The variant T allele of PvuII in ESR1 gene is a prognostic marker in early breast cancer survival

Lessons learned from a candidate gene study investigating aromatase inhibitor treatment outcome in breast cancer

The role of germline genetics in adjuvant aromatase inhibitor (AI) treatment efficacy in ER-positive breast cancer is poorly understood. We employed a two-stage candidate gene approach to examine associations between survival endpoints and common germline variants in 753 endocrine resistance-related genes. For a discovery cohort, we screened the Breast Cancer Association Consortium database (n ≥ 90,000 cases) and retrieved 2789 AI-treated patients. Cox model-based analysis revealed 125 variants associated with overall, distant relapse-free, and relapse-free survival (p-value ≤ 1E-04). In validation analysis using five independent cohorts (n = 8857), none of the six selected candidates representing major linkage blocks at CELA2B/CASP9, NR1I2/GSK3B, LRP1B, and MIR143HG (CARMN) were validated. We discuss potential reasons for the failed validation and replication of published findings, including study/treatment heterogeneity and other limitations inherent to genomic treatment outcome studies. For the future, we envision prospective longitudinal studies with sufficiently long follow-up and endpoints that reflect the dynamic nature of endocrine resistance.

Association of Polymorphisms in FSHR, ESR1, and BMP15 with Primary Ovarian Insufficiency and Meta-Analysis

Primary ovarian insufficiency (POI) can lead to menstrual disturbance, resulting in ovarian dysfunction before age 40. Prevalence of POI is usually less than 1%; however, ethnicity or population characteristics may affect prevalence. POI is a heterogeneous disease that results from abnormalities in immunological and hormonal factors. Genetic factors can also contribute to POI. Here, we examine FSHR, ESR1, and BMP15 polymorphisms in patients with POI, and controls. We examined a hormonal gene that is important for pregnancy, follicle-stimulating hormone receptor (FSHR), as well as estrogen receptor 1 (ESR1), and associated it with FSHR expression, ovulation rate, and bone morphogenetic protein 15 (BMP15). We examined 139 Korean patients under age 40 with POI, and 350 Korean control participants without POI. Genotyping was performed by a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and TaqMan assays. Each identified genotype was subjected to statistical analysis to determine the odds ratios (ORs) and 95% confidence intervals (CIs). In combination genotype analyses, FSHR rs6165 A > G combined with ESR1 rs9340799 A > G, AG/GG (OR: 5.693; 95% CI: 1.088-29.792), as well as FSHR rs6166 A > G combined with ESR1 rs9340799 C > T, AG/GG (OR: 5.940; 95% CI: 1.134-31.131), were significantly associated with POI prevalence. Furthermore, an FSHR rs6165 A > G and BMP rs17003221 C > T, AG/CC combination was associated with POI prevalence (OR: 1.874; 95% CI: (1.059-3.316; p-value: 0.031)). In meta-analysis, FSHR rs6165 AA vs. AG + GG is associated with POI (p = 0.0013), and ESR1 rs2234693 AA vs. AG + GG is also associated with POI (p = 0.0101). Here, we compared the genotypes of FSHR, ESR1, and BMP15 in patients with POI, and controls. We found significant differences in genotype combinations between polymorphisms in FSHR and other genes. Through meta-analysis, we found that ESR1 rs9340799 and rs2234693 are associated with POI prevalence, and that BMP15 rs17003221 increases POI risk. These findings help to improve POI diagnosis in Korean women.

Construction of a prognostic model for breast cancer based on moonlighting genes

Breast cancer (BRCA) is a highly heterogeneous disease, with significant differences in prognosis among patients. Existing biomarkers and prognostic models have limited ability to predict BRCA prognosis. Moonlighting genes regulate tumor progression and are associated with cancer prognosis. This study aimed to construct a moonlighting gene-based prognostic model for BRCA. We obtained differentially expressed genes (DEGs) in BRCA from The Cancer Genome Atlas and intersected them with moonlighting genes from MoonProt to acquire differential moonlighting genes. GO and KEGG results showed main enrichment of these genes in the response of BRCA cells to environmental stimuli and pentose phosphate pathway. Based on moonlighting genes, we conducted drug prediction and validated results through cellular experiments. After ABCB1 knockdown, viability and proliferation of BRCA cells were significantly enhanced. Based on differential moonlighting genes, BRCA was divided into three subgroups, among which cluster2 had the highest survival rate and immunophenoscore and relatively low tumor mutation burden. TP53 had the highest mutation frequency in cluster2 and cluster3, while PIK3CA had a higher mutation frequency in cluster1, with the majority being missense mutations. Subsequently, we established an 11-gene prognostic model in the training set based on DEGs among subgroups using univariate Cox regression, LASSO regression, and multivariable Cox regression analyses. Model prognostic performance was verified in GEO, METABRIC and ICGC validation sets. In summary, this study obtained three BRCA moonlighting gene-related subtypes and constructed an 11-gene prognostic model. The 11-gene BRCA prognostic model has good predictive performance, guiding BRCA prognosis for clinical doctors.

Autoantibodies as biomarkers for breast cancer diagnosis and prognosis

Breast cancer is the most common cancer in women worldwide and is a substantial public health problem. Screening for breast cancer mainly relies on mammography, which leads to false positives and missed diagnoses and is especially non-sensitive for patients with small tumors and dense breasts. The prognosis of breast cancer is mainly classified by tumor, node, and metastasis (TNM) staging, but this method does not consider the molecular characteristics of the tumor. As the product of the immune response to tumor-associated antigens, autoantibodies can be detected in peripheral blood and can be used as noninvasive, presymptomatic, and low-cost biomarkers. Therefore, autoantibodies can provide a possible supplementary method for breast cancer screening and prognosis classification. This article introduces the methods used to detect peripheral blood autoantibodies and the research progress in the screening and prognosis of breast cancer made in recent years to provide a potential direction for the examination and treatment of breast cancer.