Exploring tumour evolution through single-cell sequencing

Abstract

Tumours are composed of heterogeneous populations of cells which, under the pressure of the host and external treatments, evolve across time and space. Recent advances in next-generation sequencing technologies have allowed the profiling of cells across different modalities. These techniques have revealed insights into tumourigenesis and progression with previously unachievable degrees of resolution, spatiality, and throughput. In this thesis, I perform in-depth profiling of a malignant peripheral nerve sheath tumour with a multiomics approach. These different sequencing methods are then integrated together, enabling characterisation of the tumour through different lenses and mitigating the limitations of individual techniques. A detailed evolutionary history of this tumour is inferred down to the single-cell level, revealing that intra-tumour heterogeneity is predominantly driven by chromosomal instability. Using this extensive CNA heterogeneity, lineage tracing of tumour subclones was performed across space and used to reconstruct intricate growth paths. In addition, I attempt to detect rare single disseminated tumour cells by applying single-cell sequencing techniques across different cancer stages. Multiple normal tissues across different cancer types were collected through research autopsies from patients with metastatic disease. Although a disseminated tumour cell belonging to a micrometastasis was profiled, single-cell sequencing could not be performed at scale due to poor tissue quality and the lack of a specific tumour marker. In the limited disease setting, bone marrow aspirates were collected from patients with clear cell renal cell carcinoma undergoing surgery. Several cells with an abnormal chromosome complement were detected, although they did not appear to be obvious disseminated tumour cells. Overall, these results demonstrate compelling use cases for single-cell sequencing and the power of integrating multi-omics to reconstruct the development of a tumour in a spatio-temporal manner. These detailed evolutionary histories will be critical for understanding the mechanisms of tumourigenesis and developing more effective patient-specific anti-cancer therapies.