title: Unsupervised analysis reveals two molecular subgroups of serous ovarian cancer with distinct gene expression profiles and survival.
abstract: OBJECTIVE
  Ovarian cancer is typically diagnosed at late stages, and thus, patients' prognosis is poor. Improvement in treatment outcomes depends, at least partly, on better understanding of ovarian cancer biology and finding new molecular markers and therapeutic targets.
  
  
  METHODS
  An unsupervised method of data analysis, singular value decomposition, was applied to analyze microarray data from 101 ovarian cancer samples; then, selected genes were validated by quantitative PCR.
  
  
  RESULTS
  We found that the major factor influencing gene expression in ovarian cancer was tumor histological type. The next major source of variability was traced to a set of genes mainly associated with extracellular matrix, cell motility, adhesion, and immunological response. Hierarchical clustering based on the expression of these genes revealed two clusters of ovarian cancers with different molecular profiles and distinct overall survival (OS). Patients with higher expression of these genes had shorter OS than those with lower expression. The two clusters did not derive from high- versus low-grade serous carcinomas and were unrelated to histological (ovarian vs. fallopian) origin. Interestingly, there was considerable overlap between identified prognostic signature and a recently described invasion-associated signature related to stromal desmoplastic reaction. Several genes from this signature were validated by quantitative PCR; two of them-DSPG3 and LOX-were validated both in the initial and independent sets of samples and were significantly associated with OS and disease-free survival.
  
  
  CONCLUSIONS
  We distinguished two molecular subgroups of serous ovarian cancers characterized by distinct OS. Among differentially expressed genes, some may potentially be used as prognostic markers. In our opinion, unsupervised methods of microarray data analysis are more effective than supervised methods in identifying intrinsic, biologically sound sources of variability. Moreover, as histological type of the tumor is the greatest source of variability in ovarian cancer and may interfere with analyses of other features, it seems reasonable to use histologically homogeneous groups of tumors in microarray experiments.
authors.affiliation: Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice, Poland. katarzyna.lisowska@io.gliwice.pl.
authors.forename: Katarzyna M
authors.identifier: http://orcid.org/0000-0001-9786-3993
authors.initials: KM
authors.lastname: Lisowska
authors.affiliation: Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice, Poland.
authors.forename: Magdalena
authors.initials: M
authors.lastname: Olbryt
authors.affiliation: Department of Automatic Control, Silesian Technical University, Gliwice, Poland.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Student
authors.affiliation: Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice, Poland.
authors.forename: Katarzyna A
authors.initials: KA
authors.lastname: Kujawa
authors.affiliation: Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice, Poland.
authors.forename: Alexander J
authors.initials: AJ
authors.lastname: Cortez
authors.affiliation: Department of Automatic Control, Silesian Technical University, Gliwice, Poland.
authors.forename: Krzysztof
authors.initials: K
authors.lastname: Simek
authors.affiliation: Department of Pathology, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw, Poland.
authors.forename: Agnieszka
authors.initials: A
authors.lastname: Dansonka-Mieszkowska
authors.affiliation: Department of Pathology, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw, Poland.
authors.forename: Iwona K
authors.initials: IK
authors.lastname: Rzepecka
authors.affiliation: Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice, Poland.
authors.forename: Patrycja
authors.initials: P
authors.lastname: Tudrej
authors.affiliation: Department of Pathology, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw, Poland.
authors.forename: Jolanta
authors.initials: J
authors.lastname: Kupryjańczyk
mesh_terms: D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D005810:Multigene Family; D010051:Ovarian Neoplasms / Q000145:classification / Q000235:genetics*; D016133:Polymerase Chain Reaction; D011379:Prognosis; D015996:Survival Rate
keywords: Dermatan sulfate proteoglycan 3 (DSPG3); Gene expression analysis; Lysyl oxidase (LOX); Ovarian cancer; Prognostic biomarkers; Singular value decomposition (SVD)