Network modeling methods for precision medicine

We discuss in this survey several network modeling methods and their applicability to precision medicine. We review several network centrality methods (degree centrality, closeness centrality, eccentricity centrality, betweenness centrality, and eigenvector-based prestige) and two systems controlability methods (minimum dominating sets and network structural controllability). We demonstrate their applicability to precision medicine on three multiple myeloma patient disease networks. Each network consists of protein-protein interactions built around a specific patient’s mutated genes, around the targets of the drugs used in the standard of care in multiple myeloma, and around multiple myeloma-specific essential genes. For each network we demonstrate how the network methods we discuss can be used to identify personalized, targeted drug combinations uniquely suited to that patient.

[1]  Ching-tai Lin Structural controllability , 1974 .

[2]  Jimeng Sun,et al.  Centralities in Large Networks: Algorithms and Observations , 2011, SDM.

[3]  M. E. Shaw Group Structure and the Behavior of Individuals in Small Groups , 1954 .

[4]  Ulrik Brandes,et al.  On variants of shortest-path betweenness centrality and their generic computation , 2008, Soc. Networks.

[5]  S. Bringhen,et al.  Carfilzomib combination treatment as first-line therapy in multiple myeloma: where do we go from the Carthadex (KTd)-trial update? , 2019, Haematologica.

[6]  Alex Bavelas A Mathematical Model for Group Structures , 1948 .

[7]  Stacy A. Kujawa,et al.  A network analysis revealed the essential and common downstream proteins related to inguinal hernia , 2020, PloS one.

[8]  T. Akutsu,et al.  Minimum dominating set-based methods for analyzing biological networks. , 2016, Methods.

[9]  L. Hood,et al.  Systems cancer medicine: towards realization of predictive, preventive, personalized and participatory (P4) medicine , 2012, Journal of internal medicine.

[10]  Jiguo Yu,et al.  Connected dominating sets in wireless ad hoc and sensor networks - A comprehensive survey , 2013, Comput. Commun..

[11]  Sunita Gakkhar,et al.  Comparative Genome and Network Centrality Analysis to Identify Drug Targets of Mycobacterium tuberculosis H37Rv , 2015, BioMed research international.

[12]  B. A. Farbey,et al.  Structural Models: An Introduction to the Theory of Directed Graphs , 1966 .

[13]  Abdel-Rahman Hedar,et al.  Simulated annealing with stochastic local search for minimum dominating set problem , 2011, International Journal of Machine Learning and Cybernetics.

[14]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[15]  Stefan Wuchty,et al.  Controllability in protein interaction networks , 2014, Proceedings of the National Academy of Sciences.

[16]  Cristian Gratie,et al.  Controlling Directed Protein Interaction Networks in Cancer , 2017, Scientific Reports.

[17]  Andrea Marino,et al.  Computing top-k Closeness Centrality Faster in Unweighted Graphs , 2017, ALENEX.

[18]  S. Bhavani,et al.  Differentiating Cancer From Normal Protein-Protein Interactions Through Network Analysis , 2016 .

[19]  Chris Arney Network Analysis: Methodological Foundations , 2012 .

[20]  Gianna M. Del Corso,et al.  Fast PageRank Computation via a Sparse Linear System , 2005, Internet Math..

[21]  Valmir Carneiro Barbosa,et al.  A distributed algorithm to find k-dominating sets , 2004, Discret. Appl. Math..

[22]  U. Brandes A faster algorithm for betweenness centrality , 2001 .

[23]  C. Dangalchev Residual closeness in networks , 2006 .

[24]  Rong Yang,et al.  Extensions of closeness centrality? , 2011, ACM-SE '11.

[25]  Gábor Csárdi,et al.  The igraph software package for complex network research , 2006 .

[26]  Xiao-Fei Zhang,et al.  Determining minimum set of driver nodes in protein-protein interaction networks , 2015, BMC Bioinformatics.

[27]  Madhumangal Pal,et al.  Study on centrality measures in social networks: a survey , 2018, Social Network Analysis and Mining.

