The Ovarian Transcriptome of Reproductively Aged Multiparous Mice: Candidate Genes for Ovarian Cancer Protection.

In middle-aged women, the decline of ovarian follicle reserve below a critical threshold marks menopause, leading to hormonal, inflammatory, and metabolic changes linked to disease. The highest incidence and mortality of sporadic ovarian cancer (OC) occur at post-menopause, while OC risk is reduced by full-term pregnancies during former fertile life. Herein, we investigate how parity history modulates the ovarian transcriptome related to such declining follicle pool and systemic inflammation in reproductively-aged mice. Female C57BL/6 mice were housed under multiparous and virgin (nulliparous) breeding regimens from adulthood until estropause. The ovaries were then subjected to follicle count and transcriptional profiling, while a cytokine panel was determined in the sera. As expected, the follicle number was markedly decreased just by aging. Importantly, a significantly higher count of primordial and total follicles was observed in aged multiparous relative to aged virgin ovaries. Consistently, among the 65 genes of higher expression in aged multiparous ovaries, 27 showed a follicle count-like pattern, 21 had traceable evidence of roles in follicular/oocyte homeostasis, and 7 were transforming-growth factor beta (TGF-ß)/bone morphogenetic protein (BMP) superfamily members. The remaining genes were enriched in cell chemotaxis and innate-immunity, and resembled the profiles of circulating CXCL1, CXCL2, CXCL5, CSF3, and CCL3, chemokines detected at higher levels in aged multiparous mice. We conclude that multiparity during reproductive life promotes the retention of follicle remnants while improving local (ovarian) and systemic immune-innate surveillance in aged female mice. These findings could underlie the mechanisms by which pregnancy promotes the long-term reduced OC risk observed at post-menopause.

Prospective molecular profiling of melanoma metastases suggests classifiers of immune responsiveness.

We amplified RNAs from 63 fine needle aspiration (FNA) samples from 37 s.c. melanoma metastases from 25 patients undergoing immunotherapy for hybridization to a 6108-gene human cDNA chip. By prospectively following the history of the lesions, we could correlate transcript patterns with clinical outcome. Cluster analysis revealed a tight relationship among autologous synchronously sampled tumors compared with unrelated lesions (average Pearson's r = 0.83 and 0.7, respectively, P < 0.0003). As reported previously, two subgroups of metastatic melanoma lesions were identified that, however, had no predictive correlation with clinical outcome. Ranking of gene expression data from pretreatment samples identified approximately 30 genes predictive of clinical response (P < 0.001). Analysis of their annotations denoted that approximately half of them were related to T-cell regulation, suggesting that immune responsiveness might be predetermined by a tumor microenvironment conducive to immune recognition.

Transcriptomic analysis of an in vitro murine model of ovarian carcinoma: functional similarity to the human disease and identification of prospective tumoral markers and targets.

Ovarian cancer is an aggressive disease of poor prognostic when detected at advanced stage. It is widely accepted that the ovarian surface epithelium plays a central role in disease etiology, but little is known about disease progression at the molecular level. To identify genes involved in ovarian tumorigenesis, we carried out a genome-wide transcriptomic analysis of six spontaneously transformed mouse ovarian surface epithelial (MOSE) cell lines, an in vitro model for human ovarian carcinoma. Loess normalization followed by statistical analysis with control of multiple testing resulted in 509 differentially expressed genes using an adjusted P-value < or = 0.05 as cut-off. The top 20 differentially expressed genes included 10 genes (Spp1, Cyp1b1, Btg1, Cfh, Mt1, Mt2, Igfbp5, Gstm1, Gstm2, and Esr1) implicated in various aspects of ovarian carcinomas, and other 3 genes (Gsto1, Lcn7, and Alcam) associated to breast cancer. Upon functional analysis, the majority of alterations affected genes involved in glutathione metabolism and MAPK signaling pathways. Interestingly, over 20% of the aberrantly expressed genes were related to extracellular components, suggestive of potential markers of disease progression. In addition, we identified the genes Pura, Cnn3, Arpc1b, Map4k4, Tgfb1i4, and Crsp2 correlated to in vivo tumorigenic parameters previously reported for these cells. Taken together, our findings support the utility of MOSE cells in studying ovarian cancer biology and as a source of novel diagnostic and therapeutic targets.

A bioinformatics tool to select sequences for microarray studies of mouse models of oncogenesis.

UNLABELLED: One of the challenges to the effective utilization of cDNA microarray analysis in mouse models of oncogenesis is the choice of a critical set of probes that are informative for human disease. Given the thousands of genes with a potential role in human oncogenesis and the hundreds of thousands of mouse sequences available for use as probes, selection of an informative set of mouse probes can be an overwhelming task. We have developed a web based sequence mining tool using DataBase Independent (DBI) Perl to annotate publicly available sequences. The Mouse Oncochip Design Tool uses the Mouse Genome Database (MGD) developed and maintained by the Jackson Laboratories for mouse DNA sequences. There are over 380 000 sequences in their database. The output list has been ordered to present the genes more likely to be informative in a mouse model of human cancer using a candidate set of oncogenes to order the list. Mouse sequences that represent genes that are homologous with a member of a human oncogene set are listed first. In addition it provides a set of links for information on clone source gene function. CONTACT: http://nciarray.nci.nih.gov/cgi-bin/me/mouse_design.cgi

Initiating oncogenic event determines gene-expression patterns of human breast cancer models.

Molecular expression profiling of tumors initiated by transgenic overexpression of c-myc, c-neu, c-ha-ras, polyoma middle T antigen (PyMT) or simian virus 40 T/t antigen (T-ag) targeted to the mouse mammary gland have identified both common and oncogene-specific events associated with tumor formation and progression. The tumors shared great similarities in their gene-expression profiles as compared with the normal mammary gland with an induction of cell-cycle regulators, metabolic regulators, zinc finger proteins, and protein tyrosine phosphatases, along with the suppression of some protein tyrosine kinases. Selection and hierarchical clustering of the most variant genes, however, resulted in separating the mouse models into three groups with distinct oncogene-specific patterns of gene expression. Such an identification of targets specified by particular oncogenes may facilitate development of lesion-specific therapeutics and preclinical testing. Moreover, similarities in gene expression between human breast cancers and the mouse models have been identified, thus providing an important component for the validation of transgenic mammary cancer models.