ReviewCancers2025
Spatial Transcriptomics in Lung Cancer and Pulmonary Diseases: A Comprehensive Review.
Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Distinct Spatial Immune Architectures in Tumor and Tumor-Adjacent Tissues of Early-Stage Non-Small Cell Lung Cancer.bioRxiv : the preprint server for biology · 2026Article
- Review
- Spatiotemporal Profiling Defines the Epithelial and Mesenchymal Transition Window in Embryonic Lung Morphogenesis.Journal of developmental biology · 2026Article
- Macrophages in lung cancer: principal factors, regulatory mechanisms, and therapeutic opportunities: a narrative review.Translational lung cancer research · 2026Review
- Exploration of the roles of SSR2 in hepatocellular carcinogenesis based on single-cell transcriptomics and spatial transcriptomics.Discover oncology · 2026Article
- The Neutrophil-NET Axis in Immune Checkpoint Inhibitor Resistance in Non-Small Cell Lung Cancer: Roles, Biomarkers and Therapeutic Opportunities.Biomolecules · 2026Review
- S3RL: Enhancing Spatial Single-Cell Transcriptomics With Separable Representation Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Artificial Intelligence with Robotics for Metabolic Rehabilitation and Enhanced Patient Recovery in Critical Care.Research (Washington, D.C.) · 2026Review
- Dynamic orchestration of structural and immune cells in acuteFrontiers in immunology · 2026Article
- Systematic evaluation of spatial transcriptomic annotation methods reveals conserved tumor microenvironment programs in NSCLC.Frontiers in bioinformatics · 2026Article
- Natural therapeutics and traditional formulas targeting macrophage polarization in the fibrotic niche of idiopathic pulmonary fibrosis.Frontiers in immunology · 2026Review
- Decoding macrophage heterogeneity in the pulmonary fibrosis lung cancer transition.Frontiers in immunology · 2026Review
- Decoding early lung adenocarcinoma progression by single-cell and spatial transcriptomics reveals a CMA-related prognostic signature.Frontiers in immunology · 2026Article
- Lung cancer immunotherapy in 2025: where we stand and what comes next?Frontiers in immunology · 2025Review
- Beyond monoclonal antibodies: constraints and the case for alternative PD-1/PD-L1-targeting formats.Frontiers in immunology · 2025Review
- Single-cell transcriptomics in metastatic breast cancer: mapping tumor evolution and therapeutic resistance.Frontiers in genetics · 2025Review
- Single-Cell Sequencing Redefines Immune Heterogeneity and Communication Networks in ARDS: Toward Precision Therapeutics.International journal of genomics · 2025Review
- Immunotherapy Resistance and Therapeutic Strategies in PD-L1 High Expression Non-Small Cell Lung Cancer.OncoTargets and therapy · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Recent advancements in spatial transcriptomics (ST) have revolutionized our understanding of the lung's cellular organization and pathological alterations. By preserving the spatial distribution of gene expression, ST reveals localized immune niches, stromal-epithelial interactions, and disease-associated transcriptional "hotspots" that cannot be captured by conventional sequencing methods alone. In lung cancer, ST-based investigations have delineated distinct tumor microenvironments between tumor cores and invasive fronts, revealing prognostically significant gene signatures and identifying subpopulations with differential responses to immunotherapy and chemotherapy. Similarly, in chronic obstructive pulmonary disease, asthma, and idiopathic pulmonary fibrosis, ST has mapped the ecosystem, including immune cells, inflammatory mediators, and fibroblast subtypes, of discrete regions within diseased lung tissue, offering mechanistic insights into disease progression and tissue remodeling. In addition, a more recent ST study provides spatial information for where drugs act within tissues. This review highlights the emerging role of spatial transcriptomics in respiratory research, demonstrating its potential to refine disease classification, elucidate mechanisms of therapeutic resistance, and inform spatially guided personalized interventions in respiratory diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.