[28]  Anthony Dekker,et al.  Conceptual Distance in Social Network Analysis , 2005, J. Soc. Struct..

[29]  P. Stadler,et al.  Centers of complex networks. , 2003, Journal of theoretical biology.

[30]  B. Ebert,et al.  Lenalidomide induces degradation of IKZF1 and IKZF3 , 2014, Oncoimmunology.

[31]  An-Ping Zeng,et al.  The Connectivity Structure, Giant Strong Component and Centrality of Metabolic Networks , 2003, Bioinform..

[32]  R. Kálmán Mathematical description of linear dynamical systems , 1963 .

[33]  Albert-László Barabási,et al.  Controllability of complex networks , 2011, Nature.

[34]  Ernesto Estrada Virtual identification of essential proteins within the protein interaction network of yeast , 2005, Proteomics.

[35]  Jie Wu,et al.  Extended Dominating Set and Its Applications in Ad Hoc Networks Using Cooperative Communication , 2006, IEEE Transactions on Parallel and Distributed Systems.

[36]  F. Schreiber,et al.  Centrality Analysis Methods for Biological Networks and Their Application to Gene Regulatory Networks , 2008, Gene regulation and systems biology.

[37]  Jun Ren,et al.  Discovering essential proteins based on PPI network and protein complex , 2015, Int. J. Data Min. Bioinform..

[38]  Alex Bavelas,et al.  Communication Patterns in Task‐Oriented Groups , 1950 .

[39]  Britta Papendieck,et al.  On maximal entries in the principal eigenvector of graphs , 2000 .

[40]  Andre H Crepaldi,et al.  Daratumumab plus Bortezomib, Melphalan, and Prednisone for Untreated Myeloma , 2017, The New England journal of medicine.

[41]  Shao-Wu Zhang,et al.  A novel algorithm for finding optimal driver nodes to target control complex networks and its applications for drug targets identification , 2018, BMC Genomics.

[42]  Amer E. Mouawad,et al.  An exact algorithm for connected red-blue dominating set , 2010, J. Discrete Algorithms.

[43]  F. Harary,et al.  Eccentricity and centrality in networks , 1995 .

[44]  Thomas Wennekers,et al.  From Structure to Activity: Using Centrality Measures to Predict Neuronal Activity , 2016, Int. J. Neural Syst..

[45]  Vince Grolmusz,et al.  When the Web meets the cell: using personalized PageRank for analyzing protein interaction networks , 2011, Bioinform..

[46]  M. Newman Mathematics of networks , 2018, Oxford Scholarship Online.

[47]  R. Shields,et al.  Structural controliability of multi-input linear systems , 1975, 1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes.

[48]  Kurt C. Foster,et al.  A Faster Katz Status Score Algorithm , 2001, Comput. Math. Organ. Theory.

[49]  G. Golub,et al.  Eigenvalue computation in the 20th century , 2000 .

[50]  M. Kersten,et al.  Phase II study of carfilzomib, thalidomide, and low-dose dexamethasone as induction and consolidation in newly diagnosed, transplant eligible patients with multiple myeloma; the Carthadex trial , 2019, Haematologica.

[51]  Albert-László Barabási,et al.  Target control of complex networks , 2014, Nature Communications.

[52]  David S. Wishart,et al.  DrugBank 5.0: a major update to the DrugBank database for 2018 , 2017, Nucleic Acids Res..

[53]  Yoshiko Wakabayashi,et al.  The k-hop connected dominating set problem: approximation and hardness , 2017, J. Comb. Optim..

[54]  Ion Petre,et al.  NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability , 2018, BMC Bioinformatics.

[55]  V. Latora,et al.  Harmony in the Small-World , 2000, cond-mat/0008357.

[56]  Diep N. Nguyen,et al.  Solving the k-dominating set problem on very large-scale networks , 2020, Computational Social Networks.

