ArticleThe Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology2025
Unsupervised Clustering Subtype Analysis and Prognostic Risk Model of Cuproptosis-Related Genes for Liver Cancer.
Article in The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology, 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimsTo screen cuproptosis-related genes (CRGs) and construct a prognosis risk model for hepatocellular carcinoma (HCC) based on transcriptome data. MATERIALS AND
methodsTranscriptome, gene expression, and clinical data of HCC were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to screen CRGs. Differential genes were screened, and Cox analysis and LASSO regression analysis were performed. The clinical value of the constructed model for HCC patients was assessed. Patient survival rates were predicted. The expression of relevant genes in liver cancer tissues and adjacent tissues was verified, and the prognostic risk for patients was evaluated.
resultsNineteen CRGs were identified, and 15 genes were expressed differently in tumor tissues and normal tissues. Multivariate analy sis and LASSO regression analysis showed that 15 genes related to prognostic risk were screened, based on which a prediction model of 9 CRGs was constructed. High-risk patients, as determined by the prognostic model, showed a significantly decreased survival rate rela tive to low-risk patients. Tumor microenvironment and drug sensitivity were closely related to risk scores. Nomograms predicted survival probabilities for liver cancer patients over 1-, 3-, and 5-year periods at 91.6%, 62.4%, and 56.3%, respectively. Reverse transcription quantitative polymerase chain reaction experiments verified the relevant gene expression that made up the model in liver cancer and adjacent tissues.
conclusionThe constructed prognostic risk model can predict the prognosis of HCC well and may be used for risk stratification, immu notherapy evaluation, and drug susceptibility analysis. Cite this article as: Huang W, Wu Q. Unsupervised clustering subtype analysis and prognostic risk model of cuproptosis-related genes for liver cancer. Turk J Gastroenterol. 2026;37(1):75-87.
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.