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Related Experiment Video

Updated: Jun 15, 2026

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
11:12

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

Published on: August 1, 2018

Breast cancer relapse prediction based on multi-gene RT-PCR algorithm.

Elzbieta Pluciennik1, Maciej Krol, Magdalena Nowakowska

  • 1Department of Molecular Cancerogenesis, Medical University of Lodz, Mazowiecka 6/8 Str., 92-215 Lodz, Poland. elzbieta.pluciennik@umed.lodz.pl

Medical Science Monitor : International Medical Journal of Experimental and Clinical Research
|March 2, 2010
PubMed
Summary

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A new 10-gene algorithm accurately predicts disease-free survival in estrogen receptor-negative breast cancer patients, aiding personalized treatment strategies.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genomics

Background:

  • Breast cancer exhibits significant clinical and molecular heterogeneity.
  • Understanding complex gene interactions in pathways like apoptosis and signal transduction is crucial for tumor biology.
  • Advanced techniques like microarrays and RT-PCR enable comprehensive gene expression research.

Purpose of the Study:

  • To develop and validate a multigene expression algorithm for breast cancer prognosis.
  • To investigate the utility of gene expression profiling in stratifying patients based on molecular characteristics.
  • To improve individualized cancer treatment by identifying distinct molecular subtypes.

Main Methods:

  • Quantitative RT-PCR was used to analyze the expression levels of 10 genes in 119 breast cancer patient samples.

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

Published on: May 17, 2019

Related Experiment Videos

Last Updated: Jun 15, 2026

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
11:12

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

Published on: August 1, 2018

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

  • Genes included known good prognosis markers (WWOX, ESR1, CDH, BAX) and bad prognosis markers (KRT5, KRT14, KRT17, CCNE1, BCL2, BIRC5).
  • Statistical analysis was performed to correlate gene expression patterns with disease-free survival and estrogen receptor status.

    • Main Results:

    • A 10-gene algorithm identified two statistically significant patient groups with differing disease-free survival rates.
    • The algorithm demonstrated prognostic value specifically in estrogen receptor-negative breast cancer.
    • High algorithm values correlated with a good prognosis for disease-free survival in ER-negative patients (HR=0.26; p=0.0039), but not in ER-positive patients.

    Conclusions:

    • The developed multigene algorithm shows potential for outcome evaluation in estrogen receptor-negative breast cancer.
    • This approach may facilitate personalized treatment strategies for specific breast cancer molecular subtypes.
    • Further research can refine gene expression-based prognostic tools for improved breast cancer management.