Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune
evasion and resistance to therapy1. Here, using paired whole-exome and RNA sequencing
data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung
cancer tumours from 347 out of the first 421 patients prospectively recruited into
the TRACERx study2,3. Analyses of 947 tumour regions, representing both primary and
metastatic disease, alongside 96 tumour-adjacent normal tissue samples implicate the
transcriptome as a major source of phenotypic variation. Gene expression levels and
ITH relate to patterns of positive and negative selection during tumour evolution.
We observe frequent copy number-independent allele-specific expression that is linked
to epigenomic dysfunction. Allele-specific expression can also result in genomic-transcriptomic
parallel evolution, which converges on cancer gene disruption. We extract signatures
of RNA single-base substitutions and link their aetiology to the activity of the RNA-editing
enzymes ADAR and APOBEC3A, thereby revealing otherwise undetected ongoing APOBEC activity
in tumours. Characterizing the transcriptomes of primary-metastatic tumour pairs,
we combine multiple machine-learning approaches that leverage genomic and transcriptomic
variables to link metastasis-seeding potential to the evolutionary context of mutations
and increased proliferation within primary tumour regions. These results highlight
the interplay between the genome and transcriptome in influencing ITH, lung cancer
evolution and metastasis.
