Enabling precision medicine by unravelling disease pathophysiology: quantifying signal transduction pathway activity

Anja van de Stolpe1, Laurent Holtzer2, Henk van Ooijen2

  • 1Philips Research, High Tech Campus 11, 5656 AE, Eindhoven, The Netherlands. Anja.van.de.stolpe@philips.com.

Scientific Reports
|February 9, 2019
PubMed

Insights

This study introduces a novel Bayesian method to measure signal pathway activity using mRNA levels. This approach aids in understanding disease mechanisms and predicting targeted therapy response in various cancers.

Area of Science:

  • Molecular biology
  • Computational biology
  • Oncology

Background:

  • Signal transduction pathways are crucial in health and disease, particularly in cancer.
  • Targeted therapies require accurate measurement of pathway activity in patient samples for optimal treatment selection.

Purpose of the Study:

  • To develop and validate a quantitative assay for measuring functional pathway activity using Bayesian inference.
  • To model and analyze key signaling pathways including androgen receptor (AR), Hedgehog, TGFβ, and NFκB.

Main Methods:

  • Bayesian computational model inference applied to mRNA levels of target genes.
  • Development of new assays for AR, Hedgehog, TGFβ, and NFκB pathways.
  • Biological validation across multiple cell types and analysis of clinical study data.

Main Results:

  • Demonstrated increased AR activity in early prostate cancer (PCa) and variable activity in castrate-resistant PCa.
  • Observed loss of TGFβ activity and increased Wnt activity in specific PCa subtypes.
  • Identified active PI3K and NFκB pathways as potential drivers of hormonal resistance in advanced PCa.

Conclusions:

  • The developed method provides a quantitative measure of pathway activity from mRNA data.
  • Pathway activity profiling can aid in disease subtyping and predicting targeted therapy response.
  • This approach holds potential for clinical applications in personalized cancer medicine.

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