OvMark: a user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets

Integrin-linked kinase-frizzled 7 interaction maintains cancer stem cells to drive platinum resistance in ovarian cancer

BACKGROUND

Platinum-based chemotherapy regimens are a mainstay in the management of ovarian cancer (OC), but emergence of chemoresistance poses a significant clinical challenge. The persistence of ovarian cancer stem cells (OCSCs) at the end of primary treatment contributes to disease recurrence. Here, we hypothesized that the extracellular matrix protects CSCs during chemotherapy and supports their tumorigenic functions by activating integrin-linked kinase (ILK), a key enzyme in drug resistance.

METHODS

TCGA datasets and OC models were investigated using an integrated proteomic and gene expression analysis and examined ILK for correlations with chemoresistance pathways and clinical outcomes. Canonical Wnt pathway components, pro-survival signaling, and stemness were examined using OC models. To investigate the role of ILK in the OCSC-phenotype, a novel pharmacological inhibitor of ILK in combination with carboplatin was utilized in vitro and in vivo OC models.

RESULTS

In response to increased fibronectin secretion and integrin β1 clustering, aberrant ILK activation supported the OCSC phenotype, contributing to OC spheroid proliferation and reduced response to platinum treatment. Complexes formed by ILK with the Wnt receptor frizzled 7 (Fzd7) were detected in tumors and correlated with metastatic progression. Moreover, TCGA datasets confirmed that combined expression of ILK and Fzd7 in high grade serous ovarian tumors is correlated with reduced response to chemotherapy and poor patient outcomes. Mechanistically, interaction of ILK with Fzd7 increased the response to Wnt ligands, thereby amplifying the stemness-associated Wnt/β-catenin signaling. Notably, preclinical studies showed that the novel ILK inhibitor compound 22 (cpd-22) alone disrupted ILK interaction with Fzd7 and CSC proliferation as spheroids. Furthermore, when combined with carboplatin, this disruption led to sustained AKT inhibition, apoptotic damage in OCSCs and reduced tumorigenicity in mice.

CONCLUSIONS

This "outside-in" signaling mechanism is potentially actionable, and combined targeting of ILK-Fzd7 may lead to new therapeutic approaches to eradicate OCSCs and improve patient outcomes.

Integrin-linked kinase-frizzled 7 interaction maintains cancer stem cells to drive platinum resistance in ovarian cancer

Background

Platinum-based chemotherapy regimens are a mainstay in the management of ovarian cancer (OC), but emergence of chemoresistance poses a significant clinical challenge. The persistence of ovarian cancer stem cells (OCSCs) at the end of primary treatment contributes to disease recurrence. Here, we hypothesized that the extracellular matrix protects CSCs during chemotherapy and supports their tumorigenic functions by activating integrin-linked kinase (ILK), a key enzyme in drug resistance.

Methods

TCGA datasets and OC models were investigated using an integrated proteomic and gene expression analysis and examined ILK for correlations with chemoresistance pathways and clinical outcomes. Canonical Wnt pathway components, pro-survival signaling, and stemness were examined using OC models. To investigate the role of ILK in the OCSC-phenotype, a novel pharmacological inhibitor of ILK in combination with carboplatin was utilized in vitro and in vivo OC models.

Results

In response to increased fibronectin (FN) secretion and integrin β1 clustering, aberrant ILK activation supported the OCSC phenotype, contributing to OC spheroid proliferation and reduced response to platinum treatment. Complexes formed by ILK with the Wnt receptor frizzled 7 (Fzd7) were detected in tumors and showed a strong correlation with metastatic progression. Moreover, TCGA datasets confirmed that combined expression of ILK and Fzd7 in high grade serous ovarian tumors is correlated with reduced response to chemotherapy and poor patient outcomes. Mechanistically, interaction of ILK with Fzd7 increased the response to Wnt ligands, thereby amplifying the stemness-associated Wnt/β-catenin signaling. Notably, preclinical studies showed that the novel ILK inhibitor compound 22 (cpd-22) alone disrupted ILK interaction with Fzd7 and CSC proliferation as spheroids. Furthermore, when combined with carboplatin, this disruption led to sustained AKT inhibition, apoptotic damage in OCSCs and reduced tumorigenicity in mice.

Conclusions

This "outside-in" signaling mechanism is potentially actionable, and combined targeting of ILK-Fzd7 may represent a new therapeutic strategy to eradicate OCSCs and improve patient outcomes.

