title: Meta-analysis of gene expression profiles associated with histological classification and survival in 829 ovarian cancer samples.
abstract: Transcriptomic analysis of global gene expression in ovarian carcinoma can identify dysregulated genes capable to serve as molecular markers for histology subtypes and survival. The aim of our study was to validate previous candidate signatures in an independent setting and to identify single genes capable to serve as biomarkers for ovarian cancer progression. As several datasets are available in the GEO today, we were able to perform a true meta-analysis. First, 829 samples (11 datasets) were downloaded, and the predictive power of 16 previously published gene sets was assessed. Of these, eight were capable to discriminate histology subtypes, and none was capable to predict survival. To overcome the differences in previous studies, we used the 829 samples to identify new predictors. Then, we collected 64 ovarian cancer samples (median relapse-free survival 24.5 months) and performed TaqMan Real Time Polimerase Chain Reaction (RT-PCR) analysis for the best 40 genes associated with histology subtypes and survival. Over 90% of subtype-associated genes were confirmed. Overall survival was effectively predicted by hormone receptors (PGR and ESR2) and by TSPAN8. Relapse-free survival was predicted by MAPT and SNCG. In summary, we successfully validated several gene sets in a meta-analysis in large datasets of ovarian samples. Additionally, several individual genes identified were validated in a clinical cohort.
authors.affiliation: Semmelweis University, 1st Department of Gynecology, Budapest. tibfek@gmail.com
authors.forename: Tibor
authors.initials: T
authors.lastname: Fekete
authors.forename: Erzsébet
authors.initials: E
authors.lastname: Rásó
authors.forename: Imre
authors.initials: I
authors.lastname: Pete
authors.forename: Bálint
authors.initials: B
authors.lastname: Tegze
authors.forename: István
authors.initials: I
authors.lastname: Liko
authors.forename: Gyöngyi
authors.initials: G
authors.lastname: Munkácsy
authors.forename: Norbert
authors.initials: N
authors.lastname: Sipos
authors.forename: János
authors.initials: J
authors.lastname: Rigó
authors.forename: Balázs
authors.initials: B
authors.lastname: Györffy
mesh_terms: D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics; D030541:Databases, Genetic; D018450:Disease Progression; D018572:Disease-Free Survival; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis; D010051:Ovarian Neoplasms / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D010053:Ovary / Q000033:anatomy & histology / Q000378:metabolism / Q000473:pathology; D011960:Receptors, Estrogen / Q000235:genetics; D011980:Receptors, Progesterone / Q000235:genetics; D059470:Tetraspanins / Q000235:genetics; D051845:gamma-Synuclein / Q000235:genetics; D016875:tau Proteins / Q000235:genetics
chemical_list: D014408:Biomarkers, Tumor; C054369:MAPT protein, human; D009363:Neoplasm Proteins; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone; C104249:SNCG protein, human; C065609:TSPAN8 protein, human; D059470:Tetraspanins; D051845:gamma-Synuclein; D016875:tau Proteins