Conclusion
Associations between host SNPs and computed GRSs and variability in pretreatment cognitive function performance support the study hypothesis, and warrant further investigations to identify biomarkers for breast cancer-related cognitive dysfunction.
Methods
The sample (n=220) was comprised of 138 postmenopausal women newly diagnosed with early stage breast cancer and 82 postmenopausal age- and education-matched healthy controls without breast cancer. Cognitive performance was assessed after primary surgery but prior to initiation of adjuvant chemotherapy and/or hormonal therapy using a comprehensive battery of neuropsychological tests encompassing eight cognitive function composite domains: attention, concentration, executive function, mental flexibility, psychomotor speed, verbal memory, visual memory, and visual working memory. In total, 131 SNPs were included in the analysis. Standard and robust multiple linear regression modeling was used to examine relationships between each domain and the presence or absence of one or more minor alleles for each SNP. Genetic risk/protection scores (GRSs) were calculated for each domain to evaluate the collective effect of possession of multiple risk/protective alleles.
Purpose
Inspired by the hypothesis that heterogeneity in the biology of breast cancers at the cellular level may account for cognitive dysfunction symptom variability in survivors, the current study explored relationships between host single-nucleotide polymorphisms (SNPs) in 25 breast cancer-related candidate genes (AURKA, BAG1, BCL2, BIRC5, CCNB1, CD68, CENPA, CMC2, CTSL2, DIAPH3, ERBB2, ESR1, GRB7, GSTM1, MELK, MKI67, MMP11, MYBL2, NDC80, ORC6, PGR, RACGAP1, RFC4, RRM2, and SCUBE2), identified from clinically relevant prognostic multigene-expression profiles for breast cancer, and pretreatment cognitive performance. Patients and
Results
With the exception of CMC2, MMP11, and RACGAP1, significant (P<0.05) SNP main effect and/or SNP by future prescribed treatment group interactions were observed for every gene between at least one domain and one or more SNPs. All GRSs were found to be significantly (P<0.001) associated with each respective domain score.