Findlay, John Mitchell
(2016)
Precision staging and management of Barrett's oesophagus and oesophageal cancer: genomic, imaging and pathological biomarkers.
PhD thesis, University of Nottingham.
Abstract
Barrett’s oesophagus and oesophageal cancer represent two of the most important and challenging oesophageal disease processes globally, combining increasing incidences with high morbidity treatments, often with poor clinical outcomes. A major contributory factor is that disease susceptibility, progression and response to therapy are largely unpredictable, due to inherent biological complexity and variability. At present, just staging groups are used routinely as thresholds for guiding the use of therapies such as ablation, resection, and oncological therapies. However, these represent blunt tools that do not necessarily reflect patients’ experiences, or appropriately select from the range of treatments available. The aim of this thesis was to explore the potential of genomic, imaging, and pathological biomarkers in guiding more tailored and personalised therapy.
The first half of this thesis explores the role of genomic markers. The first results chapter describes the identification of new loci and gene pathways associated with susceptibility to Barrett’s oesophagus, dysplasia and oesophageal adenocarcinoma, by further replication and analysis of a genome-wide association study. In addition, all reported genomic markers of these endpoints were identified and criticised by systematic review, and synthesised by meta-analysis. Validation of these was then attempted, and lessons for markers and future research drawn.
The second results chapter describes a similar appraisal and synthesis of genomic markers of oesophageal cancer prognosis, response to therapy, and stage.
The third describes the first next generation sequencing study performed in oesophageal adenocarcinoma (and indeed any gastrointestinal cancer as far as the author is aware), before and after neoadjuvant chemotherapy. Using whole exome sequencing a new model of genomic tumour response was developed, and the implications for biomarkers explored.
The second half of this thesis follows a large cohort of patients with oesophageal cancer, from nearly 1000 undergoing staging, to more than 300 undergoing neoadjuvant chemotherapy, restaging and resection. In the fourth results chapter, the first application of decision theory to cancer staging identified the potential for routine imaging data to personalise and optimise oesophageal cancer staging.
In the following chapter, positron emission tomography-computed tomography was found to be more sensitive for identifying disease progression during neoadjuvant chemotherapy than computed tomography alone. Two factors were identified that could stratify risk of progression to incurable disease, including that encountered at surgery. These included 18F-FDG avid nodes, with new concepts of metabolic nodal stage and response developed in conjunction with predictive models.
Thereafter, a number of conventional and experimental metrics of metabolic tumour response were compared and refined as predictors of pathological response. Existing metrics of metabolic tumour response were found to be suboptimal, and these new concepts and classifications of metabolic nodal stage and response were found to have independent utility for clinical practice. Again, predictive models were generated.
Finally, the prognostic utilities of these markers were explored. Metabolic tumour response was found to be an imperfect surrogate of pathological response. However, metabolic nodal response demonstrated independent utility in identifying patients at high risk of early recurrence and death, both when used before surgery and afterwards. Indeed, a number of analyses demonstrated the additive utility of considering the primary tumour and nodal metastases as separate entities. Finally, prognostic models were generated, and a simple risk score was generated, using the four independent prognostic markers identified to stratify prognosis.
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