Foucar, Kathryn

Abstract Myelodysplastic syndromes (MDS) are clinically and biologically diverse disorders, emphasizing the need for personalized treatment approaches. The International Working Group for Prognostication of MDS (IWG_PM) recently introduced a molecular classification, referred to as the MDS taxonomy, that categorizes patients into 16 subgroups based on 21 gene mutations, 6 cytogenetic abnormalities, and loss of heterozygosity (LOH) at TP53 and TET2 loci. This study sought to validate and enhance the clinical relevance of the MDS taxonomy by analyzing a large retrospective cohort ( n = 5136) and transcriptomic data from a prospective cohort ( n = 477). The taxonomy successfully identified subgroups with distinct clinical characteristics and disease progression patterns. However, incorporating gene interactions from taxonomy subgroups did not improve the prognostic performance of the Molecular International Prognostic Scoring System (IPSS‐M). We further assessed whether the taxonomy could guide management in patients receiving disease‐modifying therapies. Except for the “ TP53 ‐complex” subgroup, taxonomy classifications were not predictive of hypomethylating agent response or transplant outcomes. Nonetheless, they correlated with overall survival, suggesting that while both IPSS‐M and the taxonomy capture disease biology, other non‐genetic factors may influence treatment response. RNA sequencing confirmed the biological distinctiveness of the taxonomy groups. Transcriptomic profiling of CD34+ bone marrow cells revealed unique, homogeneous gene expression patterns, particularly within the AML‐like, bi TET2 , SF3B1 , and TP53 ‐complex subgroups. Further integration of multi‐omics data may refine MDS classification, improving clinical decision‐making and guiding the development of targeted therapies.

ABSTRACT Background Chronic myelomonocytic leukemia (CMML) is largely a disease of individuals older than 50 years; its occurrence in patients aged 50 years and younger is rare. The authors sought to characterize the clinicopathologic features and genetic profile of young‐onset (age 50 years and younger) CMML (y‐CMML) compared with older onset (older than 50 years) CMML (o‐CMML). Methods The authors conducted a multi‐institutional study of 32 patients with y‐CMML and 119 patients with o‐CMML, analyzing clinical, morphologic, cytogenetic, and molecular data. Results Patients who had y‐CMML frequently presented with splenomegaly (59% vs. 11%; p < .001) and hepatomegaly (25% vs. 2%; p < .001) compared with those who had o‐CMML. Although the overall incidence of cytogenetic abnormalities was similar, patients who had y‐CMML exhibited distinct mutational patterns. PTPN11 mutations were significantly more common in y‐CMML (13% vs. 3%; p = .034) than in o‐CMML, whereas TET2 (6% vs. 57%; p < .001) and SRSF2 (16% vs. 46%; p = .002) mutations were significantly less frequent. In addition, multi‐hit TET2 (6% vs. 34%; p = .002) and TET2‐SRSF2 (3% vs. 29%; p = .003) co‐mutations were rare in y‐CMML. However, the molecular differences did not affect the CMML‐specific risk‐stratification categories because the clinical outcomes, including overall survival and leukemia‐free survival, did not differ between the two groups. Conclusions CMML in patients aged 50 years and younger is rare and presents with unique clinical and mutational features, suggesting a distinct pathogenesis.

ABSTRACT The World Health Organization (WHO) 5th Edition and International Consensus Classification (ICC) have continued to delineate more genetically defined acute leukemias. Both recognize genetic aberrations associated with myelodysplastic syndromes/neoplasms (MDS) as defining MDS‐related AML (AML‐MR). Mutations in RUNX1 are included in this category in the ICC, but not WHO. The current classifications are unclear on how acute leukemias with ambiguous lineage (ALAL), including those of mixed lineage (MPAL) and those without a defined lineage (AUL), should be categorized in the presence of such mutations. Our multi‐institutional study aims to determine the significance of RUNX1 mutation in ALAL compared to de novo AML. Newly diagnosed MPAL, AUL, and AML with RUNX1 mutations were collected. ALAL with MDS‐related cytogenetics, BCR::ABL1 , KMT2A rearrangements, or ZNF384 or BCL11b abnormalities were excluded. We analyzed 17 cases of ALAL and 71 cases of AML that met inclusion criteria. ALAL‐ RUNX1 and AML‐ RUNX1 showed overlapping mutational landscapes with frequent comutations in MDS‐associated genes. No ALAL‐ RUNX1 or AML‐ RUNX1 cases showed concomitant TP53 mutation. ALAL‐ RUNX1 had more bone marrow blasts and more karyotypic abnormalities; however, neither impacted survival, nor did RUNX1 variant allele frequency (VAF). Survival analysis revealed similarly poor outcomes between them. AML‐directed therapies and allogeneic hematopoietic stem cell transplant trended toward improved survival in ALAL‐ RUNX1; however, it did not reach significance. Our results suggest ALAL‐ RUNX1 is associated with younger age, higher blasts, and more karyotypic abnormalities, but has similar clinical and genetic features and outcomes to AML‐ RUNX1 . Our findings suggest, like other MR mutations, RUNX1 ‐mutated ALALs should be included within AML‐MR.

