Evidence map›Paper›PMID 38617510›Full record

ArticleTranslational cancer research2024

Cuproptosis-related molecular classification and gene signature of hepatocellular carcinoma and experimental verification.

Zehao Chen, Dongnian Du, Jiajuan Li, Wenming Zhang, Jianghua Shao

Open access · diamondAbstract read
In one paragraph

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 27% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Targeting cuproptosis in liver cancer: Molecular mechanisms and therapeutic implications.Apoptosis : an international journal on programmed cell death · 2025
    Review
  2. Article
  3. Identification ofJournal of gastrointestinal oncology · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Zehao ChenDepartment of General Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, China.
Dongnian DuDepartment of General Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, China.
Jiajuan LiDepartment of General Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, China.
Wenming ZhangDepartment of General Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, China.
Jianghua ShaoDepartment of General Surgery, the Second Affiliated Hospital of Nanchang University, Nanchang, China.
Second Affiliated Hospital of Nanchang University · CNNanchang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with poor overall prognosis. Cuproptosis, a recently proposed mode of copper-dependent cell death, plays a critical role in the malignant progression of various tumors; however, the expression and prognostic value of cuproptosis-related regulatory genes in HCC remain unclear. Methods: Genomic, genetic, and expression profiles of ten key cuproptosis-related regulatory genes were analyzed using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset and protein expression data from the Human Protein Atlas (HPA) database. Unsupervised clustering of HCC patients based on these ten key cuproptosis-related regulatory genes was used to identify different HCC subtypes and analyze the differences in clinical and immune characteristics among subtypes. Subsequently, univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox analyses were used to establish a cuproptosis-related prognostic signature, and the accuracy of prognostic signature prediction was internally validated by Kaplan-Meier survival analysis and time-dependent receiver operating characteristic curve in TCGA training and testing cohorts. The prognostic signature was externally validated using TCGA-LIHC entire cohort and International Cancer Genome Consortium Liver Cancer (ICGC-LIRI) cohorts. Finally, the expression landscape of cuproptosis-related regulatory genes in prognostic signature was explored by quantitative real-time polymerase chain reaction (qRT-PCR), western blotting and immunohistochemistry (IHC) experiments. Results: Ten cuproptosis-related genes were differentially expressed in normal and HCC tissues. Unsupervised clustering identified two subtypes and HCC patients with these two subtypes had different clinical prognoses and immune characteristics, as well as different degrees of response to immunotherapy. Lipoyltransferase 1 (LIPT1), dihydrolipoamide s-acetyltransferase (DLAT), and cyclin dependent kinase inhibitor 2A (CDKN2A) were selected to construct a prognostic signature, which significantly distinguished HCC patients with different survival periods in the TCGA training and testing cohorts and was well validated in both the TCGA-LIHC entire cohort and ICGC-LIRI cohort. The risk score of the prognostic signature was confirmed to be an independent prognostic factor, and nomograms were generated to effectively predict the probability of HCC patient survival. The qRT-PCR, western blotting and IHC results also revealed a significant imbalance in the expression of these cuproptosis-related genes in HCC. Conclusions: The classification and prognostic signature based on cuproptosis-related regulatory genes helps to explain the heterogeneity of HCC, which may contribute to the individualized treatment of patients with the disease.

Indexed as

Cuproptosishepatocellular carcinoma (HCC)immune microenvironmentprecision medicineprognostic signature

Identifiers

PMID38617510
PMCPMC11009816
OpenAlexW4393281334

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.