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

Metastasis02:30

Metastasis

5.7K
Metastasis is the spread of cancer cells from the original site to distant locations in the body. Cancer cells can spread via blood vessels (hematogenous) as well as lymph vessels in the body.
Epithelial-to-Mesenchymal Transition
The epithelial-to-mesenchymal transition or EMT is a developmental process commonly observed in wound healing, embryogenesis, and cancer metastasis. EMT is induced by transforming growth factor-beta (TGF-β) or receptor tyrosine kinase (RTK) ligands, which further...
5.7K
Genomics02:02

Genomics

37.6K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
37.6K

You might also read

Related Articles

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

Sort by
Same author

CD22 is upregulated and displays suppressive properties on CD4+ T cells upon a persistent virus infection.

Journal of immunology (Baltimore, Md. : 1950)·2026
Same author

Sphingosine 1-phosphate lyase expressed in pulmonary epithelial cells potentiates host innate defenses and alleviates influenza pathogenicity in mice.

bioRxiv : the preprint server for biology·2026
Same author

Defective cuticle-derived signals enhance extracellular ATP response and plant immunity.

The New phytologist·2026
Same author

CryoFSL: an annotation-efficient, few-shot learning framework for robust protein particle picking in cryo-electron microscopy micrographs.

Briefings in bioinformatics·2026
Same author

Evaluating AlphaFold Tools and Related Scoring Functions for Protein-peptide Complex Prediction.

Genomics, proteomics & bioinformatics·2026
Same author

G2PDeep-v2: A Web-Based Deep-Learning Framework for Phenotype Prediction and Biomarker Discovery for All Organisms Using Multi-Omics Data.

Biomolecules·2025

Related Experiment Video

Updated: Sep 19, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K

Deep-learning-enabled multi-omics analyses for prediction of future metastasis in cancer.

Xiaoying Wang1,2, Maoteng Duan3, Po-Lan Su4,5

  • 1Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.

Biorxiv : the Preprint Server for Biology
|June 6, 2025
PubMed
Summary

Predicting cancer metastasis is challenging. EmitGCL, a deep learning tool, accurately forecasts metastasis and identifies biomarkers like HSP90AA1/AB1 and YY1, improving early detection and potential therapies.

More Related Videos

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

1.7K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K

Related Experiment Videos

Last Updated: Sep 19, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K
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

1.7K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K

Area of Science:

  • Oncology
  • Bioinformatics
  • Computational Biology

Background:

  • Metastasis is the primary driver of cancer mortality.
  • Predicting metastasis and identifying reliable biomarkers remain significant clinical hurdles.

Purpose of the Study:

  • To develop EmitGCL, a deep learning framework for accurate metastasis prediction and biomarker discovery.
  • To validate EmitGCL's performance against existing computational tools.

Main Methods:

  • Benchmarking EmitGCL against other computational tools across six cancer types and seven patient cohorts.
  • Utilizing deep learning for metastasis prediction and biomarker identification.
  • Validating identified biomarkers (HSP90AA1, HSP90AB1) and metastasis drivers (YY1) through independent cohorts and functional assays.

Main Results:

  • EmitGCL demonstrated superior sensitivity and specificity in predicting metastasis compared to other tools.
  • The framework successfully identified occult metastatic cells in a lymph node-negative breast cancer patient.
  • HSP90AA1 and HSP90AB1 were validated as predictive biomarkers for breast cancer metastasis across multiple cohorts.
  • YY1 was identified as a key driver of breast cancer metastasis.

Conclusions:

  • EmitGCL offers a robust computational approach for predicting cancer metastasis and discovering biomarkers.
  • The findings highlight HSP90AA1, HSP90AB1, and YY1 as crucial players in breast cancer metastasis.
  • YY1 presents a potential therapeutic target for inhibiting cancer spread.