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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.

BackgroundVariable flip angle (VFA) and modified Look–Locker inversion recovery (MOLLI) are frequently used for noninvasive evaluation of renal interstitial fibrosis (IF) in chronic kidney disease (CKD). However, controversy remains over which method is preferred.PurposeTo compare the diagnostic efficacy of VFA and MOLLI for T1 mapping in evaluating renal IF.Study TypeProspective.SubjectsFifty‐one participants with CKD (CKD stage 1–5, 35 males) and 18 healthy volunteers (eight males).Field Strength/Sequence3.0 T, three‐dimensional gradient echo sequence for B1+ VFA, and two‐dimensional gradient echo sequence for MOLLI.AssessmentImage quality was assessed on a five‐point scale. Cortex and medulla T1 values (cT1 and mT1), corticomedullary T1 value difference (ΔT1, medulla − cortex), and corticomedullary T1 value ratio (ratio T1, cortex:medulla) were compared between VFA and MOLLI as well as between IF grade (0–4) based on biopsy.Statistical TestsIntraclass correlation coefficient, Bland–Altman analysis, analysis of variance, Kruskal–Wallis test, correlation analysis, and receiver operating characteristics analysis with the area under the curve (AUC). P‐value <0.05 was considered significant.ResultsMOLLI provided significantly better image quality compared to VFA. cT1 and mT1 values significantly differed between VFA and MOLLI (cT1‐VFA: 1771.4 ± 139.4 msec vs. cT1‐MOLLI: 1729.9 ± 132.1 msec; mT1‐VFA: 2076.0 [interquartile range (IQR): 2045.9–2129.9] msec vs. mT1‐MOLLI: 2039.2 [IQR: 1997.8–2071.6] msec). ΔT1 and ratio T1 values were not different between VFA and MOLLI (ΔT1: 300.8 ± 71.4 vs. 306.0 ± 78.4, respectively, P = 0.33 and ratio T1: 0.85 ± 0.038 vs. 0.85 ± 0.041, respectively, P = 0.064). No difference was observed between T1 variables and T1 mapping methods in diagnosing IF.Data ConclusionΔT1 and ratio T1 were not different between VFA and MOLLI. Both VFA and MOLLI are effective for noninvasive assessment of renal IF.Level of Evidence2Technical EfficacyStage 2