A causal Bayesian network model of disease progression mechanisms in chronic myeloid leukemia

Daniel Koch*, Robert S. Eisinger, Alexander Gebharter

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)

Abstract

Chronic myeloid leukemia (CML) is a cancer of the hematopoietic system initiated by a single genetic mutation which results in the oncogenic fusion protein Bcr-Abl. Untreated, patients pass through different phases of the disease beginning with the rather asymptomatic chronic phase and ultimately culminating into blast crisis, an acute leukemia resembling phase with a very high mortality. Although many processes underlying the chronic phase are well understood, the exact mechanisms of disease progression to blast crisis are not yet revealed. In this paper we develop a mathematical model of CML based on causal Bayesian networks in order to study possible disease progression mechanisms. Our results indicate that an increase of Bcr-Abl levels alone is not sufficient to explain the phenotype of blast crisis and that secondary changes such as additional mutations are necessary to explain disease progression and the poor therapy response of patients in blast crisis. (C) 2017 Elsevier Ltd. All rights reserved.

Original languageEnglish
Pages (from-to)94-105
Number of pages12
JournalJournal of Theoretical Biology
Volume433
DOIs
Publication statusPublished - 21-Nov-2017
Externally publishedYes

Keywords

  • Chronic myeloid leukemia
  • Blast crisis
  • Disease progression mechanisms
  • Causal modeling
  • Bayesian networks
  • Feedback loops
  • CHRONIC MYELOGENOUS LEUKEMIA
  • UNDERLYING ABNORMAL TRAFFICKING
  • BCR-ABL EXPRESSION
  • BLAST CRISIS
  • MALIGNANT PROGENITORS
  • INTEGRIN FUNCTION
  • IMATINIB
  • PHASE
  • ADHESION
  • CELLS

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