title: Spreaders and sponges define metastasis in lung cancer: a Markov chain Monte Carlo mathematical model.
abstract: The classic view of metastatic cancer progression is that it is a unidirectional process initiated at the primary tumor site, progressing to variably distant metastatic sites in a fairly predictable, although not perfectly understood, fashion. A Markov chain Monte Carlo mathematical approach can determine a pathway diagram that classifies metastatic tumors as "spreaders" or "sponges" and orders the timescales of progression from site to site. In light of recent experimental evidence highlighting the potential significance of self-seeding of primary tumors, we use a Markov chain Monte Carlo (MCMC) approach, based on large autopsy data sets, to quantify the stochastic, systemic, and often multidirectional aspects of cancer progression. We quantify three types of multidirectional mechanisms of progression: (i) self-seeding of the primary tumor, (ii) reseeding of the primary tumor from a metastatic site (primary reseeding), and (iii) reseeding of metastatic tumors (metastasis reseeding). The model shows that the combined characteristics of the primary and the first metastatic site to which it spreads largely determine the future pathways and timescales of systemic disease.
authors: Department of Aerospace & Mechanical Engineering, Viterbi School of Engineering, University of Southern California, Los Angles 90089, USA. newton@usc.edu
authors: Paul K
authors: PK
authors: Newton
authors: Jeremy
authors: J
authors: Mason
authors: Kelly
authors: K
authors: Bethel
authors: Lyudmila
authors: L
authors: Bazhenova
authors: Jorge
authors: J
authors: Nieva
authors: Larry
authors: L
authors: Norton
authors: Peter
authors: P
authors: Kuhn
mesh_terms: D000465:Algorithms; D001344:Autopsy; D018450:Disease Progression; D006801:Humans; D008175:Lung Neoplasms / Q000473:pathology* / Q000503:physiopathology; D008390:Markov Chains; D008495:Medical Oncology / Q000379:methods; D008962:Models, Theoretical; D009010:Monte Carlo Method; D009362:Neoplasm Metastasis; D009369:Neoplasms / Q000378:metabolism / Q000473:pathology