Science: a model and a metaphor in the work of four British composers

Many composers of the 20th century have drawn upon science in their endeavours to create music. The development of technologies has been an additional impetus for composers to interface with scientific and technological paradigms. This thesis explores the extent and scope of the application of scientific metaphors and models in the compositional œuvres of four British-born composers of the later half of the 20th century: Richard Barrett, Chris Dench, James Dillon and Brian Ferneyhough. These composers have been commonly regarded as part of a group called the ‘New Complexity’. Much of the discourse about this group has centred on the dense polyphonic textures and formidable rhythms that feature in their work. This study extends the understanding of the composers from the surface characteristics of their projects to the ideas and conceptualisation that lies behind them, with the aim of clarifying essential differences and similarities among the individual composers. The thesis finds that, although all four composers share an interest in science and a belief in its relevance to their compositional projects, specific differences can be identified in the application of scientific metaphors and models. Moreover, the findings indicate that the composers often couple these scientific references with notions of cognition. The linking of these scientific tropes to cognition not only reveals the significance of science in the composers’ respective projects, but also points us to a deeper understanding of what these composers consider music to mean

Genomic–transcriptomic evolution in lung cancer and metastasis

Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy. 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 study. 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