Citations

NPM1 mutations (NPM1+) are found in about 30% of adult AML. While NPM1+ are generally associated with favorable risk, prior studies have shown that NPM1+ older patients, defined as ≥ 65 years, have significantly worse outcomes. The updated European Leukemia Net 2022 (ELN22) now classifies NPM1+ AML patients with FLT3-ITD (ITD+) and MDS-associated mutations (MDSm+) as adverse-risk, while NPM1+/ITD-/MDSm+ patients remain favorable-risk unless they have an adverse-risk karyotype. A recent report (Chan et al., Blood Adv 2024) found MDSm+ conferred worse OS only in patients ≥ 60 years; however another report (Othman et al., Blood 2024) did not find MDSm+ were significantly associated with adverse outcomes in a larger cohort of NPM1+ patients. To further assess this question, we examined the mutational landscape in a large cohort of pre-treatment, diagnostic specimens from 456 patients enrolled in SWOG clinical trials (SWOG-9031, SWOG-9333, S0106, and S0112) and 126 patients from the UW/FHCC Hematopoietic Repository (Total N=582). Patients were treated with curative intent as per standard practice or clinical trials. Out of the 582 patients, 191 were NPM1+ (33%), of which 148 patients had cytogenetic and long-term outcome data. Kaplan-Meier and cumulative incidence estimates were estimated. C-statistics and AUC for Cox, cause-specific and logistic regression models for overall survival (OS), event-free survival (EFS), time to relapse (TTR, calculated in n=106 who achieved complete remission [CR], death in remission analyzed as a competing risk) and CR were calculated for age, ELN17, and ELN22, as well as ELN17 and ELN22 adjusting for age. ELN17 favorable-risk patients reclassified as adverse-risk (N=5 of 108) demonstrated significantly shorter EFS (HR=2.50, p=0.05) and CR rate (OR=0.20, p=0.024), although with similar OS (HR 1.30, p=0.66) and TTR (HR=1.20, p=0.86). ELN17 favorable-risk patients reclassified as ELN22 intermediate-risk (N=23 of 108) did not show a significant difference in OS (HR 1.47, p=0.20), EFS (HR 1.35, p=0.12), CR rate (OR 0.75, p=0.46), or TTR (HR=1.64, p=0.11) compared to ELN22 favorable-risk. For ELN17 intermediate-risk (N=40), 5 patients were reclassified as ELN22 adverse-risk (12.5%) and had significantly shorter EFS (HR 2.89, p=0.037) compared to ELN22 intermediate risk, although there was not a significant difference in CR rate (OR 0.31, p=0.23) or OS (HR 0.81, p=0.67). We next compared the prognostic significance of age relative to ELN risk classification. Age was associated with higher C-statistics (OS=0.65, TTR=0.57 and EFS=0.60) and AUC (CR=0.64) compared to both ELN17 (OS=0.56, TTR=0.54, EFS=0.54, CR=0.54) or ELN22 (OS=0.57, TTR=0.57, EFS=0.57, CR=0.58). The combination of age and ELN22 resulted in the highest C-statistics for OS, TTR, and EFS (OS=0.68, TTR=0.60, EFS=0.64). To further assess the impact of MDSm on risk-stratification of NPM1+ AML, we performed multivariable analyses adjusting for FLT3-ITD, MDSm, and age in patients without adverse-risk disease. These analyses showed MDSm did not have a significant association with OS when controlling for age or FLT3-ITD. We also compared ELN22 favorable-risk patients with and without MDSm (MDSm+ N=18; MDSm- N=61). Compared with the MDSm-, there was a trend toward an inferior OS (HR 1.85, p=0.054) for MDSm+ patients but not EFS (HR 1.38, p=0.3) or TTR (HR 1.2, p=0.64). When stratified by age (<65, N=53 vs. ≥65, N=26), MDSm+ in younger patients did not show a difference for OS (HR 0.96, p=0.96), EFS (HR 0.63, p=0.53) or TTR (HR 0.4, p=0.37). Older ELN22 favorable-risk patients (≥65) had similarly poor OS (MDSm- HR 3.33 and MDSm+ 3.27, respectively, p=0.001 for both) and EFS (MDSm- HR 3.11 and MDSm+ 2.39, p=0.001 and 0.01) compared to younger MDSm- patients. In our study, the ELN22 guidelines incrementally improve risk stratification for EFS in NPM1+ patients. However, age remains the most prognostic factor, and patients ≥ 65 years have similar adverse clinical outcomes, whether classified as favorable risk by ELN17, ELN22, or incorporating MDSm. Moreover, MDSm do not confer a worse prognosis in NPM1+ patients when accounting for age or FLT3-ITD status. These findings differ from a recent report by Chan et al. and are in keeping with the report by Othman et al. Therefore, further understanding of the underlying biology of age and its effect on NPM1+ AML is needed to improve outcomes for older patients.

