A gene-expression signature as a predictor of survival in breast cancer.
By M. J. van de Vijver, Yudong He, L. J. van ’t Veer, H. Dai, A. Hart, D. Voskuil, G. Schreiber, J. Peterse, C. Roberts, M. Marton and 11 more. New England Journal of Medicine, 2002
6,396 citations recorded by the source corpus.
Subfields: Cancer Research, Genetics, Pathology and Forensic Medicine
View Paper: https://www.semanticscholar.org/paper/f3c0ad0efa1e2d6447f9e200179d3c6aa33df981
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cancer Research
- H. Horlings
- R. Weinberg
- Balázs Győrffy
- K. Pantel
- Scott Valastyan
- Aleix Prat
- Navdeep S. Chandel
- Charles M. Perou
In Genetics
- Jieping Ye
- Jun Liu
- R. Weinberg
- Jelle J. Goeman
- Aldo Solari
- Guillaume Obozinski
- Robert Tibshirani
- Douglas B. Kell
In Pathology and Forensic Medicine
- Aleix Prat
- J. Reis-Filho
- S. Shak
- M. Klinkhammer-Schalke
- Jacques E. Dumont
- Douglas G. Altman
- John N. Weinstein
- Allan Balmain
Citations in the corpus
- Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer. (2006, methodology): “For example, histologic grade was not significant in a multivariate model with the van’t Veer ( 4 ) 70-gene predictor, whereas grade remained highly significant (P < 0.001) in a multivariate model including the Paik 21-gene signature (47).”
- MYB function in normal and cancer cells (2008, methodology): “These data have been reproduced in several mRNA profiling studie”
- Strategies for discovering novel cancer biomarkers through utilization of emerging technologies (2008, methodology): “The 70-gene-panel microarray study of survival prediction led to the development of MammaPrint ® (Agendia, Amsterdam, The Netherlands)”
- On the C-statistics for Evaluating Overall Adequacy of Risk Prediction Procedures with Censored Survival Data (2011, neutral): “[22].”
- Meeting highlights: international expert consensus on the primary therapy of early breast cancer 2005. (2005, methodology): “Gene profiling using cDNA microarrays was found to correlate with detailed clinico-pathological characteristics and clinical outcome [41, 42], yet this approach too was considered to require further prospective validation.”
- Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach (2015, methodology): “Note that in [15], the breast cancer patients with the same data were clustered into two groups based on a 70-gene prognosis profile,”
- Gene expression profiling and histopathological characterization of triple-negative/basal-like breast carcinomas (2007, background): “We have previously identified a 70-gene prognosis profile [12, 13 ].”
- Optimal number of features as a function of sample size for various classification rules (2005, methodology): “The patient data come from a microarray-based cancerclassification study (van de Vijver et al., 2002) that analyzes a large number of microarrays prepared with RNA from breast tumor samples of 295 patients.”