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Related Concept Videos

Tumor Progression02:07

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...

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miRNA Expression Analyses in Prostate Cancer Clinical Tissues
11:29

miRNA Expression Analyses in Prostate Cancer Clinical Tissues

Published on: September 8, 2015

Modelling gene expression profiles related to prostate tumor progression using binary states.

Emmanuel Martinez1, Victor Trevino

  • 1Cátedra de Bioinformática, Tecnológico de Monterrey, Campus Monterrey, Monterrey, Nuevo León 64849, México.

Theoretical Biology & Medical Modelling
|June 1, 2013
PubMed
Summary

This study introduces a novel method to model gene expression changes during tumor progression. The approach identifies key gene profiles, offering potential for new cancer therapies.

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Cancer involves disrupted gene activity (oncogenes, tumor-suppressor genes).
  • Tumor progression to malignancy is a dynamic process reflected in gene expression changes.
  • Existing methods lack models for gene expression levels across tumor stages.

Purpose of the Study:

  • To develop a method modeling gene expression to tumor stage.
  • To understand tumor progression dynamics and complexity.
  • To identify gene expression profiles associated with malignancy progression.

Main Methods:

  • Modeled gene activation (on-off state) per sample and stage.
  • Selected gene expression profiles based on statistical significance.
  • Utilized random permutation for dataset validation.

Main Results:

  • Identified expected oncogene and tumor suppressor gene profiles in prostate cancer.
  • Outperformed common differential expression tests and tailored methods.
  • Ontology and pathway analysis supported the identified gene profiles.

Conclusions:

  • The methodology is a valuable tool for studying tumor malignancy progression.
  • Potential to reveal novel therapeutic targets for cancer treatment.