Patterns of gene expression that characterize long-term survival in advanced stage serous ovarian cancers

Andrew Berchuck, Edwin S. Iversen, Johnathan M. Lancaster, Jennifer Pittman, Jingqin Luo, Paula Lee, Susan Murphy, Holly K. Dressman, Phillip G. Febbo, Mike West, Joseph R. Nevins, Jeffrey R. Marks

Research output: Contribution to journalArticle

207 Citations (Scopus)

Abstract

Purpose: A better understanding of the underlying biology of invasive serous ovarian cancer is critical for the development of early detection strategies and new therapeutics. The objective of this study was to define gene expression patterns associated with favorable survival. Experimental Design: RNA from 65 serous ovarian cancers was analyzed using Affymetrix U133A microarrays.This included 54 stage III/IVcases (30 short-term survivors who lived <3 years and 24 long-term survivors who lived >7 years) and 11 stage I/II cases. Genes were screened on the basis of their level of and variability in expression, leaving 7,821 for use in developing a predictive model for survival. A composite predictive model was developed that combines Bayesian classification tree and multivariate discriminant models. Leave-one-out cross-validation was used to select and evaluate models. Results: Patterns of genes were identified that distinguish short-term and long-term ovarian cancer survivors. The expression model developed for advanced stage disease classified all 11 early-stage ovarian cancers as long-term survivors. The MAL gene, which has been shown to confer resistance to cancer therapy, was most highly overexpressed in short-term survivors (3-fold compared with long-term survivors, and 29-fold compared with early-stage cases). These results suggest that gene expression patterns underlie differences in outcome, and an examination of the genes that provide this discrimination reveals that many are implicated in processes that define the malignant phenotype. Conclusions: Differences in survival of advanced ovarian cancers are reflected by distinct patterns of gene expression. This biological distinction is further emphasized by the finding that earlystage cancers share expression patterns with the advanced stage long-term survivors, suggesting a shared favorable biology.

Original languageEnglish (US)
Pages (from-to)3686-3696
Number of pages11
JournalClinical Cancer Research
Volume11
Issue number10
DOIs
StatePublished - May 15 2005

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Ovarian Neoplasms
Survivors
Gene Expression
Survival
Genes
Neoplasms
Research Design
RNA
Phenotype
Therapeutics

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Patterns of gene expression that characterize long-term survival in advanced stage serous ovarian cancers. / Berchuck, Andrew; Iversen, Edwin S.; Lancaster, Johnathan M.; Pittman, Jennifer; Luo, Jingqin; Lee, Paula; Murphy, Susan; Dressman, Holly K.; Febbo, Phillip G.; West, Mike; Nevins, Joseph R.; Marks, Jeffrey R.

In: Clinical Cancer Research, Vol. 11, No. 10, 15.05.2005, p. 3686-3696.

Research output: Contribution to journalArticle

Berchuck, A, Iversen, ES, Lancaster, JM, Pittman, J, Luo, J, Lee, P, Murphy, S, Dressman, HK, Febbo, PG, West, M, Nevins, JR & Marks, JR 2005, 'Patterns of gene expression that characterize long-term survival in advanced stage serous ovarian cancers', Clinical Cancer Research, vol. 11, no. 10, pp. 3686-3696. https://doi.org/10.1158/1078-0432.CCR-04-2398
Berchuck, Andrew ; Iversen, Edwin S. ; Lancaster, Johnathan M. ; Pittman, Jennifer ; Luo, Jingqin ; Lee, Paula ; Murphy, Susan ; Dressman, Holly K. ; Febbo, Phillip G. ; West, Mike ; Nevins, Joseph R. ; Marks, Jeffrey R. / Patterns of gene expression that characterize long-term survival in advanced stage serous ovarian cancers. In: Clinical Cancer Research. 2005 ; Vol. 11, No. 10. pp. 3686-3696.
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abstract = "Purpose: A better understanding of the underlying biology of invasive serous ovarian cancer is critical for the development of early detection strategies and new therapeutics. The objective of this study was to define gene expression patterns associated with favorable survival. Experimental Design: RNA from 65 serous ovarian cancers was analyzed using Affymetrix U133A microarrays.This included 54 stage III/IVcases (30 short-term survivors who lived <3 years and 24 long-term survivors who lived >7 years) and 11 stage I/II cases. Genes were screened on the basis of their level of and variability in expression, leaving 7,821 for use in developing a predictive model for survival. A composite predictive model was developed that combines Bayesian classification tree and multivariate discriminant models. Leave-one-out cross-validation was used to select and evaluate models. Results: Patterns of genes were identified that distinguish short-term and long-term ovarian cancer survivors. The expression model developed for advanced stage disease classified all 11 early-stage ovarian cancers as long-term survivors. The MAL gene, which has been shown to confer resistance to cancer therapy, was most highly overexpressed in short-term survivors (3-fold compared with long-term survivors, and 29-fold compared with early-stage cases). These results suggest that gene expression patterns underlie differences in outcome, and an examination of the genes that provide this discrimination reveals that many are implicated in processes that define the malignant phenotype. Conclusions: Differences in survival of advanced ovarian cancers are reflected by distinct patterns of gene expression. This biological distinction is further emphasized by the finding that earlystage cancers share expression patterns with the advanced stage long-term survivors, suggesting a shared favorable biology.",
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AU - Iversen, Edwin S.

