Classification of breast cancer for personalised therapy
Research type
Research Study
Full title
Prognostic and molecular classification of breast cancer for personalised therapy
IRAS ID
294918
Contact name
Emad Rakha
Contact email
Sponsor organisation
University of Nottingham
Clinicaltrials.gov Identifier
NA, NA
Duration of Study in the UK
5 years, 0 months, 0 days
Research summary
Over 56,000 women are diagnosed with breast cancer in the UK each year. About a third of patients develop an aggressive form of breast cancer and can die earlier. Some forms of breast cancer do not respond well to drugs and in some patients they only treatment given work for a while.
The Breast Pathology Research Group at the University of Nottingham has a long-standing national and international track record in breast cancer
The aim of this study is to extend our research activity into determining the key mechanisms, roles and drivers controlling breast cancer behaviour and prognosis in an attempt to refine classification of breast diseases and to address gaps in current management strategies.
We aim to build upon our current study cohort by using an additional 6,000 cases from Sherwood Forest Hospitals NHS Trust. This will allow subgroup analysis and to facilitate training and validation of digital pathology and postgraduate student-related research. This will provide more reliable results for breast cancer clinical and research communities.
We will use tissue and associated clinical and outcome data from patients presented with breast cancer and its precursor lesions at the Sherwood Forest Hospitals NHS Trust between 1st January 2000 - 31st December 2015. We will only use cases where there is available tissue material surplus to diagnostic pathology needs.
Our study will:1. Refine the criteria of breast cancer diagnosis and grading in the era of digital pathology.
2. Use computational pathology and the power of machine learning and artificial intelligence to evaluate various morphological features in breast cancer
3. Interrogate publicly available molecular datasets to utilise the power of gene expression microarrays and next generation sequencing which provide data on tens of thousands of genes. We will decipher these databases to identify novel targets for further investigation and validation using tissue microarray technology and different analytical techniques.REC name
North East - Tyne & Wear South Research Ethics Committee
REC reference
21/NE/0104
Date of REC Opinion
27 May 2021
REC opinion
Favourable Opinion