The Role of eIF4E Activity in Breast Cancer

Abstract

Increased eIF4E expression occurs in many breast cancers and makes fundamental contributions to carcinogenesis by stimulating expression of cancer-related genes at post-transcriptional levels. This key role is highlighted by the facts that eIF4E levels can predict prognosis and that eIF4E is an established therapeutic target. However, eIF4E activity is a complex function of expression levels and phosphorylation statuses of eIF4E and its regulatory proteins. Our hypothesis was that combined analyses of these pathway components would allow insights into eIF4E activity and its influence on cancer. We have established that mathematically combining assessments of expressions of eIF4E and its regulators in clinical tumours provides improved prognostic insights over examination of eIF4E alone. In doing so we have determined the mathematical relationships between expression of each pathway component and pathway activity, thereby allowing estimation of eIF4E activity in fixed tumour samples. Using human cell lines, we have established an assay to allow measurement of functional eIF4E activity and demonstrate that this provides predictive insights into the response of cells to the eIF4E-directed cancer therapeutic rapamycin. Work remains underway to investigate whether our estimate of eIF4E activity in fixed tumour samples predicts clinical response of breast cancers to the related cancer therapeutic RAD001.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2010
Accession Number
ADA542257

Entities

People

  • Thomas A. Hughes
  • V. Cookson

Organizations

  • University of Leeds

Tags

DTIC Thesaurus Topics

  • Breast Cancer
  • Cancer
  • Carrier Proteins
  • Cell Line
  • Cell Physiological Processes
  • Cells
  • Diseases And Disorders
  • Epithelial Cells
  • Genetic Code
  • Health Services
  • Maximum Likelihood Estimation
  • Mrna
  • Neoplasms
  • Proteins
  • Recognition
  • Statistical Analysis
  • Therapy

Fields of Study

  • Biology

Readers

  • Breast cancer cell signaling and growth regulation.
  • Computational Modeling and Simulation
  • Oncology (Cancer Research).