Biology subjects

Moss, N. S.

Publications and source records attributed to Moss, N. S..

2 recordsLinked to original sources

bioRxiv2026

Hierarchical classification of immune cell transcriptomes at population-scale

Accurate immune cell classification is essential for interpreting single-cell RNA sequencing (scRNA-seq) data. However, progress in automating cell type annotation is constrained by the lack of independent, high-resolution benchmarks, as routine data integration introduces statistical dependencies that inflate model generalizability. Here, we present the single-cell universal classification omnibus (Suco), a resource of independent, uniform expert annotations, and Compocyte, a modular hierarchical classifier. Together, they establish a framework that substantially outperforms existing classifiers while facilitating expert review of ambiguous annotations. Applying Compocyte across 50 studies, including three newly generated datasets, we classified 15.6 million leukocytes from 3,965 patients. Within this cohort, we identified a new tumor-associated resorptive macrophage phenotype, a non-canonical monocyte subtype in subclinical cytokine release syndrome, and the programmatic erosion of T cell memory stemness across metastatic sites. Suco and Compocyte thus provide a generalizable framework to uncover the principles governing human immunity at population scale. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/728980v2_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@13a6e4borg.highwire.dtl.DTLVardef@11f1626org.highwire.dtl.DTLVardef@1e72bd4org.highwire.dtl.DTLVardef@1ee799b_HPS_FORMAT_FIGEXP M_FIG C_FIG In briefThe single-cell universal classification omnibus and the modular hierarchical classifier Compocyte enable annotating single cell RNA sequencing data from 3,965 patients, revealing novel resorptive macrophage and vaccination-associated monocyte states, alongside the erosion of T cell memory stemness as a hallmark of solid tumor metastases. HighlightsO_LISuco, a benchmark enabling novel single cell artificial intelligence models C_LIO_LICompocyte, a hierarchical cell type classifier outperforming current architectures C_LIO_LIMacrophages adopt osteoclast-like gene expression states across cancer types C_LIO_LIStem-like programs erode in metastasis-infiltrating T memory cells across tumors C_LI

bioinformatics↗

bioRxiv2025

A pathogenic subpopulation of human glioma associated macrophages linked to glioma progression

Malignant gliomas follow two distinct natural histories: de novo high grade tumors such as glioblastoma, or lower grade tumors with a propensity to transform into high grade disease. Despite differences in tumor genotype, both entities converge on a common histologically aggressive phenotype, and the basis for this progression is unknown. Glioma associated macrophages (GAM) have been implicated in this process, however GAMs are ontologically and transcriptionally diverse, rendering isolation of pathogenic subpopulations challenging. Since macrophage contextual gene programs are orchestrated by transcription factors acting on cis-acting promoters and enhancers in gene regulatory networks (GRN), we hypothesized that functional populations of GAMs can be resolved through GRN inference. Here we show via parallel single cell RNA and ATAC sequencing that a subpopulation of human GAMs can be defined by a GRN centered around the Activator Protein-1 transcription factor FOSL2 preferentially enriched in high grade tumors. Using this GRN we nominate ANXA1 and HMOX1 as surrogate cell surface markers for activation, thus permitting prospective isolation and functional validation in human GAMs. These cells, termed malignancy associated GAMs (mGAMs) are pro-invasive, pro-angiogenic, pro-proliferative, possess intact antigen presentation but skew T-cells towards a CD4+FOXP3+ phenotype under hypoxia. Ontologically, mGAMs share somatic mitochondrial mutations with peripheral blood monocytes, and their presence correlates with high grade disease irrespective of underlying tumor mutation status. Furthermore, spatio-temporally mGAMs occupy distinct metabolic niches; mGAMs directly induce proliferation and mesenchymal transition of low grade glioma cells and accelerate tumor growth in vivo upon co-culture. Finally mGAMs are preferentially enriched in patients with newly transformed regions in human gliomas, supporting the view that mGAMs play a pivotal role in glioma progression and may represent a plausible therapeutic target in human high-grade glioma.

cancer biology↗