Even though tumour heterogeneity is a widely accepted fact, the possibilities to study this phenomenon and its impact on the treatment of patients are limited. The CASCADE program enables rapid autopsies after death of the patient and therefore allows unique insights into the clonality and emergent resistance mechanisms of the different metastasis. This however creates a set of new bioinformatics challenges to manage the amount of data available for each of the patients and the combined analysis of this data spanned by the different samples.
In our current work we explore variant calling capabilities of different methods in a multi-tumour-matched-normal sample scenario, to allow the reconstruction of evolutionary trajectories of all the tumour sites in the metastatic process. In this analysis we have utilised multi-regional tumour samples from 5 patients with advanced non-small cell lung cancer (n=4 EGFR mutant and 1 EGFR non-mutant) who underwent rapid autopsy through the CASCADE program. An average of 7 samples were analysed per patient by either whole exome or whole genome sequencing. To ensure high confidence variants we have used a consensus method of three variant callers. First an adapted version of the somatic variant calling with Freebayes from the BCBioinformatics pipeline, second our own developed 2-pass variant calling workflow with Strelka2 and lastly the newly developed joint calling capabilities of Mutect2 from GATK.
This work aims to develop improved approaches for sensitively characterising the diverse mutational processes governing treatment resistance in non-small cell lung cancer.