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

Niche-level immune evasion in <i>TP53</i> mutant AML residual disease revealed by spatial proteomics.

bioRxiv : the preprint server for biology·2026
Same author

Decarboxylation via a Higher Electronic Excited State Drives LSSmOrange Photoconversion.

ACS physical chemistry Au·2026
Same author

Neural network-assisted RNA velocity imputation for empowering transcript dynamics-based analyses.

iScience·2026
Same author

MIF-CD74 axis facilitates MDSC infiltration in the tumor microenvironment of pancreatic ductal adenocarcinoma.

Cancer letters·2026
Same author

Genetically Encoded Ca<sup>2+</sup> Sensors.

Cold Spring Harbor perspectives in biology·2025
Same author

Assessment of Skeletal Muscle Quality via Intramuscular Adipose Tissue Content Predicts Surgical Morbidity and Prognosis After Pancreatoduodenectomy.

Pancreas·2025

Related Experiment Video

Updated: Jun 24, 2026

Analysis of Cell Cycle Position in Mammalian Cells
12:19

Analysis of Cell Cycle Position in Mammalian Cells

Published on: January 21, 2012

A signature-based method for indexing cell cycle phase distribution from microarray profiles.

Hideaki Mizuno1, Yoshito Nakanishi, Nobuya Ishii

  • 1Kamakura Research Laboratories, Chugai Pharmaceutical Co Ltd, Kamakura, Kanagawa, Japan. mizunohda@chugai-pharm.co.jp

BMC Genomics
|April 1, 2009
PubMed
Summary

A new signature-based method analyzes cell cycle phase distribution from microarray data, revealing insights into cancer biology and patient prognosis. This systematic approach improves upon limited traditional methods for cancer characterization.

More Related Videos

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software
09:57

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Published on: December 16, 2014

Use of the Pyrimidine Analog, 5-Iodo-2&prime;-Deoxyuridine (IdU) with Cell Cycle Markers to Establish Cell Cycle Phases in a Mass Cytometry Platform
08:37

Use of the Pyrimidine Analog, 5-Iodo-2′-Deoxyuridine (IdU) with Cell Cycle Markers to Establish Cell Cycle Phases in a Mass Cytometry Platform

Published on: October 22, 2021

Related Experiment Videos

Last Updated: Jun 24, 2026

Analysis of Cell Cycle Position in Mammalian Cells
12:19

Analysis of Cell Cycle Position in Mammalian Cells

Published on: January 21, 2012

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software
09:57

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Published on: December 16, 2014

Use of the Pyrimidine Analog, 5-Iodo-2&prime;-Deoxyuridine (IdU) with Cell Cycle Markers to Establish Cell Cycle Phases in a Mass Cytometry Platform
08:37

Use of the Pyrimidine Analog, 5-Iodo-2′-Deoxyuridine (IdU) with Cell Cycle Markers to Establish Cell Cycle Phases in a Mass Cytometry Platform

Published on: October 22, 2021

Area of Science:

  • Oncology
  • Molecular Biology
  • Bioinformatics

Background:

  • The cell cycle machinery is crucial in cancer development and progression.
  • Current methods like mitotic index and S phase fraction offer limited, single-point measurements of cell cycle status.
  • A need exists for more comprehensive and systematic cell cycle analysis in cancer research.

Purpose of the Study:

  • To develop and validate a novel signature-based method for analyzing cell cycle phase distribution using microarray data.
  • To provide a more systematic approach to cell cycle analysis, accounting for both cycling and non-cycling cells.
  • To explore the utility of this method in cancer characterization and diagnostics.

Main Methods:

  • Developed a signature-based method utilizing a master gene set for overall cycling cell proportion and stage-specific subsets.
  • Indexed cell cycle phase distribution from microarray profiles, incorporating non-cycling cell populations.
  • Validated the method using established cell cycle and quiescence datasets.

Main Results:

  • The method successfully indexed cell cycle phase distribution, even when influenced by non-cycling cells.
  • Analysis of tumor models and human breast cancer data revealed significant variations in cycling cell proportions.
  • Uncovered "buried" cell cycle phase distributions linked to oncogenic events and patient prognosis.

Conclusions:

  • The developed signature-based cell cycle analysis offers a valuable tool for cancer characterization.
  • This method has the potential to enhance cancer diagnostics by providing deeper insights into cell cycle dynamics.
  • Further application of this systematic approach could advance our understanding of cancer biology.