Circulating microRNA-based screening tool for breast cancer

被引:50
作者
Freres, Pierre [1 ,2 ]
Wenric, Stephane [2 ]
Boukerroucha, Meriem [2 ]
Fasquelle, Corinne [2 ]
Thiry, Jerome [2 ]
Bovy, Nicolas [3 ]
Struman, Ingrid [3 ]
Geurts, Pierre [4 ]
Collignon, Joelle [1 ]
Schroeder, Helene [1 ]
Kridelka, Frederic [5 ]
Lifrange, Eric [6 ]
Jossa, Veronique [7 ]
Bours, Vincent [2 ]
Josse, Claire [2 ]
Jerusalem, Guy [1 ]
机构
[1] Univ Hosp CHU, Dept Med Oncol, Liege, Belgium
[2] Univ Liege, GIGA Res, Lab Human Genet, Liege, Belgium
[3] Univ Liege, GIGA Res, Lab Mol Angiogenesis, Liege, Belgium
[4] Univ Liege, GIGA Res, Dept EE & CS, Liege, Belgium
[5] Univ Hosp CHU, Dept Gynecol, Liege, Belgium
[6] Univ Hosp CHU, Dept Senol, Liege, Belgium
[7] Clin St Vincent CHC, Liege, Belgium
关键词
breast cancer; circulating microRNAs; biomarkers; minimally invasive screening; BLOOD-BASED MARKERS; POTENTIAL BIOMARKER; EXPRESSION PROFILES; FEATURE-SELECTION; SERUM; MAMMOGRAPHY; PLASMA; PERFORMANCE; SIGNATURE; TARGETS;
D O I
10.18632/oncotarget.6786
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Circulating microRNAs (miRNAs) are increasingly recognized as powerful biomarkers in several pathologies, including breast cancer. Here, their plasmatic levels were measured to be used as an alternative screening procedure to mammography for breast cancer diagnosis. A plasma miRNA profile was determined by RT-qPCR in a cohort of 378 women. A diagnostic model was designed based on the expression of 8 miRNAs measured first in a profiling cohort composed of 41 primary breast cancers and 45 controls, and further validated in diverse cohorts composed of 108 primary breast cancers, 88 controls, 35 breast cancers in remission, 31 metastatic breast cancers and 30 gynecologic tumors. A receiver operating characteristic curve derived from the 8-miRNA random forest based diagnostic tool exhibited an area under the curve of 0.81. The accuracy of the diagnostic tool remained unchanged considering age and tumor stage. The miRNA signature correctly identified patients with metastatic breast cancer. The use of the classification model on cohorts of patients with breast cancers in remission and with gynecologic cancers yielded prediction distributions similar to that of the control group. Using a multivariate supervised learning method and a set of 8 circulating miRNAs, we designed an accurate, minimally invasive screening tool for breast cancer.
引用
收藏
页码:5416 / 5428
页数:13
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