Efficient molecular subtype classification of high-grade serous ovarian cancer

High-grade serous carcinomas (HGSCs) account for approximately 70% of all epithelial ovarian cancers diagnosed. Using microarray gene expression profiling, we previously identified four molecular subtypes of HGSC: C1 (mesenchymal), C2 (immunoreactive), C4 (differentiated), and C5 (proliferative), which correlate with patient survival and have distinct biological features. Here, we describe molecular classification of HGSC based on a limited number of genes to allow cost-effective and high-throughput subtype analysis. We determined a minimal signature for accurate classification, including 39 differentially expressed and nine control genes from microarray experiments. Taqman-based (low-density arrays and Fluidigm), fluorescent oligonucleotides (Nanostring), and targeted RNA sequencing (Illumina) assays were then compared for their ability to correctly classify fresh and formalin-fixed, paraffin-embedded samples. All platforms achieved > 90% classification accuracy with RNA from fresh frozen samples. The Illumina and Nanostring assays were superior with fixed material. We found that the C1, C2, and C4 molecular subtypes were largely consistent across multiple surgical deposits from individual chemo-naive patients. In contrast, we observed substantial subtype heterogeneity in patients whose primary ovarian sample was classified as C5. The development of an efficient molecular classifier of HGSC should enable further biological characterization of molecular subtypes and the development of targeted clinical trials.

Efficient molecular subtype classification of high-grade serous ovarian cancer

High-grade serous carcinomas (HGSCs) account for approximately 70% of all epithelial ovarian cancers diagnosed. Using microarray gene expression profiling, we previously identified four molecular subtypes of HGSC: C1 (mesenchymal), C2 (immunoreactive), C4 (differentiated), and C5 (proliferative), which correlate with patient survival and have distinct biological features. Here, we describe molecular classification of HGSC based on a limited number of genes to allow cost-effective and high-throughput subtype analysis. We determined a minimal signature for accurate classification, including 39 differentially expressed and nine control genes from microarray experiments. Taqman-based (low-density arrays and Fluidigm), fluorescent oligonucleotides (Nanostring), and targeted RNA sequencing (Illumina) assays were then compared for their ability to correctly classify fresh and formalin-fixed, paraffin-embedded samples. All platforms achieved > 90% classification accuracy with RNA from fresh frozen samples. The Illumina and Nanostring assays were superior with fixed material. We found that the C1, C2, and C4 molecular subtypes were largely consistent across multiple surgical deposits from individual chemo-naive patients. In contrast, we observed substantial subtype heterogeneity in patients whose primary ovarian sample was classified as C5. The development of an efficient molecular classifier of HGSC should enable further biological characterization of molecular subtypes and the development of targeted clinical trials.

Expression of genes encoding the calcium signalosome in cellular and transgenic models of Huntington's disease

Huntington's disease (HD) is a hereditary neurodegenerative disease caused by the expansion of a polyglutamine stretch in the huntingtin (HTT) protein and characterized by dysregulated calcium homeostasis. We investigated whether these disturbances are correlated with changes in the mRNA level of the genes that encode proteins involved in calcium homeostasis and signaling (i.e., the calciosome). Using custom-made TaqMan low-density arrays containing probes for 96 genes, we quantified mRNA in the striatum in YAC128 mice, a model of HD, and wildtype mice. HTT mutation caused the increased expression of some components of the calcium signalosome, including calretinin, presenilin 2, and calmyrin 1, and the increased expression of genes indirectly involved in calcium homeostasis, such as huntingtin-associated protein 1 and calcyclin-binding protein. To verify these findings in a different model, we used PC12 cells with an inducible expression of mutated full-length HTT. Using single-cell imaging with Fura-2AM, we found that store-operated Ca²⁺ entry but not endoplasmic reticulum (ER) store content was changed as a result of the expression of mutant HTT. Statistically significant downregulation of the Orai calcium channel subunit 2, calmodulin, and septin 4 was detected in cells that expressed mutated HTT. Our data indicate that the dysregulation of calcium homeostasis correlates with changes in the gene expression of members of the calciosome. These changes, however, differed in the two models of HD used in this study. Our results indicate that each HD model exhibits distinct features that may only partially resemble the human disease.

Down-regulation of miR-145 and miR-143 might be associated with DNA methyltransferase 3B overexpression and worse prognosis in endometrioid carcinomas

The aim of this study was to determine the clinicopathologic significance of miR-145 and miR-143 down-regulation in endometrial cancers. The microRNA profiles were analyzed by microRNA microarray. The expression levels of miR-145 and miR-143 in 73 endometrial cancers were further determined by quantitative real-time polymerase chain reaction. Potential targets of miR-145/143 were defined. The status of DNA methyltransferase 3B (DNMT3B), mutL homologs 1, and phosphatase and tensin homolog was assessed using immunohistochemistry. miR-145 and miR-143 frequently co-down-regulated in endometrial cancers, but the expression levels varied greatly between endometrioid carcinomas (ECs) and non-ECs (NECs); they were significantly lower in ECs than in NECs (P < .05). DNMT3B was defined as a potential target of miR-145/143 by Internet algorithms. In ECs, DNMT3B overexpression occurred more often in the miR-145 and miR-143 down-regulation subgroups, and the correlation between DNMT3B and miR-145 status reached statistical significance (P = .021), whereas such phenomena were not present in NECs (P > .05). In univariate analysis, the combination of DNMT3B overexpression and miR-145 or miR-143 down-regulation was more powerful in predicting shorter survival (P < .05) than use of the biomarkers individually (P > .05). In multivariate analysis, such combination was not an independent predictor of disease-free survival (P > .05). Our findings suggest that the target and function of miR-145 and miR-143 may differ in ECs versus NECs. DNMT3B might be a potential target of miR-145 and miR-143 in ECs. Furthermore, the combined miR-145 or miR-143 and DNMT3B status may have a prognostic impact on ECs.