Evaluating metabolism in human renal cancer using novel surgical models

Within the last two decades, there has been increasing recognition of the pivotal roles of metabolic reprogramming in cancers. Indeed, this evidence has cumulated in the establishment of dysregulated metabolism as a contemporary hallmark of cancer. Metabolomics has been vital to define the metabolic landscape of cancers. This technique allows the simultaneous analyses of hundreds of metabolites present within a system, capturing the downstream interaction between the genome and environment. Renal cell carcinomas (RCC) are increasingly recognised as metabolically-driven types of cancers. This reprogramming of metabolism in RCC has been shown to have a causal role in tumorigenesis, progression, and aggressive disease behaviour. However, the majority of studies in RCC metabolism use conventional metabolomics techniques that provide only a static ‘snapshot’ of cellular metabolism, with limited inferences possible on dysregulated pathway activity. To overcome these limitations, isotopic tracer studies have been recently employed to capture these dynamic processes and enable tracking of nutrient utilisation in cells, thereby permitting the identification of cancer-specific pathway activities, for translation into the clinical setting. These advanced techniques and approaches to study metabolism *in vivo*, in patients have yet to be widely established in RCC and furthermore, there is a lack of clinically relevant models of RCC metabolism locally. The aim of this thesis was to develop novel models of RCC to evaluate metabolism using isotopic tracer studies. In this thesis, I established isotopic tracer studies *in vivo* in surgical patients with RCC. Using a multiomics approach, I characterised the metabolic phenotypes of these tumours and for the first time, evidenced the suppression of gluconeogenesis *in vivo*. Secondly, by developing a novel *in situ* tissue sampling method, I demonstrated the profound impact of ischaemia, a variable commonly associated with conventional tissue sampling methods, on the metabolic characterisation of RCC. Lastly, in order to develop more clinically relevant models of RCC metabolism, I utilised our access to human tissues and explored the development of two patient-derived models, in the form of patient-derived xenografts and through the novel application of an *ex vivo* normothermic perfusion model. Whilst these models demonstrated the potential to recapitulate RCC metabolism, they highlighted the challenges in modelling this aspect of tumour biology. Overall, this work has yielded new insights into the metabolic reprogramming of RCC and the ischaemia-induced perturbations on characterising these tumours. Accurate tumour profiling is fundamental in driving clinically relevant research, and these findings have critical implications for future tissue sampling methods in research. Lastly, by laying the groundwork in this thesis for the development of more clinically translatable models, my goal is to expand the current experimental systems available to ultimately strengthen our research into RCC metabolism.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2023

Author dc:creator

• Yong, Cissy

Advisor dc:contributor.advisor

• Stewart, Grant

• 13carbon metabolic tracing
• cancer metabolism
• isotopic tracer studies
• renal cancer

Licence

• https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/b84dd36c-f7f3-450b-8180-828bc81d725a/download
• https://www.rioxx.net/licenses/all-rights-reserved/

Language dc:language

eng

Author Identifier

0000-0002-8697-1494

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/358179