Exploring tumour evolution through single-cell sequencing
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ICR Authors
Authors
Yan, HX
Document Type
Thesis or Dissertation
Date
2023-10-24
Date Accepted
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.
Citation
2023
DOI
Source Title
Publisher
Institute of Cancer Research (University Of London)
ISSN
eISSN
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Research Team
Melanoma & Kidney Cancer