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Genomic analysis of 80 MM patients revealed that DRs (PFS≥1 year) had significantly fewer copy number alterations (CNAs) compared to patients with progressive disease (PFS≤6 months). Common MM driver mutations were identified, including SF3B1, KIT, NF1, and NRAS. Notably, SF3B1 mutations were predominantly found in anorectal primaries (10/17) and harbored fewer CNAs—a feature also enriched in DRs—suggesting SF3B1 mutations may promote genomic stability and enhance ICB responsiveness.
RNAseq analysis (n=67) identified a tumor cluster enriched for epithelial-mesenchymal transition and hypoxia stress pathways—features associated with poor ICB outcomes—suggesting increased invasiveness and potential resistance, and present in 37% of MM tumors.
Spatial analysis of primary and metastatic lesions revealed increased infiltration of CD8+ T cells and CD11C+ myeloid cells at metastatic sites. By delineating the tumor-stromal interface, we observed distinct localization of CD68+ macrophages, with enrichment at the tumor border in metastatic tumors, indicative of immune exclusion. In sinonasal tumors, non-metastatic patients had fewer tumor-associated macrophages (TAMs; CD163+/CD206+) in both the tumor center and border compared to those who later developed distant metastases, suggesting TAM infiltration may predict metastatic potential. We also identified colocalization of TAMs and regulatory T cells (Tregs; CD4+/FOXP3+) with a tumor subpopulation, indicating a structured immunosuppressive niche. Notably, vulvar/vaginal MM tumors—associated with the poorest outcomes—exhibited marked enrichment of this suppressive microenvironment, underscoring its role in disease progression.
Multimodal analysis of a longitudinally sampled MM patient treated with ICB revealed distinct resistance clones associated with different microenvironments. Two lymph node metastases collected post-ICB showed clonal differences; one (harboring a SOX17 mutation) exhibited lower CD8+ T cell infiltration, suggesting divergent resistance mechanisms.
Related technologies: Automated microscopy and image analysisAutomated microscopy and Spatial Proteomics
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