Functional compensators of epigenetic modifiers as targetable cancer vulnerabilities

Student thesis: Doctoral ThesisDoctor of Philosophy


Due to an increasing number of cancer sequencing screens, our knowledge of genes whose somatic alterations drive cancer initiation and progression (cancer drivers) has vastly expanded over the past 15 years. Sequencing screens have enabled a comprehensive collection of cancer drivers across tissues. This has revealed their characteristic evolutionary properties; lower gene duplicability, early evolutionary origin, ubiquitous RNA and protein expression, numerous miRNA interactions, participation in complexes by encoded proteins and a central, connected, and inter-connected position in the protein-protein interaction network. Once cancer drivers are identified, understanding the effect of their alterations forms the foundation of personalized cancer therapies. Targeting cancer-specific vulnerabilities, such as inhibiting functional compensators of genes whose function is lost in cancer cells, minimises the side effects in non-cancer cells.

Considering the continuous development of scientific knowledge in this area, the first part of this thesis addresses the improvement and expansion of the collection and characterisation of cancer drivers included in the Network of Cancer Genes resource. It comprises an up-to-date collection of 3,347 altered genes driving cancer and 95 genes driving clonal expansion in non-malignant tissues. In addition to confirming their evolutionary properties, we find that cancer drivers are more essential and less robust against damaging germline alterations. We reveal distinctive properties of different driver gene categories; known and predicted cancer drivers, drivers with coding and noncoding alterations, and genes driving cancer and non-cancer clonal expansion.

To place cancer driver properties in a wider context, the second part of this thesis characterises evolutionary properties of functional gene groups in health and disease. We integrate nine evolutionary properties into a single score using a random forest classifier. This divides 25 biological pathways encompassing 10,334 genes into three groups. Genes in high-scoring pathways perform basic cell functions and are enriched in tumour suppressors and core essential genes.
In contrast, genes in low-scoring pathways contribute to organ-specific functions and are enriched in recessive Mendelian disease genes. Intermediate-scoring pathways contribute to metabolism, development, and immune system. The integrated analysis of gene evolutionary properties using a principal component analysis prioritises a subgroup of predicted cancer genes for further validation.

We use a subset of evolutionary gene properties to predict functional compensation between gene pairs. To this aim, we develop a computational prediction method that combines genetic sequence conservation, engagement in the same protein complex and context dependent gene essentiality in cancer cell lines. We show that epigenetic modifiers are enriched in paralog pairs, genes encoding proteins that engage in complexes and context dependent essential genes and are frequently lost in cancer. Consistent with this, they are enriched in predicted functional compensator pairs, making them interesting therapeutic targets. Thus, we focus validation on epigenetic modifiers. Using CRISPR Cas9 mediated gene knockout, we validate synthetic lethality between GATA2 and GATA3, as well as context dependent synthetic lethality between TBL1X and TBL1XR1.

In summary, this thesis explores cancer gene properties, analyses them in the context of broader functional groups and prioritises new cancer genes for validation. It identifies an enrichment of epigenetic modifiers in potential paralog synthetic lethal interactions and validates synthetic lethality between two gene pairs.
Date of Award1 Dec 2022
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorFrancesca Ciccarelli (Supervisor) & Rebecca Oakey (Supervisor)

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