How chemotherapy affects carcinoma genomes is largely unknown. Here we report whole-exome and deep sequencing of 30 paired oesophageal adenocarcinomas sampled before and after neo-adjuvant chemotherapy. Most, but not all, good responders pass through genetic bottlenecks, a feature associated with higher mutation burden pre-treatment. Some poor responders pass through bottlenecks, but re-grow by the time of surgical resection, suggesting a missed therapeutic opportunity. Cancers often show major changes in driver mutation presence or frequency after treatment, owing to outgrowth persistence or loss of sub-clones, copy number changes, polyclonality and/or spatial genetic heterogeneity. Post-therapy mutation spectrum shifts are also common, particularly C>A and TT>CT changes in good responders or bottleneckers. Post-treatment samples may also acquire mutations in known cancer driver genes (for example, SF3B1, TAF1 and CCND2) that are absent from the paired pre-treatment sample. Neo-adjuvant chemotherapy can rapidly and profoundly affect the oesophageal adenocarcinoma genome. Monitoring molecular changes during treatment may be clinically useful.

Evolutionary theories are themselves subject to evolution. Clonal evolution -the model that describes the initiation and progression of cancer -is entering a period of profound change, brought about largely by technological developments in genome analysis. A flurry of recent publications, using modern mathematical and bioinformatics techniques, have revealed both punctuated and neutral evolution phenomena that are poorly explained by the conventional graduated perspectives. In this review, we propose that a hybrid model, inspired by the evolutionary model of punctuated equilibrium, could better explain these recent observations. We also discuss the conceptual changes and clinical implications of variable evolutionary tempos.

Progressive supranuclear palsy (PSP) is the most common atypical parkinsonian disorder. Abnormal tau inclusions, in selected regions of the brain, are a hallmark of the disease and the H1 haplotype of MAPT, the gene encoding tau, is the major risk factor in PSP. A 3-repeat and 4-repeat tau isoform ratio imbalance has been strongly implicated as a cause of disease. Thus, understanding tau isoform regional expression in disease and pathology-free states is crucial to elucidating mechanisms involved in PSP and other tauopathies. We used a tau-isoform specific fluorescent assay to investigate relative 4R-tau expression in 6 different brain regions in PSP cases and healthy controls. We identified marked difference in 4R-tau relative expression, both across brain regions and between MAPT haplotypes. Highest 4R-tau expression levels were identified in the globus pallidus as compared to pons, cerebellum and frontal cortex. 4R-tau expression levels were related to both the MAPT H1 and H1c haplotypes. Similar regional variation was seen in both PSP cases and controls.

Cancer evolution is driven by the acquisition of somatic mutations that provide cells with a beneficial phenotype in a changing microenvironment. However, mutations that give rise to neoantigens, novel cancer-specific peptides that elicit an immune response, are likely to be disadvantageous. Here we show how the clonal structure and immunogenotype of growing tumours is shaped by negative selection in response to neoantigenic mutations. We construct a mathematical model of neoantigen evolution in a growing tumour, and verify the model using genomic sequencing data. The model predicts that, in the absence of active immune escape mechanisms, tumours either evolve clonal neoantigens (antigen-'hot'), or have no clonally-expanded neoantigens at all (antigen-'cold'), whereas antigen-'warm' tumours (with high frequency subclonal neoantigens) form only following the evolution of immune evasion. Counterintuitively, strong negative selection for neoantigens during tumour formation leads to an increased number of antigen-warm or -hot tumours, as a consequence of selective pressure for immune escape. Further, we show that the clone size distribution under negative selection is effectively-neutral, and moreover, that stronger negative selection paradoxically leads to more neutral-like dynamics. Analysis of antigen clone sizes and immune escape in colorectal cancer exome sequencing data confirms these results.Overall, we provide and verify a mathematical framework to understand the evolutionary dynamics and clonality of neoantigens in human cancers that may inform patientspecific immunotherapy decision-making.

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Cancer is a global health issue that places enormous demands on healthcare systems. Basic research, the development of targeted treatments, and the utility of DNA sequencing in clinical settings, have been significantly improved with the introduction of whole genome sequencing. However the broad applications of this technology come with complications. To date there has been very little standardisation in how data quality is assessed, leading to inconsistencies in analyses and disparate conclusions. Manual checking and complex consensus calling strategies often do not scale to large sample numbers, which leads to procedural bottlenecks. To address this issue, we present a quality control method that integrates point mutations, copy numbers, and other metrics into a single quantitative score. We demonstrate its power on 1,065 whole-genomes from a large-scale pan-cancer cohort, and on multi-region data of two colorectal cancer patients. We highlight how our approach significantly improves the generation of cancer mutation data, providing visualisations for cross-referencing with other analyses. Our approach is fully automated, designed to work downstream of any bioinformatic pipeline, and can automatise tool parameterization paving the way for fast computational assessment of data quality in the era of whole genome sequencing.

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Aneuploidy, defined as the loss and gain of whole and part chromosomes, is a near-ubiquitous feature of cancer genomes, is prognostic, and likely an important determinant of cancer cell biology. In colorectal cancer (CRC), aneuploidy is found in virtually all tumours, including precursor adenomas. However, the temporal evolutionary dynamics that select for aneuploidy remain broadly uncharacterised. Here we perform genomic analysis of 755 samples from a total of 167 patients with colorectal-derived neoplastic lesions that cross-sectionally represent the distinct stages of tumour evolution, and longitudinally track individual tumours through metastasis and treatment. Precancer lesions (adenomas) exhibited low levels of aneuploidy but high intra-tumour heterogeneity, whereas cancers had high aneuploidy but low heterogeneity, indicating that progression is through a genetic bottleneck that suppresses diversity. Individual CRC glands from the same tumour have similar karyotypes, despite prior evidence of ongoing instability at the cell level. Pseudo-stable aneuploid genomes were observed in metastatic lesions sampled from liver and other organs, after chemo- or targeted therapies, and late recurrences detected many years after the diagnosis of a primary tumour. Modelling indicates that these data are consistent with the action of stabilising selection that ‘traps’ cancer cell genomes on a fitness peak defined by the specific pattern of aneuploidy. These data show that the initial progression of CRC requires the traversal of a rugged fitness landscape and subsequent genomic evolution, including metastatic dissemination and therapeutic resistance, is constrained by stabilising selection.