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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Local Therapy and Survival in Breast Cancer
TL;DR: Recent evidence supports a larger role for aggressive, local therapy for breast cancer, since the failure to achieve initial local control allows some tumors to disseminate later, reducing a patient's chance of long-term survival.
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Biology of breast cancer in young women
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TL;DR: The potential role of genomic signatures, the impact of pregnancy and breastfeeding on breast cancer biology, and how even current knowledge might advance the clinical management of young breast cancer patients are elucidated.
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Distinct gene mutation profiles among luminal-type and basal-type breast cancer cell lines
Antoinette Hollestelle,Jord H. A. Nagel,Marcel Smid,Suzanne Lam,Fons Elstrodt,Marijke Wasielewski,Ser Sue Ng,Pim J. French,Justine K. Peeters,Marieke J. Rozendaal,Muhammad Riaz,Daphne G. Koopman,Timo L.M. ten Hagen,Bertie de Leeuw,Ellen C. Zwarthoff,Amina F A S Teunisse,Peter J. van der Spek,Jan G. M. Klijn,Winand N.M. Dinjens,Stephen P. Ethier,Hans Clevers,Aart G. Jochemsen,Michael A. den Bakker,John A. Foekens,John W.M. Martens,Mieke Schutte +25 more
TL;DR: Two subtype-specific gene mutation profiles constitute a genetic basis for the heterogeneity observed among human breast cancers, providing clues for their underlying biology and providing guidance for targeted pharmacogenetic intervention in breast cancer patients.
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Personalized medicine: progress and promise.
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A miR-200 microRNA cluster as prognostic marker in advanced ovarian cancer.
Xiaoxia Hu,Dusten M. Macdonald,Phyllis C. Huettner,Zhihui Feng,Issam El Naqa,Julie K. Schwarz,David G. Mutch,Perry W. Grigsby,Simon N. Powell,Xiaowei Wang +9 more
TL;DR: The main aim of this study is to identify novel prognostic biomarkers for advanced ovarian cancer and suggests that miR-200 miRNAs could play an important regulatory role in ovarian cancer.
References
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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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