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

You might also read

Related Articles

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

Sort by
Same author

Distinct epidemiologic patterns of mesothelioma: evidence from a 16-year provincial cohort in China.

BMC cancer·2026
Same author

Safety of fruquintinib mono- and combo therapy in metastatic colorectal cancer: real-world subgroup analysis from China.

Future oncology (London, England)·2026
Same author

IL-17 promotes H1299 cell proliferation via LINC01518/miR-20a-5p/E2F1 axis in non-small cell lung cancer.

Neoplasma·2026
Same author

Rezivertinib in <i>EGFR</i>-Mutated Non-Small Cell Lung Cancer Patients with Central Nervous System Metastasis: Central Nervous System Efficacy from the Phase III REZOR Study.

Cancer communications (London, England)·2026
Same author

Correction to: De novo pyrimidine synthesis is a collateral metabolic vulnerability in NF2-deficient mesothelioma.

EMBO molecular medicine·2026
Same author

Deficiencies in germline DNA repair are associated with early-onset gastrointestinal cancers and inform precision prevention strategies.

Journal of translational medicine·2025

Related Experiment Video

Updated: Jan 14, 2026

Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies
07:47

Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies

Published on: September 15, 2023

2.1K

Machine Learning-Based Prognostic Model for Gastric Cancer Using Integrated Multi-Omics Data.

Minyue Shou1, Yuqing Liu1, Yongqian Shu1

  • 1Department of Oncology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.

Cancer Investigation
|October 20, 2025
PubMed
Summary
This summary is machine-generated.

This study integrates multi-omics data to create a new prognostic framework for gastric cancer (GC). This framework improves patient risk stratification and identifies potential therapeutic targets for precision medicine.

Keywords:
Gastric cancerGene expressionMethylationMolecular subtypesMulti-omics integrationPrognostic biomarker

More Related Videos

Author Spotlight: Genetic Profiling for Fluorouracil Response in Gastric Cancer
06:21

Author Spotlight: Genetic Profiling for Fluorouracil Response in Gastric Cancer

Published on: May 10, 2024

1.2K
Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
03:05

Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors

Published on: February 16, 2024

1.5K

Related Experiment Videos

Last Updated: Jan 14, 2026

Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies
07:47

Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies

Published on: September 15, 2023

2.1K
Author Spotlight: Genetic Profiling for Fluorouracil Response in Gastric Cancer
06:21

Author Spotlight: Genetic Profiling for Fluorouracil Response in Gastric Cancer

Published on: May 10, 2024

1.2K
Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
03:05

Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors

Published on: February 16, 2024

1.5K

Area of Science:

  • Genomics and Bioinformatics
  • Cancer Research
  • Molecular Oncology

Background:

  • Gastric cancer (GC) prognosis is poorly defined by current methods.
  • Molecular heterogeneity necessitates advanced approaches for accurate prognostication.

Purpose of the Study:

  • To develop a robust multi-omics prognostic framework for gastric cancer.
  • To identify molecular subtypes and prognostic signatures for improved patient stratification and targeted therapy.

Main Methods:

  • Synergistic analysis of transcriptomic, epigenomic, and clinical data from 108 GC patients.
  • Genome-wide expression profiling, methylation array analysis, and similarity network fusion.
  • Development of a LASSO-derived prognostic signature and a multi-omics nomogram.

Main Results:

  • Identified 1,243 survival-associated transcripts and 8,742 prognostic CpG sites.
  • Revealed three molecular subtypes with distinct clinical outcomes; Subtype 3 showed significantly higher mortality risk.
  • The multi-omics signature achieved superior prognostic discrimination (C-index: 0.786) and outperformed existing systems.

Conclusions:

  • Multi-omics integration offers superior prognostic refinement for gastric cancer compared to conventional methods.
  • Identified subtype-specific pathways (cell cycle, immune evasion) and potential therapeutic targets (CDK/PI3K inhibitors).
  • This framework facilitates precision therapy guidance for improved gastric cancer management.