Converting a breast cancer microarray signature into a high-throughput diagnostic test

被引:345
作者
Glas, Annuska M.
Floore, Arno
Delahaye, Leonie J. M. J.
Witteveen, Anke T.
Pover, Rob C. F.
Bakx, Niels
Lahti-Domenici, Jaana S. T.
Bruinsma, Tako J.
Warmoes, Marc O.
Bernards, Rene
Wessels, Lodewyk F. A.
Van 't Veer, Laura J.
机构
[1] Agendia BV, Slotervaart Med Ctr 9D, NL-1066 EC Amsterdam, Netherlands
[2] Netherlands Canc Inst, Dept Mol Biol, NL-1066 CX Amsterdam, Netherlands
关键词
D O I
10.1186/1471-2164-7-278
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: A 70-gene tumor expression profile was established as a powerful predictor of disease outcome in young breast cancer patients. This profile, however, was generated on microarrays containing 25,000 60-mer oligonucleotides that are not designed for processing of many samples on a routine basis. Results: To facilitate its use in a diagnostic setting, the 70-gene prognosis profile was translated into a customized microarray (MammaPrint) containing a reduced set of 1,900 probes suitable for high throughput processing. RNA of 162 patient samples from two previous studies was subjected to hybridization to this custom array to validate the prognostic value. Classification results obtained from the original analysis were then compared to those generated using the algorithms based on the custom microarray and showed an extremely high correlation of prognosis prediction between the original data and those generated using the custom mini-array ( p < 0.0001). Conclusion: In this report we demonstrate for the first time that microarray technology can be used as a reliable diagnostic tool. The data clearly demonstrate the reproducibility and robustness of the small custom-made microarray. The array is therefore an excellent tool to predict outcome of disease in breast cancer patients.
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页数:10
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共 25 条
[1]   Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling [J].
Alizadeh, AA ;
Eisen, MB ;
Davis, RE ;
Ma, C ;
Lossos, IS ;
Rosenwald, A ;
Boldrick, JG ;
Sabet, H ;
Tran, T ;
Yu, X ;
Powell, JI ;
Yang, LM ;
Marti, GE ;
Moore, T ;
Hudson, J ;
Lu, LS ;
Lewis, DB ;
Tibshirani, R ;
Sherlock, G ;
Chan, WC ;
Greiner, TC ;
Weisenburger, DD ;
Armitage, JO ;
Warnke, R ;
Levy, R ;
Wilson, W ;
Grever, MR ;
Byrd, JC ;
Botstein, D ;
Brown, PO ;
Staudt, LM .
NATURE, 2000, 403 (6769) :503-511
[2]   Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide chemotherapy in breast cancer [J].
Ayers, M ;
Symmans, WF ;
Stec, J ;
Damokosh, AI ;
Clark, E ;
Hess, K ;
Lecocke, M ;
Metivier, J ;
Booser, D ;
Ibrahim, N ;
Valero, V ;
Royce, M ;
Arun, B ;
Whitman, G ;
Ross, J ;
Sneige, N ;
Hortobagyi, GN ;
Pusztai, L .
JOURNAL OF CLINICAL ONCOLOGY, 2004, 22 (12) :2284-2293
[3]   Molecular classification of cutaneous malignant melanoma by gene expression profiling [J].
Bittner, M ;
Meitzer, P ;
Chen, Y ;
Jiang, Y ;
Seftor, E ;
Hendrix, M ;
Radmacher, M ;
Simon, R ;
Yakhini, Z ;
Ben-Dor, A ;
Sampas, N ;
Dougherty, E ;
Wang, E ;
Marincola, F ;
Gooden, C ;
Lueders, J ;
Glatfelter, A ;
Pollock, P ;
Carpten, J ;
Gillanders, E ;
Leja, D ;
Dietrich, K ;
Beaudry, C ;
Berens, M ;
Alberts, D ;
Sondak, V ;
Hayward, N ;
Trent, J .
NATURE, 2000, 406 (6795) :536-540
[4]   ArrayExpress - a public repository for microarray gene expression data at the EBI [J].
Brazma, A ;
Parkinson, H ;
Sarkans, U ;
Shojatalab, M ;
Vilo, J ;
Abeygunawardena, N ;
Holloway, E ;
Kapushesky, M ;
Kemmeren, P ;
Lara, GG ;
Oezcimen, A ;
Rocca-Serra, P ;
Sansone, SA .
NUCLEIC ACIDS RESEARCH, 2003, 31 (01) :68-71
[5]   Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer [J].
Buyse, Marc ;
Loi, Sherene ;
van't Veer, Laura ;
Viale, Giuseppe ;
Delorenzi, Mauro ;
Glas, Annuska M. ;
d'Assignies, Mahasti Saghatchian ;
Bergh, Jonas ;
Lidereau, Rosette ;
Ellis, Paul ;
Harris, Adrian ;
Bogaerts, Jan ;
Therasse, Patrick ;
Floore, Arno ;
Amakrane, Mohamed ;
Piette, Fanny ;
Rutgers, Emiel ;
Sotiriou, Christos ;
Cardoso, Fatima ;
Piccart, Martine J. .
JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2006, 98 (17) :1183-1192
[6]   Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer [J].
Chang, JC ;
Wooten, EC ;
Tsimelzon, A ;
Hilsenbeck, SG ;
Gutierrez, MC ;
Elledge, R ;
Mohsin, S ;
Osborne, CK ;
Chamness, GC ;
Allred, DC ;
O'Connell, P .
LANCET, 2003, 362 (9381) :362-369
[7]   Use of hybridization kinetics for differentiating specific from non-specific binding to oligonucleotide microarrays [J].
Dai, HY ;
Meyer, M ;
Stepaniants, S ;
Ziman, M ;
Stoughton, R .
NUCLEIC ACIDS RESEARCH, 2002, 30 (16) :e86
[8]   Gene expression profiling in follicular lymphoma to assess clinical aggressiveness and to guide the choice of treatment [J].
Glas, AM ;
Kersten, MJ ;
Delahaye, LJMJ ;
Witteveen, AT ;
Kibbelaar, RE ;
Velds, A ;
Wessels, LFA ;
Joosten, P ;
Kerkhoven, RM ;
Bernards, R ;
van Krieken, JHJM ;
Kluin, PM ;
van't Veer, LJ ;
de Jong, D .
BLOOD, 2005, 105 (01) :301-307
[9]   Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring [J].
Golub, TR ;
Slonim, DK ;
Tamayo, P ;
Huard, C ;
Gaasenbeek, M ;
Mesirov, JP ;
Coller, H ;
Loh, ML ;
Downing, JR ;
Caligiuri, MA ;
Bloomfield, CD ;
Lander, ES .
SCIENCE, 1999, 286 (5439) :531-537
[10]   Changes in gene expression associated with response to neoadjuvant chemotherapy in breast cancer [J].
Hannemann, J ;
Oosterkamp, HM ;
Bosch, CAJ ;
Velds, A ;
Wessels, LFA ;
Loo, C ;
Rutgers, EJ ;
Rodenhuis, S ;
van de Vijver, MJ .
JOURNAL OF CLINICAL ONCOLOGY, 2005, 23 (15) :3331-3342