Dysfunction of key miRNA pathways regulating basic cellular processes is a common driver of many cancers. However, the biological roles and/or clinical applications of such pathways in Merkel cell carcinoma (MCC), a rare but lethal cutaneous neuroendocrine (NE) malignancy, have yet to be determined. Previous work has established that miR-375 is highly expressed in MCC tumors, but its biological role in MCC remains unknown. Herein, we show that elevated miR-375 expression is a specific feature of well-differentiated MCC cell lines that express NE markers. In contrast, miR-375 is strikingly down-regulated in highly aggressive, undifferentiated MCC cell lines. Enforced miR-375 expression in these cells induced NE differentiation, and opposed cancer cell viability, migration, invasion, and survival, pointing to tumor-suppressive roles for miR-375. Mechanistically, miR-375-driven phenotypes were caused by the direct post-transcriptional repression of multiple Notch pathway proteins (Notch2 and RBPJ) linked to cancer and regulation of cell fate. Thus, we detail a novel molecular axis linking tumor-suppressive miR-375 and Notch with NE differentiation and cancer cell behavior in MCC. Our findings identify miR-375 as a putative regulator of NE differentiation, provide insight into the cell of origin of MCC, and suggest that miR-375 silencing may promote aggressive cancer cell behavior through Notch disinhibition.

Abstract Ovarian cancer is the leading cause of death from gynecological malignancies and the fifth major cancer in women in the world. Once diagnosed, ovarian cancer is usually treated by cytoreductive surgery followed by platinum and taxane-based chemotherapeutic drugs. However, resistance to chemotherapy is a major impediment in management of serous epithelial ovarian cancer (SEOC). We hypothesize that a multifaceted view of the alterations taking place at multiple cellular levels using molecular profiling technologies will offer insight into the mechanisms which play key roles in drug resistant ovarian carcinomas. Also, the application of appropriate bioinformatic and statistical data processing and analysis is of utmost importance in identification of key drug resistance pathways. Current study is performed on 25 high-grade serous epithelial ovarian tumor tissue samples from patients that demonstrated favorable, or unfavorable response to chemotherapy treatment. Four different microarray platforms were used for molecular profiling of the full sample cohort at different molecular levels, namely: Single Nucleotide Polymorphisms (SNP), mRNA expression, miRNA expression and promotor tiling arrays (methylation)., Integrative and systematic analyses using up-to-date statistical approaches, such as empirical Bayes, AUC, SAM, permuted t-test and lassoed PCA, among others, have been employed on these large datasets obtained through the various high-throughput platforms. Preliminary mRNA expression analysis identified an enrichment of upregulated genes involved in cellular growth and proliferation, cellular development as well as differential gene expression changes in the TGFB1, TNF, PI3K, IFNG networks, between the chemotherapy responsive and unresponsive groups. The major molecular and cellular functions associated were cell-to-cell signaling, molecular transport and cellular movement. Differences were also seen in the, CTNNB1, LH and FSH networks as analysed by Ingenuity Pathway Analysis. Additionally, genes involved in activation of NFκB pathway showed differential expression in the two groups. Furthermore, our ongoing development of a streamlined database in which the multiple data types obtained from our statistical analyses are stored, will allow for localized or genome wide querying across the multiple levels of biological data. These approaches and software will potentially elucidate the synergistic roles that the various biological levels play in the deregulation of pathways involved in primary chemoresistance. Our research findings will lead to the determination of putative candidates for diagnostic and prognostic biomarkers that can be targeted for development of treatment regimens for the treatment of SEOC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3004. doi:1538-7445.AM2012-3004

Abstract Development of primary resistance to carboplatin and paclitaxel pose a major challenge in the management of ovarian cancer. To identify the molecular mechanisms underlying this process, we used microarrays to profile the 1) copy number alteration and SNP, 2) mRNA, 3) miRNA and 4) methylation signatures in 11 chemoresistant and 13 sensitive tumour samples, as defined by the RECIST criteria. The profiles are analyzed by Bayes statistics, based on R/Bioconductor packages, and the relevant pathways determined using the Ingenuity Pathway Analysis. The data from each array platforms are integrated using bioinformatic analytical and visual tools developed in house to not only decipher the most critical biological pathways, but also to identify the molecular mechanisms driving the pathways. Analysis to date identified the metabolic network involving HNRNPC, JAK1, Erbb2, ARF1, among others, which converge to deregulate the PI3K pathway. Interestingly, this is consistent with PTEN loss which is frequently observed in serous low grade tumours. The complexity of this pathway is reflected by its implication in multiple biological functions including growth promoting pathways, proliferation, differentiation, anti-apoptosis, tumorigenesis and angiogenesis. The integrated analysis will dissect and elucidate the roles that the CNA, SNP, methylation and miRNA play in the deregulation of this and other pathways involved in primary chemoresistance. Our research findings will yield diagnostic and prognostic biomarkers that will lead to development of specific treatment regimens for the improved control of serous epithelial ovarian cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3155. doi:10.1158/1538-7445.AM2011-3155

Ovarian cancer is the 5th leading cause of cancer related death in women, and has the highest associated mortality rate of any of the gynecological cancers. Approximately 75-80% of women diagnosed will succumb to the disease. The high mortality rate associated with ovarian cancer is due to poor screening and detection methods, resulting in late stage diagnosis, and also to resistance of the tumours to chemotherapeutic drugs. Primary drug resistance occurs in about 20% of patients during their treatment phase while approximately 70-80% of women that initially respond to chemotherapy will develop drug resistance over the course of treatment or at the time of relapse. Being able to accurately predict which patients will not successfully respond to drugs is the first step in developing personalized medicine and preventing useless chemotherapy treatments. In order to discover biomarkers of cisplatin resistance, a multi-platform integrative approach was taken utilizing data from aCGH as well as miRNA and mRNA microarrays. Data were collected from a drug sensitive and drug resistant ovarian cancer cell line pair (A2780 and A2780cis). Working with the paired cell lines provided a homogeneous population with which to build an integration algorithm. Data analysis using GeneSpring and Nexus software showed an enrichment of genes involved in TGFβ and EGF signaling. These signaling pathways lead us to investigate the involvement of the epithelial to mesenchymal transition (EMT) in drug resistance. Interestingly, many of the key genes involved in the regulation of the EMT process were found to be upregulated in our mRNA expression data. Observations from cell culture work support EMT involvement. We have noted a slower growth rate and a change to a fibroblastic appearance in the resistant cells relative to their drug sensitive parents. Immunohistochemistry has also been utilized to show an increase in mesenchymal markers in the resistant cell line. In order to determine if these findings were representative of drug resistance in human ovarian cancer, expression data from cisplatin sensitive and resistant ovarian cancer tumours were mined specifically for these and other EMT genes. A large number of the same EMT genes were consistently shown to be upregulated in the drug resistant tumour tissues relative to the sensitive tumours. Together, these data suggest the potential involvement of the epithelial to mesenchymal transition in the development of cisplatin resistance in ovarian cancer. Further validation of these results in vitro is currently in progress. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1719. doi:10.1158/1538-7445.AM2011-1719