Delineation of Tumor Migration Paths by Using a Bayesian Biogeographic Approach
Delineation of Tumor Migration Paths by Using a Bayesian Biogeographic Approach
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DOI：
10.3390/cancers11121880
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发表时间：
2019-12-01
期刊：
影响因子：
5.2
通讯作者：
Kumar, Sudhir
中科院分区：
文献类型：
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作者：
Chroni, Antonia;Vu, Tracy;Kumar, Sudhir
了解肿瘤进展和转移潜力在癌症生物学中很重要。转移是克隆在次级组织中的迁移和定殖。在这里，我们认为肿瘤之间的克隆迁移事件类似于不同地理区域之间的个体扩散。这种相似性使得贝叶斯神经网络分析适合于推断癌细胞迁移路径。我们评估了贝叶斯神经网络方法（BBM）在推断转移模式中的准确性，并将其与专门开发用于推断肿瘤间克隆迁移模式的基于简约的方法（转移和克隆历史综合分析，MACHINA）的准确性进行了比较。我们使用计算机模拟的数据集，其中模拟了简单到复杂的迁移模式。BBM和MACHINA在可靠地重建从原发肿瘤到转移瘤的简单迁移模式方面是有效的。然而，他们都表现出有限的能力，准确地推断复杂的迁移路径，涉及迁移的克隆从一个转移性肿瘤到另一个和从转移到原发性肿瘤。因此，仍然需要先进的计算方法来生物学上真实地追踪迁移路径，并评估患者癌症进展期间不同类型的接种和再接种事件的相对优势。
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.