Journal: Nature Neuroscience

Article Title: Cerebrovascular vulnerability and fibrosis in human brain aneurysms

doi: 10.1038/s41593-026-02326-9

Figure Lengend Snippet: a , Heatmap with hierarchical clustering showing cell-to-cell differential interaction strength in brain aneurysms when compared to control cerebrovasculature. y -axis, source; x -axis, target. Red, increased interaction strength in aneurysms; blue, decreased interaction strength in aneurysms. EC, endothelial cell; SMC, smooth muscle cell; FbM, fibromyocyte; FB, fibroblast; aFB, activated fibroblast; mFB, myofibroblast; TC, T-cell; NK, natural killer cell; BC, B-cell; pDC, plasmacytoid dendritic cell; cDC, conventional dendritic cell; pvMϕ, perivascular macrophage; Mo, monocyte; aMϕ, APC5 + macrophage; MG, microglia; AC, astrocyte; Neu, neuron; OL, oligodendrocyte; OPC, oligodendrocyte precursor cell. b , Circle plot of differential interaction strength between activated perivascular fibroblasts (aFB) and myeloid cell populations in aneurysms. Red, increased interaction strength in aneurysms; blue, decreased interaction strength in aneurysms. Line thickness proportional to interaction strength. c , Cell-to-cell communication pathways across cell populations ranked on their differences of overall information flow within inferred networks in aneurysms (red) and control (gray). Red text, pathways statistically over-represented in brain aneurysms; gray text, pathways statistically over-represented in controls; black text, not significant. d , Chord plot showing outgoing cell communication pathways originating from myeloid cells to activated perivascular fibroblasts in aneurysms. Arrow thickness is proportional to interaction strength. e , Scatter-plot of pathways ranked by differential incoming ( y -axis) and outgoing ( x -axis) interaction strength in aFB in brain aneurysms relative to controls. Light blue, aneurysm-specific. Bold, top-nominated outgoing pathway emerging from aFB. f , Representative confocal microscopy analysis of immunostaining CD68 + (magenta) macrophages showing colocalization with CD74 receptor (yellow) and MIF ligand (cyan) in unruptured brain aneurysm (top) and control middle cerebral artery (bottom). DAPI (blue) labels cell nuclei. Colocalization, white. Scale bar, 50 µm. g , Representative confocal microscopy analysis of CD68 + macrophages (magenta) and MIF–CD74 proximity interaction (yellow) in unruptured brain aneurysm (top) and control middle cerebral artery (bottom). DAPI (blue) labels cell nuclei. Colocalization, white. Scale bar, 50 µm.

Article Snippet: Next, we added anti-CD74 antibody (MedChemExpress) at concentration of 5 μg ml −1 and incubated for 30 min followed by washing with medium.

Techniques: Control, Confocal Microscopy, Immunostaining

Journal: Nature Neuroscience

Article Title: Cerebrovascular vulnerability and fibrosis in human brain aneurysms

doi: 10.1038/s41593-026-02326-9

Figure Lengend Snippet: a , Violin plot of the established vascular destabilizing genes MMP9 and SPP1 across cell populations. EC, endothelial cell; SMC, smooth muscle cell; FbM, fibromyocyte; FB, fibroblast; aFB, activated fibroblast; mFB, myofibroblast; TC, T-cell; NK, natural killer cell; BC, B-cell; pDC, plasmacytoid dendritic cell; cDC, conventional dendritic cell; pvMϕ, perivascular macrophage; Mo, monocyte; aMϕ, APC5 + macrophage; MG, microglia; AC, astrocyte; Neu, neuron; OL, oligodendrocyte; OPC, oligodendrocyte precursor cell. b , Enriched biological processes from marker genes in ACP5 + macrophages ordered by statistical significance Benjamini-Hochberg adjusted P < 0.05; dashed line, Benjamini-Hochberg adjusted P cutoff of 0.05. c , Bar graph showing quantitative polymerase chain reaction (qPCR) analysis of MMP9 (left) and ACP5 (right) expression in primary human macrophages treated with interferon (IFN), macrophage inhibitory factor (MIF), and CD74 neutralizing antibody (anti-CD74). Mean ± s.e.m. MMP9: Media vs IFN ( P = 0.2479, ns); IFN vs IFN + MIF ( P = 0.0047, **); IFN + MIF vs IFN+anti-CD74 ( P = 0.0046, **); IFN + MIF vs IFN + MIF+anti-CD74 ( P = 0.017, *). ACP5: Media vs IFN ( P = 0.8114, ns); IFN vs IFN + MIF ( P = 0.0052, **); IFN + MIF vs IFN+anti-CD74 ( P = 0.009, **); IFN + MIF vs IFN + MIF+anti-CD74 ( P = 0.009, **). One-way ANOVA with Tukey’s multiple comparisons test (n = 3 samples). d . Boxplot of the distance (µm) from each aMϕ to its nearest neighbor of each listed cell type (n = 770 aMϕ). Dashed line marks 100 µm. Center lines indicate medians; box limits indicate the 25th and 75th percentiles; whiskers extend to the most extreme data points no more than 1.5 × IQR from the box; points beyond the whiskers are shown as outliers.

