IDH-mutant myeloid neoplasms are associated with seronegative rheumatoid arthritis and innate immune activation.

ABSTRACT: High prevalence of IDH mutations in seronegative rheumatoid arthritis (RA) with myeloid neoplasm, elevated 2-hydroxyglutarate, dysregulated innate immunity, and proinflammatory microenvironment suggests causative association between IDH mutations and seronegative RA. Our findings merit investigation of IDH inhibitors as therapeutics for seronegative IDH-mutated RA.

Beyond BCR::ABL1-The Role of Genomic Analyses in the Management of CML.

Chronic myeloid leukemia (CML) is a model of genomically based diagnosis and management where BCR::ABL1 is successfully targeted by tyrosine kinase inhibitor (TKI) therapy in most patients. The dynamics of BCR::ABL1 transcript decline during therapy is a dependable biomarker of response, relapse, and drug resistance. Missense mutations acquired within the BCR::ABL1 kinase domain that disrupt TKI binding can evolve during therapy and are frequently detected in patients for whom TKI treatment fails. Importantly, specific BCR::ABL1 missense mutations are targetable alterations and direct therapeutic decisions based on the individual mutant TKI sensitivity profile. Nevertheless, BCR::ABL1 mutations are only implicated in approximately half of the cases of acquired resistance. Furthermore, not all patients with a single BCR::ABL1 mutation that is predicted to be sensitive to a specific TKI will experience a response when switched to that TKI. Progression to blast phase heralds independence from BCR::ABL1, and this phase of the disease is notoriously difficult to treat. The independent drivers of resistance and disease progression have long been investigated to both predict progression and to find targets for therapeutic intervention. Recent data reaffirm that drug resistance and disease progression is a mutation-driven process in CML, and somatic variants in genes that are known to drive acute myeloid and lymphoid leukemia have been detected in patients in the advanced phases of CML. Genomic testing over the last few decades for patients with blood cancer has revealed of variety of genomic aberrations that drive disease. Consequently, incorporation of genomic factors into patient management for a range of blood cancers has led to the implementation of high-throughput gene testing to detect clinically actionable variants. Is it time to integrate broader genomic screening into clinical management strategies for patients with CML?

European LeukemiaNet laboratory recommendations for the diagnosis and management of chronic myeloid leukemia.

From the laboratory perspective, effective management of patients with chronic myeloid leukemia (CML) requires accurate diagnosis, assessment of prognostic markers, sequential assessment of levels of residual disease and investigation of possible reasons for resistance, relapse or progression. Our scientific and clinical knowledge underpinning these requirements continues to evolve, as do laboratory methods and technologies. The European LeukemiaNet convened an expert panel to critically consider the current status of genetic laboratory approaches to help diagnose and manage CML patients. Our recommendations focus on current best practice and highlight the strengths and pitfalls of commonly used laboratory tests.

Adverse outcomes for chronic myeloid leukemia patients with splenomegaly and low in vivo kinase inhibition on imatinib.

Variability in the molecular response to frontline tyrosine kinase inhibitor (TKI) therapy in chronic myeloid leukemia may be partially driven by differences in the level of kinase inhibition induced. We measured in vivo BCR::ABL1 kinase inhibition (IVKI) in circulating mononuclear cells after 7 days of therapy. In 173 patients on imatinib 600 mg/day, 23% had low IVKI (<11% reduction in kinase activity from baseline); this was associated with higher rates of early molecular response (EMR) failure; lower rates of major molecular response (MMR), and MR4.5 by 36 months, compared to high IVKI patients. Low IVKI was more common (39%) in patients with large spleens (≥10 cm by palpation). Notably 55% of patients with large spleens and low IVKI experienced EMR failure whereas the EMR failure rate in patients with large spleens and high IVKI was only 12% (p = 0.014). Furthermore, patients with large spleen and low IVKI had a higher incidence of blast crisis, inferior MMR, MR4.5, and event-free survival compared to patients with large spleen and high IVKI and remaining patients. In nilotinib-treated patients (n = 73), only 4% had low IVKI. The combination of low IVKI and large spleen is associated with markedly inferior outcomes and interventions in this setting warrant further studies.

Lineage-specific detection of residual disease predicts relapse in patients with chronic myeloid leukemia stopping therapy.

