Literature DB >> 19580427

MammaPrint 70-gene signature: another milestone in personalized medical care for breast cancer patients.

Elzbieta A Slodkowska1, Jeffrey S Ross.   

Abstract

The MammaPrint assay (Agendia BV, The Netherlands) is the first fully commercialized microarray-based multigene assay designed to individualize treatment for patients with breast cancer. MammaPrint, the first assay to be cleared at the 510(k) level by the US FDA's new in vitro diagnostic multivariate index assay classification, is offered as a prognostic test for women under the age of 61 years with either estrogen receptor-positive or -negative, lymph node-negative breast cancer. Unlike the Oncotype DX assay (Genomic Health, CA, USA), this test requires freshly prepared tissues collected into an RNA preservative solution. The 70 genes that comprise the MammaPrint assay are focused primarily on proliferation with additional genes associated with invasion, metastasis, stromal integrity and angiogenesis. The Microarray In Node-negative Disease may Avoid Chemotherapy (MINDACT) trial, sponsored by the European Organization for Research and Treatment of Cancer, involves the assessment of patients in the adjuvant treatment setting by the standard clinicopathologic prognostic factors included on Adjuvant! Online and by the 70-gene MammaPrint assay. The following article will consider the basic biology, technology, ease of clinical use, level of clinical validation and potential clinical utility of this test.

Entities:  

Mesh:

Year:  2009        PMID: 19580427     DOI: 10.1586/erm.09.32

Source DB:  PubMed          Journal:  Expert Rev Mol Diagn        ISSN: 1473-7159            Impact factor:   5.225


  50 in total

Review 1.  Integrative analysis of -omics data and histologic scoring in renal disease and transplantation: renal histogenomics.

Authors:  Paul Perco; Rainer Oberbauer
Journal:  Semin Nephrol       Date:  2010-09       Impact factor: 5.299

Review 2.  Machine learning approaches to drug response prediction: challenges and recent progress.

Authors:  George Adam; Ladislav Rampášek; Zhaleh Safikhani; Petr Smirnov; Benjamin Haibe-Kains; Anna Goldenberg
Journal:  NPJ Precis Oncol       Date:  2020-06-15

Review 3.  Individualization of cancer treatment from radiotherapy perspective.

Authors:  Ala Yaromina; Mechthild Krause; Michael Baumann
Journal:  Mol Oncol       Date:  2012-02-09       Impact factor: 6.603

Review 4.  Pulmonary adenocarcinoma: implications of the recent advances in molecular biology, treatment and the IASLC/ATS/ERS classification.

Authors:  Swaroop Revannasiddaiah; Priyanka Thakur; Bhaskar Bhardwaj; Sridhar Papaiah Susheela; Irappa Madabhavi
Journal:  J Thorac Dis       Date:  2014-10       Impact factor: 2.895

Review 5.  Extended Adjuvant Endocrine Therapy in Hormone Receptor-Positive Early Breast Cancer.

Authors:  Dara B Bracken-Clarke; Mairi W Lucas; Michaela J Higgins
Journal:  Breast Care (Basel)       Date:  2017-06-28       Impact factor: 2.860

6.  Predicting relapse in patients with medulloblastoma by integrating evidence from clinical and genomic features.

Authors:  Pablo Tamayo; Yoon-Jae Cho; Aviad Tsherniak; Heidi Greulich; Lauren Ambrogio; Netteke Schouten-van Meeteren; Tianni Zhou; Allen Buxton; Marcel Kool; Matthew Meyerson; Scott L Pomeroy; Jill P Mesirov
Journal:  J Clin Oncol       Date:  2011-02-28       Impact factor: 44.544

7.  Knowledge about genomic recurrence risk testing among breast cancer survivors.

Authors:  Isaac M Lipkus; Susan T Vadaparampil; Paul B Jacobsen; Cheryl A Miree
Journal:  J Cancer Educ       Date:  2011-12       Impact factor: 2.037

8.  Robust multi-tissue gene panel for cancer detection.

Authors:  Joseph Irgon; C Chris Huang; Yi Zhang; Dmitri Talantov; Gyan Bhanot; Sándor Szalma
Journal:  BMC Cancer       Date:  2010-06-22       Impact factor: 4.430

9.  Combining large number of weak biomarkers based on AUC.

Authors:  Li Yan; Lili Tian; Song Liu
Journal:  Stat Med       Date:  2015-07-30       Impact factor: 2.373

10.  Epithelial-mesenchymal transition-associated secretory phenotype predicts survival in lung cancer patients.

Authors:  Ajaya Kumar Reka; Guoan Chen; Richard C Jones; Ravi Amunugama; Sinae Kim; Alla Karnovsky; Theodore J Standiford; David G Beer; Gilbert S Omenn; Venkateshwar G Keshamouni
Journal:  Carcinogenesis       Date:  2014-02-07       Impact factor: 4.944

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.