Background. Study of myeloid neoplasms (MN) has been rapidly transformed by genome characterization. Gene mutations have been reported to influence disease phenotype and risk of disease progression, and the evaluation of mutational status can provide valuable insights to improve the decision-making process. In this international study, we evaluated the clinical impact of mutational screening in patients with CMML, which is characterized by significant clinical and genomic heterogeneity, including a substantial proportion of patients with poor outcomes and unmet needs. Currently, only limited molecular information has been incorporated into CMML classification and prognostication. Methods. We retrospectively collected 3182 CMML patients. We used MOSAIC, an AI-based framework for multimodal analysis in rare cancers (PMID: 38875514) to develop innovative, molecular-based tools for classification and prognostication. An independent validation of the results on 516 prospectively collected patients was performed. Results. Bayesian Networs and Hierarchical Dirichlet Processes were used to identify genomic associations and define a CMML molecular classification. We identified 11 clusters with distinct clinical and genomic features, including splicing machinery, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures (i.e., AML-like and TP53 mutations). Up to 15% of patients showed clear genomic overlap with other MN. Importantly, extensive multi-color flow cytometry on T lymphocytes, NK and myeloid cells (BD FACSymphony A5 Cell Analyzer) revealed specific immunologic and inflammation signatures associated with molecular subgroups. We then integrated molecular and clinical information to build an international CMML Prognostic Scoring System (iCPSS). We assessed the performance of different statistical and AI-based methods; L1-penalized Cox Model resulted as the best performing method. Selected features included hematological parameters (WBC, Hb, PLT and marrow blasts), cytogenetic abnormalities, and mutations in 10 genes (ASXL1, DNMT3A, EZH2, NRAS, RUNX1, SETBP1, STAG2, TET2, TP53, U2AF1). By Bayesian thresholds optimization, we identified 5 risk classes (i.e., very-low, low, intermediate, high and very-high) with median overall survival (OS) ranging from 99 to 9 months (P<.001), and median leukemia-free survival (LFS) ranging from 210 to 18 months (P<.001). iCPSS provided better patient discrimination across all clinical endpoints compared to currently available prognostic tools, with a Concordance Index (CI) for OS of 0.75 versus 0.62-0.64, respectively. Notably, compared to available scoring systems, up to 40% of patients were reassigned to higher or lower risk classes by the iCPSS. External validation on an independent prospective cohort confirmed that the performance of iCPSS is superior to existing prognostic models (CI for OS 0.71 vs 0.54-0.61, respectively) To demonstrate the clinical utility of iCPSS, we focused on 753 patients who underwent allogeneic stem cell transplantation (HSCT). In multivariable analysis, iCPSS stratified the probability of OS post-HSCT (P<.001) and identified groups of patients with different probabilities of disease relapse, ranging from 9% to 62% (P<.001). We employed a clinical- and genomic-based decision support system (PMID: 38723212) to determine the optimal timing of HSCT. Preliminary analyses indicated that higher-risk patients according to iCPSS (i.e., intermediate, high, and very high) benefit from an immediate HSCT strategy. Lower-risk patients (i.e., very low and low) had life expectancy maximized with delayed HSCT. Modeling decision analysis using iCPSS compared to conventional scores, resulted in a change in transplantation policy for a significant proportion of patients (up to 25%). Conclusion. Molecular information significantly improves the classification of CMML patients, providing a basis for refining diagnostic boundaries with other MN and for a more rational inclusion of patients in clinical trials. The iCPSS demonstrated superior performance over currently available scoring systems and improved HSCT decision making process.

