Identification of a Potential Ovarian Cancer Stem Cell Gene Expression Profile from Advanced Stage Papillary Serous Ovarian Cancer

Identification of gene expression profiles of cancer stem cells may have significant implications in the understanding of tumor biology and for the design of novel treatments targeted toward these cells. Here we report a potential ovarian cancer stem cell gene expression profile from isolated side population of fresh ascites obtained from women with high-grade advanced stage papillary serous ovarian adenocarcinoma. Affymetrix U133 Plus 2.0 microarrays were used to interrogate the differentially expressed genes between side population (SP) and main population (MP), and the results were analyzed by paired T-test using BRB-ArrayTools. We identified 138 up-regulated and 302 down-regulated genes that were differentially expressed between all 10 SP/MP pairs. Microarray data was validated using qRT-PCR and17/19 (89.5%) genes showed robust correlations between microarray and qRT-PCR expression data. The Pathway Studio analysis identified several genes involved in cell survival, differentiation, proliferation, and apoptosis which are unique to SP cells and a mechanism for the activation of Notch signaling is identified. To validate these findings, we have identified and isolated SP cells enriched for cancer stem cells from human ovarian cancer cell lines. The SP populations were having a higher colony forming efficiency in comparison to its MP counterpart and also capable of sustained expansion and differentiation in to SP and MP phenotypes. 50,000 SP cells produced tumor in nude mice whereas the same number of MP cells failed to give any tumor at 8 weeks after injection. The SP cells demonstrated a dose dependent sensitivity to specific γ-secretase inhibitors implicating the role of Notch signaling pathway in SP cell survival. Further the generated SP gene list was found to be enriched in recurrent ovarian cancer tumors

An RNA Interference Lethality Screen of the Human Druggable Genome to Identify Molecular Vulnerabilities in Epithelial Ovarian Cancer

Targeted therapies have been used to combat many tumor types; however, few have effectively improved the overall survival in women with epithelial ovarian cancer, begging for a better understanding of this deadly disease and identification of essential drivers of tumorigenesis that can be targeted effectively. Therefore, we used a loss-of-function screening approach to help identify molecular vulnerabilities that may represent key points of therapeutic intervention. We employed an unbiased high-throughput lethality screen using a 24,088 siRNA library targeting over 6,000 druggable genes and studied their effects on growth and/or survival of epithelial ovarian cancer (EOC) cell lines. The top 300 “hits” affecting the viability of A1847 cells were rescreened across additional EOC cell lines and non-tumorigenic, human immortalized ovarian epithelial cell lines. Fifty-three gene candidates were found to exhibit effects in all tumorigenic cell lines tested. Extensive validation of these hits refined the list to four high quality candidates (HSPA5, NDC80, NUF2, and PTN). Mechanistic studies show that silencing of three genes leads to increased apoptosis, while HSPA5 silencing appears to alter cell growth through G1 cell cycle arrest. Furthermore, two independent gene expression studies show that NDC80, NUF2 and PTN were significantly aberrantly overexpressed in serous adenocarcinomas. Overall, our functional genomics results integrated with the genomics data provide an important unbiased avenue towards the identification of prospective therapeutic targets for drug discovery, which is an urgent and unmet clinical need for ovarian cancer

Inhibition of Hedgehog Signaling Antagonizes Serous Ovarian Cancer Growth in a Primary Xenograft Model

Recent evidence links aberrant activation of Hedgehog (Hh) signaling with the pathogenesis of several cancers including medulloblastoma, basal cell, small cell lung, pancreatic, prostate and ovarian. This investigation was designed to determine if inhibition of this pathway could inhibit serous ovarian cancer growth.We utilized an in vivo pre-clinical model of serous ovarian cancer to characterize the anti-tumor activity of Hh pathway inhibitors cyclopamine and a clinically applicable derivative, IPI-926. Primary human serous ovarian tumor tissue was used to generate tumor xenografts in mice that were subsequently treated with cyclopamine or IPI-926.Both compounds demonstrated significant anti-tumor activity as single agents. When IPI-926 was used in combination with paclitaxel and carboplatinum (T/C), no synergistic effect was observed, though sustained treatment with IPI-926 after cessation of T/C continued to suppress tumor growth. Hh pathway activity was analyzed by RT-PCR to assess changes in Gli1 transcript levels. A single dose of IPI-926 inhibited mouse stromal Gli1 transcript levels at 24 hours with unchanged human intra-tumor Gli1 levels. Chronic IPI-926 therapy for 21 days, however, inhibited Hh signaling in both mouse stromal and human tumor cells. Expression data from the micro-dissected stroma in human serous ovarian tumors confirmed the presence of Gli1 transcript and a significant association between elevated Gli1 transcript levels and worsened survival.IPI-926 treatment inhibits serous tumor growth suggesting the Hh signaling pathway contributes to the pathogenesis of ovarian cancer and may hold promise as a novel therapeutic target, especially in the maintenance setting

