OBJECTIVE: The purpose of this study was to define gene expression patterns that are associated with the optimal versus suboptimal debulking of advanced-stage serous ovarian cancers. STUDY DESIGN: RNA from 44 advanced serous ovarian cancers (19 optimal, 25 suboptimal) was evaluated with microarrays that contain >22,000 genes. Genes were screened on the basis of their association with debulking status to obtain the top 120 differentially expressed genes. These genes were then used to develop a predictive model for debulking status, which was subjected to out-of-sample cross validation. RESULTS: We found that patterns of expression of 32 genes can distinguish between optimal and suboptimal debulking with 72.7% predictive accuracy. An analysis of the data that were based on clusters of co-ordinately expressed genes resulted in only a marginal improvement in predictive accuracy (75%). CONCLUSION: These data support the hypothesis that favorable survival that is associated with optimal debulking of advanced ovarian cancers is due to, at least in part, the underlying biologic characteristics of these cancers.
OBJECTIVE: The purpose of this study was to define gene expression patterns that are associated with the optimal versus suboptimal debulking of advanced-stage serous ovarian cancers. STUDY DESIGN: RNA from 44 advanced serous ovarian cancers (19 optimal, 25 suboptimal) was evaluated with microarrays that contain >22,000 genes. Genes were screened on the basis of their association with debulking status to obtain the top 120 differentially expressed genes. These genes were then used to develop a predictive model for debulking status, which was subjected to out-of-sample cross validation. RESULTS: We found that patterns of expression of 32 genes can distinguish between optimal and suboptimal debulking with 72.7% predictive accuracy. An analysis of the data that were based on clusters of co-ordinately expressed genes resulted in only a marginal improvement in predictive accuracy (75%). CONCLUSION: These data support the hypothesis that favorable survival that is associated with optimal debulking of advanced ovarian cancers is due to, at least in part, the underlying biologic characteristics of these cancers.
Authors: Neil S Horowitz; Austin Miller; Bunja Rungruang; Scott D Richard; Noah Rodriguez; Michael A Bookman; Chad A Hamilton; Thomas C Krivak; G Larry Maxwell Journal: J Clin Oncol Date: 2015-02-09 Impact factor: 44.544
Authors: Monique A Spillman; Judith Lacy; Susan K Murphy; Regina S Whitaker; Lisa Grace; Vanessa Teaberry; Jeffrey R Marks; Andrew Berchuck Journal: Gynecol Oncol Date: 2007-02-05 Impact factor: 5.482
Authors: Chad A Hamilton; Austin Miller; Caela Miller; Thomas C Krivak; John H Farley; Mildred R Chernofsky; Michael P Stany; G Scott Rose; Maurie Markman; Robert F Ozols; Deborah K Armstrong; G Larry Maxwell Journal: Gynecol Oncol Date: 2011-06-17 Impact factor: 5.482
Authors: Markus Riester; Wei Wei; Levi Waldron; Aedin C Culhane; Lorenzo Trippa; Esther Oliva; Sung-Hoon Kim; Franziska Michor; Curtis Huttenhower; Giovanni Parmigiani; Michael J Birrer Journal: J Natl Cancer Inst Date: 2014-04-03 Impact factor: 13.506