Molecular analysis of myelodysplastic syndrome with isolated deletion of the long arm of chromosome 5 reveals a specific spectrum of molecular mutations with prognostic impact: a study on 123 patients and 27 genes

The only cytogenetic aberration defining a myelodysplastic syndrome subtype is the deletion of the long arm of chromosome 5, which, along with morphological features, leads to the diagnosis of myelodysplastic syndrome with isolated deletion of the long arm of chromosome 5. These patients show a good prognosis and respond to treatment such as lenalidomide, but some cases progress to acute myeloid leukemia; however, the molecular mutation pattern is rarely characterized. Therefore, we investigated a large cohort of 123 myelodysplastic syndrome patients with isolated deletion of the long arm of chromosome 5, diagnosed following the World Health Organization classifications 2008 and 2016, by sequencing 27 genes. A great proportion of patients showed no or only one mutation. Only seven genes showed mutation frequencies >5% (SF3B1, DNMT3A, TP53, TET2, CSNK1A1, ASXL1, JAK2). However, the pattern of recurrently mutated genes was comparable to other myelodysplastic syndrome subtypes by comparison to a reference cohort, except that of TP53 which was significantly more often mutated in myelodysplastic syndrome with isolated deletion of the long arm of chromosome 5. As expected, SF3B1 was frequently mutated and correlated with ring sider-oblasts, while JAK2 mutations correlated with elevated platelet counts. Surprisingly, SF3B1 mutations led to significantly worse prognosis within cases with isolated deletion of the long arm of chromosome 5, but showed a comparable outcome to other myelodysplastic syndrome subtypes with SF3B1 mutation. However, addressing genetic stability in follow-up cases might suggest different genetic mechanisms for progression to secondary acute myeloid leukemia compared to overall myelodysplastic syndrome patients

Adverse prognostic impact of complex karyotype (≥3 cytogenetic alterations) in adult T-cell acute lymphoblastic leukemia (T-ALL)

Cytogenetics; Prognosis; TherapyCitogenética; Pronóstico; TerapiaCitogenètica; Pronòstic; TeràpiaThe potential prognostic value of conventional karyotyping in adult T-cell acute lymphoblastic leukemia (T-ALL) remains an open question. We hypothesized that a modified cytogenetic classification, based on the number and type of cytogenetic abnormalities, would allow the identification of high-risk adult T-ALL patients. Complex karyotype defined by the presence of ≥3 cytogenetic alterations identified T-ALL patients with poor prognosis in this study. Karyotypes with ≥3 abnormalities accounted for 16 % (22/139) of all evaluable karyotypes, corresponding to the largest poor prognosis cytogenetic subgroup of T-ALL identified so far. Patients carrying karyotypes with ≥3 cytogenetic alterations showed a significantly inferior response to therapy, and a poor outcome in terms of event-free survival (EFS), overall survival (OS) and cumulative incidence of relapse (CIR), independently of other baseline characteristics and the end-induction minimal residual disease (MRD) level. Additional molecular analyses of patients carrying ≥3 cytogenetic alterations showed a unique molecular profile that could contribute to understand the underlying molecular mechanisms of resistance and to evaluate novel targeted therapies (e.g. IL7R directed) with potential impact on outcome of adult T-ALL patients.This project was supported by the AECC (GC16173697BIGA); ISCIII (PI19/01828) co-funded by ERDF/ESF "A way to make Europe"/"Investing in your future", CERCA/Generalitat de Catalunya SGR 2017 288 (GRC)/ “La Caixa” P. Barba was supported by the Instituto de Salud Carlos III FIS16/01433 and PERIS 2018-2020 from Generalitat de Catalunya (BDNS357800)

Different prognostic impact of recurrent gene mutations in chronic lymphocytic leukemia depending on IGHV gene somatic hypermutation status: a study by ERIC in HARMONY

