Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

9.4K
Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
9.4K
Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

11.2K
Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
11.2K
Cancer Survival Analysis01:21

Cancer Survival Analysis

658
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
658
Relative Risk01:12

Relative Risk

2.0K
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
2.0K
Chromatin Position Affects Gene Expression02:35

Chromatin Position Affects Gene Expression

24.7K
Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences  access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area. 
Topologically Associated Domains (TADs)
The 3-dimensional positioning of chromatin in the nucleus influences the...
24.7K
Adrenergic Receptors: ɑ Subtype01:31

Adrenergic Receptors: ɑ Subtype

2.8K
Adrenoceptors are classified into α and ꞵ classes based on their potencies to catecholamine agonists. α-adrenoceptors show the following order of catecholamine potency:
Adrenaline ≥ Noradrenaline >> Isoprenaline
α-adrenoceptors are further divided into α1 and α2-adrenoceptors.
α1-Adrenoceptors: These receptors are located postsynaptically on the effector organs and cause constriction of smooth muscle mediated by activation of phospholipase...
2.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Genome-Wide Identification of Pineapple AcINH Genes and Functional Characterization of <i>AcINH3</i> in Sucrose Metabolism and Drought Tolerance.

Plants (Basel, Switzerland)·2026
Same author

Value of Thromboelastography as a Predictor of Postoperative Acute Respiratory Distress Syndrome in Patients With Acute Type A Aortic Dissection.

Reviews in cardiovascular medicine·2026
Same author

Development of a one-tube PAM-independent RCNPM platform using Cas12a for ultra-rapid simultaneous miR-499 and cTnT detection in early acute myocardial infarction diagnosis.

Journal of translational medicine·2026
Same author

Carbon dot nanozymes as free radical scavengers for the management of hepatic ischemia-reperfusion injury by regulating the liver inflammatory network and inhibiting apoptosis.

Journal of nanobiotechnology·2026
Same author

Association between Socioeconomic Position and Thyroid Cancer Incidence: A Population-Based Cohort Study in China.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology·2026
Same author

Distributed human-water relationship model based on the "four processes" of the human-water system.

iScience·2026

Related Experiment Video

Updated: Jan 25, 2026

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
10:40

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

2.8K

Unsupervised Clustering Subtype Analysis and Prognostic Risk Model of Cuproptosis-Related Genes for Liver Cancer.

WenKai Huang1, QingSong Wu1

  • 1Department of Hepatobiliary Surgery, Yuebei People's Hospital Affiliated to Shantou University, Guangdong, China.

The Turkish Journal of Gastroenterology : the Official Journal of Turkish Society of Gastroenterology
|January 24, 2026
PubMed
Summary

This study identifies cuproptosis-related genes (CRGs) and develops a prognostic risk model for hepatocellular carcinoma (HCC). The model accurately predicts patient survival, aiding in risk stratification and treatment decisions for liver cancer.

More Related Videos

A Portal Vein Injection Model to Study Liver Metastasis of Breast Cancer
07:35

A Portal Vein Injection Model to Study Liver Metastasis of Breast Cancer

Published on: December 26, 2016

42.7K
Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.8K

Related Experiment Videos

Last Updated: Jan 25, 2026

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
10:40

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

2.8K
A Portal Vein Injection Model to Study Liver Metastasis of Breast Cancer
07:35

A Portal Vein Injection Model to Study Liver Metastasis of Breast Cancer

Published on: December 26, 2016

42.7K
Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.8K

Area of Science:

  • Oncology
  • Genomics
  • Molecular Biology

Background:

  • Hepatocellular carcinoma (HCC) poses a significant global health challenge.
  • Cuproptosis, a newly identified form of programmed cell death, is implicated in various cancers.
  • Understanding the role of cuproptosis-related genes (CRGs) in HCC is crucial for developing novel therapeutic strategies.

Purpose of the Study:

  • To identify CRGs relevant to hepatocellular carcinoma (HCC).
  • To construct and validate a prognostic risk model for HCC based on CRGs.
  • To assess the model's potential for clinical application in risk stratification and treatment guidance.

Main Methods:

  • Downloaded and analyzed transcriptome, gene expression, and clinical data for HCC from TCGA and GEO databases.
  • Screened differentially expressed CRGs and performed Cox and LASSO regression analyses to build a prognostic model.
  • Validated gene expression using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and assessed model performance with nomograms.

Main Results:

  • Identified 19 CRGs, with 15 showing differential expression in HCC tissues.
  • Constructed a 9-CRG prognostic risk model, demonstrating that high-risk patients have significantly poorer survival rates.
  • The model showed strong predictive accuracy for 1-, 3-, and 5-year survival probabilities (91.6%, 62.4%, 56.3%) and correlated with tumor microenvironment and drug sensitivity.

Conclusions:

  • The developed 9-CRG prognostic risk model effectively predicts HCC prognosis.
  • This model can aid in risk stratification, immunotherapy evaluation, and drug susceptibility analysis for HCC patients.
  • CRGs represent potential therapeutic targets and prognostic biomarkers for liver cancer.