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RNA Bio research group5
Brighton & Sussex Medical School

Predicting cancer-related fatigue in women with breast cancer: integrating proteomic, clinical and psychosocial data

BSMS > Research > Clinical and experimental medicine > Cancer > Predicting cancer-related fatigue in women with breast cancer: integrating proteomic, clinical and psychosocial data

Predicting cancer-related fatigue in women with breast cancer: integrating proteomic, clinical and psychosocial data

This project explores cancer-related fatigue (CRF) in people living with cancer, with a particular interest in how biological, psychological, and lifestyle factors shape the experience of fatigue over time.

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About the project

This prospective observational study investigates whether clinical, psychosocial and biological factors can predict CRF in women with breast cancer receiving neoadjuvant treatment. Participants will complete regular fatigue measures and questionnaire assessments, provide blood samples, and have relevant clinical data collected from medical records. Proteomic analysis will be used to identify candidate proteins associated with fatigue. These data will then be used to develop multivariable prediction models and to identify trajectories of fatigue over treatment. This project aims to improve understanding of the risk factors, underlying mechanisms and temporal patterns of CRF to support early identification and management and potentially inform novel treatment targets.

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Research aims

Primary

  1. To integrate proteomic, psychosocial, clinical and behavioural data to create predictive models capable of predicting cancer-related fatigue in women with breast and ovarian cancer.  

Secondary

  1. Characterise the development of CRF over the course of treatment and recovery, identifying subgroups with distinct fatigue trajectories and the factors that distinguish them.  
  2. Examine how CRF relates to health-related quality of life, stress, anxiety, depression, self-efficacy, social support, physical activity and clinical characteristics.  
  3. Determine whether specific proteins or proteomic pathways are associated with psychosocial or clinical measures and explore shared biological mechanisms underlying CRF and its comorbid symptoms.  

Meet the team 

PhD student and Lead Supervisor

Supervisors

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