Whole-blood DNA methylation markers in early detection of breast cancer

• Verfasst von: Guan, Zhong [VerfasserIn]
• Verfasst von: Cuk, Katarina [VerfasserIn]
• Verfasst von: Zhang, Yan [VerfasserIn]
• Verfasst von: Brenner, Hermann [VerfasserIn]
• Titel: Whole-blood DNA methylation markers in early detection of breast cancer
• Titelzusatz: a systematic literature review
• Verf.angabe: Zhong Guan, Haixin Yu, Katarina Cuk, Yan Zhang, and Hermann Brenner
• Jahr: 2019
• Umfang: 10 S.
• Fussnoten: Published first November 28, 2018 ; Gesehen am 23.05.2019
• Titel Quelle: Enthalten in: Cancer epidemiology, biomarkers & prevention
• Ort Quelle: Philadelphia, Pa. : AACR, 1991
• Jahr Quelle: 2019
• Band/Heft Quelle: 28(2019), 3, Seite 496-505
• ISSN Quelle: 1538-7755
• DOI: doi:10.1158/1055-9965.EPI-18-0378
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1666186376

Abstract

Whole-blood DNA methylation markers have been suggested as potential biomarkers for early detection of breast cancer. We conducted a systematic review of the literature on whole-blood DNA methylation markers for breast cancer detection. PubMed and ISI Web of Knowledge were searched up to May 29, 2018. Overall, 33 studies evaluating 355 markers were included. The diagnostic value of most individual markers was relatively modest, with only six markers showing sensitivity >40% at specificity >75% [only 2 (HYAL2 and S100P) were independently validated]. Although relatively strong associations (OR ≤0.5 or OR ≥2) with breast cancer were reported for 14 markers, most of them were not independently validated. Two prospective studies performed epigenome-wide association analysis and identified 276 CpG sites related to breast cancer risk, but no overlap was observed between CpGs reported from these two studies. Five studies incorporated individual markers as panels, but only two of them used a test-validation approach. In conclusion, so far detected methylation markers are insufficient for breast cancer early detection, but markers or marker-combinations may be useful for breast cancer risk stratification. Utilizing high-throughput methods of methylation quantification, future studies should focus on further mining informative methylation markers and derivation of enhanced multimaker panels with thorough external validation ideally in prospective settings.