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.

Special Issue "Advances in Molecular Pathogenesis and Targeted Therapies for Myeloid Neoplasms".

Myeloid neoplasms (MNs) constitute a diverse group of haematological malignancies that includes myelodysplastic neoplasms (MDS), myeloproliferative neoplasms (MPN), MDS/MPN overlap syndrome, and acute myeloid leukaemia (AML) [...].

TP53 mutation variant allele frequency of ≥10% is associated with poor prognosis in therapy-related myeloid neoplasms.

Revised diagnostic criteria for myeloid neoplasms (MN) issued by the International Consensus Classification (ICC) and the World Health Organization (WHO) recommended major change pertaining to TP53-mutated (TP53mut) MN. However, these assertions have not been specifically examined in therapy-related myeloid neoplasm (t-MN), a subset enriched with TP53mut. We analyzed 488 t-MN patients for TP53mut. At least one TP53mut with variant allele frequency (VAF) ≥ 2% with or without loss of TP53 locus was noted in 182 (37.3%) patients and 88.2% of TP53mut t-MN had a VAF ≥10%. TP53mut t-MN with VAF ≥ 10% had a distinct clinical and biological profile compared to both TP53mut VAF < 10% and wild-type TP53 (TP53wt) cases. Notably, TP53mut VAF ≥ 10% had a significantly shorter survival compared to TP53wt (8.3 vs. 21.6 months; P < 0.001), while the survival of TP53mut VAF < 10% was comparable to TP53wt. Within TP53mut VAF ≥ 10% cohort, the inferior outcomes persisted irrespective of the single- or multi-hit status, co-mutation pattern, or treatments received. Finally, survival of TP53mut patients was poor across all the blast categories and MDS patients with >10% blasts had inferior survival compared to <5%. In summary, TP53mut VAF ≥10% signified a clinically and molecularly homogenous cohort regardless of the allelic status.

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.

A senescence stress secretome is a hallmark of therapy-related myeloid neoplasm stromal tissue occurring soon after cytotoxic exposure.

Therapy-related myeloid neoplasm (tMN) is considered a direct consequence of DNA damage in hematopoietic stem cells. Despite increasing recognition that altered stroma can also drive leukemogenesis, the functional biology of the tMN microenvironment remains unknown. We performed multiomic (transcriptome, DNA damage response, cytokine secretome and functional profiling) characterization of bone marrow stromal cells from tMN patients. Critically, we also compared (i) patients with myeloid neoplasm and another cancer but without cytotoxic exposure, (ii) typical primary myeloid neoplasm, and (iii) age-matched controls to decipher the microenvironmental changes induced by cytotoxics vs. neoplasia. Strikingly, tMN exhibited a profoundly senescent phenotype with induction of CDKN1A and ß-Galactosidase, defective phenotype, and proliferation. Moreover, tMN stroma showed delayed DNA repair and defective adipogenesis. Despite their dormant state, tMN stromal cells were metabolically highly active with a switch toward glycolysis and secreted multiple pro-inflammatory cytokines indicative of a senescent-secretory phenotype that inhibited adipogenesis. Critically, senolytics not only eliminated dormant cells, but also restored adipogenesis. Finally, sequential patient sampling showed senescence phenotypes are induced within months of cytotoxic exposure, well prior to the onset of secondary cancer. Our data underscores a role of senescence in the pathogenesis of tMN and provide a valuable resource for future therapeutics.

Clinical impact of NPM1-mutant molecular persistence after chemotherapy for acute myeloid leukemia.

Monitoring of NPM1 mutant (NPM1mut) measurable residual disease (MRD) in acute myeloid leukemia (AML) has an established role in patients who are treated with intensive chemotherapy. The European LeukemiaNet has defined molecular persistence at low copy number (MP-LCN) as an MRD transcript level <1% to 2% with a <1-log change between any 2 positive samples collected after the end of treatment (EOT). Because the clinical impact of MP-LCN is unknown, we sought to characterize outcomes in patients with persistent NPM1mut MRD after EOT and identify factors associated with disease progression. Consecutive patients with newly diagnosed NPM1mut AML who received ≥2 cycles of intensive chemotherapy were included if bone marrow was NPM1mut MRD positive at the EOT, and they were not transplanted in first complete remission. One hundred patients were followed for a median of 23.5 months; 42% remained free of progression at 1 year, either spontaneously achieving complete molecular remission (CRMRD-; 30%) or retaining a low-level NPM1mut transcript (12% for ≥12 months and 9% at last follow-up). Forty percent met the criteria for MP-LCN. Preemptive salvage therapy significantly prolonged relapse-free survival. Risk factors associated with disease progression were concurrent FLT3-internal tandem duplication at diagnosis and suboptimal MRD response (NPM1mut reduction <4.4-log) at EOT.

