How many samples are needed to infer truly clonal mutations from heterogenous tumours?

Luka Opasic,Da Zhou,David Dingli,Arne Traulsen,Benjamin Werner

doi:10.1186/s12885-019-5597-1

Abstract

BackgroundModern cancer treatment strategies aim to target tumour specific genetic (or epigenetic) alterations. Treatment response improves if these alterations are clonal, i.e. present in all cancer cells within tumours. However, the identification of truly clonal alterations is impaired by the tremendous intra-tumour genetic heterogeneity and unavoidable sampling biases.MethodsHere, we investigate the underlying causes of these spatial sampling biases and how the distribution and sizes of biopsies in sampling protocols can be optimised to minimize such biases.ResultsWe find that in the ideal case, less than a handful of samples can be enough to infer truly clonal mutations. The frequency of the largest sub-clone at diagnosis is the main factor determining the accuracy of truncal mutation estimation in structured tumours. If the first sub-clone is dominating the tumour, higher spatial dispersion of samples and larger sample size can increase the accuracy of the estimation. In such an improved sampling scheme, fewer samples will enable the detection of truly clonal alterations with the same probability.ConclusionsTaking spatial tumour structure into account will decrease the probability to misclassify a sub-clonal mutation as clonal and promises better informed treatment decisions.

Highlights

Modern cancer treatment strategies aim to target tumour specific genetic alterations
We showed how the probability to correctly classify clonal mutations scales with additional samples and how many samples are needed to identify the truncal mutations with a certain level of confidence given the life histories of a tumour [20]
In tumours where specific sub-clonal mutations undergo great expansion, it is highly likely that this expanding mutation and its sub-clonal mutations will be categorised as clonal (Fig. 2a with f = 0.9)

Summary

Introduction

Modern cancer treatment strategies aim to target tumour specific genetic (or epigenetic) alterations. Treatment response improves if these alterations are clonal, i.e. present in all cancer cells within tumours. It is often assumed that a mutation that is present in approximately 50% of the sequencing reads of a single tumour bulk sample is likely clonal (after adjusting for tumour ploidy and tumour purity). This reasoning is problematic, since it requires that the underlying sample is representative of the whole tumour. Targeting such mutations would not be expected to provide a long term therapeutic benefit as we would at best treat only the part of the tumour that contains these sub-clonal mutations

Methods

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Discussion

Conclusion