Cancer genetics; Genetics researchGenètica del càncer; Recerca genèticaGenética del cáncer; Investigación genéticaRecent evidence suggests that the prognostic impact of gene mutations in patients with chronic lymphocytic leukemia (CLL) may differ depending on the immunoglobulin heavy variable (IGHV) gene somatic hypermutation (SHM) status. In this study, we assessed the impact of nine recurrently mutated genes (BIRC3, EGR2, MYD88, NFKBIE, NOTCH1, POT1, SF3B1, TP53, and XPO1) in pre-treatment samples from 4580 patients with CLL, using time-to-first-treatment (TTFT) as the primary end-point in relation to IGHV gene SHM status. Mutations were detected in 1588 (34.7%) patients at frequencies ranging from 2.3–9.8% with mutations in NOTCH1 being the most frequent. In both univariate and multivariate analyses, mutations in all genes except MYD88 were associated with a significantly shorter TTFT. In multivariate analysis of Binet stage A patients, performed separately for IGHV-mutated (M-CLL) and unmutated CLL (U-CLL), a different spectrum of gene alterations independently predicted short TTFT within the two subgroups. While SF3B1 and XPO1 mutations were independent prognostic variables in both U-CLL and M-CLL, TP53, BIRC3 and EGR2 aberrations were significant predictors only in U-CLL, and NOTCH1 and NFKBIE only in M-CLL. Our findings underscore the need for a compartmentalized approach to identify high-risk patients, particularly among M-CLL patients, with potential implications for stratified management.The European Research Initiative on CLL (ERIC) is a partner in the HARMONY Alliance, the EHA Scientific Working group on CLL and the ELN Workpackage 7 on CLL. This work was in part supported by; Associazione Italiana per la Ricerca sul Cancro—AIRC, Milano, Italy (Investigator Grant #20246 and Special Program on Metastatic Disease—5 per mille #21198); ERA NET TRANSCAN-2 Joint Transnational Call for Proposals: JTC 2014 (project #143 GCH-CLL) and JTC 2016 (project #179 NOVEL), project code (MIS) 5041673; Bando della Ricerca Finalizzata 2018, Ministero della Salute, Roma, Italy (progetto RF-2018–12368231); “la Caixa” Foundation (Health Research 2017 Program HR17-00221); the American Association for Cancer Research (2021 AACR-Amgen Fellowship in Clinical/Translational Cancer Research, 21-40-11-NADE), the European Hematology Association (EHA Junior Research Grant 2021, RG-202012-00245), and the Lady Tata Memorial Trust (International Award for Research in Leukaemia 2021-2022, LADY_TATA_21_3223); the Hellenic Precision Medicine Network in Oncology; project ODYSSEAS (Intelligent and Automated Systems for enabling the Design, Simulation and Development of Integrated Processes and Products) implemented under the “Action for the Strategic Development on the Research and Technological Sector”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014-2020) and co-financed by Greece and the European Union, with grant agreement no: MIS 5002462”; MH CZ—DRO (FNBr, 65269705), NV19-03-00091 and the project National Institute for Cancer Research (Programme EXCELES, ID Project No. LX22NPO5102)—Funded by the European Union—Next-Generation EU; Instituto de Salud Carlos III (ISCIII), “PI21/00983”, co-funded by the European Union; the EU’s Horizon 2020 research and innovation program under grant agreement No. 739593, by the Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund, financed under the K21_137948, FK20_134253, TKP2021-EGA-24 and TKP2021-NVA-15 funding schemes, and Elixir Hungary; Instituto de Salud Carlos III (ISCIII), “PI21/00983”, co-funded by the European Union; Fondo di Ateneo per la Ricerca (FAR) 2019, 2020 and 2021 of the University of Ferrara (GMR; AC), Associazione Italiana contro le Leucemie-Linfomi e Mieloma ONLUS Ferrara (AC; GMR), BEAT Leukemia Foundation Milan Italy (AC); the Danish Cancer Society and the CLL-CLUE project under the frame of ERA PerMed; Cancer Research UK (ECRIN-M3 accelerator award C42023/A29370, Southampton Experimental Cancer Medicine Centre grant C24563/A15581, Cancer Research UK Southampton Centre grant C34999/A18087, and programme C2750/A23669); the Swedish Cancer Society (19 0425 Pj 01 H), the Swedish Research Council (2020-01750), the Knut and Alice Wallenberg Foundation (2016.0373), Region Stockholm (ALF/FoUI-962423), and Radiumhemmets Forskningsfonder (194133), Stockholm; and Lion’s Cancer Research Foundation, Uppsala

