A thermodynamic-based interpretation of protein expression heterogeneity in different glioblastoma multiforme tumors identifies tumor-specific unbalanced processes

Nataly Kravchenko-Balasha, Hannah Johnson, Forest M. White, James R. Heath*, R. D. Levine

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

We describe a thermodynamic-motivated, information theoretic analysis of proteomic data collected from a series of 8 glioblastoma multiforme (GBM) tumors. GBMs are considered here as prototypes of heterogeneous cancers. That heterogeneity is viewed here as manifesting in different unbalanced biological processes that are associated with thermodynamic-like constraints. The analysis yields a molecular description of a stable steady state that is common across all tumors. It also resolves molecular descriptions of unbalanced processes that are shared by several tumors, such as hyperactivated phosphoprotein signaling networks. Further, it resolves unbalanced processes that provide unique classifiers of tumor subgroups. The results of the theoretical interpretation are compared against those of statistical multivariate methods and are shown to provide a superior level of resolution for identifying unbalanced processes in GBM tumors. The identification of specific constraints for each GBM tumor suggests tumor-specific combination therapies that may reverse this imbalance.

Original languageAmerican English
Pages (from-to)5990-5997
Number of pages8
JournalJournal of Physical Chemistry B
Volume120
Issue number26
DOIs
StatePublished - 7 Jul 2016

Bibliographical note

Publisher Copyright:
© 2016 American Chemical Society.

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