title: Personalized anticancer therapy selection using molecular landscape topology and thermodynamics.
abstract: Personalized anticancer therapy requires continuous consolidation of emerging bioinformatics data into meaningful and accurate information streams. The use of novel mathematical and physical approaches, namely topology and thermodynamics can enable merging differing data types for improved accuracy in selecting therapeutic targets. We describe a method that uses chemical thermodynamics and two topology measures to link RNA-seq data from individual patients with academically curated protein-protein interaction networks to select clinically relevant targets for treatment of low-grade glioma (LGG). We show that while these three histologically distinct tumor types (astrocytoma, oligoastrocytoma, and oligodendroglioma) may share potential therapeutic targets, the majority of patients would benefit from more individualized therapies. The method involves computing Gibbs free energy of the protein-protein interaction network and applying a topological filtration on the energy landscape to produce a subnetwork known as persistent homology. We then determine the most likely best target for therapeutic intervention using a topological measure of the network known as Betti number. We describe the algorithm and discuss its application to several patients.
authors: BINDS Laboratory, College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA, USA.
authors: Edward A
authors: EA
authors: Rietman
authors: Wolfson Center for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, UK.|Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
authors: Jacob G
authors: JG
authors: Scott
authors: Department of Oncology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada.|Department of Physics, University of Alberta, Edmonton, Alberta, Canada.
authors: Jack A
authors: JA
authors: Tuszynski
authors: Molecular Oncology Research Institute, Tufts Medical Center, Boston, MA, USA.|Pediatric Hematology Oncology, Floating Hospital for Children at Tufts Medical Center, Boston, MA, USA.|Sackler School of Graduate Biomedical Sciences at Tufts University, Boston, MA, USA.
authors: Giannoula Lakka
authors: GL
authors: Klement
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms; D019295:Computational Biology / Q000379:methods; D005910:Glioma; D006801:Humans; D058990:Molecular Targeted Therapy / Q000379:methods*; D057285:Precision Medicine / Q000379:methods*; D013816:Thermodynamics
keywords: glioma; precision medicine; targeted agents; thermodynamic measures; topology