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利用双原发癌研究浆液性卵巢癌和基底样乳腺癌的共同病因。

Examining the common aetiology of serous ovarian cancers and basal-like breast cancers using double primaries.

作者信息

Begg Colin B, Rice Megan S, Zabor Emily C, Tworoger Shelley S

机构信息

Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10017, USA.

Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA.

出版信息

Br J Cancer. 2017 Apr 11;116(8):1088-1091. doi: 10.1038/bjc.2017.73. Epub 2017 Mar 23.

Abstract

BACKGROUND

The somatic molecular profiles of basal-like breast cancers and high-grade serous ovarian cancers share many similarities, leading to the hypothesis that they have similar aetiologies, in which case they should occur together in the same patient more often than expected.

METHODS

We identified 545 women with double independent primary cancers of the breast and ovary reported to the California Cancer Registry from 1999 to 2013 and examined the coincidence of subtype combinations.

RESULTS

For most subtype combinations the observed frequencies were similar to their expected frequencies, but in 103 observed cases vs 43.8 expected (O/E=2.35; 95% CI 1.90-2.81) a triple-negative breast tumour (typically basal-like) was matched with a serous ovarian tumour (typically high-grade).

CONCLUSIONS

The results provide compelling evidence that basal-like breast cancer and high-grade serous ovarian cancer share a much more similar aetiology than breast and ovarian cancers more broadly. Further research is needed to clarify the influence of germ-line BRCA1 mutations and other risk factors on these results.

摘要

背景

基底样乳腺癌和高级别浆液性卵巢癌的体细胞分子特征有许多相似之处,这引发了一种假设,即它们具有相似的病因,在这种情况下,它们在同一患者中同时出现的频率应高于预期。

方法

我们确定了1999年至2013年向加利福尼亚癌症登记处报告的545例患有乳腺和卵巢双原发独立癌症的女性,并检查了亚型组合的一致性。

结果

对于大多数亚型组合,观察到的频率与其预期频率相似,但在103例观察病例中,与预期的43.8例相比(观察值/预期值=2.35;95%置信区间1.90-2.81),三阴性乳腺肿瘤(通常为基底样)与浆液性卵巢肿瘤(通常为高级别)相匹配。

结论

结果提供了令人信服的证据,表明基底样乳腺癌和高级别浆液性卵巢癌的病因比更广泛的乳腺癌和卵巢癌更为相似。需要进一步研究以阐明种系BRCA1突变和其他风险因素对这些结果的影响。

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本文引用的文献

1
The association between reproductive and hormonal factors and ovarian cancer by estrogen-α and progesterone receptor status.
Gynecol Oncol. 2016 Dec;143(3):628-635. doi: 10.1016/j.ygyno.2016.09.024. Epub 2016 Oct 5.
2
Ovarian Cancer Risk Factors by Histologic Subtype: An Analysis From the Ovarian Cancer Cohort Consortium.
J Clin Oncol. 2016 Aug 20;34(24):2888-98. doi: 10.1200/JCO.2016.66.8178. Epub 2016 Jun 20.
3
Germline BRCA1/2 mutation testing is indicated in every patient with epithelial ovarian cancer: A systematic review.
Eur J Cancer. 2016 Jul;61:137-45. doi: 10.1016/j.ejca.2016.03.009. Epub 2016 May 19.
4
Bilateral oophorectomy and risk of cancer in African American women.
Cancer Causes Control. 2014 Apr;25(4):507-13. doi: 10.1007/s10552-014-0353-y. Epub 2014 Feb 1.
5
Reproductive risk factors and breast cancer subtypes: a review of the literature.
Breast Cancer Res Treat. 2014 Feb;144(1):1-10. doi: 10.1007/s10549-014-2852-7. Epub 2014 Jan 30.
6
Biomarker-based ovarian carcinoma typing: a histologic investigation in the ovarian tumor tissue analysis consortium.
Cancer Epidemiol Biomarkers Prev. 2013 Oct;22(10):1677-86. doi: 10.1158/1055-9965.EPI-13-0391. Epub 2013 Jul 23.
8
Comprehensive molecular portraits of human breast tumours.
Nature. 2012 Oct 4;490(7418):61-70. doi: 10.1038/nature11412. Epub 2012 Sep 23.
9
The KRAS-variant is associated with risk of developing double primary breast and ovarian cancer.
PLoS One. 2012;7(5):e37891. doi: 10.1371/journal.pone.0037891. Epub 2012 May 25.
10
The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.
Nature. 2012 Apr 18;486(7403):346-52. doi: 10.1038/nature10983.

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