Over the past two decades, the 5-year survival for ovarian cancer patients has substantially improved owing to more effective surgery and treatment with empirically optimized combinations of cytotoxic drugs, but the overall cure rate remains approximately 30%. Many investigators think that further empirical trials using combinations of conventional agents are likely to produce only modest incremental improvements in outcome. Given the heterogeneity of this disease, increases in long-term survival might be achieved by translating recent insights at the molecular and cellular levels to personalize individual strategies for treatment and to optimize early detection.

/pdf/the-biology-of-ovarian-cancer-new-opportunities-for-11pxy8eu1m.pdf

The biology of ovarian cancer: new opportunities for translation

The validation of prognostic biomarkers in large independent patient cohorts is a major bottleneck in ovarian cancer research. We implemented an online tool to assess the prognostic value of the expression levels of all microarray-quantified genes in ovarian cancer patients. First, a database was set up using gene expression data and survival information of 1287 ovarian cancer patients downloaded from Gene Expression Omnibus and The Cancer Genome Atlas (Affymetrix HG-U133A, HG-U133A 2.0, and HG-U133 Plus 2.0 microarrays). After quality control and normalization, only probes present on all three Affymetrix platforms were retained (n=22,277). To analyze the prognostic value of the selected gene, we divided the patients into two groups according to various quantile expressions of the gene. These groups were then compared using progression-free survival (n=1090) or overall survival (n=1287). A Kaplan-Meier survival plot was generated and significance was computed. The tool can be accessed online at www.kmplot.com/ovar. We used this integrative data analysis tool to validate the prognostic power of 37 biomarkers identified in the literature. Of these, CA125 (MUC16; P=3.7×10(-5), hazard ratio (HR)=1.4), CDKN1B (P=5.4×10(-5), HR=1.4), KLK6 (P=0.002, HR=0.79), IFNG (P=0.004, HR=0.81), P16 (P=0.02, HR=0.66), and BIRC5 (P=0.00017, HR=0.75) were associated with survival. The combination of several probe sets can further increase prediction efficiency. In summary, we developed a global online biomarker validation platform that mines all available microarray data to assess the prognostic power of 22,277 genes in 1287 ovarian cancer patients. We specifically used this tool to evaluate the effect of 37 previously published biomarkers on ovarian cancer prognosis.

/pdf/implementing-an-online-tool-for-genome-wide-validation-of-216eg7vz86.pdf

Implementing an online tool for genome-wide validation of survival-associated biomarkers in ovarian-cancer using microarray data from 1287 patients.

Tumour stage, residual disease after initial surgery, histological type and tumour grade are the most important clinical-pathological factors related to the clinical outcome of patients with epithelial ovarian cancer. In the last years, several investigations have assessed different biological variables in sera and in tissue samples from patients with this malignancy in order to detect biomarkers able to reflect either the response to chemotherapy or survival. The present paper reviewed the literature data about the predictive or prognostic relevance of serum CA 125, soluble cytokeratin fragments, serum human kallikreins, serum cytokines, serum vascular endothelial growth factor and plasma d-dimer as well as of tissue expression of cell cycle- and apoptosis-regulatory proteins, human telomerase reverse transcriptase, membrane tyrosine kinase receptors and matrix metalloproteinases. A next future microarray technology will hopefully offer interesting perspectives of translational research for the identification of novel predictive and prognostic biomarkers for epithelial ovarian cancer.

Serum and tissue biomarkers as predictive and prognostic variables in epithelial ovarian cancer.