Identification of Novel Therapeutic Targets in Microdissected Clear Cell Ovarian Cancers

Clear cell ovarian cancer is an epithelial ovarian cancer histotype that is less responsive to chemotherapy and carries poorer prognosis than serous and endometrioid histotypes. Despite this, patients with these tumors are treated in a similar fashion as all other ovarian cancers. Previous genomic analysis has suggested that clear cell cancers represent a unique tumor subtype. Here we generated the first whole genomic expression profiling using epithelial component of clear cell ovarian cancers and normal ovarian surface specimens isolated by laser capture microdissection. All the arrays were analyzed using BRB ArrayTools and PathwayStudio software to identify the signaling pathways. Identified pathways validated using serous, clear cell cancer cell lines and RNAi technology. In vivo validations carried out using an orthotopic mouse model and liposomal encapsulated siRNA. Patient-derived clear cell and serous ovarian tumors were grafted under the renal capsule of NOD-SCID mice to evaluate the therapeutic potential of the identified pathway. We identified major activated pathways in clear cells involving in hypoxic cell growth, angiogenesis, and glucose metabolism not seen in other histotypes. Knockdown of key genes in these pathways sensitized clear cell ovarian cancer cell lines to hypoxia/glucose deprivation. In vivo experiments using patient derived tumors demonstrate that clear cell tumors are exquisitely sensitive to antiangiogenesis therapy (i.e. sunitinib) compared with serous tumors. We generated a histotype specific, gene signature associated with clear cell ovarian cancer which identifies important activated pathways critical for their clinicopathologic characteristics. These results provide a rational basis for a radically different treatment for ovarian clear cell patients

Low-grade and high-grade serous Mullerian carcinoma: Review and analysis of publicly available gene expression profiles.

OBJECTIVE: Mullerian low grade serous carcinoma (LGSC) and high grade serous carcinoma (HGSC) have distinct molecular profiles, clinical behavior and treatment response. Our objective was to study the biological profiles of these carcinomas. METHODS: This study examines publicly available gene expression profiles of LGSC and HGSC to identify differentially expressed genes and key pathways involved in carcinogenesis and chemotherapy response. RESULTS: Our analysis supports the hypothesis that serous mullerian carcinoma develop through two different pathways yielding two distinct malignancies, namely LGSC and HGSC. Furthermore, genes potentially involved in chemotherapeutic resistance of LGSC were identified. Suppressing the levels of these genes/proteins may increase clinical response to standard chemotherapy in patients with LGSC. CONCLUSION: In summary, this review shows the molecular profile of LGSC and HGSC through multi-center analysis of gene expression profiles of these tumors. The gene signatures of these neoplasms may potentially be used to develop disease-specific, targeted therapy for LGSC and HGSC. Gynecol Oncol 2013 Mar; 128(3):488-92

Expression profiling of SP/MP cells from ascites specimens.

<p>(A) Heatmap showing the expression pattern of 438 probesets that discriminated SP cells from MP cells in ovarian cancer patients. Vertical columns represent individual samples; horizontal rows represent individual genes. The red and blue color indicates up and down-regulation respectively. (B) Validation of microarray data using qRT-PCR: 19 randomly selected genes were used to validate the microarray data. To calculate the relative expression for each gene, the 2^−ΔΔCT method was used averaging the CT values for the three housekeeping genes (Cyclophilin A, GUSB, GAPDH) for a single reference gene value. (C) Representative plots for correlation analysis between the microarray and qRT-PCR data: The 2^−ΔCT values (qRT-PCR) were plotted against signal intensity values (Microarray). The correlation analysis was performed for each gene by Pearson's and Spearman's method using GraphPad Prism version 4.00.</p

Validation of SP cells from cell lines and the effect of GSI-IX inhibitor on SP cells colony forming efficiency.

