Phylogenetic quantification of intra-tumour heterogeneity

TL;DR

This paper introduces MEDICC, a novel phylogenetic method for accurately quantifying intra-tumour heterogeneity from copy number data, addressing previous challenges in reconstructing evolutionary histories in cancer genomics.

Contribution

MEDICC provides a new approach for phylogenetic reconstruction and quantification of intra-tumour heterogeneity that outperforms existing methods, especially in complex copy number variation scenarios.

Findings

MEDICC achieves higher accuracy in phylogenetic reconstruction.

It enables unbiased numerical quantification of intra-tumour heterogeneity.

Applicable to both sequencing and array CGH data.

Abstract

Background: Intra-tumour heterogeneity (ITH) is the result of ongoing evolutionary change within each cancer. The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance and if so would have prognostic and predictive utility. However, methods for objectively quantifying ITH have been missing and are particularly difficult to establish in cancers where predominant copy number variation prevents accurate phylogenetic reconstruction owing to horizontal dependencies caused by long and cascading genomic rearrangements. Results: To address these challenges we present MEDICC, a method for phylogenetic reconstruction and ITH quantification based on a Minimum Event Distance for Intra-tumour Copynumber Comparisons. Using a transducer-based pairwise comparison function we determine optimal phasing of major and minor alleles, as well as evolutionary distances between samples, and are able to reconstruct ancestral genomes. Rigorous simulations and an extensive clinical study show the power of our method, which outperforms state-of-the-art competitors in reconstruction accuracy and additionally allows unbiased numerical quantification of ITH. Conclusions: Accurate quantification and evolutionary inference are essential to understand the functional consequences of ITH. The MEDICC algorithms are independent of the experimental techniques used and are applicable to both next-generation sequencing and array CGH data.