ArticleScience advances2022
Reconstructing codependent cellular cross-talk in lung adenocarcinoma using REMI.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
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.
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- MetaCCI: meta cell-cell interaction inference and its application to CCIs characteristics of MDS.Bioinformatics (Oxford, England) · 2026Article
- DD-CC-II: Data Driven Cell-Cell Interaction Inference and Its Application to COVID-19.International journal of molecular sciences · 2025Article
- Advances and challenges in cell-cell communication inference: a comprehensive review of tools, resources, and future directions.Briefings in bioinformatics · 2025Review
- Cellular interactions within the immune microenvironment underpins resistance to cell cycle inhibition in breast cancers.Nature communications · 2025Article
- A quantitative spatial cell-cell colocalizations framework enabling comparisons between in vitro assembloids and pathological specimens.Nature communications · 2025Article
- Multicompartment duct platform to study epithelial-endothelial crosstalk associated with lung adenocarcinoma.APL bioengineering · 2024Article
- The diversification of methods for studying cell-cell interactions and communication.Nature reviews. Genetics · 2024Review
- Unraveling the tumor immune microenvironment of lung adenocarcinoma using single-cell RNA sequencing.Therapeutic advances in medical oncology · 2024Review
- The promising application of cell-cell interaction analysis in cancer from single-cell and spatial transcriptomics.Seminars in cancer biology · 2023Review
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
Cellular cross-talk in tissue microenvironments is fundamental to normal and pathological biological processes. Global assessment of cell-cell interactions (CCIs) is not yet technically feasible, but computational efforts to reconstruct these interactions have been proposed. Current computational approaches that identify CCI often make the simplifying assumption that pairwise interactions are independent of one another, which can lead to reduced accuracy. We present REMI (REgularized Microenvironment Interactome), a graph-based algorithm that predicts ligand-receptor (LR) interactions by accounting for LR dependencies on high-dimensional, small-sample size datasets. We apply REMI to reconstruct the human lung adenocarcinoma (LUAD) interactome from a bulk flow-sorted RNA sequencing dataset, then leverage single-cell transcriptomics data to increase the cell type resolution and identify LR prognostic signatures among tumor-stroma-immune subpopulations. We experimentally confirmed colocalization of CTGF:LRP6 among malignant cell subtypes as an interaction predicted to be associated with LUAD progression. Our work presents a computational approach to reconstruct interactomes and identify clinically relevant CCIs.
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.