Does obesity modify the expression of cyclin D1 and pten in endometrial polyps in postmenopausal women?
Mario Vicente GiordanoTatiana Fonseca AlvarengaCesar de Souza Bastos JúniorMario Gáspare GiordanoEdmund Chada BaracatJosé Maria Soares JúniorPublished in: Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology (2020)
To assess cyclin D1 and PTEN immunoexpression in benign endometrial polyps (EPs) in asymptomatic postmenopausal women and its correlation with obesity. Methods: This was a cross-sectional study based on data from a sample of 52 patients diagnosed with EP between February 2018 and January 2019. The women included in this study were amenorrheal for at least 1 year and were asymptomatic (no postmenopausal bleeding). Obesity defined by body mass index (BMI) was investigated for correlation with Cyclin-D1 and PTEN gene expression (immunohistochemistry) in glandular and stromal compartments of polyps. Results: No significant differences among groups were identified in any clinical and epidemiological parameter (age, age of menopause, time since menopause, number of gestations, polyp size, leucocyte count, fasting blood glucose and basic pathologies), except for BMI. Body mass index did not alter PTEN or Cyclin D1 immunoexpression. Conclusion: Our study shows that obesity does not appear to be a relevant factor in the immunoexpression of PTEN and Cyclin D1 in benign EP, in either the stromal or glandular compartments.
Keyphrases
- breast cancer risk
- postmenopausal women
- body mass index
- weight gain
- bone mineral density
- insulin resistance
- cell cycle
- cell proliferation
- blood glucose
- pi k akt
- metabolic syndrome
- weight loss
- cell cycle arrest
- type diabetes
- high fat diet induced
- gene expression
- physical activity
- bone marrow
- signaling pathway
- end stage renal disease
- poor prognosis
- adipose tissue
- dna methylation
- chronic rhinosinusitis
- atrial fibrillation
- glycemic control
- ejection fraction
- blood pressure
- pregnant women
- high resolution
- polycystic ovary syndrome
- endometrial cancer
- chronic kidney disease
- machine learning
- cell death
- peritoneal dialysis
- mass spectrometry
- risk factors
- atomic force microscopy
- high speed