ReviewClinical and translational medicine2021
Understanding cell-cell communication and signaling in the colorectal cancer microenvironment.
Review in Clinical and translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 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
89 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Non-Coding RNAs Implicated in the Tumor Microenvironment of Colorectal Cancer: Roles, Mechanisms and Clinical Study.Frontiers in oncology · 2022Pooled it
- Decoding cell-cell communication in spatial transcriptomics: mechanistic insights, modeling constraints, and analytical caveats.Briefings in bioinformatics · 2026Review
- Chronic inflammation-responsive hydrogel restores myeloid-T cell crosstalk to reinvigorate antitumor immunity against metastatic colorectal cancer.Bioactive materials · 2026Article
- Review
- Phosphorylation beyond the plasma membrane: How secretory pathway kinases sculpt the cellular dialogue in cancer (Review).International journal of molecular medicine · 2026Review
- Single-cell identifies and validates human circulating Treg subtype/state TregSignal transduction and targeted therapy · 2026Article
- Development of a deep neural network model for simultaneous analysis of extracellular analyte gradients for a population of cells.Artificial intelligence in the life sciences · 2026Article
- Basal cell subsets, as biomarker to predict the therapeutic effect of neoadjuvant therapy for esophageal carcinoma.Journal of cancer research and clinical oncology · 2026Article
- Hsa_circ_0007158 promotes colorectal cancer progression via the ceRNA axis and its association with immune infiltration.Cancer cell international · 2026Article
- Cancer-associated fibroblasts drive metabolic heterogeneity in colorectal cancer cells: predictions from metabolic modeling.NPJ systems biology and applications · 2026Article
- The advancements in organoids: Potential and challenges in researching the esophagus and esophageal squamous cell carcinoma.Genes & diseases · 2026Review
- Mechanistic insights into daidzin from Glycine max against breast cancer via network pharmacology and multi-level molecular modeling.PloS one · 2026Article
- Integrated single-cell and spatial transcriptomics reveal immune landscape and NKT-Th1 signatures in colorectal cancer.Frontiers in immunology · 2026Article
- Single-cell transcriptomic analysis of cutaneous squamous cell carcinoma identifies an NR1H3-associated angiogenic macrophage state.Frontiers in immunology · 2026Article
- Characterization of stem cell landscape and identification of stemness-related gene ENY2 in colorectal cancer by intergrated transcriptomic analysis.Global medical genetics · 2025Article
- Advances in Hereditary Colorectal Cancer: How Precision Medicine Is Changing the Game.Cancers · 2025Review
- Integrating the secretome and interactome to identify novel biomarkers and therapeutic targets in colorectal cancer.Cell communication and signaling : CCS · 2025Article
- Artificial intelligence and systems biology analysis in stem cell research and therapeutics development.Stem cells translational medicine · 2025Review
- Focal Adhesion Kinase Intersects With the BRD4-MYC Axis and YAP1 to Drive Tumor Cell Growth, Phenotypic Plasticity, Stemness, and Metastatic Potential in Colorectal Cancer.Cancer medicine · 2025Article
- Finding spatially variable ligand-receptor interactions with functional support from downstream genes.Nature communications · 2025Article
29 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Carcinomas are complex heterocellular systems containing epithelial cancer cells, stromal fibroblasts, and multiple immune cell-types. Cell-cell communication between these tumor microenvironments (TME) and cells drives cancer progression and influences response to existing therapies. In order to provide better treatments for patients, we must understand how various cell-types collaborate within the TME to drive cancer and consider the multiple signals present between and within different cancer types. To investigate how tissues function, we need a model to measure both how signals are transferred between cells and how that information is processed within cells. The interplay of collaboration between different cell-types requires cell-cell communication. This article aims to review the current in vitro and in vivo mono-cellular and multi-cellular cultures models of colorectal cancer (CRC), and to explore how they can be used for single-cell multi-omics approaches for isolating multiple types of molecules from a single-cell required for cell-cell communication to distinguish cancer cells from normal cells. Integrating the existing single-cell signaling measurements and models, and through understanding the cell identity and how different cell types communicate, will help predict drug sensitivities in tumor cells and between- and within-patients responses.
Indexed as
Identifiers
What Socratic 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 Socratic graph.