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Related Experiment Video

Updated: Jul 5, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

Microarray gene-expression profiling to predict lymph node metastasis in penile carcinoma.

Bin K Kroon1, Joost A P Leijte, Hester van Boven

  • 1Department of Urology, the Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands.

BJU International
|May 15, 2008
PubMed
Summary

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Gene expression profiling was evaluated for predicting lymph node status in penile cancer patients. The study found that this method was not a useful classifier for determining nodal involvement in this patient group.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genomics

Background:

  • Penile carcinoma staging often relies on lymph node status.
  • Accurate prediction of nodal involvement is crucial for treatment planning.

Purpose of the Study:

  • To assess the utility of gene-expression profiling in predicting regional lymph node status in penile carcinoma patients.

Main Methods:

  • Gene expression analysis was performed on tumor samples from 56 penile squamous cell carcinoma patients using 35k oligoarrays.
  • A 44-probe classifier was developed and validated on separate training and validation sets.

Main Results:

  • The classifier achieved 97% accuracy in the training set but only 54% accuracy in the validation set.

Related Experiment Videos

Last Updated: Jul 5, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

  • Sensitivity for detecting nodal involvement was 71%, while specificity was only 22% in the validation set.
  • Conclusions:

    • Gene expression profiling, as applied in this study, did not yield a reliable classifier for predicting nodal involvement in penile carcinoma.
    • Further research may be needed to explore alternative genomic markers or refine existing methods.