OBJECTIVES: The molecular pathogenesis of ovarian serous tumors of low malignant potential (S-LMP) is not well understood, although the collective data suggest that they arise through molecular mechanisms distinct from those leading to conventional serous carcinomas (S-Ca). To further examine the molecular differences between these two diseases, we studied the gene expression pattern of ovarian S-LMP and S-Ca using high-density spotted cDNA and tissue microarrays. METHODS: Total RNA from 23 ovarian S-LMP and S-Ca was analyzed on 43,200 spot cDNA microarrays and the differential expression of proteins encoded by differentially expressed genes was validated using tissue microarrays. RESULTS: Unsupervised hierarchical clustering analysis of filtered data showed a complete separation between S-LMP and S-Ca, based predominantly on a small set of genes expressed at higher levels in S-LMP than in S-Ca. Many genes previously identified as up-regulated in ovarian carcinoma relative to normal ovarian tissue were expressed at even higher levels in S-LMP. These genes included mucin-1, mesothelin, HE4, PAX 8, and apolipoprotein J/clusterin. Immunohistochemical staining of tissue microarrays confirmed higher expression of selected proteins encoded by these genes in the S-LMP. Few genes were expressed at a higher level in S-Ca; these included E2F1, topoisomerase IIalpha, and cyclin E, with higher levels of cyclin E protein confirmed by immunohistochemistry. CONCLUSIONS: S-LMP and S-Ca are distinguished at the molecular level by a relatively small gene set, suggesting the pathogenesis of S-LMP as well as S-Ca may involve molecular pathways that escape detection by global gene expression profiling. In order to obtain biologically and clinically relevant information about the mechanisms involved in ovarian carcinogenesis, future studies based on molecular profiles of ovarian cancer should include analyses of low malignant potential tumors. Inclusion of such tumors is also critical to the evaluation of the efficacy of potential new diagnostic and/or therapeutic biomarkers.
OBJECTIVES: The molecular pathogenesis of ovarian serous tumors of low malignant potential (S-LMP) is not well understood, although the collective data suggest that they arise through molecular mechanisms distinct from those leading to conventional serous carcinomas (S-Ca). To further examine the molecular differences between these two diseases, we studied the gene expression pattern of ovarian S-LMP and S-Ca using high-density spotted cDNA and tissue microarrays. METHODS: Total RNA from 23 ovarian S-LMP and S-Ca was analyzed on 43,200 spot cDNA microarrays and the differential expression of proteins encoded by differentially expressed genes was validated using tissue microarrays. RESULTS: Unsupervised hierarchical clustering analysis of filtered data showed a complete separation between S-LMP and S-Ca, based predominantly on a small set of genes expressed at higher levels in S-LMP than in S-Ca. Many genes previously identified as up-regulated in ovarian carcinoma relative to normal ovarian tissue were expressed at even higher levels in S-LMP. These genes included mucin-1, mesothelin, HE4, PAX 8, and apolipoprotein J/clusterin. Immunohistochemical staining of tissue microarrays confirmed higher expression of selected proteins encoded by these genes in the S-LMP. Few genes were expressed at a higher level in S-Ca; these included E2F1, topoisomerase IIalpha, and cyclin E, with higher levels of cyclin E protein confirmed by immunohistochemistry. CONCLUSIONS: S-LMP and S-Ca are distinguished at the molecular level by a relatively small gene set, suggesting the pathogenesis of S-LMP as well as S-Ca may involve molecular pathways that escape detection by global gene expression profiling. In order to obtain biologically and clinically relevant information about the mechanisms involved in ovarian carcinogenesis, future studies based on molecular profiles of ovarian cancer should include analyses of low malignant potential tumors. Inclusion of such tumors is also critical to the evaluation of the efficacy of potential new diagnostic and/or therapeutic biomarkers.
Authors: Takayo Ota; Amy C Clayton; Douglas M Minot; Viji Shridhar; Lynn C Hartmann; C Blake Gilks; Jeremy R Chien Journal: Mod Pathol Date: 2010-11-12 Impact factor: 7.842
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Authors: Sharon J Pitteri; Lellean JeBailey; Vitor M Faça; Jason D Thorpe; Melissa A Silva; Reneé C Ireton; Marc B Horton; Hong Wang; Liese C Pruitt; Qing Zhang; Kuang H Cheng; Nicole Urban; Samir M Hanash; Daniela M Dinulescu Journal: PLoS One Date: 2009-11-19 Impact factor: 3.240
Authors: Cheng-Han Lee; Subbaya Subramanian; Andrew H Beck; Inigo Espinosa; Janine Senz; Shirley X Zhu; David Huntsman; Matt van de Rijn; C Blake Gilks Journal: PLoS One Date: 2009-10-02 Impact factor: 3.240
Authors: Melissa A Merritt; Peter G Parsons; Tanya R Newton; Adam C Martyn; Penelope M Webb; Adèle C Green; David J Papadimos; Glen M Boyle Journal: BMC Cancer Date: 2009-10-23 Impact factor: 4.430