Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis.

By C. Sotiriou, P. Wirapati, S. Loi, AdrianL. Harris, Steve Fox, J. Smeds, H. Nordgren, P. Farmer, Viviane Praz, Benjamin Haibe-Kains and 10 more. Journal of the National Cancer Institute, 2006

2,034 citations recorded by the source corpus.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/6ba139d9a4a569b06a67b81675431860c925fd35

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

In Molecular Biology

Citations in the corpus

Most Random Gene Expression Signatures Are Significantly Associated with Breast Cancer Outcome (2011, background): “markers such as proliferation [6–9] or grade [10–12].”
American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. (2007, methodology): “Markers of proliferation and genomic instability have also been measured using microarray profiling analyses.(128,263) While these studies are in early stages and require validation, the current data suggest that these measures may capture more meaningful information than single gene markers of prol”
Latent bone metastasis in breast cancer tied to Src-dependent survival signals (2009, background): “Multivariate analyses showed that the association of SRS+ status with bone relapse and/or lateonset bone relapse was independent of PR (progesterone receptor) status, HER2 status, molecular subtypes, Genomic Grade Index, and differentiation (Sotiriou et al., 2006) (Tables S3, S4 and S5).”
Breast cancer intrinsic subtype classification, clinical use and future trends. (2015, methodology): “, MammaPrint [43, 44], Veridex 76-gene signature [44], MapQuant Dx [45] and its simplified version [46], Oncotype DX [30, 47] and Theros [48, 49] were developed for the prediction of clinical outcome among breast cancer patients, which are summarized in Table 2.”
Systematic Analysis of Breast Cancer Morphology Uncovers Stromal Features Associated with Survival (2011, methodology): “In addition to standard clinical measurements, the tumors from all patients in the NKI data set had previously undergone expression profiling by microarray, allowing each case to be classified according to several standard breast cancer molecular signatures: the 70-gene prognosis signature score (24”
Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures (2008, methodology): “Our results confirmed these observations, as proliferation genes are even better indicators of tumor grade [18].”
Breast cancer prognostic classification in the molecular era: the role of histological grade (2010, methodology): “Sotiriou and colleagues [66] developed a 97-gene classifi er that can accurately identify cases diagnosed as NGS I or NGS III.”
Learning on Weighted Hypergraphs to Integrate Protein Interactions and Gene Expressions for Cancer Outcome Prediction (2008, positive): “7e− 36) are well known to be functionally involved with metastasis and development of breast cancer [15, 19, 4, 18].”
Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer. (2006, background): “(49) published their findings of a 97-gene expression grade index associated with histologic grade and correlated with relapse-free survival in estrogen receptor–positive breast cancer.”
Microarray analysis of altered sphingolipid metabolism reveals prognostic significance of sphingosine kinase 1 in breast cancer (2008, background): “study) Miller et al. [13] Pawitan et al. [14] Sotiriou et al. [ 15 ] Wang et al. [12] http://www.intgen.org/ Breast Cancer Res Treat (2008) 112:41–52 43”