CML Prognostic Factors Project Group. \u003cem\u003eJNCI: Journal of the National Cancer Institute\u003c/em\u003e 1998; \u003cstrong\u003e90\u003c/strong\u003e: 850\u0026ndash;859.\u003c/li\u003e\n \u003cli\u003eSokal JE, Cox EB, Baccarani M, Tura S, Gomez GA, Robertson JE \u003cem\u003eet al.\u003c/em\u003e Prognostic discrimination in \u0026lsquo;good-risk\u0026rsquo; chronic granulocytic leukemia. \u003cem\u003eBlood\u003c/em\u003e 1984; \u003cstrong\u003e63\u003c/strong\u003e: 789\u0026ndash;99.\u003c/li\u003e\n \u003cli\u003eKalmanti L, Saussele S, Lauseker M, Proetel U, M\u0026uuml;ller MC, Hanfstein B \u003cem\u003eet al.\u003c/em\u003e Younger patients with chronic myeloid leukemia do well in spite of poor prognostic indicators: results from the randomized CML study IV. \u003cem\u003eAnn Hematol\u003c/em\u003e 2014; \u003cstrong\u003e93\u003c/strong\u003e: 71\u0026ndash;80.\u003c/li\u003e\n \u003cli\u003eCastagnetti F, Gugliotta G, Baccarani M, Breccia M, Specchia G, Levato L \u003cem\u003eet al.\u003c/em\u003e Differences among young adults, adults and elderly chronic myeloid leukemia patients. \u003cem\u003eAnn Oncol\u003c/em\u003e 2015; \u003cstrong\u003e26\u003c/strong\u003e: 185\u0026ndash;192.\u003c/li\u003e\n \u003cli\u003eSchmidt M, Rinke J, Sch\u0026auml;fer V, Schnittger S, Kohlmann A, Obstfelder E \u003cem\u003eet al.\u003c/em\u003e Molecular-defined clonal evolution in patients with chronic myeloid leukemia independent of the BCR-ABL status. \u003cem\u003eLeukemia\u003c/em\u003e 2014; \u003cstrong\u003e28\u003c/strong\u003e: 2292\u0026ndash;2299.\u003c/li\u003e\n \u003cli\u003eSch\u0026ouml;nfeld L, Rinke J, Hinze A, Nagel SN, Sch\u0026auml;fer V, Schenk T \u003cem\u003eet al.\u003c/em\u003e ASXL1 mutations predict inferior molecular response to nilotinib treatment in chronic myeloid leukemia. \u003cem\u003eLeukemia\u003c/em\u003e 2022; \u003cstrong\u003e36\u003c/strong\u003e: 2242\u0026ndash;2249.\u003c/li\u003e\n \u003cli\u003eBranford S, Kim DDH, Apperley JF, Eide CA, Mustjoki S, Ong ST \u003cem\u003eet al.\u003c/em\u003e Laying the foundation for genomically-based risk assessment in chronic myeloid leukemia. \u003cem\u003eLeukemia\u003c/em\u003e 2019; \u003cstrong\u003e33\u003c/strong\u003e: 1835\u0026ndash;1850.\u003c/li\u003e\n \u003cli\u003eShanmuganathan N, Wadham C, Shahrin N, Feng J, Thomson D, Wang P \u003cem\u003eet al.\u003c/em\u003e Impact of additional genetic abnormalities at diagnosis of chronic myeloid leukemia for first-line imatinib-treated patients receiving proactive treatment intervention. \u003cem\u003eHaematologica\u003c/em\u003e 2023. doi:10.3324/haematol.2022.282184.\u003c/li\u003e\n \u003cli\u003eAdnan Awad S, Kankainen M, Ojala T, Koskenvesa P, Eldfors S, Ghimire B \u003cem\u003eet al.\u003c/em\u003e Mutation accumulation in cancer genes relates to nonoptimal outcome in chronic myeloid leukemia. \u003cem\u003eBlood Adv\u003c/em\u003e 2020; \u003cstrong\u003e4\u003c/strong\u003e: 546\u0026ndash;559.\u003c/li\u003e\n \u003cli\u003eMidic D, Rinke J, Perner F, M\u0026uuml;ller V, Hinze A, Pester F \u003cem\u003eet al.\u003c/em\u003e Prevalence and dynamics of clonal hematopoiesis caused by leukemia-associated mutations in elderly individuals without hematologic disorders. \u003cem\u003eLeukemia\u003c/em\u003e 2020; \u003cstrong\u003e34\u003c/strong\u003e: 2198\u0026ndash;2205.\u003c/li\u003e\n \u003cli\u003eBranford S, Wadham C, Shanmuganathan N, Fernandes A, Shahrin NH, Feng J \u003cem\u003eet al.\u003c/em\u003e Age-Related Clonal Hematopoiesis Mutations Detected at the Time of Stopping Tyrosine Kinase Inhibitor Therapy Predict the Achievement of Treatment-Free Remission for Patients with CML. \u003cem\u003eBlood\u003c/em\u003e 2023; \u003cstrong\u003e142\u003c/strong\u003e: 447\u0026ndash;447.\u003c/li\u003e\n \u003cli\u003eErnst T, Busch M, Rinke J, Ernst J, Haferlach C, Beck JF \u003cem\u003eet al.\u003c/em\u003e Frequent ASXL1 mutations in children and young adults with chronic myeloid leukemia. \u003cem\u003eLeukemia\u003c/em\u003e 2018; \u003cstrong\u003e32\u003c/strong\u003e: 2046\u0026ndash;2049.\u003c/li\u003e\n \u003cli\u003eBenesova A, De Santis S, Polivkova V, Pecherkova P, Krizkova J, Suchankova P \u003cem\u003eet al.\u003c/em\u003e Unstable major molecular response as a trigger for next generation sequencing‐based \u003cem\u003eBCR::ABL1\u003c/em\u003e mutation testing in chronic myeloid leukemia. \u003cem\u003eAm J Hematol\u003c/em\u003e 2024; \u003cstrong\u003e99\u003c/strong\u003e: 759\u0026ndash;762.\u003c/li\u003e\n \u003cli\u003eKopanos C, Tsiolkas V, Kouris A, Chapple CE, Albarca Aguilera M, Meyer R \u003cem\u003eet al.\u003c/em\u003e VarSome: the human genomic variant search engine. \u003cem\u003eBioinformatics\u003c/em\u003e 2019; \u003cstrong\u003e35\u003c/strong\u003e: 1978\u0026ndash;1980.\u003c/li\u003e\n \u003cli\u003eCross NCP, White HE, M\u0026uuml;ller MC, Saglio G, Hochhaus A. Standardized definitions of molecular response in chronic myeloid leukemia. \u003cem\u003eLeukemia\u003c/em\u003e 2012; \u003cstrong\u003e26\u003c/strong\u003e: 2172\u0026ndash;2175.\u003c/li\u003e\n \u003cli\u003ePemmaraju N, Kantarjian H, Shan J, Jabbour E, Quintas-Cardama A, Verstovsek S \u003cem\u003eet al.\u003c/em\u003e Analysis of outcomes in adolescents and young adults with chronic myelogenous leukemia treated with upfront tyrosine kinase inhibitor therapy. \u003cem\u003eHaematologica\u003c/em\u003e 2012; \u003cstrong\u003e97\u003c/strong\u003e: 1029\u0026ndash;1035.\u003c/li\u003e\n \u003cli\u003eShi H, Yamamoto S, Sheng M, Bai J, Zhang P, Chen R \u003cem\u003eet al.\u003c/em\u003e ASXL1 plays an important role in erythropoiesis. \u003cem\u003eSci Rep\u003c/em\u003e 2016; \u003cstrong\u003e6\u003c/strong\u003e: 28789.\u003c/li\u003e\n \u003cli\u003eYamamoto S, Shi H, Chen S, Zhang P, Zhou Y, Xu M \u003cem\u003eet al.\u003c/em\u003e ASXL1 Is a Key Regulator for Erythroid Development and Asxl1 Loss Impairs Erythropoiesis In Vivo. \u003cem\u003eBlood\u003c/em\u003e 2015; \u003cstrong\u003e126\u003c/strong\u003e: 3644\u0026ndash;3644.\u003c/li\u003e\n \u003cli\u003eKim T, Tyndel MS, Kim HJ, Ahn J-S, Choi SH, Park HJ \u003cem\u003eet al.\u003c/em\u003e Spectrum of somatic mutation dynamics in chronic myeloid leukemia following tyrosine kinase inhibitor therapy. \u003cem\u003eBlood\u003c/em\u003e 2017; \u003cstrong\u003e129\u003c/strong\u003e: 38\u0026ndash;47.\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 2 are available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"leukemia","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"leu","sideBox":"Learn more about [Leukemia](http://www.nature.com/leu/)","snPcode":"41375","submissionUrl":"https://mts-leu.nature.com/cgi-bin/main.plex","title":"Leukemia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"AYA, CML, ASXL1, somatic mutations, eryhtropoiesis","lastPublishedDoi":"10.21203/rs.3.rs-5789724/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5789724/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAdolescent and young adult (AYA) patients with chronic myeloid leukemia in chronic phase (CML-CP) reportedly fare worse on tyrosine kinase inhibitor (TKIs) than adults. This real-life study compared mutation profiles and outcomes in 80 AYA, 97 