Literature DB >> 18197005

Critical review of microarray-based prognostic tests and trials in breast cancer.

Serge Koscielny1.   

Abstract

PURPOSE OF REVIEW: We critically review the methods used in microarray profiling, the reliability of published genomic signatures and the design of ongoing trials based on two of these signatures. RECENT
FINDINGS: The main limitations of microarray prognostic signatures are known: instability of gene lists, overoptimistic performance indicators and inadequate validation. Two commercially available gene expression-based prognostic tests (MammaPrint and OncotypeDX) are currently being assessed in two large randomized clinical trials. The overall concordance between patient classification resulting from these tests is only slightly better than the concordance between MammaPrint and the Saint Gallen risk. In North America, TAILORx is specifically evaluating the usefulness of chemotherapy in intermediate-risk patients. In the case of MINDACT, ongoing in the European Union, clinical validation of the prognostic test will be considered successful if the proportion of failures among patients classified as having a good prognosis by the prognostic test is below a predefined level. Randomization will not address the validation of the gene expression-based prognostic test in either of these two trials.
SUMMARY: Microarray-based prognostic tests are irremediably moving to the clinics, but their clinical utility might never be formally established.

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Year:  2008        PMID: 18197005     DOI: 10.1097/GCO.0b013e3282f39d9e

Source DB:  PubMed          Journal:  Curr Opin Obstet Gynecol        ISSN: 1040-872X            Impact factor:   1.927


  10 in total

Review 1.  Ten questions about systems biology.

Authors:  Michael J Joyner; Bente K Pedersen
Journal:  J Physiol       Date:  2011-01-04       Impact factor: 5.182

Review 2.  Multidimensionality of microarrays: statistical challenges and (im)possible solutions.

Authors:  Stefan Michiels; Andrew Kramar; Serge Koscielny
Journal:  Mol Oncol       Date:  2011-02-03       Impact factor: 6.603

3.  Identification of CD44 as a surface biomarker for drug resistance by surface proteome signature technology.

Authors:  Jason W Cain; Robert S Hauptschein; Jean K Stewart; Tugba Bagci; Gary G Sahagian; Daniel G Jay
Journal:  Mol Cancer Res       Date:  2011-02-25       Impact factor: 5.852

Review 4.  Signatures of tumor-immune interactions as biomarkers for breast cancer prognosis.

Authors:  Masoud H Manjili; Kayvan Najarian; Xiang-Yang Wang
Journal:  Future Oncol       Date:  2012-06       Impact factor: 3.404

5.  Predictive and prognostic molecular markers for cancer medicine.

Authors:  Sunali Mehta; Andrew Shelling; Anita Muthukaruppan; Annette Lasham; Cherie Blenkiron; George Laking; Cristin Print
Journal:  Ther Adv Med Oncol       Date:  2010-03       Impact factor: 8.168

6.  An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer.

Authors:  Iker Sánchez-Navarro; Angelo Gámez-Pozo; Alvaro Pinto; David Hardisson; Rosario Madero; Rocío López; Belén San José; Pilar Zamora; Andrés Redondo; Jaime Feliu; Paloma Cejas; Manuel González Barón; Juan Angel Fresno Vara; Enrique Espinosa
Journal:  BMC Cancer       Date:  2010-06-28       Impact factor: 4.430

7.  Sorafenib plus dacarbazine in solid tumors: a phase I study with dynamic contrast-enhanced ultrasonography and genomic analysis of sequential tumor biopsy samples.

Authors:  Vladimir Lazar; Nathalie Lassau; Guillaume Meurice; Yohann Loriot; Carol Peña; Christophe Massard; Caroline Robert; Thomas Robert; Marie-Aude Le Berre; Thierry de Baere; Philippe Dessen; Jean-Charles Soria; Jean-Pierre Armand
Journal:  Invest New Drugs       Date:  2013-08-27       Impact factor: 3.850

8.  Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

Authors:  Yotam Drier; Eytan Domany
Journal:  PLoS One       Date:  2011-03-14       Impact factor: 3.240

9.  Comparison of prognostic gene profiles using qRT-PCR in paraffin samples: a retrospective study in patients with early breast cancer.

Authors:  Enrique Espinosa; Iker Sánchez-Navarro; Angelo Gámez-Pozo; Alvaro Pinto Marin; David Hardisson; Rosario Madero; Andrés Redondo; Pilar Zamora; Belén San José Valiente; Marta Mendiola; Manuel González Barón; Juan Angel Fresno Vara
Journal:  PLoS One       Date:  2009-06-15       Impact factor: 3.240

10.  The utility of conventional and molecular pathology in managing breast cancer.

Authors:  D Craig Allred
Journal:  Breast Cancer Res       Date:  2008-12-18       Impact factor: 6.466

  10 in total

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