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An Integrative MuSiCO Algorithm: From the Patient-Specific Transcriptional Profiles to Novel Checkpoints in Disease Pathobiology

  • Anastasia Meshcheryakova
  • Philip Zimmermann
  • Rupert Ecker
  • Felicitas Mungenast
  • Georg Heinze
  • Diana Mechtcheriakova
Chapter
Part of the RNA Technologies book series (RNATECHN)

Abstract

Strong efforts are invested in the field of cancer and other multifactorial diseases to evaluate the applicability of gene expression patterns for identification of novel disease-relevant checkpoints and nomination of promising biomarkers for disease and/or targets. Deciphering the disease complexity demands the implementation of a holistic approach, which covers the levels of the biological hierarchy from molecules to functional gene network(s) and biological pathways and further to disease (patho)mechanisms and clinical relevance. In this chapter we describe the systems biology-based integrative algorithm, named by us as MuSiCO/fromMultigeneSignature to Patient-OrientatedClinicalOutcome, and discuss its applicability for translational research. This innovative approach is based on the implementation of consecutive analytical modules integrating advanced gene expression profiling of clinical patient specimens, prognostic/predictive modeling, digital pathology, and systems biology. It consolidates in-depth expertise from diverse scientific and medical disciplines and hereby bridges systems biology and systems medicine to maximize the benefit of the patient.

Keywords

MuSiCO algorithm Multigene signature Gene expression profiling Statistical modeling for survival prediction and therapy response AID/APOBEC gene family Sphingolipid system Systems biology Next generation digital pathology Personalized medicine 

List of Abbreviations

AICDA

Activation-induced cytidine deaminase

CRCLM

Colorectal cancer metastasis in the liver

EMT

Epithelial to mesenchymal transition

MuSiCO

from Multigene signature to patient-orientated clinical outcome

ROIs

Regions of interest

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Anastasia Meshcheryakova
    • 1
  • Philip Zimmermann
    • 2
  • Rupert Ecker
    • 3
  • Felicitas Mungenast
    • 1
  • Georg Heinze
    • 4
  • Diana Mechtcheriakova
    • 1
  1. 1.Department of Pathophysiology and Allergy ResearchCenter for Pathophysiology, Infectiology and Immunology, Medical University of ViennaViennaAustria
  2. 2.Nebion AGZürichSwitzerland
  3. 3.TissueGnosticsViennaAustria
  4. 4.Section for Clinical BiometricsCenter for Medical Statistics, Informatics, and Intelligent Systems, Medical University of ViennaViennaAustria

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