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Predicting the clinical status of human breast cancer by using gene expression profiles.

Publication ,  Journal Article
West, M; Blanchette, C; Dressman, H; Huang, E; Ishida, S; Spang, R; Zuzan, H; Olson, JA; Marks, JR; Nevins, JR
Published in: Proc Natl Acad Sci U S A
September 25, 2001

Prognostic and predictive factors are indispensable tools in the treatment of patients with neoplastic disease. For the most part, such factors rely on a few specific cell surface, histological, or gross pathologic features. Gene expression assays have the potential to supplement what were previously a few distinct features with many thousands of features. We have developed Bayesian regression models that provide predictive capability based on gene expression data derived from DNA microarray analysis of a series of primary breast cancer samples. These patterns have the capacity to discriminate breast tumors on the basis of estrogen receptor status and also on the categorized lymph node status. Importantly, we assess the utility and validity of such models in predicting the status of tumors in crossvalidation determinations. The practical value of such approaches relies on the ability not only to assess relative probabilities of clinical outcomes for future samples but also to provide an honest assessment of the uncertainties associated with such predictive classifications on the basis of the selection of gene subsets for each validation analysis. This latter point is of critical importance in the ability to apply these methodologies to clinical assessment of tumor phenotype.

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Published In

Proc Natl Acad Sci U S A

DOI

ISSN

0027-8424

Publication Date

September 25, 2001

Volume

98

Issue

20

Start / End Page

11462 / 11467

Location

United States

Related Subject Headings

  • Reproducibility of Results
  • Receptors, Estrogen
  • Probability
  • Predictive Value of Tests
  • Phenotype
  • Oligonucleotide Array Sequence Analysis
  • Multigene Family
  • Lymph Nodes
  • Lymph Node Excision
  • Humans
 

Citation

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West, M., Blanchette, C., Dressman, H., Huang, E., Ishida, S., Spang, R., … Nevins, J. R. (2001). Predicting the clinical status of human breast cancer by using gene expression profiles. Proc Natl Acad Sci U S A, 98(20), 11462–11467. https://doi.org/10.1073/pnas.201162998
West, M., C. Blanchette, H. Dressman, E. Huang, S. Ishida, R. Spang, H. Zuzan, J. A. Olson, J. R. Marks, and J. R. Nevins. “Predicting the clinical status of human breast cancer by using gene expression profiles.Proc Natl Acad Sci U S A 98, no. 20 (September 25, 2001): 11462–67. https://doi.org/10.1073/pnas.201162998.
West M, Blanchette C, Dressman H, Huang E, Ishida S, Spang R, et al. Predicting the clinical status of human breast cancer by using gene expression profiles. Proc Natl Acad Sci U S A. 2001 Sep 25;98(20):11462–7.
West, M., et al. “Predicting the clinical status of human breast cancer by using gene expression profiles.Proc Natl Acad Sci U S A, vol. 98, no. 20, Sept. 2001, pp. 11462–67. Pubmed, doi:10.1073/pnas.201162998.
West M, Blanchette C, Dressman H, Huang E, Ishida S, Spang R, Zuzan H, Olson JA, Marks JR, Nevins JR. Predicting the clinical status of human breast cancer by using gene expression profiles. Proc Natl Acad Sci U S A. 2001 Sep 25;98(20):11462–11467.
Journal cover image

Published In

Proc Natl Acad Sci U S A

DOI

ISSN

0027-8424

Publication Date

September 25, 2001

Volume

98

Issue

20

Start / End Page

11462 / 11467

Location

United States

Related Subject Headings

  • Reproducibility of Results
  • Receptors, Estrogen
  • Probability
  • Predictive Value of Tests
  • Phenotype
  • Oligonucleotide Array Sequence Analysis
  • Multigene Family
  • Lymph Nodes
  • Lymph Node Excision
  • Humans