Abstract Objective The successful diagnosis and classification of lymphoid neoplasms in blood and bone marrow is the responsibility of the practicing pathologist. This guide provides a general “roadmap” for this process, from initial case recognition to final classification. Methods The integration of hematologic, morphologic, immunophenotypic, and genetic features for the full spectrum of precursor and mature B-cell, T-cell, and natural killer–cell neoplasms that typically manifest in blood and bone marrow is included. Results Classification systems for lymphoid neoplasms provide criteria for pathologists to render a diagnosis that is optimal for patient care, treatment, and outcome prediction. Conclusions This guide provides diagnostic strategies for lymphoid neoplasms encountered in blood and bone marrow specimens using both the International Consensus Classification and the World Health Organization fifth edition classification systems. Key tips are provided for each entity along with testing requirements, differential diagnosis, nonneoplastic mimics, and other unique features based on the experience of the Bone Marrow Pathology Group members.

Abstract The classification of myeloid neoplasms and acute leukemias was last updated in 2016 within a collaboration between the World Health Organization (WHO), the Society for Hematopathology, and the European Association for Haematopathology. This collaboration was primarily based on input from a clinical advisory committees (CACs) composed of pathologists, hematologists, oncologists, geneticists, and bioinformaticians from around the world. The recent advances in our understanding of the biology of hematologic malignancies, the experience with the use of the 2016 WHO classification in clinical practice, and the results of clinical trials have indicated the need for further revising and updating the classification. As a continuation of this CAC-based process, the authors, a group with expertise in the clinical, pathologic, and genetic aspects of these disorders, developed the International Consensus Classification (ICC) of myeloid neoplasms and acute leukemias. Using a multiparameter approach, the main objective of the consensus process was the definition of real disease entities, including the introduction of new entities and refined criteria for existing diagnostic categories, based on accumulated data. The ICC is aimed at facilitating diagnosis and prognostication of these neoplasms, improving treatment of affected patients, and allowing the design of innovative clinical trials.

AbstractEnumeration of blasts and promonocytes is essential for World Health Organization (WHO) classification of myelomonocytic neoplasms. The accuracy of distinguishing blasts, promonocytes and monocytes, including normal vs abnormal monocytes, remains controversial. The objective of this analysis is to assess concordances between experienced hematopathologists in classifying cells as blasts, promonocytes, and monocytes according to WHO criteria. Each of 11 hematopathologists assessed glass slides from 20 patients [12 with chronic myelomonocytic leukemia (CMML) and 8 with acute myeloid leukemia (AML)] including blood and BM aspirate smears, and limited nonspecific esterase (NSE) stains. All cases were blindly reviewed. Fleiss’ extension of Cohen's kappa for multiple raters was used on these variables, separately for peripheral blood (PB) and bone marrow (BM). Spearman's rank correlation was used to assess correlations between each pair of hematopathologists for each measurement. For the classification based on the sum of blasts and promonocytes in the BM, Fleiss’ kappa was estimated as 0.744. For PB, categorizing patients according to the sum of blasts and promonocytes, Fleiss’ kappa was estimated as 0.949. Distinction of abnormal monocytes from normal monocytes in PB did not achieve a good concordance and showed strong evidence of differences between hematopathologists (P < .0001). The hematopathologists achieved a good concordance rate of 74% in CMML vs AML classification and a high k rate, confirming that criteria for defining the blasts equivalents (blasts plus promonocytes) could be applied consistently. Identification of monocyte subtypes (abnormal vs normal) was not concordant. Our results support the practice of combining blasts/promonocytes into a single category.

It is controversial whether acute myeloid leukemia (AML) patients with 20–29% bone marrow (BM) blasts, formerly referred to as refractory anemia with excess blasts in transformation (RAEBT), should be considered AML or myelodysplastic syndrome (MDS) for the purposes of treatment and prognostication. We retrospectively studied 571 de novo AML in patients aged >50 years, including 142 RAEBT and 429 with ≥30% blasts (AML30), as well as 151 patients with 10–19% BM blasts (RAEB2). RAEBT patients were older and had lower white blood count, but higher hemoglobin, platelet count, and karyotype risk scores compared to AML30, while these features were similar to RAEB2. FLT3 and NPM1 mutations and monocytic morphology occurred more commonly in AML30 than in RAEBT. RAEBT patients were treated less often with induction therapy than AML30, whereas allogeneic stem cell transplant frequency was similar. The median and 4‐year OS of RAEBT patients were longer than those of AML30 patients (20.5 vs 12.0 months and 28.6% vs 20.4%, respectively, P = 0.003); this difference in OS was manifested in patients in the intermediate UKMRC karyotype risk group, whereas OS of RAEBT patients and AML30 patients in the adverse karyotype risk group were not significantly different. Multivariable analysis showed that RAEBT (P < 0.0001), hemoglobin (P = 0.005), UKMRC karyotype risk group (P = 0.002), normal BM karyotype (P = 0.004), treatment with induction therapy (P < 0.0001), and stem cell transplant (P < 0.0001) were associated with longer OS. Our findings favor considering de novo RAEBT as a favorable prognostic subgroup of AML. Am. J. Hematol. 89:E193–E199, 2014. © 2014 Wiley Periodicals, Inc.