AU - Lancaster, Johnathan M.

AU - Pittman, Jennifer

AU - Luo, Jingqin

AU - Lee, Paula

AU - Murphy, Susan

AU - Dressman, Holly K.

AU - Febbo, Phillip G.

AU - West, Mike

AU - Nevins, Joseph R.

AU - Marks, Jeffrey R.

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N2 - Purpose: A better understanding of the underlying biology of invasive serous ovarian cancer is critical for the development of early detection strategies and new therapeutics. The objective of this study was to define gene expression patterns associated with favorable survival. Experimental Design: RNA from 65 serous ovarian cancers was analyzed using Affymetrix U133A microarrays.This included 54 stage III/IVcases (30 short-term survivors who lived <3 years and 24 long-term survivors who lived >7 years) and 11 stage I/II cases. Genes were screened on the basis of their level of and variability in expression, leaving 7,821 for use in developing a predictive model for survival. A composite predictive model was developed that combines Bayesian classification tree and multivariate discriminant models. Leave-one-out cross-validation was used to select and evaluate models. Results: Patterns of genes were identified that distinguish short-term and long-term ovarian cancer survivors. The expression model developed for advanced stage disease classified all 11 early-stage ovarian cancers as long-term survivors. The MAL gene, which has been shown to confer resistance to cancer therapy, was most highly overexpressed in short-term survivors (3-fold compared with long-term survivors, and 29-fold compared with early-stage cases). These results suggest that gene expression patterns underlie differences in outcome, and an examination of the genes that provide this discrimination reveals that many are implicated in processes that define the malignant phenotype. Conclusions: Differences in survival of advanced ovarian cancers are reflected by distinct patterns of gene expression. This biological distinction is further emphasized by the finding that earlystage cancers share expression patterns with the advanced stage long-term survivors, suggesting a shared favorable biology.

AB - Purpose: A better understanding of the underlying biology of invasive serous ovarian cancer is critical for the development of early detection strategies and new therapeutics. The objective of this study was to define gene expression patterns associated with favorable survival. Experimental Design: RNA from 65 serous ovarian cancers was analyzed using Affymetrix U133A microarrays.This included 54 stage III/IVcases (30 short-term survivors who lived <3 years and 24 long-term survivors who lived >7 years) and 11 stage I/II cases. Genes were screened on the basis of their level of and variability in expression, leaving 7,821 for use in developing a predictive model for survival. A composite predictive model was developed that combines Bayesian classification tree and multivariate discriminant models. Leave-one-out cross-validation was used to select and evaluate models. Results: Patterns of genes were identified that distinguish short-term and long-term ovarian cancer survivors. The expression model developed for advanced stage disease classified all 11 early-stage ovarian cancers as long-term survivors. The MAL gene, which has been shown to confer resistance to cancer therapy, was most highly overexpressed in short-term survivors (3-fold compared with long-term survivors, and 29-fold compared with early-stage cases). These results suggest that gene expression patterns underlie differences in outcome, and an examination of the genes that provide this discrimination reveals that many are implicated in processes that define the malignant phenotype. Conclusions: Differences in survival of advanced ovarian cancers are reflected by distinct patterns of gene expression. This biological distinction is further emphasized by the finding that earlystage cancers share expression patterns with the advanced stage long-term survivors, suggesting a shared favorable biology.

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