COMP-01. MODELING THE EVOLUTION OF PLOIDY IN A RESOURCE RESTRICTED ENVIRONMENT. (11th November 2019)

• Record Type: Journal Article
• Authors: Andor, Noemi; Barnholtz-Sloan, Jill; Ji, Hanlee
• Is Part Of: Neuro-oncology. Volume 21(2019)Supplement 6
• Page Start: vi61
• Page End: vi61
• Publication Date: 2019-11-11
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noz175.244
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Progression of lower-grade gliomas (LGG) to glioblastoma (GBM) is accompanied by a phenotypic switch to an invasive cell phenotype. Converging evidence from colorectal-, breast-, and lung-cancers, suggests a strong enrichment of high ploidy cells among metastatic lesions as compared to the primary. Even in normal development: trophoblast giant cells are responsible for invading the placenta during embryogenesis and these cells often have tens of copies of the genome. We formulate a mechanistic Grow-or-go model that postulates higher energy demands of high-ploidy cells as driver of invasive behavior. The unit we are modeling is a cell, that comes with a certain ploidy, proliferation-, and death-rate. Variations in ploidy emerge as a result of chromosome missegregations. For each cell we calculate the probability of cell-division as a function of energy availability in the neighborhood vs. ploidy-dependent energy demand of the cell. Underlying this comparison is the dual role of integrin signaling: integrin-mediated signals allow cells to progress from G1 to S-phase. At the same time integrins mediate cell migration. The model was implemented as a cellular automaton and 2, 500 simulations were ran at variable energies and missegregation rates. In low-energy environments high-ploidy clones were enriched at the leading edge of the tumor. This was not the case in high-energy environments. We applied the model to analyze previously published exome sequencing data from 14 multi-spatial and longitudinal LGG biopsies. Using the size and ploidy of co-existing clones as summary statistics for Approximate Bayesian Computation, we infer relative chromosome missegregation rates in primary LGG. A higher missegregation rate was predictive of faster progression of LGG to GBM (multivariate Cox: HR = 7.96, P = 0.041). Future validation experiments will evaluate the potential of the model to explain differences in the prognostic power of integrin signaling and cell cycle progression between males and females.