Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.725327
Title: Personalised medicine in rectal cancer : understanding and predicting response to neoadjuvant chemoradiotherapy
Author: Alderdice, Matthew
ISNI:       0000 0004 6423 2257
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2017
Availability of Full Text:
Full text unavailable from EThOS. Thesis embargoed until 01 May 2019
Abstract:
Around 12-15% of patients with locally advanced rectal cancer (LARC) undergo a pathologically complete response (Tumour Regression Grade 4 - TRG4) to neoadjuvant chemoradiotherapy; the remainder exhibit a spectrum of tumour regression (TRG1-3). Understanding therapy-related genomic alterations may help us better predict response, progression-free and overall survival, and also identify both novel and repurposed treatment strategies based on the underlying biology of the disease. The Northern Ireland Biobank provided 48 formalin fixed paraffin embedded (FFPE) rectal cancer biopsies and matched resections following neoadjuvant therapy (discovery cohort). These were analysed using high-throughput gene expression microarray, DNA mutational profiling and microsatellite instability profiling. Differential gene expression analysis (analysis of variance) was performed contrasting tumour regression grades in both biopsies and resections to identify predictive and therapy related features. Real time PCR was utilised for microarray validation while immunohistochemistry (IHC) was employed to measure CD56+ cell populations in an independent (validation) cohort (n=150). A NK cell-like gene expression signature was observed following long course chemoradiotherapy in a tumour regression-dependent manner. CD56+ NK cel, populations were measured by IHC and found to be significantly higher in TRG3 patients. Furthermore, it was observed that patients positive for CD56 ceils after therapy had a better overall survival (HR=0.282, 95%C,=0.109-0.729, x2=7.854, p=.OO5). In silico drug selection using QUADrATiC analysis identified clinically relevant therapeutic FDA-approved compounds based upon the NK cell-like signature. We demonstrated that identifying an independently validated predictive signature from biopsies for LARC patients treated with LCPCRT was not possible. However, we identified a novel post-therapeutic NK-like transcription signature in patients responding to neoadjuvant chemoradiotherapy. Furthermore, CD56 positive patients had better overall survival. Therefore, harnessing an NK-like response after therapy may improve outcomes for locally advanced rectal cancer patients.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.725327  DOI: Not available
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