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esiCancer: Evolutionary In Silico Cancer Simulator
The evolution of cancer is inferred mainly from samples taken at discrete points that represent glimpses of the complete process. In this study, we present esiCancer as a cancer-evolution simulator. It uses a branching process, randomly applying events to a diploid oncogenome, altering probabilities...
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Published in: | Cancer research (Chicago, Ill.) Ill.), 2019-03, Vol.79 (5), p.1010-1013 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The evolution of cancer is inferred mainly from samples taken at discrete points that represent glimpses of the complete process. In this study, we present esiCancer as a cancer-evolution simulator. It uses a branching process, randomly applying events to a diploid oncogenome, altering probabilities of proliferation and death of the affected cells. Multiple events that occur over hundreds of generations may lead to a gradual change in cell fitness and the establishment of a fast-growing population. esiCancer provides a platform to study the impact of several factors on tumor evolution, including dominance, fitness, event rate, and interactions among genes as well as factors affecting the tumor microenvironment. The output of esiCancer can be used to reconstruct clonal composition and Kaplan-Meier-like survival curves of multiple evolutionary stories. esiCancer is an open-source, standalone software to model evolutionary aspects of cancer biology. SIGNIFICANCE: This study provides a customizable and hands-on simulation tool to model the effect of diverse types of genomic alterations on the fate of tumor cells. |
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ISSN: | 0008-5472 1538-7445 |
DOI: | 10.1158/0008-5472.can-17-3924 |