Brain Connectivity & Machine Learning

Multisite tumor sampling enhances the detection of intratumor heterogeneity at all different temporal stages of tumor evolution

A. Erramuzpe, JM Cortes and JI Lopez. Multisite tumor sampling enhances the detection of intratumor heterogeneity at all different temporal stages of tumor evolution. Virchows Arch 472:187-194, 2018 [pdf]
Abstract
Intratumor heterogeneity (ITH) is an inherent process of tumor development that has received much attention in previous years, as it has become a major obstacle for the success of targeted therapies. ITH is also temporally unpredictable across tumor evolution, which makes its precise characterization even more problematic since detection success depends on the precise temporal snapshot at which ITH is analyzed. New and more efficient strategies for tumor sampling are needed to overcome these difficulties which currently rely entirely on the pathologist’s interpretation. Recently, we showed that a new strategy, the multisite tumor sampling, works better than the routine sampling protocol for the ITH detection when the tumor time evolution was not taken into consideration. Here, we extend this work and compare the ITH detections of multisite tumor sampling and routine sampling protocols across tumor time evolution, and in particular, we provide in silico analyses of both strategies at early and late temporal stages for four different models of tumor evolution (linear, branched, neutral, and punctuated). Our results indicate that multisite tumor sampling outperforms routine protocols in detecting ITH at all different temporal stages of tumor evolution. We conclude that multisite tumor sampling is more advantageous than routine protocols in detecting intratumor heterogeneity.

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