• 2018-07
  • 2018-10
  • 2018-11
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • br Materials and methods br Statistical


    Materials and methods
    Statistical analysis All statistical analyses were performed using SPSS software version 20. Protein NP118809 sale data of DNMTs and clinicopathological parameters were collected. Mann-Whitney U Test was used to assess the differential expression of nonparametric data of DNMTs protein expression between TAM-S and TAM-R breast tumor tissues. Association of patient\'s clinicopathological characteristics with DNMTs expression was determined using Pearson chi-square or Fisher\'s exact test when appropriate. Spearman rank correlation test was performed to analyze the association between DNMT1, DNMT3A, and DNMT3B expression. The crude and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by the performance of Logistic regression analysis in order to define the relation between expression levels of DNMTs and tamoxifen response. The effects of DNMTs overexpression on patient survival were estimated by the Kaplan–Meier method and the differences between the two groups were compared using the log-rank test. To evaluate the statistical power of the individual covariates as treatment predictors and unfavorable prognosis, univariate and multivariate Cox proportional hazard survival analyses were performed for DFS and OS. HR was represented with 95% confidence intervals (95% CI). P < 0.05 was considered statistically significant.
    Conclusion Various genetic and epigenetic modifications influence on tamoxifen refractory in breast carcinoma patients. Therefore, resistance development can hardly be attributed to a particular factor. However, according to our previous works and the results of the present study, DNMTs may be at least partly responsible for the progression of disease recurrence in ER+ tamoxifen-treated breast carcinoma patients. More studies are needed to confirm overexpression of DNMTs as an important tamoxifen resistance prognosis marker and introduce them as a new target for the prevention of disease recurrence. It could be interesting to investigate the correlation between methylation status of the promoters of hormone receptors and TSGs with DNMTs expression in tamoxifen-treated breast cancer patients in the future studies. Additionally, it could be valuable to evaluate the combined effects of routine breast cancer treatment protocol with epigenetic therapies to better management of tamoxifen treatment.
    Rational and aims Neuroendocrine tumors (NET) are rare, but their incidence is rising and their prevalence is high [1]. Most occur in the digestive system (68%) and the bronchopulmonary system (25%), and more than 60% are diagnosed at advanced, unresectable stages [1]. Chemotherapy is one of the few therapeutic weapons, along with targeted therapies, somatostatin analogs, and metabolic radiotherapy. Alkylating agents (ALKY), temozolomide and streptozotocin, are one of the main systemic treatments used [2], [3], [4], at least for advanced duodeno-pancreatic NETs; the response rate is 30%–40% and the median progression-free survival is 4–18 months [2], [5], [6], [7], [8], [9]. However, it should be noted that for pulmonary NETs, called typical and atypical carcinoids, the level of proof of efficacy of these treatments is lower than for duodeno-pancreatic NETs. One of the mechanisms of ALKY cytotoxicity is the induction of DNA alkylation/methylation at O6-guanine sites, resulting in DNA mismatch and cell death in tumor tissue [10]. However, ALKY-induced DNA damage can be repaired by O6-Methylguanine-DNA methyltransferase (MGMT). Any reduction in MGMT activity may therefore potentiate the effect of ALKY. The expression of MGMT has been shown to be decreased in some tumor cells, mainly as a result of gene promoter hypermethylation [11]. Thus, MGMT status has been proposed as a predictive factor for the response to ALKY; it can be assessed at the protein level (by immunohistochemistry, IHC) and at the gene level (through methylation analysis). The current literature is conflicted as to the value of MGMT to predict response to ALKY, in part because MGMT status is assessed by multiple techniques with various accuracy, but also because of the retrospective nature of the studies reported and the low number of patients included [12], [13], [14], [15], [16], [17], [18], [19], [20], [21] (Table 1).