ArticleScience advances2025
Single-cell multimodal analysis reveals tumor microenvironment predictive of treatment response in non-small cell lung cancer.
Article in Science advances, 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.
- Advancing the understanding of the immune escape in lung cancer immunotherapy: Global trends, collaborations, and future directions.Human vaccines & immunotherapeutics · 2026Article
- Mitochondrial mechanisms underlying spatial immune phenotypes in non‑small cell lung cancer: Implications for ICI response and cold‑to‑hot tumor conversion (Review).Oncology reports · 2026Review
- The spatial architecture of tumor immunity: Emerging predictive biomarkers across cancer.Immunologic research · 2026Review
- Single-cell multiomics identifies an ALDH9A1-carnitine signaling axis driving resistance of NSCLC to immunotherapy.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Landscape of Cell States and Multicellular Ecotypes in Non-Small Cell Lung Cancer.International journal of molecular sciences · 2026Article
- A Circulating GPNMB-Based Multimodal Model Integrates Tumor-Immune Crosstalk to Predict Immunotherapy Response in Esophageal Cancer.Cancer discovery · 2026Article
- An interpretable multi-task whole-slide histopathology AI model for non-small cell lung cancer: Cross-cohort generalisation, spatial attention-transcriptomic integration, and molecular-immune profiling.Clinical and translational medicine · 2026Article
- Context-dependent roles of lncRNA JPX in human cancers.Discover oncology · 2026Review
- Integration of spatial single-cell proteomics and spatial metabolomics reveals tumor microenvironment predictive of immunotherapy response in mucosal melanoma.bioRxiv : the preprint server for biology · 2026Article
- Single-Cell and Spatial Omics: Methods and Applications.MedComm · 2026Review
- Role of SPAG6 in regulating physiological functions and tumorigenesis (Review).International journal of oncology · 2026Review
- The MAD2L1-FOXM1 axis negatively regulates CD4⁺ T cell and macrophages infiltration in lung adenocarcinoma.Discover oncology · 2026Article
- Emerging Predictive Biomarkers of Immunotherapy Sensitivity in Patients with Non-Small Cell Lung Cancer.ImmunoTargets and therapy · 2026Review
- PLAID: ultrafast single-sample gene set enrichment scoring.Bioinformatics (Oxford, England) · 2025Article
- Single cell and machine learning identify type II pneumocyte-derived biomarkers HN1/OCIAD2/SFTA2 for non-small cell lung cancer prognosis and immune regulation.European journal of medical research · 2025Article
- PSMD11 facilitates immune escape by recruiting USP14 to modulate the deubiquitinating degradation of PD-L1 in non-small cell lung cancer.Journal of thoracic disease · 2025Article
- Emerging Techniques of Translational Research in Immuno-Oncology: A Focus on Non-Small Cell Lung Cancer.Cancers · 2025Review
- AI-based hardware and software tools in microscopy to boost research in immunology and virology.Frontiers in immunology · 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
Non-small cell lung cancer (NSCLC) constitutes over 80% of lung cancer cases and remains a leading cause of cancer-related mortality worldwide. Despite the advent of immune checkpoint inhibitors, their efficacy is limited to 27 to 45% of patients. Identifying likely treatment responders is essential for optimizing healthcare and improving quality of life. We generated multiplex immunofluorescence (mIF) images, histopathology, and RNA sequencing data from human NSCLC tissues. Through the analysis of mIF images, we characterized the spatial organization of 1.5 million cells based on the expression levels for 33 biomarkers. To enable large-scale characterization of tumor microenvironments, we developed NucSegAI, a deep learning model for automated nuclear segmentation and cellular classification in histology images. With this model, we analyzed the morphological, textural, and topological phenotypes of 45.6 million cells across 119 whole-slide images. Through unsupervised phenotype discovery, we identified specific lymphocyte phenotypes predictive of immunotherapy response. Our findings can improve patient stratification and guide selection of effective therapeutic regimens.
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.