[57]  Yannick Rochat,et al.  Closeness Centrality Extended to Unconnected Graphs: the Harmonic Centrality Index , 2009 .

[58]  Mohammad Reza Meybodi,et al.  Minimum positive influence dominating set and its application in influence maximization: a learning automata approach , 2018, Applied Intelligence.

[59]  Britta Ruhnau,et al.  Eigenvector-centrality - a node-centrality? , 2000, Soc. Networks.

[60]  P. Sonneveld,et al.  Bortezomib, thalidomide, and dexamethasone with or without daratumumab for transplantation-eligible patients with newly diagnosed multiple myeloma (CASSIOPEIA): health-related quality of life outcomes of a randomised, open-label, phase 3 trial. , 2020, The Lancet. Haematology.

[61]  H. Leavitt Some effects of certain communication patterns on group performance. , 1951, Journal of abnormal psychology.

[62]  L. Freeman Centrality in social networks conceptual clarification , 1978 .

[63]  Mason A. Porter,et al.  Dynamic network centrality summarizes learning in the human brain , 2012, J. Complex Networks.

[64]  Weiping Chen,et al.  A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks , 2016, Briefings Bioinform..

[65]  P. Bonacich Power and Centrality: A Family of Measures , 1987, American Journal of Sociology.

[66]  Aric Hagberg,et al.  Exploring Network Structure, Dynamics, and Function using NetworkX , 2008, Proceedings of the Python in Science Conference.

[67]  Matteo Pontecorvi,et al.  Betweenness Centrality - Incremental and Faster , 2013, MFCS.

[68]  S. Mousses,et al.  Identification of molecular vulnerabilities in human multiple myeloma cells by RNA interference lethality screening of the druggable genome. , 2012, Cancer research.

[69]  Chavdar Dangalchev,et al.  Residual Closeness and Generalized Closeness , 2011, Int. J. Found. Comput. Sci..

[70]  Philip Kollmannsberger,et al.  Biological network growth in complex environments: A computational framework , 2020, bioRxiv.

[71]  Charles Auffray,et al.  Systems Medicine: The Future of Medical Genomics, Healthcare, and Wellness. , 2016, Methods in molecular biology.

[72]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[73]  Matthew W. Hahn,et al.  Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. , 2005, Molecular biology and evolution.

[74]  A. McKenna,et al.  Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy. , 2014, Cancer cell.

[75]  Ashish Goel,et al.  Fast Incremental and Personalized PageRank , 2010, Proc. VLDB Endow..

[76]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[77]  Tatsuya Akutsu,et al.  Analysis of critical and redundant nodes in controlling directed and undirected complex networks using dominating sets , 2014, J. Complex Networks.

[78]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[79]  Noga Alon,et al.  Transversal numbers of uniform hypergraphs , 1990, Graphs Comb..

[80]  Christian F. A. Negre,et al.  Eigenvector centrality for characterization of protein allosteric pathways , 2017, Proceedings of the National Academy of Sciences.

[81]  M. Prokopenko,et al.  Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks , 2013, PloS one.

[82]  M. A. Beauchamp AN IMPROVED INDEX OF CENTRALITY. , 1965, Behavioral science.

[83]  Amy Nicole Langville,et al.  A Survey of Eigenvector Methods for Web Information Retrieval , 2005, SIAM Rev..

[84]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[85]  Mark Gerstein,et al.  The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics , 2007, PLoS Comput. Biol..

[86]  N. Lin Foundations of social research , 1976 .

[87]  Krishna Kanhaiya,et al.  Identifying efficient controls of complex interaction networks using genetic algorithms , 2020, ArXiv.

[88]  Ion Petre,et al.  Structural Target Controllability of Linear Networks , 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[89]  Yan Shi,et al.  On positive influence dominating sets in social networks , 2011, Theor. Comput. Sci..

[90]  Leo Katz,et al.  A new status index derived from sociometric analysis , 1953 .

[91]  Gert Sabidussi,et al.  The centrality index of a graph , 1966 .