Gene expression profile predicts outcome after anthracycline-based adjuvant chemotherapy in early breast cancer View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-06

AUTHORS

François Bertucci, Nathalie Borie, Henri Roche, Thomas Bachelot, Jean-Marc Le Doussal, Gaëtan Macgrogan, Stéphane Debono, Agnès Martinec, Isabelle Treilleux, Pascal Finetti, Benjamin Esterni, Jean-Marc Extra, Jean Geneve, Fabienne Hermitte, Christian Chabannon, Jocelyne Jacquemier, Anne-Laure Martin, Michel Longy, Dominique Maraninchi, Vincent Fert, Daniel Birnbaum, Patrice Viens

ABSTRACT

Prognosis of early beast cancer is heterogeneous. Today, no histoclinical or biological factor predictive for clinical outcome after adjuvant anthracycline-based chemotherapy (CT) has been validated and introduced in routine use. Using DNA microarrays, we searched for a gene expression signature associated with metastatic relapse after adjuvant anthracycline-based CT without taxane. We profiled a multicentric series of 595 breast cancers including 498 treated with such adjuvant CT. The identification of the prognostic signature was done using a metagene-based supervised approach in a learning set of 323 patients. The signature was then tested on an independent validation set comprising 175 similarly treated patients, 128 of them from the PACS01 prospective clinical trial. We identified a 3-metagene predictor of metastatic relapse in the learning set, and confirmed its independent prognostic impact in the validation set. In multivariate analysis, the predictor outperformed the individual current prognostic factors, as well as the Nottingham Prognostic Index-based classifier, both in the learning and the validation sets, and added independent prognostic information. Among the patients treated with adjuvant anthracycline-based CT, with a median follow-up of 68 months, the 5-year metastasis-free survival was 82% in the "good-prognosis" group and 56% in the "poor-prognosis" group. Our predictor refines the prediction of metastasis-free survival after adjuvant anthracycline-based CT and might help tailoring adjuvant CT regimens. More... »

PAGES

363-373

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10549-010-1003-z

    DOI

    http://dx.doi.org/10.1007/s10549-010-1003-z

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1007524045

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/20585850


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    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10549-010-1003-z'

    N-Triples is a line-based linked data format ideal for batch operations.

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    Turtle is a human-readable linked data format.

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