Abstract
Understanding tumor progression and metastatic potential are important in cancer biology. Metastasis is the migration and colonization of clones in secondary tissues. Here, we posit that clone migration events between tumors resemble the dispersal of individuals between distinct geographic regions. This similarity makes Bayesian biogeographic analysis suitable for inferring cancer cell migration paths. We evaluated the accuracy of a Bayesian biogeography method (BBM) in inferring metastatic patterns and compared it with the accuracy of a parsimony-based approach (metastatic and clonal history integrative analysis, MACHINA) that has been specifically developed to infer clone migration patterns among tumors. We used computer-simulated datasets in which simple to complex migration patterns were modeled. BBM and MACHINA were effective in reliably reconstructing simple migration patterns from primary tumors to metastases. However, both of them exhibited a limited ability to accurately infer complex migration paths that involve the migration of clones from one metastatic tumor to another and from metastasis to the primary tumor. Therefore, advanced computational methods are still needed for the biologically realistic tracing of migration paths and to assess the relative preponderance of different types of seeding and reseeding events during cancer progression in patients.
Highlights
Cancer’s uniqueness emerges from its fundamental traits of tumor growth, cell expansion, and dissemination from a tumor of origin to surrounding and distant tissues [1]
We found that the performance of both methods is dictated by the number of tumor sites and the complexity of migration paths
We considered four different tumor clone seeding scenarios based on the numbers of seeding clones (1–3), sources of the seeding clones, and the presence of reseeding of the primary tumors by clone(s) from metastases
Summary
Cancer’s uniqueness emerges from its fundamental traits (hallmarks) of tumor growth, cell expansion, and dissemination from a tumor of origin (primary) to surrounding and distant tissues (metastases) [1]. Cancer cells gain the ability to migrate, invade, and modulate tumor microenvironments. Due to genomic instability [3,4,5,6] and the generation of intratumor genetic heterogeneity, metastatic lesions cause failures of therapeutic approaches to eradicate metastases, subsequently making metastasis the dominant cause of cancer mortality [7,8]. Metastasis involves the migration of clones (i.e., cancer cells with identical genotypes) between primary and metastatic tumor sites, both of which accumulate somatic mutations over a patient’s life [11]. Tumor clone seeding or migration events are generally visualized in the form of migration graphs that show the Cancers 2019, 11, 1880; doi:10.3390/cancers11121880 www.mdpi.com/journal/cancers
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