Literature DB >> 18515733

Commercialized multigene predictors of clinical outcome for breast cancer.

Jeffrey S Ross1, Christos Hatzis, W Fraser Symmans, Lajos Pusztai, Gabriel N Hortobágyi.   

Abstract

In the past 5 years, a number of commercialized multigene prognostic and predictive tests have entered the complex and expanding landscape of breast cancer companion diagnostics. These tests have used a variety of formats ranging from the familiar slide-based assays of immunohistochemistry and fluorescence in situ hybridization to the nonmorphology-driven molecular platforms of quantitative multiplex real-time polymerase chain reaction and genomic microarray profiling. In this review, 14 multigene assays are evaluated as to their scientific validation, current clinical utility, regulatory approval status, and estimated cost-benefit ratio. Emphasis is placed on two tests: oncotype DX and MammaPrint. Current evidence indicates that the oncotype DX test has the advantages of earlier commercial launch, wide acceptance for payment by third-party payors in the U.S., ease of use of formalin-fixed paraffin-embedded tissues, recent listing by the American Society of Clinical Oncology Breast Cancer Tumor Markers Update Committee as recommended for use, continuous scoring system algorithm, ability to serve as both a prognostic test and predictive test for certain hormonal and chemotherapeutic agents, demonstrated cost-effectiveness in one published study, and a high accrual rate for the prospective validation clinical trial (Trial Assigning Individualized Options for Treatment). The MammaPrint assay has the advantages of a 510(k) clearance by the U.S. Food and Drug Administration, a larger gene number, which may enhance further utility, and a potentially wider patient eligibility, including lymph node-positive, estrogen receptor (ER)-negative, and younger patients being accrued into the prospective trial (Microarray in Node-Negative Disease May Avoid Chemotherapy). A number of other assays have specific predictive goals that are most often focused on the efficacy of tamoxifen in ER-positive patients, such as the two-gene ratio test and the cytochrome P450 CYP2D6 genotyping assay.

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Year:  2008        PMID: 18515733     DOI: 10.1634/theoncologist.2007-0248

Source DB:  PubMed          Journal:  Oncologist        ISSN: 1083-7159


  68 in total

Review 1.  Gene-expression-based prognostic assays for breast cancer.

Authors:  Chungyeul Kim; Soonmyung Paik
Journal:  Nat Rev Clin Oncol       Date:  2010-05-04       Impact factor: 66.675

2.  Is Chemoendocrine Treatment without Alternative?

Authors:  Richard Greil
Journal:  Breast Care (Basel)       Date:  2008-08-22       Impact factor: 2.860

Review 3.  DNA microarray-based gene expression profiling of estrogenic chemicals.

Authors:  Ryoiti Kiyama; Yun Zhu
Journal:  Cell Mol Life Sci       Date:  2014-01-08       Impact factor: 9.261

4.  The effect of Oncotype DX recurrence score on treatment recommendations for patients with estrogen receptor-positive early stage breast cancer and correlation with estimation of recurrence risk by breast cancer specialists.

Authors:  Jennifer E Joh; Nicole N Esposito; John V Kiluk; Christine Laronga; M Catherine Lee; Loretta Loftus; Hatem Soliman; Judy C Boughey; Carol Reynolds; Thomas J Lawton; Peter I Acs; Lucio Gordan; Geza Acs
Journal:  Oncologist       Date:  2011-10-20

5.  Chip-based nLC-TOF-MS is a highly stable technology for large-scale high-throughput analyses.

Authors:  L Renee Ruhaak; Sandra L Taylor; Suzanne Miyamoto; Karen Kelly; Gary S Leiserowitz; David Gandara; Carlito B Lebrilla; Kyoungmi Kim
Journal:  Anal Bioanal Chem       Date:  2013-03-23       Impact factor: 4.142

6.  Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.

Authors:  Vlad Popovici; Weijie Chen; Brandon G Gallas; Christos Hatzis; Weiwei Shi; Frank W Samuelson; Yuri Nikolsky; Marina Tsyganova; Alex Ishkin; Tatiana Nikolskaya; Kenneth R Hess; Vicente Valero; Daniel Booser; Mauro Delorenzi; Gabriel N Hortobagyi; Leming Shi; W Fraser Symmans; Lajos Pusztai
Journal:  Breast Cancer Res       Date:  2010-01-11       Impact factor: 6.466

7.  Survival Online: a web-based service for the analysis of correlations between gene expression and clinical and follow-up data.

Authors:  Luca Corradi; Valentina Mirisola; Ivan Porro; Livia Torterolo; Marco Fato; Paolo Romano; Ulrich Pfeffer
Journal:  BMC Bioinformatics       Date:  2009-10-15       Impact factor: 3.169

8.  Integrating complex genomic datasets and tumour cell sensitivity profiles to address a 'simple' question: which patients should get this drug?

Authors:  Cyril Benes; Jeff Settleman
Journal:  BMC Med       Date:  2009-12-14       Impact factor: 8.775

Review 9.  Breast cancer in young women and its impact on reproductive function.

Authors:  M Hickey; M Peate; C M Saunders; M Friedlander
Journal:  Hum Reprod Update       Date:  2009-01-27       Impact factor: 15.610

10.  MicroRNA signatures predict oestrogen receptor, progesterone receptor and HER2/neu receptor status in breast cancer.

Authors:  Aoife J Lowery; Nicola Miller; Amanda Devaney; Roisin E McNeill; Pamela A Davoren; Christophe Lemetre; Vladimir Benes; Sabine Schmidt; Jonathon Blake; Graham Ball; Michael J Kerin
Journal:  Breast Cancer Res       Date:  2009-05-11       Impact factor: 6.466

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