Purpose: The aim of this study was to identify successful recruitment strategies and obstacles reported by principal investigators (PIs) of the Zoster Eye Disease Study (ZEDS). Methods: A web-based survey was created by a subset of ZEDS PIs and distributed to ZEDS PIs after study enrollment was closed. The survey queried investigators about recruitment strategies and obstacles, use of prophylactic oral antiviral medication, electronic medical records, telemedicine, COVID-19 effect, turnover of research staff, and recruitment outreach to minority and underserved populations. The survey allowed objective measures and free-text options. Analysis from centers with higher enrollment was compared with centers with lower enrollment to identify successful strategies and common obstacles. Results: The most frequently cited helpful strategies were participation from ophthalmologists within the PI's institution (33/63, 52%), ophthalmology resident referrals (23/63, 37%), and chart review (23/63, 37%). Travel to participating clinical center (42/63, 67%) and ongoing prophylactic use of oral systemic antiviral medication (39/63, 62%) were common obstacles. Research coordinator turnover was identified as a contributor to reduced recruitment success by 49% (31/63) of PIs and made recruitment much harder for 22% (14/63). A small number of investigators used telemedicine (18/63, 29%) and few made efforts to recruit from minority and underserved populations (10/63, 16%). Conclusions: Our survey highlights the importance of internal ophthalmologist referral, chart review, and research coordinator commitment for successful clinical trial recruitment. We discuss the impact of prophylactic use of oral antiviral medication on recruitment. Future randomized clinical trials should mobilize the helpful recruitment strategies and improve outreach to underserved populations.

AbstractIntroductionAcute myeloid leukemia (AML) remains one of the deadliest hematopoietic malignancies. A better understanding of the molecular biology governing AML may lead to improved risk stratification and facilitate the development of novel therapies. Proteins are responsible for much of the biology of cells. Several studies have examined the global proteome in bulk mononuclear cells (MNCs) from AML specimens, which are comprised a heterogenous population of cells at various stages of differentiation.MethodsGiven the potential impact of the nonleukemic cells on protein expression profiles, we applied an integrative proteogenomic approach utilizing next‐generation sequencing and mass spectrometry‐based proteomics to identify novel protein biomarkers in unsorted MNCs and viable leukemic blasts (VLBs) isolated from blood and bone marrow specimens obtained at the time of AML diagnosis.ResultsWe identified significant differences in protein expression between VLBs and MNCs. Subsequent studies (N = 27) focused on proteomic profiling of VLBs that identified novel candidate biomarkers associated with mutational genotypes and clinical outcome, some of which were recapitulated in an independent cohort of patients. Using mass spectrometry, we also detected mutated protein products, some of which were predicted via in silico analyses to be potential neoantigens amenable to adoptive immunotherapy. As previously described, analyses comparing transcript and protein expression showed an overall modest correlation between mRNA and protein dataset, but enriching for genes associated with mutations significantly improved the protein–RNA correlation.ConclusionTogether, the results provide insight into the biology of VLBs and demonstrate the gains derived from examining the proteome in addition to genome and transcriptome.

The pathogenesis of asthma in elderly is not well understood. Using a mouse model of asthma, we show that aging results in decreased lung function and less responsiveness to allergen exposure, impacted by locally produced brain-derived neurotrophic factor. Aging also decreases allergen-induced inflammation but increases airway remodeling and senescence. Our results suggest that senescence pathways may contribute to asthma pathogenesis in elderly.

Endotoxemia is closely related to many diseases. As the largest endotoxin reservoir in the human body, the gut microbiota should be a key target for alleviating endotoxemia. The intestinal microbiota is believed to cause endotoxemia directly or indirectly by modifying the intestinal barrier function through dysbiosis, changing intestinal mucosal permeability and bacterial translocation. Diet is known to be the main environmental factor affecting the intestinal microbiota, and different diets and food components have a large impact on the gut microbiota. The Mediterranean diet, which received much attention in recent years, is believed to be able to regulate the gut microbiota, thereby maintaining the function of the intestinal barrier and alleviating endotoxemia. In this review, we focus on the relationship between the gut microbiota and endotoxemia, and how the Mediterranean dietary (MD) pattern can interfere with endotoxemia through the gut microbiota.

Most patients with metastatic prostate cancer eventually develop resistance to primary androgen deprivation therapy. To identify predictive biomarker for Abiraterone acetate/prednisone resistance, we screened alternative splice variants between responders and non-responders from the PROMOTE clinical study and pinned down the most significant variant, CENPK–delta8. Through preclinical patient-derived mouse xenograft (PDX) and 3D organoids obtained from responders and non-responders, as well as in vitro models, aberrant CENPK–delta8 expression was determined to link to drug resistance via enhanced migration and proliferation. The FLNA and FLOT1 were observed to specifically bind to CENK–delta8 rather than wild-type CENPK, underscoring the role of CENPK–delta8 in cytoskeleton organization and cell migration. Our study, leveraging data from the PROMOTE study, TCGA, and TCGA SpliceReq databases, highlights the important function of alternative splice variants in drug response and their potential to be prognostic biomarkers for improving individual therapeutic outcomes in precision medicine.