IARC 60th Anniversary - 19-21 May 2026
Session : 19/05/26 - Posters
Investigating the repurposing potential of cardiometabolic and hormonal medications for cancer treatment using Mendelian randomisation
MAHMOUD O. 15,16, TILLING K. 1, BATE T. 1,2, MARTIN R. 2,3, YARMOLINSKY J. 1,2,4, HAYCOCK P. 1,2, RUTH K. 5, DONG M. 6, SMITH-BYRNE K. 7, ATKINS J. 7, OGAMBA C. 7, BROWN M. 8, HUNG R. 9, LIU G. 8, XU W. 6, ILES M. 10, LAW M. 11, SEVIIRI M. 11, GUSEV A. 12, LIU Y. 12, CONSORTIUM I. 13, CONSORTIUM P. 14
1 Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; 2 Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; 3 University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, NIHR Bristol Biomedical Research Centre, Bristol, United Kingdom; 4 Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; 5 University of Exeter Medical School, University of Exeter, Exeter, United Kingdom; 6 Dalla Lana School of Public Health, University of Toronto, Ontario, Canada; 7 Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; 8 Princess Margaret Cancer Centre, University of Toronto, Ontario, Canada; 9 Lunenfeld-Tanenbaum Research Institute of Sinai Health, Toronto, United Kingdom; 10 Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom; 11 Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Brisbane, Australia; 12 Dana-Farber Cancer Institute, Boston, United States; 13 International Lung Cancer Consortium (ILCCO), Lyon, France; 14 Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium, London, United States; 15 Institute of Public Health, United Arab Emirates University, Al Ain, United Arab Emirates; 16 Department of Mathematical Sciences, University of Essex, Colchester, United Kingdom
Background: Cardiometabolic diseases (e.g. hypertension, hyperlipidaemia, obesity) and cancers share underlying pathways such as inflammation. Hormonal pathways, particularly oestrogen signalling, also have proposed involvement in cancer progression. Therefore, medications targeting cardiometabolic and hormonal pathways represent repurposing opportunities for cancer treatment.
Objectives: We aimed to investigate the repurposing potential of approved anti-hypertensive, lipid-lowering, weight loss, or hormonal therapies for improving cancer survival using the causal inference method Mendelian randomisation (MR).
Methods: We performed summary-level MR to estimate effects of medications on all-cause or cancer-specific mortality for breast, colorectal, lung, melanoma, ovarian or prostate cancer using data on 203,031 cancer patients from large-scale consortia. Genetic instruments were constructed to proxy effects of medication targets (anti-hypertensive: ACE, ADRB1, SLC12A3 (encodes sodium-chloride cotransporter (NCC)); lipid-lowering: HMGCR, NPC1L1, PCSK9; anti-adiposity: GIPR; hormonal: CYP19A1) or biomarkers targeted by these medications (systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-c), body mass index (BMI)). We assessed the probability of findings with MR evidence (p<0.05) having shared causal variants for effects on proxied exposures and cancer survival (i.e. colocalising). Where there was MR evidence (p<0.05) to support exposure effects on cancer incidence, which may induce biased effects on risk of mortality at the same site, survival MR estimates were adjusted for collider bias. Instruments were validated using current indications. As instruments were constructed using data obtained from populations not restricted to cancer patients, we also assessed instrument validity for application to cancer patient populations.
Results: Per SD decrease in genetically proxied BMI, we observed nominal evidence to support protective effects on risk of mortality for breast (HR [95% CI]=0.90 [0.83-0.98]) and prostate (HR=0.87 [0.79-0.96]) cancer patients. We also observed nominal evidence to support harmful effects of HMGCR inhibition on risk of mortality for breast cancer patients (HR per SD decrease LDL-c=1.81 [1.15-2.83]), and of NCC inhibition (HR per mmHg decrease SBP=1.33 [1.07-1.67]), PCSK9 inhibition (HR per SD decrease LDL-c=1.43 [1.06-1.92]) and LDL-c lowering (HR per SD decrease LDL-c=1.07 [1.01-1.15]) on risk of mortality for prostate cancer patients. There was no evidence to support these observed effects colocalising. Findings were not robust to multiple testing correction (false discovery rate p<0.05). Aside from the observed effect of BMI on breast cancer survival, there was no evidence to support these findings being driven by collider bias. Instruments generally had evidence to support expected effects on positive control outcomes and for application to cancer patient populations.
Conclusions/Implications: We observed some evidence to support a potentially protective effect of BMI lowering for prostate cancer patients, but also potentially harmful effects of HMGCR inhibition (statins) for breast cancer patients and NCC inhibition (sodium thiazides), PCSK9 inhibition and LDL-c lowering for prostate cancer patients. These null effects across the majority of analyses and possible adverse effects of inhibition of select drug targets contrast with prior evidence from observational studies. However, as the prostate cancer survival genome-wide association study was not adjusted for histological stage or grade, findings for this outcome may be biased and so should be interpreted with strong caution.