ArticleCancers2026
Spatial Architecture of B7-H3-Expressing Cell Subpopulations Predicts Patient Prognosis in Lung Cancer Brain Metastases: A Pilot Study.
Article in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- [Tumor Cell and Brain Microenvironment Interactions in Non-small Cell Lung Cancer Brain Metastasis: Mechanisms and Emerging Insights].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2026Review
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Authors and funding
6 authors.
Funding
Abstract
backgroundThe clinical outcomes of lung cancer brain metastases (LCBMs) are highly variable. Traditional pathology relies on bulk cell densities. These static measures fail to capture the spatial architecture of the tumor immune microenvironment (TIME). B7-H3 (CD276) represents a key immune checkpoint in LCBMs. We investigated whether the spatial orchestration of B7-H3-expressing cell populations is associated with patient prognosis.
methodsMultiplex immunohistochemistry (mIHC) for B7-H3 and Iba1 (a macrophage marker) was performed on surgically resected tissues from 22 patients, with single-cell segmentation and classification in QuPath. We then applied spatial point pattern and spatial autocorrelation analyses to evaluate the relative positioning of single cells, computing spatial interaction metrics, including cross-Moran's I and the cross-K function, within a 35 μm radius. These metrics were correlated with postoperative overall survival (OS), and prognostic thresholds were determined via time-dependent ROC curve analysis.
resultsStandard cell densities generally did not correlate with OS, although B7-H3
conclusionsDecoding the spatial architecture of B7-H3-expressing cell subpopulations provides superior prognostic stratification compared with standard density-based metrics. These localized spatial niches represent potential biomarkers and therapeutic targets for personalized LCBM management.
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