Suppr超能文献

卵巢肿瘤中雌激素受体-β的表达及其与卵巢癌危险因素的关系。

Estrogen Receptor-β Expression of Ovarian Tumors and Its Association with Ovarian Cancer Risk Factors.

机构信息

Division of Adolescent/Young Adult Medicine, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts.

Boston Center for Endometriosis, Brigham and Women's Hospital and Boston Children's Hospital, Boston, Massachusetts.

出版信息

Cancer Epidemiol Biomarkers Prev. 2020 Nov;29(11):2211-2219. doi: 10.1158/1055-9965.EPI-20-0618. Epub 2020 Aug 20.

Abstract

BACKGROUND

Differential associations between ovarian cancer risk factors and estrogen receptor-α (ERα) ovarian tumor expression have been noted; however, no research has assessed estrogen receptor-β (ERβ) expression. Thus, in exploratory analyses, we assessed the association of several factors with ovarian cancer risk by ERβ tumor status.

METHODS

We conducted a nested case-control study within the prospective Nurses' Health Study cohorts (NHS/NHSII), with exposures collected through biennial questionnaires. Paraffin-embedded tumor blocks were requested for cases diagnosed from 1976 to 2006 (NHS) and 1989 to 2005 (NHSII) and tissue microarrays were stained for nuclear ERβ (ERβ-nuc) and cytoplasmic ERβ (ERβ-cyto), with any staining considered positive (+). We obtained odds ratios (OR) and 95% confidence intervals (CI) using multivariate polytomous logistic regression.

RESULTS

We included 245 cases [43% ERβ-cyto (+) and 71% ERβ-nuc (+)] and 1,050 matched controls. An inverse association was observed between parity and risk of ERβ-nuc (+) (OR, parous vs. nulliparous: 0.46; 95% CI, 0.26-0.81), but not ERβ-nuc (-) tumors (OR, parous vs. nulliparous: 1.51; 95% CI, 0.45-5.04; = 0.04). Conversely, parity was inversely associated with ERβ-cyto (-) tumors (OR, parous vs. nulliparous: 0.42; 95% CI, 0.23-0.78), but was not associated with ERβ-cyto (+) tumors (OR, parous vs. nulliparous: 1.08; 95% CI, 0.45-2.63; = 0.05). Associations for other exposures, including hormone therapy, did not differ by ERβ-nuc or ERβ-cyto status.

CONCLUSIONS

Our results suggest that parity may influence ovarian cancer risk, in part, through alterations in ERβ localization within tumor cells.

IMPACT

Alterations in ERβ expression and localization appear to be important for ovarian cancer etiology. Future research should confirm our results and assess potential biologic mechanisms for the observed associations.

摘要

背景

卵巢癌风险因素与雌激素受体-α(ERα)卵巢肿瘤表达之间存在差异关联;然而,尚无研究评估雌激素受体-β(ERβ)的表达。因此,在探索性分析中,我们根据 ERβ 肿瘤状态评估了几种因素与卵巢癌风险的关联。

方法

我们在前瞻性护士健康研究队列(NHS/NHSII)中进行了巢式病例对照研究,通过每两年一次的问卷调查收集暴露情况。请求诊断为 1976 年至 2006 年(NHS)和 1989 年至 2005 年(NHSII)的病例的石蜡包埋肿瘤块,并进行核雌激素受体-β(ERβ-nuc)和细胞质雌激素受体-β(ERβ-cyto)染色,任何染色均视为阳性(+)。我们使用多变量多项式逻辑回归获得比值比(OR)和 95%置信区间(CI)。

结果

我们纳入了 245 例病例[43%ERβ-cyto(+)和 71%ERβ-nuc(+)]和 1050 名匹配的对照。发现产次与 ERβ-nuc(+)肿瘤的风险呈负相关(OR,经产 vs. 未产:0.46;95%CI,0.26-0.81),但与 ERβ-nuc(-)肿瘤无相关性(OR,经产 vs. 未产:1.51;95%CI,0.45-5.04; = 0.04)。相反,产次与 ERβ-cyto(-)肿瘤呈负相关(OR,经产 vs. 未产:0.42;95%CI,0.23-0.78),但与 ERβ-cyto(+)肿瘤无关(OR,经产 vs. 未产:1.08;95%CI,0.45-2.63; = 0.05)。其他暴露因素(包括激素治疗)的相关性不因 ERβ-nuc 或 ERβ-cyto 状态而异。

结论

我们的结果表明,产次可能通过改变肿瘤细胞内 ERβ 的定位来影响卵巢癌的风险。

影响

雌激素受体-β 表达和定位的改变似乎对卵巢癌的病因学很重要。未来的研究应证实我们的结果,并评估观察到的关联的潜在生物学机制。

相似文献

7
Lifestyle and Reproductive Factors and Ovarian Cancer Risk by p53 and MAPK Expression.生活方式和生殖因素与 p53 和 MAPK 表达的卵巢癌风险。
Cancer Epidemiol Biomarkers Prev. 2018 Jan;27(1):96-102. doi: 10.1158/1055-9965.EPI-17-0609. Epub 2017 Nov 13.

引用本文的文献

1
Estrogens and the risk of breast cancer: A narrative review of literature.雌激素与乳腺癌风险:文献综述
Heliyon. 2023 Sep 17;9(9):e20224. doi: 10.1016/j.heliyon.2023.e20224. eCollection 2023 Sep.

本文引用的文献

2
The rs1256031 of estrogen receptor β gene is associated with type 2 diabetes.雌激素受体β基因的rs1256031与2型糖尿病相关。
Diabetes Metab Syndr. 2018 Sep;12(5):631-633. doi: 10.1016/j.dsx.2018.04.018. Epub 2018 Apr 12.
5
Pathogenesis and heterogeneity of ovarian cancer.卵巢癌的发病机制与异质性
Curr Opin Obstet Gynecol. 2017 Feb;29(1):26-34. doi: 10.1097/GCO.0000000000000340.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验