Background and aims
Early detection of oesophageal cancer is the most effective strategy to improve its
outcome. The thesis explores the metabolic characteristics of oesophageal tumours as
compared to normal tissue from same patients as well as that from healthy individuals.
The aim is to characterise the basic metabolic profile of oesophageal cancer, detect
possible evidence of field cancerization and to characterise effect of chemotherapy on
oesophageal cancer tissue. The clinical benefit is to develop a non-invasive early test to
be translated to the bed side/laboratory practice for screening, diagnosis and prediction of
response to chemotherapy for patients with oesophageal tumours.
Methods
Using 1H Magic Angle Spinning – Nuclear Magnetic Resonance (MAS-NMR)
spectroscopy of intact tissue, we generated metabolic profiles of tumour tissue, proximal
histologically normal mucosa from cancer patients (PHINOM) and mucosa from a
control group. Using multivariate regression and receiver-operator characteristic analysis
we were able to identify a panel of metabolites discriminating malignant and
histologically-normal tissues from cancer patients from that of controls.
Results
While 26% and 12% of the spectral profile regions were uniquely discriminating tumour
or control tissue respectively, 5% of the profile exhibited a significant progressive change
in signal intensity from controls to PHINOM to tumour. Regions identified were assigned
to phosphocholine, glutamate, myo-inositol, adenosine-containing compounds, uridine4
containing compounds and inosine. In particular, the phosphocholine to glutamate
metabolite ratio in histologically-normal tissue signified the presence of oesophageal
cancer (n=123, AUC 0.84, p<0.001). Metabolites that were found to be significantly
altered in correlation to response to chemotherapy are lysine, glutathione, creatine,
taurine, uracil and tyrosine
Conclusion
The results of the study enable better understanding of the metabolic perturbations in
oesophageal and cancer. The findings support the hypothesis that field effects are present
in oesophageal cancer, even in the absence of Barrett’s oesophagus. This indicates that
metabolic profiling of tissue can potentially play a role in the surveillance of cancer
especially in high risk groups. It also shows the potential of using this methodology to
study the prediction of response to chemotherapy. This helps aiding the clinical decision
making process and the implementation of personalized treatment protocols for different
patients according to their disease extent and potential for response to chemotherapeutics.