ABSTRACT: Patients with chronic myeloid leukemia who are eligible for treatment-free remission (TFR) may still relapse after tyrosine kinase inhibitor (TKI) cessation. There is a need for accurate predictors of outcome to enable patients with a favorable profile to proceed while avoiding futile attempts. Sensitive detection of residual disease in total leukocytes at treatment cessation is associated with relapse but is not highly discriminatory, likely because it is a composite measure of residual leukemia derived from different cell lineages, whereas only some lineages are relevant for relapse. We prospectively measured BCR::ABL1 DNA as a predictive yes/no binary test in 5 cellular fractions from 48 patients meeting conventional criteria for TKI discontinuation. The median BCR::ABL1 DNA level was higher in granulocytes and T cells, but not in other lineages, in patients who relapsed. Among the 40 patients undergoing their first TFR attempt, we defined 3 groups with differing relapse risk: granulocyte-positive group (100%), granulocyte-negative/T-cell-positive group (67%), and granulocyte-negative /T-cell-negative group (25%). These data show the critical importance of lineage-specific assessment of residual disease in the selection of patients who can attempt to achieve TFR with a high expectation of success and, concurrently, defer patients who have a high probability of relapse.

Immune modulation in chronic myeloid leukaemia patients treated with nilotinib and interferon-alpha.

The addition of interferon to tyrosine kinase inhibitors (TKIs), to improve deep molecular response (DMR) and potentially treatment-free remission (TFR) rates in chronic-phase chronic myeloid leukaemia (CP-CML) patients is under active investigation. However, the immunobiology of this combination is poorly understood. We performed a comprehensive longitudinal assessment of immunological changes in CML patients treated with nilotinib and interferon-alpha (IFN-α) within the ALLG CML11 trial (n = 12) or nilotinib alone (n = 17). We demonstrate that nilotinib+IFN transiently reduced absolute counts of natural killer (NK) cells, compared with nilotinib alone. Furthermore, CD16+ -cytolytic and CD57+ CD62L- -mature NK cells were transiently reduced during IFN therapy, without affecting NK-cell function. IFN transiently increased cytotoxic T-lymphocyte (CTL) responses to leukaemia-associated antigens (LAAs) proteinase-3, BMI-1 and PRAME; and had no effect on regulatory T cells, or myeloid-derived suppressor cells. Patients on nilotinib+IFN who achieved MR4.5 by 12 months had a significantly higher proportion of NK cells expressing NKp46, NKp30 and NKG2D compared with patients not achieving this milestone. This difference was not observed in the nilotinib-alone group. The addition of IFN to nilotinib drives an increase in NK-activating receptors, CTLs responding to LAAs and results in transient immune modulation, which may influence earlier DMR, and its effect on long-term outcomes warrants further investigation.

Impact of additional genetic abnormalities at diagnosis of chronic myeloid leukemia for first-line imatinib-treated patients receiving proactive treatment intervention.

The BCR::ABL1 gene fusion initiates chronic myeloid leukemia (CML); however, evidence has accumulated from studies of highly selected cohorts that variants in other cancer-related genes are associated with treatment failure. Nevertheless, the true incidence and impact of additional genetic abnormalities (AGA) at diagnosis of chronic phase (CP)-CML is unknown. We sought to determine whether AGA at diagnosis in a consecutive imatinib-treated cohort of 210 patients enrolled in the TIDEL-II trial influenced outcome despite a highly proactive treatment intervention strategy. Survival outcomes including overall survival, progression-free survival, failure-free survival, and BCR::ABL1 kinase domain mutation acquisition were evaluated. Molecular outcomes were measured at a central laboratory and included major molecular response (MMR, BCR::ABL1 ≤0.1%IS), MR4 (BCR::ABL1 ≤0.01%IS), and MR4.5 (BCR::ABL1 ≤0.0032%IS). AGA included variants in known cancer genes and novel rearrangements involving the formation of the Philadelphia chromosome. Clinical outcomes and molecular response were assessed based on the patient's genetic profile and other baseline factors. AGA were identified in 31% of patients. Potentially pathogenic variants in cancer-related genes were detected in 16% of patients at diagnosis (including gene fusions and deletions) and structural rearrangements involving the Philadelphia chromosome (Ph-associated rearrangements) were detected in 18%. Multivariable analysis demonstrated that the combined genetic abnormalities plus the EUTOS long-term survival clinical risk score were independent predictors of lower molecular response rates and higher treatment failure. Despite a highly proactive treatment intervention strategy, first-line imatinib-treated patients with AGA had poorer response rates. These data provide evidence for the incorporation of genomically-based risk assessment for CML.

Molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis.

