ArticleCell reports. Medicine2026
Single-cell spatial transcriptomics reveals tumor microenvironment heterogeneity in primary and lymph node-metastatic small cell lung cancer.
Article in Cell reports. Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Unveiling the role of spatial transcriptomics in the analysis of the tumor immune microenvironment (Review).International journal of molecular medicine · 2026Review
- BraMARS: An Interpretable Histopathology-Driven Deep Learning Model for Brain Metastasis Risk Stratification in Surgically Resected Limited-Stage SCLC.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Harnessing Cancer Stem Cells and 3D Organoids in Unravelling Spatial and Cellular Heterogeneity in Cancer.International journal of molecular sciences · 2026Review
- Amino acid metabolic regulatory network in tumor immune escape: mechanistic exploration and intervention directions.Frontiers in immunology · 2026Review
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Authors and funding
11 authors.
Funding
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Abstract
Lymph node metastasis (LNM) is a critical prognostic and therapeutic determinant in small cell lung cancer (SCLC), yet its spatial cellular ecosystem remains poorly understood. Here, we perform single-cell spatial transcriptomics using the CosMx Spatial Molecular Imager on 105 primary and metastatic lymph node specimens from 75 SCLC patients, generating a comprehensive atlas of over 600,000 cells. We identify three LNM-enriched malignant subclusters with distinct metabolic and angiogenic programs that spatially correlate with immune exclusion features. Spatial analysis reveals vascular-immune crosstalk, wherein endothelial cells orchestrate immune activation through avoidance of malignant cells while forming functional perivascular niches with cytotoxic T cells during LNM. Cellular neighborhood analysis delineates distinct multicellular niches and identifies a pan-immune hotspot (PIHs-1) whose abundance is an independent predictor of survival. This study provides a high-resolution spatial map of the SCLC tumor microenvironment during LNM and establishes spatially defined architectures as both mechanistic insights and translatable biomarkers.
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