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 Experiment Video

Updated: Jul 7, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

Merging microarray data from separate breast cancer studies provides a robust prognostic test.

Lei Xu1, Aik Choon Tan, Raimond L Winslow

  • 1The Institute for Computational Medicine and Center for Cardiovascular Bioinformatics and Modeling, Johns Hopkins University, Baltimore, MD 21218, USA. leixu@jhu.edu

BMC Bioinformatics
|February 29, 2008
PubMed
Summary
This summary is machine-generated.

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

irAE.AI: AI-powered exploration of real-world immune-related adverse events.

JAMIA open·2026
Same author

Targeting of MEK and Autophagy in Pancreatic Adenocarcinoma and Analysis of Treatment Sensitivity in Preclinical and Clinical Models: MEKiAUTO.

JCO precision oncology·2026
Same author

Clinico-genomic nomograms for estimation of survival risk in metastatic castrate-resistant prostate cancer.

JNCI cancer spectrum·2026
Same author

Associations Between Two-Year Immune-Related Adverse Events and Psychological Distress and Subsequent Survival Outcomes Among ICI-Treated Survivors Diagnosed With Advanced Cancers in the US.

Psycho-oncology·2026
Same author

Impact of baseline medications on real-world overall survival in immune checkpoint inhibitor-treated patients with cancer in the RADIOHEAD cohort.

Med (New York, N.Y.)·2026
Same author

A Strategic Partnership to Advance AI Applications in Genomics and Bioinformatics for Health Innovation.

JMIR bioinformatics and biotechnology·2026

This study integrates multiple breast cancer gene expression datasets to identify a novel prognostic signature. This signature accurately predicts the risk of distant metastases, potentially improving patient treatment strategies.

Area of Science:

  • Genomics
  • Biostatistics
  • Oncology

Background:

  • Accurate prognostic markers for breast cancer metastases are crucial for effective patient therapy.
  • Existing gene expression signatures have limited predictive power due to small sample sizes and low overlap.
  • Integrating multiple microarray datasets offers a promising approach to develop robust prognostic tests.

Purpose of the Study:

  • To develop a more accurate prognostic test for breast cancer distant metastases.
  • To identify a robust gene expression signature by integrating independent microarray datasets.
  • To assess the predictive power of the developed signature in an independent test set.

Main Methods:

  • Integrated three independent breast cancer microarray gene expression datasets using a stable data aggregation procedure.

Related Experiment Videos

Last Updated: Jul 7, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

  • Identified a prognostic signature comprising 112 genes organized into 80 pair-wise expression comparisons.
  • Applied a likelihood ratio test (weighted voting) for prediction on an independent external test set.

    • Main Results:

    • Developed a prognostic signature of 112 genes from integrated microarray data.
    • Achieved 88.6% sensitivity and 54.6% specificity in an independent test set of 154 samples.
    • The signature demonstrated high informativeness for predicting distant metastases within five years (hazard ratio 9.3).

    Conclusions:

    • Rank-based features enable stable integration of multi-study microarray data, invariant to normalization.
    • The developed prognostic signature can predict distant metastases in breast cancer within a statistical modeling framework.
    • Further validation could establish this signature as a powerful tool to guide adjuvant systemic treatment, reducing costs and side effects.