Biomedical Research

All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.
Reach Us +44-7360-538437

Review Article - Biomedical Research (2018) Volume 29, Issue 6

Genetic polymorphisms associated with common symptoms experienced by breast cancer patients

The recent advances have led to a considerable increase in the proportion of breast cancer survivors, however, majority of them experience symptoms such as fatigue, pain, depression and sleep disturbances that impair their Quality of Life (QOL) significantly. In addition, a significant inter-individual variability in QOL of breast cancer patients exists which has been partly attributed to genetic variations. However, details of how these variations are influenced by genetic factors remain largely unknown. Therefore, detecting patients with greater susceptibility to reduced QOL using genetic markers may help in designing intervention strategies for personalized medicine. Although limited number of studies have reported on the associations between genetic polymorphisms and QOL, cytokine gene polymorphisms has consistently been linked to increased susceptibility to the development of common symptoms (fatigue, pain, depression and sleep disturbances) in breast cancer patients. More interestingly, these symptoms share some common molecular pathways making it possible to consider them as symptom cluster. In this review, the relationship between genetic variation and common symptoms among breast cancer patients is discussed. In order for genetic factors to be integrated into clinical practice and nursing care of breast cancer patients with impaired QOL, additional studies are encouraged to understand the underlying molecular mechanisms involved in the development of these symptoms and their impact on QOL for identification of patients based on the presence of a symptom cluster using genetic biomarkers.

Author(s): Murtala B. Abubakar, Siew H. Gan

Abstract Full Text PDF

Get the App