Article Snippet: Next, we added anti-CD74 antibody (MedChemExpress) at concentration of 5 μg ml −1 and incubated for 30 min followed by washing with medium.

Techniques: Marker, Real-time Polymerase Chain Reaction, Expressing

Journal: Therapeutic Advances in Medical Oncology

Article Title: S100A4 characterize antigen-presenting cancer-associated fibroblasts and predicts surgical outcomes in relapsed ovarian cancer

doi: 10.1177/17588359261436959

Figure Lengend Snippet: Immune spatial interactions and prognostic significance of CD74 + S100A4 + antigen-presenting CAFs in ROC. (a, b) Spatial proximity analysis between CAF subpopulations and CD4 + T cells using mIHC and computational phenotyping. (a) Representative mIHC images showing spatial relationships between αSMA + , S100A4 + , CD74 + S100A4 + CAFs, and CD4 + T cells. Lines indicate nearest neighbor distances between cells. Scale bar, 50 µm. (b) Boxplot quantification of mean number of CD4 + T cells within 20 µm radius of each CAF subtype. CD74 + S100A4 + CAFs displayed significantly closer proximity to CD4 + T cells. ( p < 0.05) as shown in representative image (a). (c–e) Differences in CD74 + S100A4 + CAFs distribution and their spatial relationship with CD4 + T cells between patients achieving R0 versus Non-R0. (c) Representative images of mIHC staining illustrating differences in spatial cell arrangement. Scale bar, 200 µm. (d) Quantification of CD74 + S100A4 + CAFs densities (cells/mm²) and (e) mean count of CD4 + T cells within 20 µm of CD74 + S100A4 + CAFs between R0 and Non-R0 groups. (f, g) Prognostic significance of S100A4 + apCAFs based on multi-dataset transcriptomic analysis. (f) Forest plot showing HR of S100A4 + apCAFs-associated gene signature across 11 ovarian cancer datasets. Each horizontal black square represents the HR estimate from an individual dataset, and the horizontal line indicates the 95% CI. The overall HR for S100A4 + apCAFs is shown at the bottom, with the dashed vertical line indicating the reference value HR = 1. (g) In the TCGA ovarian cancer cohort, patients were stratified into a high-expression group (top 30%, n = 68, shown in blue) and a low-expression group (bottom 30%, n = 68, shown in red) based on the expression levels of the top 100 S100A4 + apCAFs signature genes. The Kaplan–Meier survival curves compare overall survival between these groups. The x -axis represents time since diagnosis (in months), and the y -axis indicates overall survival probability. CAF, cancer-associated fibroblasts; CI, confidence interval; HR, hazard ratio; mIHC, multiplex immunohistochemistry; ROC, relapsed ovarian cancer; S100A4, S100 calcium-binding protein A4; TCGA, The Cancer Genome Atlas; αSMA, α-smooth muscle actin.

Article Snippet: Sections underwent antigen retrieval in citrate or EDTA buffer, followed by endogenous peroxidase blocking with 3% H 2 O 2 , serum blocking, and overnight incubation at 4°C with primary antibodies: αSMA (#19245, Cell Signaling Technology, Danvers, MA, USA), FAP (#ab207178, Abcam, Cambridge, UK), S100A4 (#13018, Cell Signaling Technology, Danvers, MA, USA), PDPN (#26981, Cell Signaling Technology, Danvers, MA, USA), PAX8 (#1F8-3A8, Thermo Fisher Scientific, Waltham, MA, USA), and CD74 (#77274, Cell Signaling Technology, Danvers, MA, USA).

Techniques: Staining, Expressing, Biomarker Discovery, Multiplex Assay, Immunohistochemistry, Binding Assay