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Samantha A. O’Connor

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Open access Jul 2026

Multi-omics characterization of IDH-mutant astrocytoma-derived cell lines reveals NOTCH-regulated plastic quiescent astrocyte-like state and insights into progression.

Diffuse IDH-mutant astrocytomas are brain tumors typically diagnosed as low-grade but capable of progressing to higher grades. They exhibit three cellular states resembling astrocytes, oligodendrocytes, and neural progenitor (NPC) cells. Understanding their biology has been limited by the scarcity of relevant in vitro models. Here, we established and extensively characterized four astrocytoma cell lines (LGG275, LGG336, LGG85, LGG349) derived from IDH-mutant astrocytomas of different grades and analyzed them using multi-omics approaches. These lines display growth rates in vitro and in vivo consistent with tumor grade and recapitulate some key molecular alterations observed in patient tumors, including IDH1, ATRX, and TP53 mutations, ALT (alternative lengthening of telomeres) activation and, in more aggressive lines, MET and PDGFRA alterations. Single-cell RNA sequencing revealed three major transcriptional states (astrocyte-like, oligodendrocyte-like, and NPC-like), consistent with those described in patient tumors. A hallmark of higher-grade-derived lines (LGG85, LGG349) is the persistence of NPC-like populations without growth factors possibly reflecting tumor progression. The LGG275 line most accurately mirrors slow-growing astrocytomas. Using CD44 and GLAST, we isolated astrocyte-like (CD44⁺/GLAST⁺) cells from LGG275 that preferentially adopt a quiescent state yet retain remarkable plasticity, generating oligodendrocyte-like cells (CD44⁻/GLAST⁻). Transcriptomic and proteomic analyses revealed that astrocyte-like and oligodendrocyte-like cells populations resemble, respectively, quiescent and activated neural stem (NSC) cells from the adult subventricular zone (SVZ). Finally, we provide evidence that NOTCH signaling contributes to the regulation of cell state balance, promoting transitions toward an astrocyte-like transcriptional program while DLL3, an anti-Notch protein, expressed by oligodendrocyte-like cells, modulates both proliferation and phenotype. These cell lines represent valuable resources for dissecting lineage dynamics, heterogeneity, and progression mechanisms in IDH-mutant astrocytomas.

L. Garcia, C. Granotier-Beckers, D. Pineau et al. · 0 citations
Open access Jul 2026

Resolving Immune Lineage and Cell-State Heterogeneity in Human PBMCs via Mass Spectrometry-Based Single-Cell Proteomics

Single-cell proteomics (SCP) currently lacks validated benchmarking standards, and cell annotation often relies on transcriptomic proxies. Unsupervised clustering offers a proxy-free alternative, but its success depends on biological signal outweighing technical variation. In homogeneous samples this is achievable, but in heterogeneous populations, where closely related cell types differ only subtly, technical variation can dominate the clustering and obscure the biology needed for annotation. To address this, we developed an integrated experimental and computational pipeline for protein-level cell annotation and applied it to human PBMCs as an immune-cell test case. We isolated T cells, B cells, monocytes, and NK cells by negative-selection sorting to build a high-fidelity reference. In parallel, unsorted PBMCs from the same donor were processed on a cellenONE and acquired using label-free DIA on an Orbitrap Astral Zoom. Using the labeled reference dataset, we systematically benchmarked normalization, imputation, and clustering methods to assess their effect on cell-type separation. Unsupervised analysis resolved functional subpopulations within each lineage, and a probabilistic SCP classifier trained on these annotations identified the corresponding cell types and states in the unsorted PBMC fraction, validating the pipeline on unenriched, heterogeneous samples. Together, this work delivers an analytically benchmarked SCP workflow that resolves immune lineage and cell-state heterogeneity in human PBMCs and provides a classifier-ready, protein-level reference for immune-cell assignment.

S. O'Connor, Romell B. Gletten, Ritin Sharma et al. · 0 citations

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