Aptamer-based proteomic signature of intensive phase treatment response in pulmonary tuberculosis.
Aptamer-based proteomic signature of intensive phase treatment response in pulmonary tuberculosis.
复制标题
DOI:
10.1016/j.tube.2014.01.006
复制
发表时间:
2014-05
期刊:
影响因子:
--
通讯作者:
Ochsner UA
中科院分区:
文献类型:
--
作者:
Nahid P;Bliven-Sizemore E;Jarlsberg LG;De Groote MA;Johnson JL;Muzanyi G;Engle M;Weiner M;Janjic N;Sterling DG;Ochsner UA
New drug regimens of greater efficacy and shorter duration are needed for tuberculosis (TB) treatment. The identification of accurate, quantitative, non-culture based markers of treatment response would improve the efficiency of Phase 2 TB drug testing. In an unbiased biomarker discovery approach, we applied a highly multiplexed, aptamer-based, proteomic technology to analyze serum samples collected at baseline and after 8 weeks of treatment from 39 patients with pulmonary TB from Kampala, Uganda enrolled in a Centers for Disease Control and Prevention (CDC) TB Trials Consortium Phase 2B treatment trial. We identified protein expression differences associated with 8-week culture status, including Coagulation Factor V, SAA, XPNPEP1, PSME1, IL-11 Rα, HSP70, Galectin-8, α2-Antiplasmin, ECM1, YES, IGFBP-1, CATZ, BGN, LYNB, and IL-7. Markers noted to have differential changes between responders and slow-responders included nectin-like protein 2, EphA1 (Ephrin type-A receptor 1), gp130, CNDP1, TGF-b RIII, MRC2, ADAM9, and CDON. A logistic regression model combining markers associated with 8-week culture status revealed an ROC curve with AUC=0.96, sensitivity=0.95 and specificity=0.90. Additional markers showed differential changes between responders and slow-responders (nectin-like protein), or correlated with time-to-culture-conversion (KLRK1). Serum proteins involved in the coagulation cascade, neutrophil activity, immunity, inflammation, and tissue remodeling were found to be associated with TB treatment response. A quantitative, non-culture based, five-marker signature predictive of 8-week culture status was identified in this pilot study.
登录
查看更多内容
影响因子:
3.7
作者:
Gold L;Ayers D;Bertino J;Bock C;Bock A;Brody EN;Carter J;Dalby AB;Eaton BE;Fitzwater T;Flather D;Forbes A;Foreman T;Fowler C;Gawande B;Goss M;Gunn M;Gupta S;Halladay D;Heil J;Heilig J;Hicke B;Husar G;Janjic N;Jarvis T;Jennings S;Katilius E;Keeney TR;Kim N;Koch TH;Kraemer S;Kroiss L;Le N;Levine D;Lindsey W;Lollo B;Mayfield W;Mehan M;Mehler R;Nelson SK;Nelson M;Nieuwlandt D;Nikrad M;Ochsner U;Ostroff RM;Otis M;Parker T;Pietrasiewicz S;Resnicow DI;Rohloff J;Sanders G;Sattin S;Schneider D;Singer B;Stanton M;Sterkel A;Stewart A;Stratford S;Vaught JD;Vrkljan M;Walker JJ;Watrobka M;Waugh S;Weiss A;Wilcox SK;Wolfson A;Wolk SK;Zhang C;Zichi D
通讯作者:
Zichi D
DOI:
10.1164/rccm.201105-0827ws
发表时间:
2011-10-15
影响因子:
24.7
作者:
Nahid, Payam;Saukkonen, Jussi;Burman, William
通讯作者:
Burman, William
影响因子:
8.6
作者:
Nemeth, Johannes;Winkler, Heide-Maria;Winkler, Stefan
通讯作者:
Winkler, Stefan
影响因子:
5.4
作者:
Gold, Larry;Walker, Jeffrey J.;Williams, Stephen
通讯作者:
Williams, Stephen
DOI:
10.1016/s0140-6736(06)69342-2
发表时间:
2006-09-16
期刊:
Lancet (London, England)
影响因子:
--
作者:
Agranoff D;Fernandez-Reyes D;Papadopoulos MC;Rojas SA;Herbster M;Loosemore A;Tarelli E;Sheldon J;Schwenk A;Pollok R;Rayner CF;Krishna S
通讯作者:
Krishna S