Research Themes
Delivering innovation in early
detection science.
Our ambition is to deliver a step change in early detection research across areas of unmet or greatest need in the community. We want to make a real impact to the lives of individuals and so focus our research on delivering world-leading basic, translational and clinical research across three key research themes and several disease sites.
Novel Technology and Tissue Models
- Developing and validating new technologies and methodologies for detecting cancer at the earliest stages with a view to clinical implementation for the benefit of patients.
- To develop novel ex vivo models that define the micro- environmental and genetic instability mechanisms driving early tumourigenesis in lung, breast and endometrial cancers.
Explore the projects and pilots funded through ACED through the links below.
Ex-Vivo Models in Cancer
Developing an Ex Vivo Models in Breast and Lung Cancers
NanoOmics
Title: "NanoOmics: Nanoparticle-enabled multi-omic blood biomarker discovery in early stage Non-Small Cell Lung Cancer", co-led by Dr Marilena Hadjidemetriou.
Limit PCa
Title: "Luminal Index MRI Identification of Treatment critical Prostate Cancer (LIMIT PCa)", with Manchester collaboration
Precision Risk & Population Health
- Building on the historic strengths of Manchester in this area, projects focus on understanding and calculating individual risk allowing targeting screening and diagnosis.
- Projects also aim to build engagement with the community and improve participation in research.
Explore the projects and pilots funded through ACED through the links below.
Developing a GM Cancer Plan Biomarker TestBed
Title: "Developing a GM Cancer Plan Biomarker TestBed for Impacting on NHS Pathways: A Breast Cancer Stratification Exemplar", Led by Dr Sacha Howell
The Riskman-TARGET Study
Title: "Tiered integrated diagnostics for the early detection of aggressive Prostate Cancer: The Riskman-TARGET study to develop a novel screening approach for prostate cancer.", co-led by Prof. Ken Muir and Dr Artitaya (Li) Lophatananon.
Risk factors for postpartum breast cancer: developing a model for early detection
Title: "Risk factors for postpartum breast cancer: developing a model for early detection", co-led by Prof. Gareth Evans
Stratifying Risk for Early Detection in Hereditary Breast and Ovarian Cancer
Title: "Stratifying Risk for Early Detection in Hereditary Breast and Ovarian Cancer", co-led by Prof. Gareth Evans
Multiparametric Investigation in Lung Nodules
Title: "Multiparametric Investigation and Stratification of Indeterminate Lung Nodules MISIL1", co-led by Dr Phil Crosbie
REPRESENT: A Community Engagement Roadmap
Title: "REPRESENT: A Community Engagement Roadmap to Improve Participant Representation in Cancer Research Early Detection", co-led by Dr Bella Starling
Molecular and Tumour Biology
- Earlier detection of cancer relies on understanding the earliest changes in molecular and tumour biology and the biomarkers available in the blood and other tissue samples. This theme also aims to identify why some tumours will develop into more or less aggressive variants by studying hereditary cancers to understand the genetic drivers behind them.
Explore the projects and pilots funded through ACED through the links below.
Interrogating Inflammation and Immunology Markers in EDx: A Lung Cancer Biomarker
Title: "Interrogating Inflammation and Immunology Markers in EDx: A Lung Cancer Biomarker", led by Dr Phil Crosbie
Targeting obesity related microenvironment factors
Title: "Targeting obesity related microenvironment factors for biomarkers avenues of early female reproductive cancer detection.", co-led by Prof. Emma Crosbie
Detection of Early Cancer with Deep Histopathological Analysis
Title: "Detection of Early Cancer with Deep Histopathological Analysis", co-led by Prof. Richard Marais
ELECTRIC
Title: "ELECTRIC: Early Detection of Hereditary Renal Cancer (RCC)", co-led by Dr Emma Woodward
Using HDGC to build a toolkit to distinguish indolent from consequential early cancer lesions
Title: "Using HDGC to build a toolkit to distinguish indolent from consequential early cancer lesions", co-led by Prof. David Wedge