Cancer associated fibroblasts serve as an ovarian cancer stem cell niche through noncanonical Wnt5a signaling

Frequent relapse and chemoresistance cause poor outcome in ovarian cancer (OC) and cancer stem cells (CSCs) are important contributors. While most studies focus exclusively on CSCs, the role of the microenvironment in providing optimal conditions to maintain their tumor-initiating potential remains poorly understood. Cancer associated fibroblasts (CAFs) are a major constituent of the OC tumor microenvironment and we show that CAFs and CSCs are enriched following chemotherapy in patient tumors. CAFs significantly increase OC cell resistance to carboplatin. Using heterotypic CAF-OC cocultures and in vivo limiting dilution assay, we confirm that the CAFs act by enriching the CSC population. CAFs increase the symmetric division of CSCs as well as the dedifferentiation of bulk OC cells into CSCs. The effect of CAFs is limited to OC cells in their immediate neighborhood, which can be prevented by inhibiting Wnt. Analysis of single cell RNA-seq data from OC patients reveal Wnt5a as the highest expressed Wnt in CAFs and that certain subpopulations of CAFs express higher levels of Wnt5a. Our findings demonstrate that Wnt5a from CAFs activate a noncanonical Wnt signaling pathway involving the ROR2/PKC/CREB1 axis in the neighboring CSCs. While canonical Wnt signaling is found to be predominant in interactions between cancer cells in patients, non-canonical Wnt pathway is activated by the CAF-OC crosstalk. Treatment with a Wnt5a inhibitor sensitizes tumors to carboplatin in vivo. Together, our results demonstrate a novel mechanism of CSC maintenance by signals from the microenvironmental CAFs, which can be targeted to treat OC chemoresistance and relapse.

Gene co-expression network analysis revealed novel biomarkers for ovarian cancer

Ovarian cancer is the second most common gynecologic cancer and remains the leading cause of death of all gynecologic oncologic disease. Therefore, understanding the molecular mechanisms underlying the disease, and the identification of effective and predictive biomarkers are invaluable for the development of diagnostic and treatment strategies. In the present study, a differential co-expression network analysis was performed via meta-analysis of three transcriptome datasets of serous ovarian adenocarcinoma to identify novel candidate biomarker signatures, i.e. genes and miRNAs. We identified 439 common differentially expressed genes (DEGs), and reconstructed differential co-expression networks using common DEGs and considering two conditions, i.e. healthy ovarian surface epithelia samples and serous ovarian adenocarcinoma epithelia samples. The modular analyses of the constructed networks indicated a co-expressed gene module consisting of 17 genes. A total of 11 biomarker candidates were determined through receiver operating characteristic (ROC) curves of gene expression of module genes, and miRNAs targeting these genes were identified. As a result, six genes (CDT1, CNIH4, CRLS1, LIMCH1, POC1A, and SNX13), and two miRNAs (mir-147a, and mir-103a-3p) were suggested as novel candidate prognostic biomarkers for ovarian cancer. Further experimental and clinical validation of the proposed biomarkers could help future development of potential diagnostic and therapeutic innovations in ovarian cancer.

Analysis of the Effect of SNAI Family in Breast Cancer and Immune Cell

SNAI family members are transcriptional repressors that induce epithelial-mesenchymal transition during biological development. SNAIs both have tumor-promoting and tumor-inhibiting effect. There are key regulatory effects on tumor onset and development, and patient prognosis in infiltrations of immune cell and tumor microenvironmental changes. However, the relationships between SNAIs and immune cell infiltration remain unclear. We comprehensively analyzed the roles of SNAIs in cancer. We used Oncomine and TCGA data to analyze pan-cancer SNAI transcript levels. By analyzing UALCAN data, we found correlations between SNAI transcript levels and breast cancer patient characteristics. Kaplan–Meier plotter analysis revealed that SNAI1 and SNAI2 have a bad prognosis, whereas SNAI3 is the opposite. Analysis using the cBio Cancer Genomics Portal revealed alterations in SNAIs in breast cancer subtypes. Gene Ontology analysis and gene set enrichment analysis were used to analyze differentially expressed genes related to SNAI proteins in breast cancer. We used TIMER to analyze the effects of SNAI transcript levels, mutations, methylation levels, and gene copy number in the infiltration of immune cell. Further, we found the relationships between immune cell infiltration, SNAI expression levels, and patient outcomes. To explore how SNAI proteins affect immune cell, we further studied the correlations between immunomodulator expression, chemokine expression, and SNAI expression. The results showed that SNAI protein levels were correlated with the expression of several immunomodulators and chemokines. Through analysis of PharmacoDB data, we identified antitumor drugs related to SNAI family members and analyzed their IC50 effects on various breast cancer cell lines. In summary, our study revealed that SNAI family members regulate different immune cells infiltrations by gene copy number, mutation, methylation, and expression level. SNAI3 and SNIA1/2 have opposite regulatory effects. They all play a key role in tumor development and immune cell infiltration, and can provide a potential target for drug therapy.

