Circulating miR-17, miR-20a, miR-29c, and miR-223 combined as non-invasive biomarkers in nasopharyngeal carcinoma.
Circulating miR-17, miR-20a, miR-29c, and miR-223 combined as non-invasive biomarkers in nasopharyngeal carcinoma.
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循环 miR-17、miR-20a、miR-29c 和 miR-223 组合作为鼻咽癌的非侵入性生物标志物
DOI:
10.1371/journal.pone.0046367
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发表时间:
2012
期刊:
影响因子:
3.7
通讯作者:
Peng S
中科院分区:
文献类型:
--
作者:
Zeng X;Xiang J;Wu M;Xiong W;Tang H;Deng M;Li X;Liao Q;Su B;Luo Z;Zhou Y;Zhou M;Zeng Z;Li X;Shen S;Shuai C;Li G;Fang J;Peng S
Background MicroRNAs have been considered as a kind of potential novel biomarker for cancer detection due to their remarkable stability in the blood and the characteristics of their expression profile in many diseases. Methods We performed microarray-based serum miRNA profiling on the serum of twenty nasopharyngeal carcinoma patients at diagnosis along with 20 non-cancerous individuals as controls. This was followed by a real-time quantitative Polymerase Chain Reaction (RT-qPCR) in a separate cohort of thirty patients with nasopharyngeal carcinoma and thirty age- matched non-cancerous volunteers. A model for diagnosis was established by a conversion of mathematical calculation formula which has been validated by analyzing 74 cases of patients with nasopharyngeal carcinoma and 57 cases of non-cancerous volunteers. Results The profiles showed that 39 and 17 miRNAs are exclusively expressed in the serum of non-cancerous volunteers and of patients with nasopharyngeal carcinoma respectively. 4 miRNAs including miR-17, miR-20a, miR-29c, and miR-223 were found to be expressed differentially in the serum of NPC compared with that of non-cancerous control. Based on this, a diagnosis equation with Ct difference method has been established to distinguish NPC cases and non-cancerous controls and validated with high sensitivity and specificity. Conclusions We demonstrate that the serum miRNA-based biomarker model become a novel tool for NPC detection. The circulating 4-miRNA-based method may provide a novel strategy for NPC diagnosis.
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影响因子:
4.8
作者:
Gourzones C;Gelin A;Bombik I;Klibi J;Vérillaud B;Guigay J;Lang P;Témam S;Schneider V;Amiel C;Baconnais S;Jimenez AS;Busson P
通讯作者:
Busson P
影响因子:
51.1
作者:
Liu, Na;Chen, Nian-Yong;Ma, Jun
通讯作者:
Ma, Jun
影响因子:
8.8
作者:
Chen, H-C;Chen, G-H;Chen, Y-H;Liao, W-L;Liu, C-Y;Chang, K-P;Chang, Y-S;Chen, S-J
通讯作者:
Chen, S-J
影响因子:
3.7
作者:
Gilad S;Meiri E;Yogev Y;Benjamin S;Lebanony D;Yerushalmi N;Benjamin H;Kushnir M;Cholakh H;Melamed N;Bentwich Z;Hod M;Goren Y;Chajut A
通讯作者:
Chajut A
影响因子:
11
作者:
Li S;Li Z;Guo F;Qin X;Liu B;Lei Z;Song Z;Sun L;Zhang HT;You J;Zhou Q
通讯作者:
Zhou Q