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
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TLDR
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.Abstract:
background The likelihood of distant recurrence in patients with breast cancer who have no involved lymph nodes and estrogen-receptor–positive tumors is poorly defined by clinical and histopathological measures. methods We tested whether the results of a reverse-transcriptase–polymerase-chain-reaction (RT-PCR) assay of 21 prospectively selected genes in paraffin-embedded tumor tissue would correlate with the likelihood of distant recurrence in patients with node-negative, tamoxifen-treated breast cancer who were enrolled in the National Surgical Adjuvant Breast and Bowel Project clinical trial B-14. The levels of expression of 16 cancerrelated genes and 5 reference genes were used in a prospectively defined algorithm to calculate a recurrence score and to determine a risk group (low, intermediate, or high) for each patient. results Adequate RT-PCR profiles were obtained in 668 of 675 tumor blocks. The proportions of patients categorized as having a low, intermediate, or high risk by the RT-PCR assay were 51, 22, and 27 percent, respectively. The Kaplan–Meier estimates of the rates of distant recurrence at 10 years in the low-risk, intermediate-risk, and high-risk groups were 6.8 percent (95 percent confidence interval, 4.0 to 9.6), 14.3 percent (95 percent confidence interval, 8.3 to 20.3), and 30.5 percent (95 percent confidence interval, 23.6 to 37.4). The rate in the low-risk group was significantly lower than that in the high-risk group (P<0.001). In a multivariate Cox model, the recurrence score provided significant predictive power that was independent of age and tumor size (P<0.001). The recurrence score was also predictive of overall survival (P<0.001) and could be used as a continuous function to predict distant recurrence in individual patients. conclusions 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.read more
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Relevance of Spatial Heterogeneity of Immune Infiltration for Predicting Risk of Recurrence After Endocrine Therapy of ER+ Breast Cancer
Andreas Heindl,Andreas Heindl,Ivana Sestak,Kalnisha Naidoo,Jack Cuzick,Mitchell Dowsett,Mitchell Dowsett,Yinyin Yuan,Yinyin Yuan +8 more
TL;DR: The results provide a missing link between tumor immunity and disease outcome in ER+ disease by examining tumor spatial architecture and suggest a lasting memory of protumor immunity that may impact disease progression and evolution of endocrine treatment resistance.
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Personalized medicine: Factors influencing reimbursement
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TL;DR: In order to achieve favorable coverage and reimbursement and to support premium prices for PM, manufacturers will need to bring better clinical evidence to the marketplace and better establish the value of their products.
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A functional Notch–survivin gene signature in basal breast cancer
Connie Wing-Ching Lee,Karl Simin,Qin Liu,Janet Plescia,Minakshi Guha,Ashraf Khan,Chung-Cheng Hsieh,Dario C. Altieri +7 more
TL;DR: A Notch-1–survivin functional gene signature is a hallmark of basal breast cancer, and may contribute to disease pathogenesis, and Antagonists of Notch and survivin currently in the clinic may be tested as novel molecular therapy for these recurrence-prone patients.
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Molecular Dependence of Estrogen Receptor–Negative Breast Cancer on a Notch-Survivin Signaling Axis
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Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration.
Lisa M. McShane,Margaret M. Cavenagh,Tracy Lively,David A. Eberhard,William L. Bigbee,P. M. Williams,Jill P. Mesirov,Mei Yin C. Polley,Kelly Y. Kim,James V. Tricoli,Jeremy M. G. Taylor,Deborah J. Shuman,Richard M. Simon,James H. Doroshow,Barbara A. Conley +14 more
TL;DR: A checklist of criteria to consider when evaluating the body of evidence supporting the clinical use of a predictor to guide patient therapy is presented, including issues pertaining to specimen and assay requirements, the soundness of the process for developing predictor models, expectations regarding clinical study design and conduct, and attention to regulatory, ethical, and legal issues.
References
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Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications
Therese Sørlie,Charles M. Perou,Robert Tibshirani,Turid Aas,Stephanie Geisler,Hilde Johnsen,Trevor Hastie,Michael B. Eisen,Matt van de Rijn,Stefanie S. Jeffrey,T. Thorsen,Hanne Quist,John C. Matese,Patrick O. Brown,David Botstein,Per Eystein Lønning,Anne Lise Børresen-Dale +16 more
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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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