ArticleTranslational cancer research2024
Comprehensive profiling of cell subsets of gastric cancer and liver metastasis based on single cell RNA-sequencing analysis.
Article in Translational cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 10 citations in OpenAlex.
- Predicting Clinical Outcomes and Immunotherapy Responses in Lung Adenocarcinoma Based on Nicotine Response Characteristics.Current medicinal chemistry · 2026Article
- Transcriptomic Analysis Reveals the Role ofHuman mutation · 2026Article
- Identification and Validation of a Two-Gene NK Cell-Related Risk Model for COPD: Integration of Single-Cell and Bulk RNA-Seq Analysis.International journal of chronic obstructive pulmonary disease · 2026Article
- A Histone Deacetylase Activity Model for the Discovery and Validation of Sepsis Biomarkers.Endocrine, metabolic & immune disorders drug targets · 2026Article
- Spatial Fibroblast-Macrophage Niches in Gastric Cancer: Mechanisms of Immune Exclusion, Therapeutic Resistance, and Targeted Intervention.OncoTargets and therapy · 2026Review
- Construction and validation of a lung adenocarcinoma prognostic model based on neutrophil extracellular traps and oxidative stress-related genes.European journal of medical research · 2025Article
- Endothelial-specific genes TMTC1, RPS6KA2, and F8 are downregulated in hypertrophic cardiomyopathy.European journal of medical research · 2025Article
- Correlation between dyslipidaemia and gastric cancer: pathogenesis to prevention and treatment strategies.Lipids in health and disease · 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
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Liver metastasis (Li) is one of the most common distant metastatic sites for gastric cancer. A deeper understanding of its mechanism of action from a bioinformatics perspective may provide new insights. Therefore, the aim of this study was to use single cell RNA sequencing (scRNA-seq) to evaluate cell subtypes and understand the molecular mechanism of gastric cancer Li. Methods: The scRNA-seq data GSE163558 of gastric cancer and Li were downloaded from Gene Expression Omnibus (GEO). Single cell data were analyzed by various R packages such as Seurat, CellChat, gene set variation analysis (GSVA), monocle, gene set enrichment analysis (GSEA), and survival analysis and the results were plotted by ggplot2, R4.1.1. Protein expression was confirmed by immunohistochemistry in an additional patient cohort. Results: The genes Conclusions: The present study revealed the difference between Li and gastric PT by scRNA-seq, demonstrating the impact of partial gene expression on patient prognosis. Our study provides new insights into gastric cancer and Li.
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.