ArticleJournal of physiology and biochemistry2025
Prognostic model development using novel genetic signature associated with adenosine metabolism and immune status for patients with hepatocellular carcinoma.
Article in Journal of physiology and biochemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Integrating Transcriptomics and 3D Spheroid Models Reveals Microenvironment-Dependent Purinergic Modulation in Hepatocellular Carcinoma.Metabolites · 2026Article
- Deciphering adenosine signaling in hepatocellular carcinoma: Pathways, prognostic models, and therapeutic implications.Clinical and molecular hepatology · 2025Review
- Adenosine receptors on the immuno-oncology expressway: TIME, perspectives, and translation.Frontiers in immunology · 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.
Funding
Abstract
The high mortality rate of hepatocellular carcinoma (HCC) is partly due to advanced diagnosis, emphasizing the need for effective predictive tools in HCC treatment. The aim of this study is to propose a novel prognostic model for HCC based on adenosine metabolizing genes and explore the potential relationship between them. Regression analysis was performed to identify differentially expressed genes associated with adenosine metabolism in HCC patients using RNA sequencing data obtained from a public database. Adenosine metabolism-related risk score (AMrisk) was derived using the least absolute shrinkage and selection operator (LASSO) Cox regression and verified using another database. Changes in adenosine metabolism in HCC were analyzed using functional enrichment analysis and multiple immune scores. The gene expression levels in patient samples were validated using quantitative reverse transcription polymerase chain reaction. Thirty adenosine metabolism-related differentially expressed genes were identified in HCC, and six genes (ADA, P2RY4, P2RY6, RPIA, SLC6A3, and VEGFA) were used to calculate the AMrisk score; the higher the risk scores, the lower the overall survival. Moreover, immune infiltration activation and immune checkpoints were considerably higher in the high-risk group. Additional in vitro experiments validated the enhanced expression of these six genes in HCC. The established predictive model demonstrated that adenosine metabolism-related genes was significantly associated with prognosis in HCC patients.
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.