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Breast cancer continues being the most commonly diagnosed cancer and the most leading cause of cancer death among females in over 100 countries. The common diagnosis methods of breast cancer include mammography/digital mammography, magnetic resonance imaging (MRI), molecular breast imaging (MBI) and breast biopsy.


Our study uses multivariate analysis and AI-based approaches to facilitate early diagnosis of breast cancer and capsular contracture focusing on the underlying relationship between the metabolite changes and the clinical characteristics of the breast cancer patients with/without capsular contracture.

The study therefore, is the first stage in the development of a low-cost and high throughput biomarker assay (or panel of biomarker profiles) which may help to detect changes linked to early stage breast cancer. Ultimately, these biomarkers may represent as an adjunct tool to the current mammogram diagnostic test, which give rapid assessment of breast cancer and capsular contracture status and further may facilitate the personalized treatment plan for the patients. 


Research Context

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Created using BioRender.com and clipart-library.com


  •  To identify the biomarkers for early detection of breast cancer (BC), biofilm formation and capsular contracture (CC) using minimally invasive samples through OMICs & Artificial intelligence (AI)-based approaches.

  • To investigate the underlying relationships between the biomarkers and inflammatory response that cause the rejection of breast implants following BC surgery.

  • To develop a low-cost and high throughput biomarker assay (or panel of biomarker profiles), detecting disease status, stage and type in the diagnosis and treatment of BC.


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Team engagement meeting for BECA with Prof. Mandana O Pennick (Consultant Oncoplastic Breast Surgeon Ysbyty Glan Clwyd) cum co-supervisor for the project, radiology consultant, breast implant consultant and research nurses at Betsi Cadwaladr University Health Board (BCUHB), Glan Clwyd Hospital, Rhyl on 14th June 2022.


Miss Aimi Zainurin

Doctoral Student

Aimi graduated with Biochemical-Biotechnology Engineering (Hons) and Masters of Science in Biotechnology Engineering in 2017 and 2019 respectively from International Islamic University Malaysia (IIUM), studied metabolites and the biological activities of natural products. Currently, she is pursuing her PhD at Aberystwyth University, investigating the novel biomarkers for early detection of breast cancer (BC) & capsular contracture (CC) employing OMICs & artificial intelligence (AI)-based approaches. 

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