Obesity, Metabolic Health and Prostate Cancer version 1.0
Research type
Research Study
Full title
Obesity, metabolic health and prostate cancer; leveraging radiogenomics data to predict outcomes
IRAS ID
276857
Contact name
Emma H. Allott
Contact email
Sponsor organisation
Queen's University Belfast
Duration of Study in the UK
0 years, 11 months, 31 days
Research summary
Obesity is associated with increased risk of aggressive prostate cancer and higher prostate cancer-specific mortality, however the mechanisms responsible for this link are incompletely understood. Periprostatic adipose tissue (PPAT), a type of visceral fat that surrounds the prostate is proposed to contribute to prostate cancer etiology given its close proximity. Previous studies have demonstrated that elevated PPAT area is associated with higher tumour grade but the association of PPAT with long-term prostate cancer-specific outcomes has not been studied.
This retrospective study will investigate the role of abdominal and periprostatic obesity, and metabolic health in prostate cancer outcomes in men with prostate cancer, treated with radiotherapy at Northern Ireland Cancer Centre between 2005 and 2009. Standard image analysis will be used to quantify subcutaneous and visceral (both abdominal and periprostatic) adipose tissue, waist circumference, and skeletal muscle area and attenuation (muscle density) from radiation planning CT scans. An advanced image analysis method called radiomics will be applied to the PPAT to extract quantitative and qualitative features which may provide additional information on the composition and characteristics of this fat type. We will examine the association of these measures of obesity with clinical tumour characteristics and prostate cancer-specific outcomes such as recurrence-free and metastasis-free survival, and all-cause mortality, overall and stratified by androgen deprivation therapy receipt. Lastly, we will examine the associations between PPAT characteristics (quantity and radiomics features) with tumour gene expression data. Furthermore, bioinformatics analysis of tumour biopsy gene expression will aim to identify novel pathways linking periprostatic obesity to poor prostate cancer outcomes. In future, this could enable identification of individuals with a periprostatic obesity subtype at heightened risk of disease progression using routine CT scans. This could identify patients who may benefit from additional treatment or inform secondary prevention efforts such as dietary or lifestyle interventions.REC name
West Midlands - South Birmingham Research Ethics Committee
REC reference
20/WM/0060
Date of REC Opinion
17 Feb 2020
REC opinion
Favourable Opinion