Oligonucleotide microarray analysis of chromosome 17 gene expression in a model human epithelial ovarian cancer cell line, TOV112D, and in epithelial ovarian tumors and ovarian malignant ascites
Notice bibliographique
Résumé
The importance of developing relevant ovarian cancer models led us to test the applicability of a system comprised of epithelial ovarian cancer cell lines. The high frequency of loss of heterozygosity (LOH) and rearrangements of chromosome 17 in ovarian tumors provide evidence of a role of chromosome 17 genes in ovarian tumorigenesis. Oligonucleotide microarray expression analysis was applied to assess the expression profiles of 864 probe sets that map to chromosome 17. The TOV112D ovarian cancer cell line, a spontaneously immortalized and tumorigenic ovarian cancer cell line derived from an endometrioid histopathological subtype, which has been shown to exhibit LOH of chromosome 17, was used as a model to identify candidate genes based on Affymetrix expression microarray analyses in comparative analysis with three primary cultures derived from normal ovarian surface epithelium (NOSE). Two-way comparative analyses identified 81 probe sets, representing 64 differentially expressed genes, which exhibited at least a three-fold difference in expression relative to the mean of NOSE samples. The expression of these 64 candidate genes was investigated by microarray analysis in 31 fresh solid malignant ovarian tumors of different histopathologies, six ovarian tumors of borderline pathology, 32 primary cultures of ovarian tumors, 28 primary cultures of malignant ovarian ascites, and 16 NOSE samples. The chromosome 17 expression profile of TOV112D monolayer was compared with this cell line grown as a three-dimensional spheroid, solid tumors and monolayer cultures of these tumors from intraperitoneal and subcutaneous injection into nude mice. The expression profiles of selected candidates were validated by RT-PCR. About 63% of the candidates overexpressed at least three-fold relative to TOV112D were also overexpressed in some of the solid malignant ovarian tumors, and about 91% of the candidates that were underexpressed at least three-fold in TOV112D were also underexpressed in some of these tumors. The same differential pattern of gene expression of candidates was also observed in primary cultures of ovarian tumors and ovarian ascites, however, the effect in primary cultures was reduced. These results indicate that TOV112D, representing a spontaneously immortalized long-term passage, was more representative of solid ovarian tumors compared with the primary cultures. Growth conditions showed little impact on the expression profile of candidates when TOV112D was grown in different culture environments such as in vitro monolayer or mouse tumor xenograft. The finding that TOV112D identified differentially expressed genes in ovarian tumor samples regardless of histopathological subtype indicates that it is a useful model, not only to study the endometrioid subtype, but also serous and clear cell subtypes of epithelial ovarian cancer. Comparison of the expression profiles of our candidate genes identified by microarray analysis with published reports revealed that eight genes (ACACA, SFRS2, CCL2, CSF3, IGFBP4, KRT19, ITGA3, and TIMP2) were previously implicated in ovarian cancer, and 23 including MAC30 and TBX2 were implicated in tumorigenesis of other types of cancers. The use of long-term ovarian cancer cultures provides scientists with a model to study candidate genes, some of which may prove important for early detection or represent targets for the development of new ovarian cancer treatments.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».