adult, and 16 pediatric CML-CP patients, alongside 81 \u003cem\u003eBCR::ABL1\u003c/em\u003e-positive acute lymphoblastic leukemia (ALL) patients. Somatic mutations in cancer-related genes (CRGs) were more frequent in AYAs with CML-CP (25.0%) than in adults (19.6%) or children (12.5%). AYAs with Ph+ ALL also exhibited higher mutational frequencies (53.3%) compared to children (26.7%) and adults (38.9%). Mutation landscapes differed at diagnosis with \u003cem\u003eASXL1\u003c/em\u003e, \u003cem\u003eDNMT3A\u003c/em\u003e, and \u003cem\u003eTET2\u003c/em\u003edominant in CML-CP and \u003cem\u003eRUNX1\u003c/em\u003e, \u003cem\u003eIKZF1\u003c/em\u003e, and \u003cem\u003eBCR::ABL1\u003c/em\u003epredominated in Ph+ ALL. \u003cem\u003eASXL1 \u003c/em\u003emutations correlated with reduced progression-free survival (PFS) in AYAs and adults, with adults showing increased\u003cem\u003e BCR::ABL1 \u003c/em\u003emutations during TKI therapy, a trend not observed in AYAs. Nilotinib improved PFS in AYAs with ASXL1 mutations, highlighting the efficacy of higher-generation TKIs. \u003cem\u003eASXL1\u003c/em\u003e mutations also impaired erythropoiesis, warranting further validation. Despite a higher mutational burden, AYAs did not show worse prognoses than adults, with lower mutation rates at follow-up suggesting better adherence. Mutation profiling and optimized TKI use are crucial to mitigate progression risks in CRG-mutated patients.\u003c/p\u003e","manuscriptTitle":"Somatic Mutations and Outcomes in CML Adolescent and Young Adults Compared to Children, Adults, and BCR::ABL1-positive ALL Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-13 17:33:54","doi":"10.21203/rs.3.rs-5789724/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-01-27T16:24:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-01-27T11:26:27+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-01-23T14:28:00+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-01-09T13:05:43+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-01-09T12:58:19+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-01-09T12:31:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-09T12:20:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-09T12:20:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Leukemia","date":"2025-01-08T14:02:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"leukemia","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"leu","sideBox":"Learn more about [Leukemia](http://www.nature.com/leu/)","snPcode":"41375","submissionUrl":"https://mts-leu.nature.com/cgi-bin/main.plex","title":"Leukemia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7dc013ee-2ac0-44a4-aec2-e319059ffde1","owner":[],"postedDate":"January 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":42622471,"name":"Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Chronic myeloid leukaemia"},{"id":42622472,"name":"Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Acute lymphocytic leukaemia"}],"tags":[],"updatedAt":"2025-04-29T07:08:10+00:00","versionOfRecord":{"articleIdentity":"rs-5789724","link":"https://doi.org/10.1038/s41375-025-02609-3","journal":{"identity":"leukemia","isVorOnly":false,"title":"Leukemia"},"publishedOn":"2025-04-28 04:00:00","publishedOnDateReadable":"April 28th, 2025"},"versionCreatedAt":"2025-01-13 17:33:54","video":"","vorDoi":"10.1038/s41375-025-02609-3","vorDoiUrl":"https://doi.org/10.1038/s41375-025-02609-3","workflowStages":[]},"version":"v1","identity":"rs-5789724","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5789724","identity":"rs-5789724","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}