ArticleDiscover oncology2025
A novel immune-metabolic prognostic model stratifies survival and personalizes therapy in hepatocellular carcinoma.
Article in Discover oncology, 2025. 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
8 authors.
Funding
Abstract
backgroundThe etiology of HCC is multifactorial, with pathogenesis involving immune and metabolic pathways. This study developed a prognostic model based on immune- and metabolism-related genes (IMRGs) to improve personalized HCC management.
methodsTranscriptomic data from HCC patients were obtained from TCGA (n = 377) and GEO (n = 115). Differentially expressed IMRGs between tumor and adjacent normal tissues were identified, and patients were stratified using non-negative matrix factorization (NMF). A LASSO-Cox prognostic model was constructed and validated, with assessments of immune microenvironment, therapeutic sensitivity, and functional pathways.
resultsHCC patients were classified into two subgroups with distinct immune microenvironment features. LASSO regression identified nine key prognostic genes from 54 consensus IMRGs, forming a robust risk model. High-risk patients had significantly worse survival, and the model outperformed existing immune/metabolic signatures (5-year AUC = 0.700 vs. 0.570-0.603) and clinical parameters (AUC = 0.720 vs. 0.470-0.712). Functional analysis revealed enhanced chromosome separation and nuclear division in high-risk patients, while low-risk patients showed elevated amino acid catabolism and fatty acid metabolism. High-risk patients also exhibited reduced Natural Killer cell activity and type II interferon responses but increased oxaliplatin sensitivity and 5-Fluorouracil resistance.
conclusionThis IMRG-based prognostic model effectively predicts HCC outcomes, enabling risk stratification and personalized therapy. It demonstrates strong clinical utility, advancing precision medicine in HCC management.
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.