<p>(A) Repopulation Assay: The SKOV3 and A224 cells were stained with Hoechst 33342 dye and sorted for SP and MP populations. The cells were cultured for 8 days for repopulation, and then reanalyzed by flow cytometry. This demonstrated the enrichment of SP cells (22.5% and 10.4% for SKOV3 and A224 resp.) with a capacity to regenerate to MP cells. (B, C, D) qRT-PCR analysis for stem cell marker genes and transporter genes (p<0.01). To calculate the relative expression for each gene, the 2^−ΔΔCT method was used averaging the CT values for the three housekeeping genes (Cyclophilin A, GUSB, GAPDH) for a single reference gene value. (E, F) Inhibitory effect of GSI-IX on Colony forming efficiency of sorted SP and MP cells from SKOV3. Cells were sorted to SP and MP populations and treated with 10 and 20 µg of GSI-IX. The inhibitor carrier DMSO is used as a control.</p

Identification and validation of side population cells from ovarian cancer cell lines.

<p>(A) Identification of SP cells in established human ovarian cancer cell lines. SKOV3 and A224 cell lines were labeled with Hoechst 33342 dye and analyzed by flow cytometry. The SP cells, which disappeared in the presence of Verapamil (a multidrug transporter inhibitor), are outlined and shown as the percentage of the total cell population. Similar results were obtained for three independent measurements. (B) Validation of randomly selected genes from the SP gene list on the SP and MP cells isolated from the SKOV3 cell lines. (C, D) Colony forming efficiency assay: Colony forming efficiency of sorted SP and MP cells from SKOV3 and A224 cell lines. For the analysis of colony forming efficiency (CFE), SP and MP cells were sorted and plated in equal numbers in tissue culture six well plates and grown for 14 days. The cells were then fixed with cold methanol and stained with 0.5% crystal violet solution to count the number of colonies by microscopy. The experiments were carried out in triplicates. (E, F) Passage Number: Colony forming efficiency of sorted SP and MP cells from SKOV3 and A224 cell lines were evaluated as a function of passage number. Cells were fixed with cold methanol and stained with 0.5% crystal violet.</p

The percentage of the SP cells identified in ascites samples.

<p>n.d. (not determined).</p

Identification of putative signaling events contributing to ovarian cancer SP cell survival, self-renewal and tumor maintenance.

<p>(A) Gene ontology analysis of microarray data (P value<0.01): The pie diagram shows the biological functions of the differentially expressed genes among SP and MP cells. The gene signature was enriched for genes in gene ontology biological processes of apoptosis, cell cycle, cell proliferation, transport, signal transduction, transcription, translation, protein modification, metabolism and proteolysis. Other represents genes involved in defense response, vasculogenesis, blood coagulation, visual perception, ontogenesis, cell matrix adhesion, and initiation of primordial ovarian follicle growth. (B) Graphical representation of the literature derived facts about the biological pathways involved in SP cells. Pathway Studio 6.0 software was used to identify the activated pathways in SP cells. Solid symbols representing the genes (EGFR, TNFRSF6, BCL2L11, FOXO3A, RUNX1) as down regulated in SP cells, the open symbols represents the upregulated genes (EPHB4, EPHB2, PAWR, AKT1) and gray symbols are the genes whose expression did not change significantly between SP and MP cells. (C) The Notch signaling pathway: The figure shows the schematic of Notch signal transduction elements. The overexpressed proteins in SP cells (FPTG, ST3GAL6 and ADAM19) are shown in blue color. Post-translational modification of precursor Notch-protein includes cleavage by proteases and glycosylations in the trans-Golgi. Adherence of Notch extracellular domain (ECN) with Notch intracellular domain (ICN) results in mature Notch heterodimers and they are transferred to the cell membrane. Receptor interaction with the ligands of the DSL family (Delta, Serrate, Lag3) on neighboring cells is modulated by glycosylations of ECN. Successful interaction of extracellular ligand regions with EGF-like repeats of ECN lead to the proteolytic cleavages of Notch transmembrane domain by two sequential steps by ADAM proteases and presenilins with γ–secretase activity. The released Notch intracellular domain is translocated to the nuclease where it interacts with CSL1, replacing CSL repressors and forming a transcription complex with Mastermind-like factors and transcriptional coactivators. This transcriptional complex activates downstream target genes and may account for cancer stem cell survival, self-renewal and tumor maintenance in ovary.</p