Open AccessJournal Article
Molecular profiling assays in breast cancer: are we ready for prime time?
Yesim Gökmen-Polar,Sunil Badve +1 more
TLDR
The current data on commercially available molecular profiling assays in breast cancer is presented and the challenges surrounding their incorporation into routine clinical practice as prognostic and predictive tools are discussed.Abstract:
Breast cancer is a heterogeneous disease with diverse morphologies, molecular characteristics, and clinical behavior. The advances in molecular profiling technologies have changed our understanding of breast cancer and led to the identification of prognostic/predictive gene signatures. Despite the huge quantity of information gleaned from these profiling technologies and the increasing number of gene signatures, their incorporation into clinical decision making is a slow process and is limited in various aspects. The 70-gene assay (MammaPrint, Agendia, Netherlands) and the 21-gene assay (Oncotype DX, Genomic Health, USA) are the most widely used breast cancer multigene classifier assays. A 50-gene assay (PAM50, NanoString, USA) has shown promise but needs further independent validation. In this review, we will present the current data on commercially available molecular profiling assays in breast cancer and discuss the challenges surrounding their incorporation into routine clinical practice as prognostic and predictive tools.read more
Citations
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Breast cancer prognostic classification in the molecular era: the role of histological grade
Emad A. Rakha,Jorge S. Reis-Filho,Frederick L. Baehner,David J. Dabbs,Thomas Decker,Vincenzo Eusebi,Stephen B. Fox,Shu Ichihara,Jocelyne Jacquemier,Sunil R. Lakhani,José Palacios,Andrea L. Richardson,Stuart J. Schnitt,Fernando Schmitt,Puay Hoon Tan,Gary M.K. Tse,Sunil V. Badve,Ian O. Ellis +17 more
TL;DR: An analysis of the validity of Histological grade as a prognostic factor and a consensus view on the significance of histological grade and its role in breast cancer classification and staging systems in this era of emerging clinical use of molecular classifiers are presented.
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Prognostic relevance of cancer-associated fibroblasts in human cancer.
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Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients.
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Triple-negative breast carcinoma: current and emerging concepts.
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Molecular and protein markers for clinical decision making in breast cancer: Today and tomorrow
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References
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Charles M. Perou,Therese Sørlie,Michael B. Eisen,Matt van de Rijn,Stefanie S. Jeffrey,Christian A. Rees,Jonathan R. Pollack,Douglas T. Ross,Hilde Johnsen,Lars A. Akslen,Øystein Fluge,Alexander Pergamenschikov,Cheryl A. Williams,Shirley Zhu,Per Eystein Lønning,Anne Lise Børresen-Dale,Patrick O. Brown,David Botstein +17 more
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Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications
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TL;DR: Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
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Gene expression profiling predicts clinical outcome of breast cancer
Laura J. van't Veer,Hongyue Dai,Marc J. van de Vijver,Yudong D. He,Augustinus A. M. Hart,Mao Mao,Hans Peterse,Karin van der Kooy,Matthew J. Marton,Anke T. Witteveen,George J. Schreiber,Ron M. Kerkhoven,Christopher J. Roberts,Peter S. Linsley,René Bernards,Stephen H. Friend +15 more
TL;DR: DNA microarray analysis on primary breast tumours of 117 young patients is used and supervised classification is applied to identify a gene expression signature strongly predictive of a short interval to distant metastases (‘poor prognosis’ signature) in patients without tumour cells in local lymph nodes at diagnosis, providing a strategy to select patients who would benefit from adjuvant therapy.
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A Gene-Expression Signature as a Predictor of Survival in Breast Cancer
Marc J. van de Vijver,Yudong D. He,Laura J. van't Veer,Hongyue Dai,Augustinus A. M. Hart,D.W. Voskuil,George J. Schreiber,Johannes L. Peterse,Christopher J. Roberts,Matthew J. Marton,Mark Parrish,Douwe Atsma,Anke T. Witteveen,Annuska M. Glas,Leonie J. M. J. Delahaye,Tony van de Velde,Harry Bartelink,Sjoerd Rodenhuis,Emiel J. Th. Rutgers,Stephen H. Friend,René Bernards +20 more
TL;DR: The gene-expression profile studied is a more powerful predictor of the outcome of disease in young patients with breast cancer than standard systems based on clinical and histologic criteria.
Journal ArticleDOI
A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer
Soonmyung Paik,Steven Shak,Gong Tang,Chungyeul Kim,Joffre B. Baker,Maureen T. Cronin,Frederick L. Baehner,Michael G. Walker,Drew Watson,Taesung Park,William Hiller,Edwin R. Fisher,D. Lawrence Wickerham,John Bryant,Norman Wolmark +14 more
TL;DR: The recurrence score has been validated as quantifying the likelihood of distant recurrence in tamoxifen-treated patients with node-negative, estrogen-receptor-positive breast cancer and could be used as a continuous function to predict distant recurrent in individual patients.
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