Biswas, Dhruva;
(2021)
Molecular Portraits of Cancer Evolution and Ecology.
Doctoral thesis (Ph.D), UCL (University College London).
Preview |
Text
Biswas_10132436_Thesis.pdf Download (18MB) | Preview |
Abstract
Research on the molecular lesions that drive cancers holds the translational promise of unmasking distinct disease subtypes in otherwise pathologically identical patients. Yet clinical adoption is hindered by the reproducibility crisis for cancer biomarkers. In this thesis, a novel metric uncovered transcriptional diversity within individual non-small cell lung cancers, driven by chromosomal instability. Existing prognostic biomarkers were confounded by tumour sampling bias, arising from this diversity, in ~50% of patients assessed. An atlas of consistently expressed genes was derived to address this diagnostic challenge, yielding a clonal biomarker robust to sampling bias. This diagnostic based on cancer evolutionary principles maintained prognostic value in a metaanalysis of >900 patients, and over known risk factors in stage I disease, motivating further development as a clinical assay. Next, in situ RNA profiles of immune, fibroblast and endothelial cell subsets were generated from cancerous and adjacent non-malignant lung tissue. The phenotypic adaptation of stromal cells in the tumour microenvironment undermined the performance of existing molecular signatures for cell-type enumeration. Transcriptome-wide analysis delineated ~10% of genes displaying cell-type-specific expression, paving the way for high-fidelity signatures for the accurate digital dissection of tumour ecology. Lastly, the impact of branching, Darwinian evolution on the detection of epistatic interactions was evaluated in a pan-cancer analysis. The clonal status of driver genes was associated with the proportion of significant epistatic findings in 44-78% of the cancer-types assessed. Integrating the clonal architecture of tumours in future analyses could help decipher evolutionary dependencies. This work provides pragmatic solutions for refining molecular portraits of cancer in the light of their evolutionary and ecological features, moving the needle for precision cancer diagnostics.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Molecular Portraits of Cancer Evolution and Ecology |
| Event: | UCL (University College London) |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2021. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10132436 |
Archive Staff Only
 |
View Item |
