Background: Connectivity mapping is a novel bioinformatics technique linking gene expression data with expression events induced by medications. It therefore allows medications to be screened to assess carcinogenicity and anti-cancer properties. This connectivity map process has been implemented, using publically available gene expression datasets, to identify prescription medications (used for non-cancer purposes) that may alter risk of breast cancer progression.
Aims: To determine the association between use of the identified medications (from connectivity mapping) and breast-cancer specific mortality.
Methods: A cohort study will be conducted. Breast cancer patients will be identified from cancer registries. Candidate medication use will be determined from prescription records and cancer-specific mortality from ONS mortality records. Cox regression models (with medication use as a time-varying covariate) will be used to calculate hazard ratios (HRs), and 95% confidence intervals (95%CIs), for the association between candidate medication use after diagnosis and cancer-specific mortality after adjustment for potential confounders.
Potential: The study could identify (previously unrecognized) medications which increase the risk of breast cancer progression; current licensing of such medications may need to be reconsidered. This study also has the potential to identify licensed medications that reduce risk of breast cancer progression and warrant further study in clinical trials.
To determine if use of the identified medications after breast cancer diagnosis is associated with increased, or reduced, breast cancer-specific mortality
Chris Cardwell - Chief Investigator - Queen's University Belfast
Chris Cardwell - Corresponding Applicant - Queen's University Belfast
Fabio Liberante - Collaborator - Queen's University Belfast
Gayathri Thillaiyampalam - Collaborator - Queen's University Belfast
Ken Mills - Collaborator - Queen's University Belfast
Liam Murray - Collaborator - Queen's University Belfast
Shu-Dong Zhang - Collaborator - Queen's University Belfast