Genomic-transcriptomic evolution in lung cancer and metastasis.
Creators: name: Martínez-Ruiz, Carlos
name: Black, James RM
name: Puttick, Clare
name: Hill, Mark S
name: Demeulemeester, Jonas
name: Cadieux, Elizabeth Larose
name: Thol, Kerstin
name: Jones, Thomas P
name: Veeriah, Selvaraju
name: Naceur-Lombardelli, Cristina
name: Toncheva, Antonia
name: Prymas, Paulina
name: Rowan, Andrew
name: Ward, Sophia
name: Cubitt, Laura
name: Athanasopoulou, Foteini
name: Pich, Oriol
name: Karasaki, Takahiro
name: Moore, David A
name: Salgado, Roberto
name: Colliver, Emma
name: Castignani, Carla
name: Dietzen, Michelle
name: Huebner, Ariana
name: Al Bakir, Maise
name: Tanić, Miljana
name: Watkins, Thomas BK
name: Lim, Emilia L
name: Al-Rashed, Ali M
name: Lang, Danny
name: Clements, James
name: Cook, Daniel E
name: Rosenthal, Rachel
name: Wilson, Gareth A
name: Frankell, Alexander M
name: de Carné Trécesson, Sophie
name: East, Philip
name: Kanu, Nnennaya
name: Litchfield, Kevin
name: Birkbak, Nicolai J
name: Hackshaw, Allan
name: Beck, Stephan
name: Van Loo, Peter
name: Jamal-Hanjani, Mariam
name: Consortium, TRACERx
name: Swanton, Charles
name: McGranahan, Nicholas
Publisher: name: The Francis Crick Institute
Year: 2023
Subjects: subject: Model organisms
subject: Tumour Biology
subject: Signalling &amp; Oncogenes
subject: Gene Expression
subject: Genetics &amp; Genomics
subject: Genome Integrity &amp; Repair
subject: Human Biology &amp; Physiology
subject: Cell Biology
subject: Cell Cycle &amp; Chromosomes
subject: Stem Cells
subject: Chemical Biology &amp; High Throughput
subject: Ecology,Evolution &amp; Ethology
subject: Immunology
subject: FOS: Clinical medicine
subject: Computational &amp; Systems Biology

description: 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.