Given the graft-versus-leukemia effect observed with allogeneic hematopoietic stem cell transplantation in refractory or relapsed acute myeloid leukemia (AML), immunotherapies have been explored in nontransplant settings. We applied a multiomic approach to examine bone marrow interactions in patients with AML treated with pembrolizumab and decitabine. Using extensively trained nuclear and membrane segmentation models, we achieved precise transcript assignment and deep learning–based image analysis. To address read-depth limitations, we integrated single-cell RNA sequencing with single-cell spatial transcriptomics from the same sample. Quantifying cell-cell distances at the edge level enabled more accurate tumor microenvironment analysis, revealing global and local immune cell enrichment near leukemia cells postpembrolizumab treatment, potentially linked to clinical response. Furthermore, ligand-receptor analysis indicated potential alterations in specific signaling pathways between leukemia and immune cells following immunotherapy treatment. These findings provide insights into immune interactions in AML and may inform therapeutic strategies.

Uveal melanoma (UVM) is an aggressive cancer with a poor prognosis, particularly in metastatic cases. This study aimed to develop and validate a novel extracellular matrix (ECM) gene expression signature to predict prognosis and stratify patients by risk. ECM-related genes were identified and used to construct a prognostic model through Lasso–Cox regression analysis, leveraging RNA sequencing data from 80 UVM patients in The Cancer Genome Atlas (TCGA). The model was validated using an independent cohort of 63 UVM patients. Survival analyses, immune infiltration profiling, and functional enrichment analyses were conducted to evaluate the biological significance and clinical utility of the signature. The ECM signature stratified patients into high- and low-risk groups with significant differences in survival outcomes. High-risk patients showed elevated expression of MMP1 and MMP12, which are associated with ECM remodeling and immune modulation, alongside increased infiltration of immunosuppressive cells, such as M2 macrophages. Validation confirmed the prognostic value of the signature across cohorts. Functional analyses highlighted the involvement of ECM-related pathways, epithelial–mesenchymal transition, and immune system interactions in tumor progression. This ECM gene expression signature is a robust prognostic tool for UVM, offering insights into tumor biology and immune microenvironment interactions. It holds promise for improving patient stratification and guiding personalized therapeutic strategies. Further research is warranted to explore the functional roles of these genes in UVM progression.