About this trial
This project aims to characterise the tumour cell and tumour microenvironment of colorectal cancer peritoneal metastases, understand molecular changes leading to colorectal peritoneal metastasis, identify potential biomarkers and novel treatment strategies.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Patients ≥ 18 years old who have been diagnosed with colorectal cancer and have colorectal peritoneal metastases,
have had cytoreductive surgery at the Christie
have availability of archival tumour tissue (paired CRC and CRPM)
Disqualifiers
None
Trial population
Colorectal cancer peritoneal metastases
Trial design
Other
Retrospective
Treatments tested in this trial
Retrospective tissue sample analysis
Other interventionArchival formalin-fixed, paraffin-embedded (FFPE) tumour tissue from colorectal cancer peritoneal metastasis and paired primary tumours, where available - taken as standard care
Treatment groups
Trial outcomes
Primary outcomes
Proportion of genetic mutations
Descriptive analysis of the proportion of genetic mutations identified in colorectal cancer and their matched peritoneal metastases: concordance and discordance rates.
Secondary outcomes
Proportion differences of genetic mutations
The descriptive difference in proportion of genetic mutations identified in primary colorectal tumours compared to mutations in colorectal cancer peritoneal metastases. Generate hypotheses about changes that occur during the metastatic process.
Correlations of results
Correlation of results from genetic tests with clinical patient data. Identification of genetic mutations which are associated with differences in survival.
Association with molecular subtypes and categorical variables
Association between molecular subtypes and categorical variables to be measured by Fisher's exact or X2 tests. Associations with continuous variables will be evaluated by Kruskal-Wallis tests or ANOVA. Kaplan-Meier methods will calculate survival outcomes. Univariate and multivariate cox proportional hazard regression models stratified by tumour subtype will identify predictive factors of clinical outcomes. Results with a p-value \<0.05 will be considered statistically different.
Sponsors and contacts
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The Christie NHS Foundation Trust
Lead sponsor
University of Manchester
Collaborator