CKLF and IL1B transcript levels at diagnosis are predictive of relapse in children with pre-B-cell acute lymphoblastic leukaemia.

Disease relapse is the greatest cause of treatment failure in paediatric B-cell acute lymphoblastic leukaemia (B-ALL). Current risk stratifications fail to capture all patients at risk of relapse. Herein, we used a machine-learning approach to identify B-ALL blast-secreted factors that are associated with poor survival outcomes. Using this approach, we identified a two-gene expression signature (CKLF and IL1B) that allowed identification of high-risk patients at diagnosis. This two-gene expression signature enhances the predictive value of current at diagnosis or end-of-induction risk stratification suggesting the model can be applied continuously to help guide implementation of risk-adapted therapies.

Modelling ponatinib resistance in tyrosine kinase inhibitor-naïve and dasatinib resistant BCR-ABL1+ cell lines.

TKI resistance remains a major impediment to successful treatment of CML. In this study, we investigated the emerging modes of ponatinib resistance in TKI-naïve and dasatinib resistant BCR-ABL1+ cell lines. To investigate potential resistance mechanisms, ponatinib resistance was generated in BCR-ABL1+ cell-lines by long-term exposure to increasing concentrations of ponatinib. Two cell lines with prior dasatinib resistance demonstrated BCR-ABL1 kinase domain (KD) mutation(s) upon exposure to ponatinib. In one of these cell lines the T315I mutation had emerged during dasatinib exposure. When further cultured with ponatinib, the T315I mutation level and BCR-ABL1 mRNA expression level were increased. In the other cell line, compound mutations G250E/E255K developed with ponatinib exposure. In contrast, the ponatinib resistant cell lines that had no prior exposure to other TKIs (TKI-naïve) did not develop BCR-ABL1 KD mutations. Rather, both of these cell lines demonstrated Bcr-Abl-independent resistance via Axl overexpression. Axl, a receptor tyrosine kinase, has previously been associated with imatinib and nilotinib resistance. Ponatinib sensitivity was restored following Axl inhibition or shRNA-mediated-knockdown of Axl, suggesting that Axl was the primary driver of resistance and a potential target for therapy in this setting.

Co-fuse: a new class discovery analysis tool to identify and prioritize recurrent fusion genes from RNA-sequencing data.

Recurrent oncogenic fusion genes play a critical role in the development of various cancers and diseases and provide, in some cases, excellent therapeutic targets. To date, analysis tools that can identify and compare recurrent fusion genes across multiple samples have not been available to researchers. To address this deficiency, we developed Co-occurrence Fusion (Co-fuse), a new and easy to use software tool that enables biologists to merge RNA-seq information, allowing them to identify recurrent fusion genes, without the need for exhaustive data processing. Notably, Co-fuse is based on pattern mining and statistical analysis which enables the identification of hidden patterns of recurrent fusion genes. In this report, we show that Co-fuse can be used to identify 2 distinct groups within a set of 49 leukemic cell lines based on their recurrent fusion genes: a multiple myeloma (MM) samples-enriched cluster and an acute myeloid leukemia (AML) samples-enriched cluster. Our experimental results further demonstrate that Co-fuse can identify known driver fusion genes (e.g., IGH-MYC, IGH-WHSC1) in MM, when compared to AML samples, indicating the potential of Co-fuse to aid the discovery of yet unknown driver fusion genes through cohort comparisons. Additionally, using a 272 primary glioma sample RNA-seq dataset, Co-fuse was able to validate recurrent fusion genes, further demonstrating the power of this analysis tool to identify recurrent fusion genes. Taken together, Co-fuse is a powerful new analysis tool that can be readily applied to large RNA-seq datasets, and may lead to the discovery of new disease subgroups and potentially new driver genes, for which, targeted therapies could be developed. The Co-fuse R source code is publicly available at https://github.com/sakrapee/co-fuse .