Summary

Breast cancer (BC) is the most common cancer in women worldwide, with 2.3 million new cases and 670,000 deaths reported in 2022.

These figures represent 24% of all cancer diagnoses and 15% of cancer-related mortality among women (WHO 2022). Nutritional factors, particularly folate deficiency, have been increasingly recognised as contributors to cancer initiation and development (Pieroth 2018; Linhart 2009).

Folate (and synthetic folic acid) is an essential B vitamin central to one-carbon metabolism, a system of biochemical reactions that transfer single-carbon units required for DNA and RNA synthesis, amino acid interconversion, and cellular methylation pathways (Bailey et al. 2015).

Folate, together with vitamin B12, enables homocysteine remethylation to methionine, which is then converted into S-adenosylmethionine (SAM), the universal methyl donor.

Through SAM-dependent methylation, folate availability influences gene expression, tumour suppressor regulation, and proto-oncogene activity. Folate is also required for the thymidylate synthesis pathway (conversion of dUMP to dTMP), essential for accurate DNA replication and repair.

Low folate status has been linked to increased risks of leukaemia, lymphoma, colorectal, prostate, and breast cancers (Xu et al. 2009; Bailey et al. 2015).

Mechanistically, folate deficiency can lead to uracil misincorporation into DNA in place of thymine, causing DNA strand breaks, chromosomal instability, and abnormal karyotypes—changes that favour malignant transformation (Duthie 2011).

Deficiency also contributes to hypomethylated DNA, potentially leading to inappropriate activation of cancer-promoting genes. However, the folate–cancer relationship is complex: while adequate folate prevents early carcinogenic events, high folic acid intake has been hypothesised to accelerate the growth of existing neoplastic lesions (Mason 2009).

These complexities highlight the need for sophisticated interdisciplinary approaches.

This research programme will integrate artificial intelligence (AI) and machine learning (ML) to investigate the role of folate in breast cancer prevention across three interconnected aims spanning epidemiology, clinical biomarkers, and molecular analysis.

1. Epidemiological study:

Using data from approximately 500,000 UK Biobank participants, the project will model relationships among folate status, genetic factors, and breast cancer risk. AI/ML platforms will be developed to manage and analyse these large-scale datasets, enabling detection of nutrient–gene interactions relevant to breast cancer susceptibility.

2. Clinical study:

A pilot case–control study will recruit 50 breast cancer patients and 50 healthy controls undergoing breast reduction surgery, in collaboration with the Norfolk and Norwich University Hospital and the University of East Anglia. Ethical approval will be sought from the relevant committees.

Blood and breast tissue samples will be collected and transferred to Ulster University. Biomarker analyses will measure red blood cell (RBC) folate, plasma folate, homocysteine, and vitamins B12, B6, and riboflavin—key components of one-carbon metabolism—to compare metabolic profiles between cases and controls.

3. Molecular studies:

Breast tissue samples will undergo histological and molecular profiling, including H&E and γ-H2AX co-staining to assess tissue architecture and DNA damage; LC-MS/MS quantification of global DNA methylation (%5-mC); and RT² Profiler™ PCR array analysis of DNA damage signalling pathways.

Together, these integrated studies will clarify how folate status, one-carbon metabolism, and related molecular pathways influence breast cancer risk, ultimately informing preventive strategies based on optimising folate and B-vitamin nutrition.

This studentship is supported by a highly interdisciplinary supervisory team, combining expertise in preclinical breast cancer biology (Dr Kyle Matchett), nutritional science and folate metabolism (Prof Helene McNulty), advanced AI and machine learning methodologies (Prof Huiru (Jane) Zheng), and clinical input from a Consultant Breast Cancer Surgeon (Dr Maged Hussein).

Furthermore, the successful candidate will be based at Personalised Medicine Centre, School of Medicine, Ulster University, which is unique interdisciplinary environment of both experimental and computational scientists.

AccessNI clearance required

Please note, the successful candidate will be required to obtain AccessNI clearance prior to registration due to the nature of the project.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Experience using research methods or other approaches relevant to the subject domain
• Sound understanding of subject area as evidenced by a comprehensive research proposal
• A comprehensive and articulate personal statement
• Research proposal of 1500 words detailing aims, objectives, milestones and methodology of the project

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Masters at 70%
• Research project completion within taught Masters degree or MRES
• Experience using research methods or other approaches relevant to the subject domain
• Publications record appropriate to career stage
• Experience of presentation of research findings

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• BBSRC/UKRI Doctoral Landscape Award

This scholarship will cover tuition fees and provide a maintenance allowance of £21,000* (tbc) per annum for four years (subject to satisfactory academic performance).  A Research Training Support Grant (RTSG) of approximately £5000 per annum is also available.

To be eligible for these scholarships, applicants must meet the following criteria:

• Be a UK National, or
• Have settled status, or
• Have pre-settled status, or
• Have indefinite leave to remain or enter, or
• be an Irish National

Applicants should also meet the residency criteria which requires that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies.