International Alliance for Early Detection funded projects
The International Alliance for Cancer Early Detection (ACED) funds research to drive innovation and change in how and when cancer is detected. The partnership was originally founded by Cancer Research UK, The University of Manchester, University College London, the Knight Cancer Institute at OHSU, The University of Cambridge and the Canary Center at Stanford University.
ACED continues to grow and bring onboard new partners, supporting new and pioneering ideas, expanding multidisciplinary skills and driving forward exceptional science with a strong focus on innovation.
Explore some selected examples from the ACED portfolio.
ACED Programme Awards
An ACED Programme Award provides long-term support for broad, multidisciplinary research where the aim is to answer an interrelated set of questions within early detection of cancer fields.
Harnessing the immune system for cancer early detection
This programme aims to study which immune cells are responsible for cancer surveillance, the markers of whether they have seen early (or pre-) cancer, and if they could have been detected years before clinical diagnosis. The programme includes an ambitious array of analytic modalities brought together by cutting edge machine learning.
Project leads: Jamie Blundell, Robert Bristow, Evan Lind, Parag Mallick and Benny Chain
Collaborating institutions: University of Cambridge, University of Manchester, OHSU, Stanford University and University College London
Early markers for ovarian cancer detection
The team is identifying the early changes that occur in the fallopian tubes preceding ovarian cancer to establish strategies for identification of patients at high risk of developing ovarian cancer and for prevention of disease progression.
Project leads: Filipe Correia Martins, Christine Schmidt, Sharon Pitteri, Michelle Gomes and Marc Tischkowitz
Collaborating institutions: University College London, University of Manchester, Stanford University, OHSU and University of Cambridge
ACED Project Awards
The aim of this award is to fund exceptional science that builds on previously established research with supporting data and a strong focus on innovation.
Assessing cancer risk using electronic health records data
The project aims to improve how we can predict the risk of cancer in patients who visit their doctor with new symptoms.
Using data from medical records, this will help doctors decide when to refer patients for further tests to check for cancer.
Project leads: Yoryos Lyratzopoulos, Antonis Antoniou and Ruth Etzioni
Collaborating institutions: University College London, University of Cambridge and OHSU
Early prostate cancer detection
The team is using deep learning methods to connect prostate cancer imaging with past tissue evidence, enabling personalised targets to be forecasted without requiring a biopsy.
Project leads: Yipeng Hu and Geoffrey Sonn
Collaborating institutions: University College London and Canary Center at Stanford
Deep histopathological analysis
This study aims to create machine learning tools that will analyse histopathological information with genetic signatures known to be correlated with poor outcomes.
This will help to determine if the lesions have the potential to become aggressive cancer.
Project leads: Rajan Kulkarni and Richard Marais
Collaborating institutions: OHSU and University of Manchester
Mapping of breast cancer premalignancy
The project aims to build a high-resolution map of cellular and molecular transition along the breast tumour development. Using this map, the team wants to understand the impact of germline mutations on tumour initiation and disease progression.
Project leads: Walid Khaled, Hisham Mohammed
Collaborating institutions: University of Cambridge and OHSU
ACED Pilot Awards
These awards provide seed funding to support new and pioneering research ideas and pilot studies of high scientific risk, with no requirement for extensive preliminary data.
Hereditary kidney cancer
This project aims to identify new methods for early detection of hereditary kidney cancer by studying the molecular information in blood platelets from both hereditary and non-hereditary kidney cancer patients.
Project leads: Emma Woodward, Alice Fan, Eamon Maher and James Whitworth
Collaborating institutions: University of Manchester, Canary Center at Stanford and University of Cambridge
Prostate cancer progression
This team is developing AI software that analyses MRI images collected in patients on active surveillance over time to track changes in prostate tumours. The aim is to detect cancer progression early and automatically.
Project leads: Dean Barratt and Geoffrey Sonn
Collaborating institutions: University College London and Canary Center at Stanford
NanoOmics: a blood test platform
They are developing a blood analysis platform using nanoparticles to isolate tumour-specific molecules, making it easier to discover new biomarkers for cancer detection.
Project leads: Marilena Hadjidemetriou and Parag Mallick
Collaborating institutions: University of Manchester and Canary Center at Stanford
Measuring immunity in ovarian cancer
The team is studying early immune responses in ovarian cancer to develop a blood test to detect specific immune cells.
Project leads: James Brenton and Alice Fan
Collaborating institutions: University of Cambridge and Canary Center at Stanford
ACED Pathway Award
This award supports early career researchers establishing their independence helping to expand their multidisciplinary skills, providing mentorship with eminent researchers in the field, and to obtain preliminary data for future independent fellowship applications.
Methylation clock
This award is helping to create a new way to predict cancer risk by studying changes in DNA methylation over time and studying how these changes relate to aging and cancer development.
Project leads: Jamie Blundell, Hisham Mohammed and Adriana Fonseca
Collaborating institutions: University of Cambridge and OHSU
Contact us
If you’re interested in hearing more about ACED, have a question about funding opportunities, or would like to discuss partnerships, we’d love to hear from you.