Plasma microRNAs as biomarkers of pancreatic cancer risk in a prospective cohort study.
Plasma microRNAs as biomarkers of pancreatic cancer risk in a prospective cohort study.
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DOI：
10.1002/ijc.30790
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发表时间：
2017-09-01
影响因子：
6.4
通讯作者：
Korc M
中科院分区：
文献类型：
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作者：
Duell EJ;Lujan-Barroso L;Sala N;Deitz McElyea S;Overvad K;Tjonneland A;Olsen A;Weiderpass E;Busund LT;Moi L;Muller D;Vineis P;Aune D;Matullo G;Naccarati A;Panico S;Tagliabue G;Tumino R;Palli D;Kaaks R;Katzke VA;Boeing H;Bueno-de-Mesquita HBA;Peeters PH;Trichopoulou A;Lagiou P;Kotanidou A;Travis RC;Wareham N;Khaw KT;Ramon Quiros J;Rodríguez-Barranco M;Dorronsoro M;Chirlaque MD;Ardanaz E;Severi G;Boutron-Ruault MC;Rebours V;Brennan P;Gunter M;Scelo G;Cote G;Sherman S;Korc M
迫切需要无创生物标志物用于早期胰腺导管腺癌（PDAC）诊断和疾病风险分层。我们在前瞻性癌症与营养调查（EPIC）队列中进行了一项巢式病例对照研究，以评估诊断前microRNAs （miRs）作为随后PDAC风险的生物标志物。在225例显微镜下确诊的PDAC病例和225例对照中，根据我们组先前的证据对8组mir （miR-10a、-10b、-21-3p、-21-5p、-30c、-106b、-155和-212）进行了评估，这些对照与中心、性别、禁食状态和年龄/日期/采血时间相匹配。采用定量RT-PCR检测诊断前血浆样品MiR水平。采用Logistic回归对水平和PDAC风险进行建模，调整协变量，并估计受试者工作特征曲线（AUC）下的面积。血浆miR-10b、-21-5p、-30c和-106b水平在采血2年内确诊的病例中显著高于匹配对照组（p值均<0.04）。根据调整后的logistic回归模型，6种miRs （miR-10a、-10b、-21-5p、-30c、-155和-212）的总体水平，以及4种miRs （miR-10a、-10b、-21-5p和-30c）在采血和诊断之间较短随访时间（≤5年，≤2年）的水平与风险有统计学显著相关。基于面板的评分显示与风险呈线性剂量-反应趋势（p值=0.0006）。对于较短的随访（≤5年），评分的AUC为0.73，单个mir的范围为0.73 （miR-212）至0.79 （miR-21-p）。
Non-invasive biomarkers for early pancreatic ductal adenocarcinoma (PDAC) diagnosis and disease risk stratification are greatly needed. We conducted a nested case-control study within the Prospective Investigation into Cancer and Nutrition (EPIC) cohort to evaluate pre-diagnostic microRNAs (miRs) as biomarkers of subsequent PDAC risk. A panel of eight miRs (miR-10a, -10b, -21-3p, -21-5p, -30c, -106b, -155, and -212) based on previous evidence from our group was evaluated in 225 microscopically confirmed PDAC cases and 225 controls matched on center, sex, fasting status, and age/date/time of blood collection. MiR levels in pre-diagnostic plasma samples were determined by quantitative RT-PCR. Logistic regression was used to model levels and PDAC risk, adjusting for covariates, and to estimate area under the receiver operating characteristic curves (AUC). Plasma miR-10b, -21-5p, -30c and -106b levels were significantly higher in cases diagnosed within 2 yr of blood collection compared to matched controls (all P-values <0.04). Based on adjusted logistic regression models, levels for six miRs (miR-10a, -10b, -21-5p, -30c, -155, and -212) overall, and for four miRs (-10a, -10b, -21-5p, and -30c) at shorter follow-up time between blood collection and diagnosis (≤5 yr, ≤2 yr), were statistically significantly associated with risk. A score based on the panel showed a linear dose-response trend with risk (P-value=0.0006). For shorter follow-up (≤5 yr), AUC for the score was 0.73, and for individual miRs ranged from 0.73 (miR-212) to 0.79 (miR-21-p).
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影响因子：
64.8
作者：
Notta F;Chan-Seng-Yue M;Lemire M;Li Y;Wilson GW;Connor AA;Denroche RE;Liang SB;Brown AM;Kim JC;Wang T;Simpson JT;Beck T;Borgida A;Buchner N;Chadwick D;Hafezi-Bakhtiari S;Dick JE;Heisler L;Hollingsworth MA;Ibrahimov E;Jang GH;Johns J;Jorgensen LG;Law C;Ludkovski O;Lungu I;Ng K;Pasternack D;Petersen GM;Shlush LI;Timms L;Tsao MS;Wilson JM;Yung CK;Zogopoulos G;Bartlett JM;Alexandrov LB;Real FX;Cleary SP;Roehrl MH;McPherson JD;Stein LD;Hudson TJ;Campbell PJ;Gallinger S
通讯作者：
Gallinger S
影响因子：
11.1
作者：
Degueurce G;D'Errico I;Pich C;Ibberson M;Schütz F;Montagner A;Sgandurra M;Mury L;Jafari P;Boda A;Meunier J;Rezzonico R;Brembilla NC;Hohl D;Kolios A;Hofbauer G;Xenarios I;Michalik L
通讯作者：
Michalik L
影响因子：
6.4
作者：
Lee, Eun Jon;Gusev, Yuriy;Schmittgen, Thomas D.
通讯作者：
Schmittgen, Thomas D.
影响因子：
--
作者：
Brunetti O;Russo A;Scarpa A;Santini D;Reni M;Bittoni A;Azzariti A;Aprile G;Delcuratolo S;Signorile M;Gnoni A;Palermo L;Lorusso V;Cascinu S;Silvestris N
通讯作者：
Silvestris N
影响因子：
64.8
作者：
Bailey, Peter;Chang, David K.;Grimmond, Sean M.
通讯作者：
Grimmond, Sean M.