ObjectivesCancer-related cognitive impairment (CRCI) is a highly prevalent and debilitating symptom reported by breast cancer survivors (BCS). The etiology of CRCI remains unclear, leading to poor symptom management. Building from prior studies, BCS with the C/C genotype of apolipoprotein E (APOE) rs7412 and the T/T genotype of brain-derived neurotrophic factor (BDNF) rs6265 were hypothesized to experience more severe CRCI. Therefore, we investigated the relationships between the severity of CRCI and polymorphisms of APOE and BDNF among BCS. MethodsThis was a subanalysis of data from a larger descriptive, correlational, and cross-sectional study. Subjective and objective CRCI were measured using the Patient-Reported Outcomes Measurement Information System and CANTAB Cambridge Cognitive assessment, respectively. Buccal swab samples were collected to evaluate the single nucleotide polymorphisms. Multivariable generalized linear regression models were used to analyze data. ResultsAPOE rs7412 and BDNF rs6265 were significantly associated with lower self-reported cognitive abilities in a total of 353 BCS. Age was positively associated with self-reported cognitive scores, indicating that younger BCS perceived lower cognitive abilities. Individuals carrying genotype of C/T for APOE with the C/C or C/T for BDNF showed positive associations with cognitive abilities. ConclusionsYounger BCS with the C/C genotype for APOE rs7412 and the T/T genotype for BDNF rs6265 may be at risk for CRCI. Knowledge regarding predictive markers for CRCI symptoms is essential for precision symptom management. Further investigation with a longitudinal and translational design is necessary to explore the etiologies for CRCI. Implications for Nursing PracticeIntegrating genetic phenotyping into routine clinical practice will provide nurses with unique opportunities to understand individual susceptibilities, and how symptoms may trigger other symptoms. Further, findings from these innovative investigations will provide symptom interventionists and implementation scientists with critical data to optimize individualized strategies for symptom prevention, detection, and management.