Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors

By Jonathan R. Pollack, T. Sørlie, Charles M. Perou, Christian A. Rees, S. Jeffrey, P. Lønning, Robert Tibshirani, David Botstein, A. Børresen-Dale, Patrick O. Brown. Proceedings of the National Academy of Sciences of the United States of America, 2002

1,200 citations recorded by the source corpus.

Subfields: Cancer Research, Genetics, Pediatrics, Perinatology and Child Health

View Paper: https://www.semanticscholar.org/paper/4bda5ad9b87c44870349622791ba464b454bc886

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Citations in the corpus

Regularized Multivariate Regression for Identifying Master Predictors with Application to Integrative Genomics Study of Breast Cancer (2008, background): “Particularly, this helps to discern more subtle (yet biologically important) genetic regulatory relationships in cancer cells (Pollack et al. 2002).”
A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. (2006, background): “In fact, over a thousand genes have now been reported to be deregulated by recurrent genome aberrations in breast cancer alone (Fridlyand et al., 2006; Hyman et al., 2002; Pollack et al., 2002).”
Principles of Cancer Therapy: Oncogene and Non-oncogene Addiction (2009, neutral): “However, they also result in corresponding increases and decreases in transcript levels (Pollack et al., 2002; Torres et al., 2007; Tsafrir et al., 2006) that produce imbalances in the stoichiometry of protein complex subunits (Papp et al.”
High-level coexpression of JAG1 and NOTCH1 is observed in human breast cancer and is associated with poor overall survival. (2005, neutral): “Hi 44 49% (34-64) 53 mo (30-83) NOTCH3 Lo 150 61% (53-69) 82 mo (71-122) 0.”
A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers (2006, background): “However, significant correspondence has been observed between chromosome copy number alterations and gene expression changes in the affected region”
Sensitive and accurate detection of copy number variants using read depth of coverage. (2009, background): “Analysis of CNV in diseases such as cancer (Lucito et al. 2000; Pollack et al. 2002; Albertson and Pinkel 2003), and in developmental and neuropsychiatric disorders (Feuk et al.”
Improved classification of breast cancer by analysis of genetic alterations and gene expression profiling (2011, background): “Association between copy number change and gene expression levels has been shown, and ∼12% of gene expression variation can be explained by differences in DNA copy number (10).”
Molecular Profiling of Breast Cancer Cell Lines Defines Relevant Tumor Models and Provides a Resource for Cancer Gene Discovery (2009, methodology): “aCGH was performed using cDNA arrays containing 39,632 cDNAs, representing 22,279 mapped human genes (18,049 UniGene clusters [20], together with 4,230 additional mapped ESTs not assigned to UniGene IDs), according to previously published protocols [21,22].”
Circular binary segmentation for the analysis of array-based DNA copy number data. (2004, methodology): “A third technique to estimate copy number is to simply employ the same cDNA arrays used for gene expression studies (Pollack et al., 1999, 2002).”
A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. (2009, background): “phism (SNP) data include Hyman et al. (2002), Pollack et al. (2002) , Morley et al. (2004), Stranger et al.”
Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data (2005, methodology): “For instance, a moving average was used to process the ratios, and a ‘normal vs normal’ hybridization was used to compute a threshold level (Pollack et al., 2002).”