An approach to analysis of large-scale correlations between genome changes and clinical endpoints in ovarian cancer

S. Suzuki, D. H. Moore, D. G. Ginzinger, T. E. Godfrey, J. Barclay, B. Powell, D. Pinkel, C. Zaloudek, K. Lu, Gordon Mills, A. Berchuck, Joe Gray

Research output: Contribution to journalArticle

101 Citations (Scopus)

Abstract

This report describes analyses of associations of genome copy number abnormalities in ovarian cancers with clinical features using genome-wide graphical and analytical procedures. These studies show that tumor grade is a better indicator of the extent of genomic progression than stage, that loss of chromosome 4 occurs preferentially in high-grade tumors, and that gains of 3q26-qter, 8q24-qter, and 20q13-qter occur frequently in low-grade and low-stage tumors and thus may be early events in ovarian cancer development. In addition, loss of chromosome 16q24 and a total number of independent genome copy number aberrations > 7 are associated with reduced survival duration. The association of loss of 16q24 (D16S3026) with decreased survival duration was confirmed by quantitative PCR. Regions that frequently are abnormal and associated with altered survival duration are strong candidates for higher resolution analysis and gene discovery and may be useful markers for prediction of clinical outcome.

Original languageEnglish (US)
Pages (from-to)5382-5385
Number of pages4
JournalCancer Research
Volume60
Issue number19
StatePublished - Oct 1 2000
Externally publishedYes

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Ovarian Neoplasms
Genome
Neoplasms
Chromosomes, Human, Pair 4
Genetic Association Studies
Chromosomes
Biomarkers
Polymerase Chain Reaction

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

Cite this

Suzuki, S., Moore, D. H., Ginzinger, D. G., Godfrey, T. E., Barclay, J., Powell, B., ... Gray, J. (2000). An approach to analysis of large-scale correlations between genome changes and clinical endpoints in ovarian cancer. Cancer Research, 60(19), 5382-5385.

An approach to analysis of large-scale correlations between genome changes and clinical endpoints in ovarian cancer. / Suzuki, S.; Moore, D. H.; Ginzinger, D. G.; Godfrey, T. E.; Barclay, J.; Powell, B.; Pinkel, D.; Zaloudek, C.; Lu, K.; Mills, Gordon; Berchuck, A.; Gray, Joe.

In: Cancer Research, Vol. 60, No. 19, 01.10.2000, p. 5382-5385.

Research output: Contribution to journalArticle

Suzuki, S, Moore, DH, Ginzinger, DG, Godfrey, TE, Barclay, J, Powell, B, Pinkel, D, Zaloudek, C, Lu, K, Mills, G, Berchuck, A & Gray, J 2000, 'An approach to analysis of large-scale correlations between genome changes and clinical endpoints in ovarian cancer', Cancer Research, vol. 60, no. 19, pp. 5382-5385.
Suzuki S, Moore DH, Ginzinger DG, Godfrey TE, Barclay J, Powell B et al. An approach to analysis of large-scale correlations between genome changes and clinical endpoints in ovarian cancer. Cancer Research. 2000 Oct 1;60(19):5382-5385.
Suzuki, S. ; Moore, D. H. ; Ginzinger, D. G. ; Godfrey, T. E. ; Barclay, J. ; Powell, B. ; Pinkel, D. ; Zaloudek, C. ; Lu, K. ; Mills, Gordon ; Berchuck, A. ; Gray, Joe. / An approach to analysis of large-scale correlations between genome changes and clinical endpoints in ovarian cancer. In: Cancer Research. 2000 ; Vol. 60, No. 19. pp. 5382-5385.
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