[Gene-age interaction study of breast cancer prognosis based on epigenomic data].

Objective: Exploring gene-age interactions associated with breast cancer prognosis based on epigenomic data. Methods: Differential expression analysis of DNA methylation was conducted using multiple independent epigenomic datasets of breast cancer from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The false discovery rate (FDR) method was used for multiple corrections, retaining differentially methylated sites with q-FDR≤0.05. A three-stage analytic strategy was implemented, using a multivariable Cox proportional hazards regression model to examine gene-age interactions. In the discovery phase, signals with q-FDR ≤ 0.05 were screened out using TCGA-BRCA database. In validation phaseⅠ, the interaction was validated using GSE72245 data, with criteria of P≤0.05 and consistent effect direction. In validation phaseⅡ, the signals were further validated using GSE37754 and GSE75067 data. A prognostic prediction model was constructed by incorporating clinical indicators and interaction signals. Results: The three-stage analytic strategy identified a methylation site (cg16126280EBF1), which interacted with age to jointly affect the overall survival time of patients (interaction HR= 1.001 1,95%CI:1.000 7-1.001 5,P<0.001). Stratified analysis by age showed that the effect of hypermethylation of cg16126280EBF1 was completely opposite in younger patients (HR=0.550 5, 95%CI: 0.383 8-0.789 6, P=0.001) and older patients (HR=2.166 5, 95%CI: 1.285 2-3.652 2, P=0.004). Conclusions: The DNA methylation site cg16126280EBF1 exhibits an interaction with age, jointly influencing the prognosis of breast cancer in a complex association pattern. This finding contributes new population-based evidence for the development of age-specific targeted drugs.

[Efficacy of decitabine in patients with glucocorticoid-resistant primary immune thrombocytopenia: factors influencing treatment responses].

Objective: This study aimed to evaluate the efficacy of decitabine (DAC) and identify factors influencing treatment responses in patients with primary immune thrombocytopenia (ITP) who had failed glucocorticoid therapy. Methods: Clinical data of 61 patients with glucocorticoid-resistant ITP who received DAC therapy (5 mg·m(-2)·d(-1)×3 d via intravenous infusion) for at least three cycles with 3-4-week intervals at the Department of Hematology, Qilu Hospital of Shandong University, from November 2015 to June 2021 were analyzed retrospectively. Results: The 61 patients comprised 20 males and 41 females, with a median age of 45 years (range: 15-81 years). Among them, 43 patients were glucocorticoid-dependent (glucocorticoid-dependent group), while 18 patients were glucocorticoid-resistant (glucocorticoid-resistant group). Following DAC treatment, 12 patients (19.67% ) achieved complete response (CR), and 16 patients (26.23% ) exhibited response (R), resulting in an overall response (OR) rate of 45.90% (28/61). Comparison between the OR group (n=28) and the non-response (NR) group (n=33) revealed significant differences in responses to glucocorticoids (dependent or resistant) and platelet counts before treatment (χ(2)=8.789, P=0.003; z=-2.416, P=0.016). The glucocorticoid-dependent group showed higher platelet counts than the glucocorticoid-resistant group after the second and third cycles of DAC treatment (P=0.032, 0.024). Moreover, the OR rates after the first, second, and third cycles of DAC treatment in the glucocorticoid-dependent group were all higher than those in the glucocorticoid-resistant group (P=0.042, P=0.012, P=0.029). A significant correlation was observed between glucocorticoid dependence and responses to DAC treatment (OR=9.213, 95% CI 1.937-43.820, P=0.005) . Conclusion: DAC demonstrates definitive efficacy with mild adverse effects in a subset of patients with glucocorticoid-resistant primary ITP. Glucocorticoid dependence and higher platelet counts before treatment are associated with a favorable response to DAC therapy.