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Related Experiment Video

Updated: Jun 29, 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

Microarray methods to identify factors determining breast cancer progression: potentials, limitations, and

B van der Vegt1, G H de Bock, H Hollema

  • 1Department of Pathology and Laboratory Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.

Critical Reviews in Oncology/Hematology
|October 14, 2008
PubMed
Summary

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Many breast cancer patients don't benefit from current adjuvant therapy. New microarray methods offer promising biomarkers for personalized breast cancer treatment, improving patient outcomes.

Area of Science:

  • Oncology
  • Genomics
  • Biomarker Discovery

Background:

  • Classical markers for adjuvant therapy in breast cancer are insufficient, potentially leading to 65-80% of patients not benefiting.
  • There's a critical need for novel biomarkers to personalize breast cancer treatment strategies.

Purpose of the Study:

  • To provide an overview of commonly used microarray methods for identifying breast tumor progression markers.
  • To discuss the applications, potentials, limitations, and statistical analyses of these microarray techniques.

Main Methods:

  • Oligonucleotide (oligo) or complementary DNA (cDNA) arrays
  • Comparative Genomic Hybridization (CGH) arrays
  • Polymerase Chain Reaction (PCR) arrays
  • Tissue microarrays

Related Experiment Videos

Last Updated: Jun 29, 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

Main Results:

  • Microarray studies have significantly enhanced understanding of breast carcinoma complexity and diversity.
  • These methods have identified clinically relevant breast cancer subgroups amenable to tailored treatments.
  • Examples from literature illustrate the application of various microarray techniques.

Conclusions:

  • Microarray technologies have advanced the identification of novel prognostic indicators for breast cancer.
  • Further extensive external validation and long-term follow-up are required for clinical implementation.
  • Novel indicators are likely to complement existing classical prognostic factors in personalized medicine.