ArticleNature communications2025
A quantitative spatial cell-cell colocalizations framework enabling comparisons between in vitro assembloids and pathological specimens.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Genetic and Pharmacologic Targeting of Eya3 in Macrophages Drives Anti-Tumor Immunity in Triple-Negative Breast Cancer.bioRxiv : the preprint server for biology · 2026Article
- Spotlight on challenges and novel methods in highly multiplexed tissue imaging-based spatial proteomics.Journal of translational medicine · 2026Review
- Parabiosis, Assembloids, Organoids (PAO).Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy.Cancer drug resistance (Alhambra, Calif.) · 2026Review
- Temporal reassignment and correspondence evaluation with quality control for time-course imaging of 3D cell culture.Cell reports methods · 2025Article
- Spatial omics in 3D culture model systems: decoding cellular positioning mechanisms and microenvironmental dynamics.Journal of translational medicine · 2025Review
- Cancer therapy resistance from a spatial-omics perspective.Clinical and translational medicine · 2025Review
- A quantitative spatial cell-cell colocalizations framework enabling comparisons between in vitro assembloids and pathological specimens.Nature communications · 2025Article
- A flexible systems analysis pipeline for elucidating spatial relationships in the tumor microenvironment linked with cellular phenotypes and patient-level features.Frontiers in immunology · 2025Article
- Generation of Human 3D Airway Assembloids for Advanced Modeling.International journal of biological sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Spatial omics is enabling unprecedented tissue characterization, but the ability to adequately compare spatial features across samples under different conditions is lacking. We propose a quantitative framework that catalogs significant, normalized, colocalizations between pairs of cell subpopulations, enabling comparisons among a variety of biological samples. We perform cell-pair colocalization analysis on multiplexed immunofluorescence images of assembloids constructed with lung adenocarcinoma (LUAD) organoids and cancer-associated fibroblasts derived from human tumors. Our data show that assembloids recapitulate human LUAD tumor-stroma spatial organization, justifying their use as a tool for investigating the spatial biology of human disease. Intriguingly, drug-perturbation studies identify drug-induced spatial rearrangements that also appear in treatment-naïve human tumor samples, suggesting potential directions for characterizing spatial (re)-organization related to drug resistance. Moreover, our work provides an opportunity to quantify spatial data across different samples, with the common goal of building catalogs of spatial features associated with disease processes and drug response.
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.