Tyrosine kinase inhibitor therapy revolutionized chronic myeloid leukemia treatment and showed how targeted therapy and molecular monitoring could be used to substantially improve survival outcomes. We used chronic myeloid leukemia as a model to understand a critical question: why do some patients have an excellent response to therapy, while others have a poor response? We studied gene expression in whole blood samples from 112 patients from a large phase III randomized trial (clinicaltrials gov. Identifier: NCT00471497), dichotomizing cases into good responders (BCR::ABL1 ≤10% on the International Scale by 3 and 6 months and ≤0.1% by 12 months) and poor responders (failure to meet these criteria). Predictive models based on gene expression demonstrated the best performance (area under the curve =0.76, standard deviation =0.07). All of the top 20 pathways overexpressed in good responders involved immune regulation, a finding validated in an independent data set. This study emphasizes the importance of pretreatment adaptive immune response in treatment efficacy and suggests biological pathways that can be targeted to improve response.

Association of TIM-3 checkpoint receptor expression on T cells with treatment-free remission in chronic myeloid leukemia.

Dysregulation of immune-checkpoint receptors has been reported at diagnosis of chronic myeloid leukemia (CML), however, their role in the maintenance of remission after tyrosine kinase inhibitor (TKI) cessation is unclear. We assessed programmed cell death-1 (PD-1), T-cell immunoglobulin, and mucin-domain containing protein-3 (TIM-3), cytotoxic T-lymphocyte-associated protein-4 (CTLA-4), lymphocyte-activation gene-3 (LAG-3), and T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif (ITIM) domains (TIGIT) expression on T-cell subsets, regulatory T cells (T-regs), and natural killer (NK) cells at the time of TKI cessation in 44 patients (22 patients sustained treatment-free remission [TFR] and 22 experienced molecular relapse [MolR]). We confirmed our previous finding that absolute numbers of T-regs are increased in patients who experienced MolR compared with those who sustained TFR. The immune-checkpoint receptors PD-1, CTLA-4, LAG-3, and TIGIT on T or NK cells were not differentially expressed between the MolR and TFR groups. However, TIM-3 was consistently upregulated on bulk T cells (CD3+) and T-cell subsets including, CD4+ T cells, CD8+ T cells, and T-regs, in patients who relapsed in comparison with those who maintained TFR after discontinuation. Furthermore, gene expression analysis from publicly available data sets showed increased TIM-3 expression on CML stem cells compared with normal hematopoietic stem cells. These findings suggest that among the targetable immune-checkpoint molecules, TIM-3 blockade may potentially improve effector immune response in patients with CML stopping TKI, while concomitantly targeting leukemic stem cells and could be a promising therapeutic strategy for preventing relapse after cessation of TKI in patients with CML.

Measurable residual disease in chronic myeloid leukemia.

Chronic myeloid leukemia is characterized by a single genetic abnormality resulting in a fusion gene whose mRNA product is easily detected and quantified by reverse-transcriptase polymerase chain reaction analysis. Measuring residual disease was originally introduced to identify patients relapsing after allogeneic stem cell transplantation but rapidly adopted to quantify responses to tyrosine kinase inhibitors. Real-time quantitative polymerase chain reaction is now an essential tool for the management of patients and is used to influence treatment decisions. In this review we track this development including the international collaboration to standardize results, discuss the integration of molecular monitoring with other factors that affect patients' management, and describe emerging technology. Four case histories describe varying scenarios in which the accurate measurement of residual disease identified patients at risk of disease progression and allowed appropriate investigations and timely clinical intervention.

Genomic profiling for clinical decision making in myeloid neoplasms and acute leukemia.

Myeloid neoplasms and acute leukemias derive from the clonal expansion of hematopoietic cells driven by somatic gene mutations. Although assessment of morphology plays a crucial role in the diagnostic evaluation of patients with these malignancies, genomic characterization has become increasingly important for accurate diagnosis, risk assessment, and therapeutic decision making. Conventional cytogenetics, a comprehensive and unbiased method for assessing chromosomal abnormalities, has been the mainstay of genomic testing over the past several decades and remains relevant today. However, more recent advances in sequencing technology have increased our ability to detect somatic mutations through the use of targeted gene panels, whole-exome sequencing, whole-genome sequencing, and whole-transcriptome sequencing or RNA sequencing. In patients with myeloid neoplasms, whole-genome sequencing represents a potential replacement for both conventional cytogenetic and sequencing approaches, providing rapid and accurate comprehensive genomic profiling. DNA sequencing methods are used not only for detecting somatically acquired gene mutations but also for identifying germline gene mutations associated with inherited predisposition to hematologic neoplasms. The 2022 International Consensus Classification of myeloid neoplasms and acute leukemias makes extensive use of genomic data. The aim of this report is to help physicians and laboratorians implement genomic testing for diagnosis, risk stratification, and clinical decision making and illustrates the potential of genomic profiling for enabling personalized medicine in patients with hematologic neoplasms.

