ArticleScientific reports2017
Extracting Intercellular Signaling Network of Cancer Tissues using Ligand-Receptor Expression Patterns from Whole-tumor and Single-cell Transcriptomes.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 55 papers, 1 of them a synthesis that pooled it.
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
55 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application.Molecular neurodegeneration · 2022Pooled it
- Metabolic Cross Talk in the Tumor Microenvironment.Cancer treatment and research · 2026Review
- DeepPNCC: reconstructing pseudo-spatial cell-cell interaction landscapes from single-cell data to decipher breast cancer pathogenesis.Journal of translational medicine · 2025Article
- Review
- Adipocyte‑derived extracellular vesicles sustain mitochondrial metabolism in breast cancer cells: New insights into the cross‑talk between cancer cells and the tumor microenvironment.International journal of oncology · 2025Article
- Uncovering Cellular Interactome Drivers of Immune Checkpoint Inhibitor Response in Advanced Melanoma Patients.Cellular and molecular bioengineering · 2025Article
- SEnSCA: Identifying possible ligand-receptor interactions and its application in cell-cell communication inference.Journal of cellular and molecular medicine · 2024Article
- CellCommuNet: an atlas of cell-cell communication networks from single-cell RNA sequencing of human and mouse tissues in normal and disease states.Nucleic acids research · 2024Article
- Detection of reproducible liver cancer specific ligand-receptor signaling in blood.Frontiers in bioinformatics · 2024Article
- Sctensor detects many-to-many cell-cell interactions from single cell RNA-sequencing data.BMC bioinformatics · 2023Article
- Reconstructing the cell-cell interaction network among mouse immune cells.Biotechnology and bioengineering · 2023Article
- PERK-Mediated Cholesterol Excretion from IDH Mutant Glioma Determines Anti-Tumoral Polarization of Microglia.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Mechanisms driving the immunoregulatory function of cancer cells.Nature reviews. Cancer · 2023Review
- DiSiR: fast and robust method to identify ligand-receptor interactions at subunit level from single-cell RNA-sequencing data.NAR genomics and bioinformatics · 2023Article
- Melanoma molecular subtyping and scoring model construction based on ligand-receptor pairs.Frontiers in genetics · 2023Article
- RobustCCC: a robustness evaluation tool for cell-cell communication methods.Frontiers in genetics · 2023Article
- Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications.Military Medical Research · 2022Review
- Direct cell-to-cell transfer in stressed tumor microenvironment aggravates tumorigenic or metastatic potential in pancreatic cancer.NPJ genomic medicine · 2022Article
- Evaluation of cell-cell interaction methods by integrating single-cell RNA sequencing data with spatial information.Genome biology · 2022Article
- Uncovering the dynamic effects of DEX treatment on lung cancer by integrating bioinformatic inference and multiscale modeling of scRNA-seq and proteomics data.Computers in biology and medicine · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
Abstract
Many behaviors of cancer, such as progression, metastasis and drug resistance etc., cannot be fully understood by genetic mutations or intracellular signaling alone. Instead, they are emergent properties of the cell community which forms a tumor. Studies of tumor heterogeneity reveal that many cancer behaviors critically depend on intercellular communication between cancer cells themselves and between cancer-stromal cells by secreted signaling molecules (ligands) and their cognate receptors. We analyzed public cancer transcriptome database for changes in cell-cell interactions as the characteristic of malignancy. We curated a list (>2,500 ligand-receptor pairs) and identified their joint enrichment in tumors from TCGA pan-cancer data. From single-cell RNA-Seq data for a case of melanoma and the specificity of the ligand-receptor interactions and their gene expression measured in individual cells, we constructed a map of a cell-cell communication network that indicates what signal is exchanged between which cell types in the tumor. Such networks establish a new formal phenotype of cancer which captures the cell-cell communication structure - it may open new opportunities for identifying molecular signatures of coordinated behaviors of cancer cells as a population - in turn may become a determinant of cancer progression potential and prognosis.
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.