Strategies to identify novel therapeutic targets for oesophageal adenocarcinoma
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Date
28/11/2014Author
O'Neill, John Robert
Metadata
Abstract
Oesophageal adenocarcinoma (OAC) is a leading cause of cancer death in the UK
and current systemic therapies are ineffective for the majority of patients. The
central aim of this work was to explore strategies to identify novel therapeutic
targets.
Research has failed, thus far, to identify a dominant oncogene in OAC, although the
tumour suppressor p53 is frequently mutated. Inhibiting the mitotic kinase, polo-like
kinase 1 (PLK-1), was proposed as a synthetic lethal strategy. PLK-1 was
demonstrated to be over-expressed in both verified OAC cell lines and human OAC
tissue compared to non-transformed cells and epithelium. Mutation of p53 was
associated with over-expression of PLK-1 in both OAC and ovarian cancer tissue.
Using a carefully validated viability assay, both an established and novel PLK-1
inhibitor were demonstrated to induce a G2/M arrest and reduce OAC cell
proliferation. Relative selectivity was demonstrated for OAC compared to non-transformed
cells. This therapeutic window could be enhanced with the induction of
cancer cell cytotoxicity by pulsed administration of a short half-life inhibitor.
Immunotherapeutics offer potential tumour-selectivity but no OAC-specific proteins
have been defined. A comparative proteomic approach was employed to identify
OAC-specific proteins as potential therapeutic targets. A tissue resource was
established and methods to lyse fresh frozen biopsies optimised. An isobaric
quantitative proteomic workflow was applied to OAC and matched normal biopsies
and quantitative accuracy confirmed for 6 candidate proteins by
immunohistochemistry. Proteome coverage and quantitative dynamic range were
compared between isobaric and label-free systematic sequencing proteomic
strategies applied to further patients’ tissues. The challenges of combining
incomplete datasets were approached with a Bayesian framework to estimate the
probability that a protein was missed during an experiment compared to not being
present in the sample. This method was applied to generate a complete set of protein
identifications and relative tissue expression. To gain insight into the dysregulated cellular processes in human OAC tissue, a
network analysis was applied to the quantitative proteomic data. Enriched functional
clusters were identified suggesting deranged glucose metabolism, potentially due to
the Warburg effect. These findings were duplicated and candidate tumour-specific
proteins identified in a further set of biopsies using the optimised quantitative
proteomic method. The combined quantitative oesophageal proteomic dataset
represents the largest in OAC to date.
This thesis demonstrates a hypothesis-driven, synthetic lethal approach can yield
cancer-selective therapeutic effects. Novel candidate therapeutic targets are also
revealed through the development of quantitative proteomic methods and the
application of network analysis.