Tet2 loss leads to hypermutagenicity in haematopoietic stem/progenitor cells

TET2 is a dioxygenase that catalyses multiple steps of 5-methylcytosine oxidation. Although TET2 mutations frequently occur in various types of haematological malignancies, the mechanism by which they increase risk for these cancers remains poorly understood. Here we show that Tet2?/? mice develop spontaneous myeloid, T- and B-cell malignancies after long latencies. Exome sequencing of Tet2?/? tumours reveals accumulation of numerous mutations, including Apc, Nf1, Flt3, Cbl, Notch1 and Mll2, which are recurrently deleted/mutated in human haematological malignancies. Single-cell-targeted sequencing of wild-type and premalignant Tet2?/? Lin?c-Kit+ cells shows higher mutation frequencies in Tet2?/? cells. We further show that the increased mutational burden is particularly high at genomic sites that gained 5-hydroxymethylcytosine, where TET2 normally binds. Furthermore, TET2-mutated myeloid malignancy patients have significantly more mutational events than patients with wild-type TET2. Thus, Tet2 loss leads to hypermutagenicity in haematopoietic stem/progenitor cells, suggesting a novel TET2 loss-mediated mechanism of haematological malignancy pathogenesis

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

Tet2 loss leads to hypermutagenicity in haematopoietic stem/progenitor cells

TET2 is a dioxygenase that catalyses multiple steps of 5-methylcytosine oxidation. Although TET2 mutations frequently occur in various types of haematological malignancies, the mechanism by which they increase risk for these cancers remains poorly understood. Here we show that Tet2-/- mice develop spontaneous myeloid, T- and B-cell malignancies after long latencies. Exome sequencing of Tet2-/- tumours reveals accumulation of numerous mutations, including Apc, Nf1, Flt3, Cbl, Notch1 and Mll2, which are recurrently deleted/mutated in human haematological malignancies. Single-cell-targeted sequencing of wild-type and premalignant Tet2-/- Lin-c-Kit+ cells shows higher mutation frequencies in Tet2-/- cells. We further show that the increased mutational burden is particularly high at genomic sites that gained 5-hydroxymethylcytosine, where TET2 normally binds. Furthermore, TET2-mutated myeloid malignancy patients have significantly more mutational events than patients with wild-type TET2. Thus, Tet2 loss leads to hypermutagenicity in haematopoietic stem/progenitor cells, suggesting a novel TET2 loss-mediated mechanism of haematological malignancy pathogenesis

A Machine Learning Model of Response to Hypomethylating Agents in Myelodysplastic Syndromes

Hypomethylating agents (HMA) prolong survival and improve cytopenias in individuals with higher-risk myelodysplastic syndrome (MDS). Only 30-40% of patients, however, respond to HMAs, and responses may not occur for more than 6 months after HMA initiation. We developed a model to more rapidly assess HMA response by analyzing early changes in patients’ blood counts. Three institutions’ data were used to develop a model that assessed patients’ response to therapy 90 days after the initiation using serial blood counts. The model was developed with a training cohort of 424 patients from2 institutions and validated on an independent cohort of 90 patients. The final model achieved an area under the receiver operating characteristic curve (AUROC) of 0.79 in the train/test group and 0.84 in the validation group. The model provides cohort-wide and individual- level explanations for model predictions, and model certainty can be interrogated to gauge the reliability of a given prediction

TP53 mutation status divides myelodysplastic syndromes with complex karyotypes into distinct prognostic subgroups

Risk stratification is critical in the care of patients with myelodysplastic syndromes (MDS). Approximately 10% have a complex karyotype (CK), defined as more than two cytogenetic abnormalities, which is a highly adverse prognostic marker. However, CK-MDS can carry a wide range of chromosomal abnormalities and somatic mutations. To refine risk stratification of CK-MDS patients, we examined data from 359 CK-MDS patients shared by the International Working Group for MDS. Mutations were underrepresented with the exception of TP53 mutations, identified in 55% of patients. TP53 mutated patients had even fewer co-mutated genes but were enriched for the del(5q) chromosomal abnormality (p 10%), abnormal 3q, abnormal 9, and monosomy 7 as having the greatest survival risk. The poor risk associated with CK-MDS is driven by its association with prognostically adverse TP53 mutations and can be refined by considering clinical and karyotype features

Special considerations in the management of adult patients with acute leukaemias and myeloid neoplasms in the COVID-19 era: recommendations from a panel of international experts

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 is a global public health crisis. Multiple observations indicate poorer post-infection outcomes for patients with cancer than for the general population. Herein, we highlight the challenges in caring for patients with acute leukaemias and myeloid neoplasms amid the COVID-19 pandemic. We summarise key changes related to service allocation, clinical and supportive care, clinical trial participation, and ethical considerations regarding the use of lifesaving measures for these patients. We recognise that these recommendations might be more applicable to high-income countries and might not be generalisable because of regional differences in health-care infrastructure, individual circumstances, and a complex and highly fluid health-care environment. Despite these limitations, we aim to provide a general framework for the care of patients with acute leukaemias and myeloid neoplasms during the COVID-19 pandemic on the basis of recommendations from international experts

The use of immunosuppressive therapy in MDS: clinical outcomes and their predictors in a large international patient cohort

Most studies of immunosuppressive therapy (IST) in myelodysplastic syndromes (MDS) are limited by small numbers and their single-center nature, and report conflicting data regarding predictors for response to IST. We examined outcomes associated with IST and predictors of benefit in a large international cohort of patients with MDS. Data were collected from 15 centers in the United States and Europe. Responses, including red blood cell (RBC) transfusion independence (TI), were assessed based on the 2006 MDS International Working Group criteria, and overall survival (OS) was estimated by Kaplan-Meier methods. Logistic regression models estimated odds for response and TI, and Cox Proportional Hazard models estimated hazards ratios for OS. We identified 207 patients with MDS receiving IST, excluding steroid monotherapy. The most common IST regimen was anti-thymocyte globulin (ATG) plus prednisone (43%). Overall response rate (ORR) was 48.8%, including 11.2% (95% confidence interval [CI], 6.5%-18.4%) who achieved a complete remission and 30% (95% CI, 22.3%-39.5%) who achieved RBC TI. Median OS was 47.4 months (95% CI, 37-72.3 months) and was longer for patients who achieved a response or TI. Achievement of RBC TI was associated with a hypocellular bone marrow (cellularity < 20%); horse ATG plus cyclosporine was more effective than rabbit ATG or ATG without cyclosporine. Age, transfusion dependence, presence of paroxysmal nocturnal hemoglobinuria or large granular lymphocyte clones, and HLA DR15 positivity did not predict response to IST. IST leads to objective responses in nearly half the selected patients with the highest rate of RBC TI achieved in patients with hypocellular bone marrows

Precision Medicine in Myelodysplastic Syndromes and Leukemias: Lessons from Sequential Mutations

Precision medicine can be simply defined as the identification of personalized treatment that matches patient-specific clinical and genomic characteristics. Since the completion of the Human Genome Project in 2003, significant advances have been made in our understanding of the genetic makeup of diseases, especially cancers. The identification of somatic mutations that can drive cancer has led to the development of therapies that specifically target the abnormal proteins derived from these mutations. This has led to a paradigm shift in our treatment methodology. Although some success has been achieved in targeting some genetic abnormalities, several challenges and limitations exist when applying precision-medicine concepts in leukemia and myelodysplastic syndromes. We review the current understanding of genomics in myelodysplastic syndromes (MDS) and leukemias and the limitations of precision-medicine concepts in MDS