ArticleEuropean journal of medical research2026
A gene signature associated with alpha-linolenic acid metabolism predicts clinical prognosis in hepatocellular carcinoma.
Article in European journal of medical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
objectiveAlpha-linolenic acid (ALA) has been implicated in the initiation and progression of multiple cancer types. Nevertheless, the molecular mechanism by which ALA metabolism influences hepatocellular carcinoma (HCC), as well as its effects on the HCC immune microenvironment, is still largely unclear.
methodsData from HCC patients were collected from the TCGA-LIHC project, HCCDB18, and GEO database. ssGSEA, consensus clustering, and COX regression were employed to identify differentially expressed genes (DEGs) linked to ALA metabolism. Based on these findings, a novel prognostic model was developed and validated. Subsequently, functional pathways, immune infiltration levels, potential response to immunotherapy, and drug sensitivity associated with the identified risk genes were explored. Additionally, RT-qPCR was performed to assess the expression levels of key genes in THLE2 and Huh7 cell lines.
resultsThree distinct molecular subtypes were classified based on ALA metabolism-related gene expression patterns, and DEGs across these subtypes were identified. A six-gene prognostic signature, termed the RiskScore model, was constructed and shown to effectively stratify patients according to clinicopathological features, immune infiltration levels, immunotherapy responsiveness, and drug sensitivity. Multivariate Cox regression incorporating both the RiskScore and clinicopathological features confirmed the RiskScore as the most prominent independent predictor of survival, demonstrating superior prognostic accuracy. Moreover, the risk-related genes TBL1X exhibited significantly higher expression in Huh7 cells compared to THLE2 cells.
conclusionThis study provides a comprehensive analysis of ALA metabolism-associated genes in HCC and proposes a novel risk-based prognostic framework. The developed model demonstrates strong predictive performance for patient survival outcomes, representing the first such approach with robust validation in forecasting prognosis in HCC.
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.