Repeated observation of breast tumor subtypes in independent gene expression data sets
By T. Sørlie, Robert Tibshirani, Joel Parker, Trevor J. Hastie, James Stephen Marron, Andrew B. Nobel, Shibing Deng, H. Johnsen, Robert Pesich, S. Geisler and 6 more. Proceedings of the National Academy of Sciences of the United States of America, 2003
5,528 citations recorded by the source corpus.
Subfields: Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/c8ab2dddf63bea242ddf0c441812eaf76297fff4
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
- J. Massagué
- Daniel C. Koboldt
- Jill P. Mesirov
- Zena Werb
- J. Reis-Filho
- Aleix Prat
- M. Wiznerowicz
In Molecular Biology
- H. Horlings
- Peter W. Laird
- Elaine R. Mardis
- Hui Shen
- Daniel C. Koboldt
- Manel Esteller
- S. Baylin
- Alan Ashworth
Citations in the corpus
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- Homologous Recombination Deficiency (HRD) Score Predicts Response to Platinum-Containing Neoadjuvant Chemotherapy in Patients with Triple-Negative Breast Cancer (2016, background): “Sporadic (BRCA1 and BRCA2 germline wild type) TNBCs share many characteristics with BRCA1 mutation-associated cancers, including a basal-like gene expression profile, frequent p53 mutations, and a high burden of genomic aberrations such as loss of heterozygosity (1-7).”
- Differential Response to Neoadjuvant Chemotherapy Among 7 Triple-Negative Breast Cancer Molecular Subtypes (2013, background): “Even for the well-known intrinsic subtypes, several types of gene signatures have been derived in each study, and none of the classification systems tested have produced perfect agreement (8, 21-23).”
- A Comparison of MCC and CEN Error Measures in Multi-Class Prediction (2010, background): “, in medical diagnosis tasks such as cancer subtyping [33] or image classification problems (e.”
- PAGE: Parametric Analysis of Gene Set Enrichment (2005, neutral): “While individual microarray studies can be highly informative, it is generally difficult to compare independently obtained data sets addressing the same biological problem [18], regardless of whether the same or different microarray platform was used [19-23].”
- siRNA vs. shRNA: similarities and differences. (2009, background): “expression signatures) identified in tumor samples from patients with breast cancer are not only strongly correlated with prognosis [1–4] but can actually be subclassified into differing prognostic categories [5].”
- Molecular classification and molecular forecasting of breast cancer: ready for clinical application? (2005, background): “Luminal A has, in general, higher expression of ER-related genes and lower expression of proliferative genes than luminal B.(5,8)”
- Supervised risk predictor of breast cancer based on intrinsic subtypes. (2009, positive): “To identify prototypic tumor samples, we started with an expanded “intrinsic” gene set comprised of genes found in four previous microarray studies.(1,6,8,11) The normal-like class was represented using true “normals” from reduction mammoplasty or grossly uninvolved tissue, thus we have removed the ”
- TGFbeta primes breast tumors for lung metastasis seeding through angiopoietin-like 4. (2008, neutral): “Within poorprognosis tumor subsets defined by other features, such as size >2cm, basal subtype geneexpression signature (Sorlie et al., 2003), 70-gene poor prognosis signature (van de Vijver et al.”
- Molecular classification of head and neck squamous cell carcinomas using patterns of gene expression. (2004, methodology): “Immunohistochemical (IHC) analysis of Figures 1C and 1E. Contained within Figure 1C were the genes these tumors for gene products from Figure 1E showed that all for Bullous Pemphigoid Antigen 1, P-Cadherin, Laminin 2, 16 tested had high expression of Cytokeratin 14 and 14/16 were Collagen XVII- , an”
- Triple-Negative Breast Cancer: Clinical Features and Patterns of Recurrence (2007, methodology): “NOTE: A Cox model, including age at diagnosis, grade (1, 2, 3), nodal status (negative, positive), tumor size (T1, T2, T3), chemotherapy (yes, no), and tamoxifen therapy (yes, no), was used to estimate the adjusted HRs.”