Recent updates to monocyte count thresholds recognize oligomonocytic chronic myelomonocytic leukemia (OM-CMML) as an early form of CMML. However, the clinical validity of these changes remains uncertain without incorporating biological and genomic factors. In this study, we analyzed a cohort of 911 patients (249 with OM-CMML, 359 with overt CMML, and 303 with myelodysplastic syndromes) using unsupervised clustering to evaluate the role of genomic determinants in refining CMML diagnosis. Our findings show that CMML molecular signatures (biallelic TET2 mutations or SRSF2-TET2 comutations) are linked to a distinct transcriptome, monocytic bias, classical monocytosis, and a higher risk of progression to overt CMML in OM-CMML cases. We developed a weighted genomic model and diagnostic workflow showing that combining genomic signatures with bone marrow monocyte frequencies in OM-CMML more accurately predicts progression to overt CMML. These findings support integrating genomic determinants and our clinic-ready diagnostic workflow into the CMML diagnostic framework to improve accuracy. SIGNIFICANCE:Through comprehensive clinical and genomic profiling of a large patient cohort, alongside immunophenotypic and transcriptional cellular analyses, this study provides evidence that incorporating genomic determinants into the diagnostic criteria for OM-CMML improves diagnostic accuracy and refines the identification of early-stage CMML, thereby preventing misclassification.

Penalized time-to-event model for CMML progression (cumulative incidence of CMML).

Association of biTET2/SRSF2 and monocytic differentiation parameters in a validation cohort.

Numbers at risk by survival time point by genomic group (Figure 4N).

IntroductionPhotothermal therapy (PTT) faces limitations due to tumor microenvironment (TME) heterogeneity and single-modality constraints, including hypoxia, redox imbalance, and uneven heat distribution, which compromise therapeutic durability. Integrating nanozyme catalysis with PTT presents a promising strategy to amplify oxidative stress, yet achieving a balance among catalytic efficiency, photothermal performance, biocompatibility, and stability remains challenging.MethodsHerein, we developed an epigallocatechin gallate (EGCG)-modified palladium-based nanozyme (EGCG-PdZyme) for the precision treatment of esophageal cancer. This multifunctional platform was engineered to integrate catalase-like oxygen generation, peroxidase-like reactive oxygen species (ROS) production, and near-infrared photothermal conversion capabilities.ResultsWhile EGCG modification slightly attenuated the intrinsic catalytic activity and peak photothermal temperature, it established an optimized thermo-catalytic synergy. Sustained mild hyperthermia amplified oxidative stress, effectively offsetting the reduced catalytic output and minimizing thermal damage to peritumoral tissues. Mechanistically, persistent photothermal heating boosted enzymatic ROS generation within the TME, initiating a self-amplifying therapeutic cascade. Furthermore, EGCG functionalization significantly enhanced colloidal stability and biosafety, enabling effective tumor ablation with negligible systemic toxicity.DiscussionThis study demonstrates a paradigm shift from maximizing isolated parameters toward achieving a dynamic equilibrium between catalytic functionality and biological compatibility. By integrating TME modulation with controlled photothermal amplification, the EGCG-PdZyme platform offers a viable strategy for clinically translatable precision oncotherapy.

Spatial transcriptomics (ST) provides unprecedented insights into gene expression patterns while retaining spatial context, making it a valuable tool for understanding complex tissue architectures, such as those found in cancers. Seurat, by far the most popular tool for analyzing ST data, uses the Wilcoxon rank-sum test by default for differential expression analysis. However, as a nonparametric method that disregards spatial correlations, the Wilcoxon test can lead to inflated false positive rates and misleading findings. This limitation highlights the need for a more robust statistical approach that effectively incorporates spatial correlations. To this end, we propose a Generalized Estimating Equations (GEE) framework as a robust solution for differential gene expression analysis in ST. We conducted a comprehensive comparison of the GEE-based tests with existing methods, including the Wilcoxon rank-sum test and z-test. By appropriately accounting for spatial correlations, extensive simulations showed that the GEE test with robust standard error, referred to as the Independent GEE, demonstrated superior Type I error control and comparable power relative to other methods. Applications to ST datasets from breast and prostate cancer showed poor calibration of the p-values and potential false positive findings from the Wilcoxon rank-sum test. Our comparative study based on simulations and real data applications suggests that the Independent GEE test is well-suited for ST data, offering more accurate identification of biologically relevant gene expression changes and complementing the Wilcoxon rank-sum test. We have implemented the proposed method in R package "SpatialGEE", available on GitHub.