Sulforaphane (SFN), an isothiocyanate phytochemical present predominantly in cruciferous vegetables such as brussels sprout and broccoli, is considered a promising chemo-preventive agent against cancer. In-vitro exposure to SFN appears to result in the induction of apoptosis and cell-cycle arrest in a variety of tumor types. However, the molecular mechanisms leading to the inhibition of cell cycle progression by SFN are poorly understood in epithelial ovarian cancer cells (EOC). The aim of this study is to understand the signaling mechanisms through which SFN influences the cell growth and proliferation in EOC. SFN at concentrations of 5 - 20 μM induced a dose-dependent suppression of growth in cell lines MDAH 2774 and SkOV-3 with an IC50 of ~8 μM after a 3 day exposure. Combination treatment with chemotherapeutic agent, paclitaxel, resulted in additive growth suppression. SFN at ~8 μM decreased growth by 40% and 20% on day 1 in MDAH 2774 and SkOV-3, respectively. Cells treated with cytotoxic concentrations of SFN have reduced cell migration and increased apoptotic cell death via an increase in Bak/Bcl-2 ratio and cleavage of procaspase-9 and poly (ADP-ribose)-polymerase (PARP). Gene expression profile analysis of cell cycle regulated proteins demonstrated increased levels of tumor suppressor retinoblastoma protein (RB) and decreased levels of E2F-1 transcription factor. SFN treatment resulted in G1 cell cycle arrest through down modulation of RB phosphorylation and by protecting the RB-E2F-1 complex. SFN induces growth arrest and apoptosis in EOC cells. Inhibition of retinoblastoma (RB) phosphorylation and reduction in levels of free E2F-1 appear to play an important role in EOC growth arrest.

/pdf/sulforaphane-induces-cell-cycle-arrest-by-protecting-rb-e2f-23emftx8n8.pdf

Sulforaphane induces cell cycle arrest by protecting RB-E2F-1 complex in epithelial ovarian cancer cells

Classically, as a transcription factor family, the E2Fs are known to regulate the expression of various genes whose products are involved in a multitude of biological functions, many of which are deregulated in diseases including cancers. E2F is deregulated and hyperactive in most human cancers with context dependent, dichotomous and contradictory roles in almost all cancers. Cancer cells have an insatiable demand for transcription to ensure that gene products are available to sustain various biological processes that support their rapid growth and survival. In this context, cutting-off hyperactivity of transcription factors that support transcription dependence could be a valuable therapeutic strategy. However, one of the greatest challenges of targeting a transcription factor is the global effects on non-cancerous cells given that they control cellular functions in general. Recently, there is growing realization regarding the possibility to target the oncogenic activation of transcription factors to modulate transcription addiction without affecting the normal activity required for cell functions. In this review, we used E2F1 as a prototype transcription factor to address transcription factor activity in cancer cell functions. We focused on melanoma considering that E2F1 executes critical functions in response to UV, an etiological factor of cutaneous melanoma and lies immediately downstream of the CDKN2A/pRb axis, which is frequently deregulated in melanoma. Further, activation of E2F1 in melanomas can also occur independent of loss of CDKN2A. Given its activated status and the ability to transcriptionally control a plethora of genes involved in regulating melanoma development and progression, we review the current literature on its differential role in controlling signaling pathways involved in melanoma as well as therapeutic resistance, and discuss the practical value of weaning melanoma cells from E2F1-mediated transcription dependence for melanoma management.

/pdf/transcription-addiction-can-we-garner-the-yin-and-yang-3hf6l2gx80.pdf

Transcription addiction: can we garner the Yin and Yang functions of E2F1 for cancer therapy?

E2F-1 is a downstream regulator of the Rb pathway and is a transcription factor that plays a key role in the control of cell cycle progression. Deregulation of E2F-1 expression and Rb pathway is involved in carcinogenesis. The aim of this study was to evaluate E2F-1 expression and Rb pathway alteration and to elucidate their correlation with clinical and pathologic parameters in epithelial ovarian cancer (EOC). We investigated overexpression of E2F-1 and alterations of p16INK4a, cyclin D1, CDK4, and pRb using immunohistochemistry and tissue microarray methods in 72 EOC patients. Overexpression of E2F-1 was detected in 45.8% of samples. The overall abnormal expression frequencies of p16INK4a, cyclin D1, CDK4, and pRb were 33.3%, 11.1%, 12.5%, and 38.9%, respectively. E2F-1 overexpression was not associated with alteration of the Rb pathway. E2F-1 overexpression was correlated with FIGO stage, histologic grade, and mitotic index; it was a valuable prognostic variable along with FIGO stage in the multivariated analysis. The results suggest that E2F-1 has a growth-promoting effect in EOC and that E2F-1 overexpression may provide a useful prognostic indicator for EOC.

https://ijgc.bmj.com/content/ijgc/18/3/492.full.pdf

Significance of E2F-1 overexpression in epithelial ovarian cancer.

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Significance of E2F-1 overexpression in epithelial ovarian cancer.