title: Gene expression signature with independent prognostic significance in epithelial ovarian cancer.
abstract: OBJECTIVE
  Currently available clinical and molecular prognostic factors provide an imperfect assessment of prognosis for patients with epithelial ovarian cancer (EOC). In this study, we investigated whether tumor transcription profiling could be used as a prognostic tool in this disease.
  
  
  METHODS
  Tumor tissue from 68 patients was profiled with oligonucleotide microarrays. Samples were randomly split into training and validation sets. A three-step training procedure was used to discover a statistically significant Kaplan-Meier split in the training set. The resultant prognostic signature was then tested on an independent validation set for confirmation.
  
  
  RESULTS
  In the training set, a 115-gene signature referred to as the Ovarian Cancer Prognostic Profile (OCPP) was identified. When applied to the validation set, the OCPP distinguished between patients with unfavorable and favorable overall survival (median, 30 months v not yet reached, respectively; log-rank P = .004). The signature maintained independent prognostic value in multivariate analysis, controlling for other known prognostic factors such as age, stage, grade, and debulking status. The hazard ratio for death in the unfavorable OCPP group was 4.8 (P = .021 by Cox proportional hazards analysis).
  
  
  CONCLUSIONS
  The OCPP is an independent prognostic determinant of outcome in EOC. The use of gene profiling may ultimately permit identification of EOC patients appropriate for investigational treatment approaches, based on a low likelihood of achieving prolonged survival with standard first-line platinum-based therapy.
authors.affiliation: Program of Gynecologic Medical Oncology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA.
authors.forename: Dimitrios
authors.initials: D
authors.lastname: Spentzos
authors.forename: Douglas A
authors.initials: DA
authors.lastname: Levine
authors.forename: Marco F
authors.initials: MF
authors.lastname: Ramoni
authors.forename: Marie
authors.initials: M
authors.lastname: Joseph
authors.forename: Xuesong
authors.initials: X
authors.lastname: Gu
authors.forename: Jeff
authors.initials: J
authors.lastname: Boyd
authors.forename: Towia A
authors.initials: TA
authors.lastname: Libermann
authors.forename: Stephen A
authors.initials: SA
authors.lastname: Cannistra
mesh_terms: D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000378:metabolism; D001707:Biopsy, Needle; D017024:Chemotherapy, Adjuvant; D003131:Combined Modality Therapy; D018076:DNA, Complementary / Q000032:analysis; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D020022:Genetic Predisposition to Disease; D006801:Humans; D007150:Immunohistochemistry; D008875:Middle Aged; D009367:Neoplasm Staging; D009375:Neoplasms, Glandular and Epithelial / Q000235:genetics* / Q000401:mortality* / Q000473:pathology / Q000628:therapy; D010051:Ovarian Neoplasms / Q000235:genetics* / Q000401:mortality* / Q000473:pathology / Q000628:therapy; D010052:Ovariectomy / Q000379:methods; D011237:Predictive Value of Tests; D011379:Prognosis; D012334:RNA, Neoplasm / Q000032:analysis; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D016019:Survival Analysis; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor; D018076:DNA, Complementary; D012334:RNA, Neoplasm