Correlation between RAS pathway mutation variant allele frequencies and monocytic parameters.

Cytogenetic abnormalities and somatic mutations among all patients included in the validation cohort.

Landscape of SF3B1 mutations in the SF3B1 cluster by diagnosis.

Characteristics of patients in whom bulk RNA-sequencing was performed in bone marrow CD34+ cells.

Numbers at risk by survival time point by hierarchical cluster (Figure 4L).

t-SNE plot of model-based unsupervised clustering.

The xenotransplantation of human cells into porcine hosts holds immense potential in the fields of regenerative medicine and organ transplantation. However, the low survival rate of human-derived cells within porcine remains a critical bottleneck constraining the application of xenotransplantation. Whether porcine cells exert negative effect on human cell growth is not studied. Here, we established an in vitro direct co-culture model of human and porcine mesenchymal stem cells (hMSCs and pMSCs) to investigate the competitive relationship between human and porcine-derived cells. The results demonstrated that the proliferation capability of hMSCs in the co-culture system was significantly suppressed compared to those cultured in isolation. Moreover, an increasing number of pMSCs exhibited enhanced inhibition of hMSC proliferation. Notably, results from transwell assays and treatment with porcine-conditioned medium indicated that the inhibition of hMSCs by pMSCs was not mediated through soluble cytokines. To elucidate the underlying molecular mechanisms, RNA sequencing analysis was performed and the result revealed that direct co-culture significantly downregulated the expression of proliferation-related genes in hMSCs, including CYP1B1, SLC7A11, TFAP2C, and PSAT1. Concurrently, the co-culture paradigm disrupted endoplasmic reticulum function and multiple amino acid transport processes within hMSCs, while activating the NF-κB signaling pathway, thereby achieving negative regulation of hMSC proliferation. Collectively, our primary study characterized the competitive interactions between hMSCs and pMSCs and uncovered possible underlying mechanisms which provided new experimental foundations for improving human cell survival in porcine hosts to advance xenotransplantation application.

Osteoarthritis (OA) is a prevalent degenerative joint disease characterized by multifactorial pathological mechanisms, and remains a significant clinical challenge. Exosome therapy represents a future direction for delaying OA progression, yet its efficacy is often compromised by inflammatory microenvironment within the joints. To overcome these limitations, we present a novel combinatorial therapeutic platform that alleviates OA through a multi-targeted strategy, including the scavenging of reactive oxygen species (ROS), suppression of macrophage-driven inflammation, and inhibition of chondrocyte ferroptosis. This platform combines dental pulp stem cells-derived exosomes (Exo) with hollow mesoporous cerium oxide nanozymes, which were first loaded with curcumin and subsequently coated with hyaluronic acid, termed HA@Cur@CeO2. In vitro, this combination reduced intracellular ROS and promoted macrophage polarization toward the anti-inflammatory M2 phenotype, thereby remodeling the OA microenvironment and halting the inflammatory cascade. Additionally, Exo and HA@Cur@CeO2 nanozymes complementarily modulated ALOX12-and GPX4-dependent ferroptosis pathways in chondrocytes, with the combined approach yielding superior anti-ferroptotic effects. For in vivo assessment, Exo and HA@Cur@CeO2 were encapsulated within a chitosan/β-glycerophosphate hydrogel to achieve sustained release (Exo/HA@Cur@CeO2/Gel). This formulation significantly reduced inflammation, chondrocyte ferroptosis, cartilage degeneration, and subchondral bone remodeling, ultimately slowing OA progression. With excellent biocompatibility, this innovative combinatorial therapeutic strategy represents a comprehensive approach for enhancing Exo efficacy in OA treatment with promising translational potential.

Consort diagram for patient selection for CMML progression analysis.

Survival outcomes by hierarchical cluster within diagnostic groups.

Clinicopathologic features of distinct hierarchical clusters among OM-CMML.

Survival outcomes of SF3B1 cluster compared to other NOS clusters.

Unsupervised clustering based on BM CD34+ cell transcriptional profiling.

Cytogenetic abnormalities and somatic mutations among all patients included in the test cohort.