Defining Higher-Risk Chronic Myeloid Leukemia: Risk Scores, Genomic Landscape, and Prognostication.

PURPOSE OF REVIEW: The chronic myeloid leukemia (CML) treatment success story is incomplete as some patients still fail therapy, leading to end-stage disease and death. Here we discuss recent research into CML incidence, the role of comorbidities on survival and detecting patients at risk of failing therapy. RECENT FINDINGS: The incidence of CML has fallen markedly in high social-demographic index (SDI) regions of the world but there is disturbing evidence that this is not the case in low and low-middle SDI countries. Now that CML patients more frequently die from their co-morbid conditions than from CML the Adult Comorbidity Evaluation-27 score can assist in risk assessment at diagnosis. Non-adherence to therapy contributes greatly to treatment failure. A good doctor-patient relationship and social support promote good adherence, but patient age, gender, and financial burden have negative effects, suggesting avenues for intervention. Mutations in cancer-associated genes adversely affect outcome and their detection at diagnosis may guide therapeutic choice and offer non-BCR::ABL1 targeted therapies. A differential gene expression signature to assist risk detection is a highly sought-after diagnostic tool being actively researched on several fronts. Detecting patients at risk of failing therapy is being assisted by recent technological advances enabling highly sensitive genomic and expression analysis of insensitive cells. However, patient lifestyle, adherence to therapy, and comorbidities are critical risk factors that need to be addressed by interventions such as social and financial support.

International Consensus Classification of Myeloid Neoplasms and Acute Leukemias: integrating morphologic, clinical, and genomic data.

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.

RNA-Based Targeted Gene Sequencing Improves the Diagnostic Yield of Mutant Detection in Chronic Myeloid Leukemia.

Mutation detection is increasingly used for the management of hematological malignancies. Prior whole transcriptome and whole exome sequencing studies using total RNA and DNA identified diverse mutation types in cancer-related genes associated with treatment failure in patients with chronic myeloid leukemia. Variants included single-nucleotide variants and small insertions/deletions, plus fusion transcripts and partial or whole gene deletions. The hypothesis that all of these mutation types could be detected by a single cost-effective hybridization capture next-generation sequencing method using total RNA was assessed. A method was developed that targeted 130 genes relevant for myeloid and lymphoid leukemia. Retrospective samples with 121 precharacterized variants were tested using total RNA and/or DNA. Concordance of detection of precharacterized variants using RNA or DNA was 96%, whereas the enhanced sensitivity identified additional variants. Comparison between 24 matched DNA and RNA samples demonstrated 95.3% of 170 variants detectable using DNA were detected using RNA, including all but one variant predicted to activate nonsense-mediated decay. RNA identified an additional 10 variants, including fusion transcripts. Furthermore, the true effect of splice variants on RNA splicing was only evident using RNA. In conclusion, capture sequencing using total RNA alone is suitable for detecting a range of variants relevant in chronic myeloid leukemia and may be more broadly applied to other hematological malignancies where diverse variant types define risk groups.

Genomic Mechanisms Influencing Outcome in Chronic Myeloid Leukemia.

Chronic myeloid leukemia (CML) represents the disease prototype of genetically based diagnosis and management. Tyrosine kinase inhibitors (TKIs), that target the causal BCR::ABL1 fusion protein, exemplify the success of molecularly based therapy. Most patients now have long-term survival; however, TKI resistance is a persistent clinical problem. TKIs are effective in the BCR::ABL1-driven chronic phase of CML but are relatively ineffective for clinically defined advanced phases. Genomic investigation of drug resistance using next-generation sequencing for CML has lagged behind other hematological malignancies. However, emerging data show that genomic abnormalities are likely associated with suboptimal response and drug resistance. This has already been supported by the presence of BCR::ABL1 kinase domain mutations in drug resistance, which led to the development of more potent TKIs. Next-generation sequencing studies are revealing additional mutations associated with resistance. In this review, we discuss the initiating chromosomal translocation that may not always be a straightforward reciprocal event between chromosomes 9 and 22 but can sometimes be accompanied by sequence deletion, inversion, and rearrangement. These events may biologically reflect a more genomically unstable disease prone to acquire mutations. We also discuss the future role of cancer-related gene mutation analysis for risk stratification in CML.