ArticleTranslational cancer research2024
Bioinformatics prediction and experimental verification identify a cuproptosis-related gene signature as prognosis biomarkers of hepatocellular carcinoma.
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 1 paper.
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
1 citing paper in PubMed.
- Targeting cuproptosis in liver cancer: Molecular mechanisms and therapeutic implications.Apoptosis : an international journal on programmed cell death · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Hepatocellular carcinoma (HCC) of which its prognostic prediction is still unclarified is a highly heterogeneous disease. Cuproptosis is a form of cell death that depends on copper regulation. Whether the cuproptosis-related genes can be the prognostic indicators of HCC is yet to be elucidated. The aim of this study is to investigate whether cuproptosis-related genes play a role in HCC and can be used as a diagnostic index to predict the occurrence of liver cancer. Methods: We downloaded HCC patients' gene expression profiles and their corresponding clinical data from a public database. To screen data, we used single factor Cox regression analysis, meanwhile, polymerase chain reaction (PCR) was used for the verification. After that, the risk score was calculated and the relationship between risk score and clinical factors was analyzed. Besides, a nomogram map was constructed for predicting the prognosis of HCC, and calibration map and decision curve analysis (DCA) map were used to test the model. Results: Compared to the high expression group of four cuproptosis-related genes, the low expression group showed better overall survival (OS) [hazard ratio (HR) =2.58; 95% confidence interval (CI): 1.72-3.89, P<0.01]. The expression of the four cuproptosis-relate genes increased in liver cancer cell lines compared to liver cell lines (P<0.05). Based on these four genes, we calculated the risk score and divided them into two groups as high-risk group and low-risk group. The risk factor map showed the high-risk group had shorter survival time and the four genes were highly expressed. The area under curve (AUC) of receiver operating characteristic (ROC) prediction curve for the first year was 0.726. Risk scores were closely related to clinical factors and immune cells. Finally, we constructed a nomogram for predicting the prognosis of HCC. Conclusions: The risk score for cuproptosis-related genes was established and involved in the construction of the nomogram, providing a new perspective on the prognosis and copper metabolism of 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.