A case of familial donor-derived acute myeloid leukemia with underlying pre-leukemic mutations

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Fusion partner–specific mutation profiles and KRAS mutations as adverse prognostic factors in MLL-rearranged AML

急性骨髄性白血病の予後を予測する新規マーカーを発見 --リスクに応じた適切な治療につながる可能性--. 京都大学プレスリリース. 2020-10-02.Mixed-lineage leukemia (MLL) gene rearrangements are among the most frequent chromosomal abnormalities in acute myeloid leukemia (AML). MLL fusion patterns are associated with the patient’s prognosis; however, their relationship with driver mutations is unclear. We conducted sequence analyses of 338 genes in pediatric patients with MLL-rearranged (MLL-r) AML (n = 56; JPLSG AML-05 study) alongside data from the TARGET study’s pediatric cohorts with MLL-r AML (n = 104), non–MLL-r AML (n = 581), and adult MLL-r AML (n = 81). KRAS mutations were most frequent in pediatric patients with high-risk MLL fusions (MLL-MLLLT10, MLL-MLLT4, and MLL-MLLT1). Pediatric patients with MLL-r AML (n = 160) and a KRAS mutation (KRAS-MT) had a significantly worse prognosis than those without a KRAS mutation (KRAS-WT) (5-year event-free survival [EFS]: 51.8% vs 18.3%, P < .0001; 5-year overall survival [OS]: 67.3% vs 44.3%, P = .003). The adverse prognostic impact of KRAS mutations was confirmed in adult MLL-r AML. KRAS mutations were associated with adverse prognoses in pediatric patients with both high-risk (MLLT10+MLLT4+MLLT1; n = 60) and intermediate-to-low–risk (MLLT3+ELL+others; n = 100) MLL fusions. The prognosis did not differ significantly between patients with non–MLL-r AML with KRAS-WT or KRAS-MT. Multivariate analysis showed the presence of a KRAS mutation to be an independent prognostic factor for EFS (hazard ratio [HR], 2.21; 95% confidence interval [CI], 1.35-3.59; P = .002) and OS (HR, 1.85; 95% CI, 1.01-3.31; P = .045) in MLL-r AML. The mutation is a distinct adverse prognostic factor in MLL-r AML, regardless of risk subgroup, and is potentially useful for accurate treatment stratification. This trial was registered at the UMIN (University Hospital Medical Information Network) Clinical Trials Registry (UMIN-CTR; http://www.umin.ac.jp/ctr/index.htm) as #UMIN000000511

Machine learning integrates genomic signatures for subclassification beyond primary and secondary acute myeloid leukemia

Although genomic alterations drive the pathogenesis of acute myeloid leukemia (AML), traditional classifications are largely based on morphology, and prototypic genetic founder lesions define only a small proportion of AML patients. The historical subdivision of primary/de novo AML and secondary AML has shown to variably correlate with genetic patterns. The combinatorial complexity and heterogeneity of AML genomic architecture may have thus far precluded genomic-based subclassification to identify distinct molecularly defined subtypes more reflective of shared pathogenesis. We integrated cytogenetic and gene sequencing data from a multicenter cohort of 6788 AML patients that were analyzed using standard and machine learning methods to generate a novel AML molecular subclassification with biologic correlates corresponding to underlying pathogenesis. Standard supervised analyses resulted in modest cross-validation accuracy when attempting to use molecular patterns to predict traditional pathomorphologic AML classifications. We performed unsupervised analysis by applying the Bayesian latent class method that identified 4 unique genomic clusters of distinct prognoses. Invariant genomic features driving each cluster were extracted and resulted in 97% cross-validation accuracy when used for genomic subclassification. Subclasses of AML defined by molecular signatures overlapped current pathomorphologic and clinically defined AML subtypes. We internally and externally validated our results and share an open-access molecular classification scheme for AML patients. Although the heterogeneity inherent in the genomic changes across nearly 7000 AML patients was too vast for traditional prediction methods, machine learning methods allowed for the definition of novel genomic AML subclasses, indicating that traditional pathomorphologic definitions may be less reflective of overlapping pathogenesis