Tissue transglutaminase activates integrin-linked kinase and β-catenin in ovarian cancer

Ovarian cancer (OC) is the most lethal gynecological cancer. OC cells have high proliferative capacity, are invasive, resist apoptosis, and tumors often display rearrangement of extracellular matrix (ECM) components, contributing to accelerated tumor progression. The multifunctional protein tissue transglutaminase (TG2) is known to be secreted in the tumor microenvironment (TME), where it interacts with fibronectin (FN) and the cell surface receptor β1 integrin. However, the mechanistic role of TG2 in cancer cell proliferation is unknown. Here, we demonstrate TG2 directly interacts with and facilitates the phosphorylation and activation of the integrin effector protein integrin-linked kinase (ILK) at Ser246. We show TG2 and p-Ser246-ILK form a complex that is detectable in patient-derived OC primary cells grown on FN-coated slides. In addition, we show co-expression of TGM2 and ILK correlates with poor clinical outcome. Mechanistically, we demonstrate TG2-mediated ILK activation causes phosphorylation of glycogen synthase kinase-3α/β (GSK-3α/β), allowing β-catenin nuclear translocation and transcriptional activity. Furthermore, inhibition of TG2 and ILK using small molecules, neutralizing antibodies, or shRNA-mediated knockdown block cell adhesion to the FN matrix, as well as the Wnt receptor response to the Wnt-3A ligand, and ultimately, cell adhesion, growth, and migration. In conclusion, we demonstrate TG2 directly interacts with and activates ILK in OC cells and tumors, and define a new mechanism which links ECM cues with β-catenin signaling in OC. These results suggest a central role of TG2/FN/integrin clusters in ECM rearrangement and indicate downstream effector ILK may represent a potential new therapeutic target in OC.

The EMT-activator ZEB1 is unrelated to platinum drug resistance in ovarian cancer but is predictive of survival

The IGROVCDDP cisplatin-resistant ovarian cancer cell line is an unusual model, as it is also cross-resistant to paclitaxel. IGROVCDDP, therefore, models the resistance phenotype of serous ovarian cancer patients who have failed frontline platinum/taxane chemotherapy. IGROVCDDP has also undergone epithelial-mesenchymal transition (EMT). We aim to determine if alterations in EMT-related genes are related to or independent from the drug-resistance phenotypes. EMT gene and protein markers, invasion, motility and morphology were investigated in IGROVCDDP and its parent drug-sensitive cell line IGROV-1. ZEB1 was investigated by qPCR, Western blotting and siRNA knockdown. ZEB1 was also investigated in publicly available ovarian cancer gene-expression datasets. IGROVCDDP cells have decreased protein levels of epithelial marker E-cadherin (6.18-fold, p = 1.58e-04) and higher levels of mesenchymal markers vimentin (2.47-fold, p = 4.43e-03), N-cadherin (4.35-fold, p = 4.76e-03) and ZEB1 (3.43-fold, p = 0.04). IGROVCDDP have a spindle-like morphology consistent with EMT. Knockdown of ZEB1 in IGROVCDDP does not lead to cisplatin sensitivity but shows a reversal of EMT-gene signalling and an increase in cell circularity. High ZEB1 gene expression (HR = 1.31, n = 2051, p = 1.31e-05) is a marker of poor overall survival in high-grade serous ovarian-cancer patients. In contrast, ZEB1 is not predictive of overall survival in high-grade serous ovarian-cancer patients known to be treated with platinum chemotherapy. The increased expression of ZEB1 in IGROVCDDP appears to be independent of the drug-resistance phenotypes. ZEB1 has the potential to be used as biomarker of overall prognosis in ovarian-cancer patients but not of platinum/taxane chemoresistance.

Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer

BACKGROUND

Late-stage diagnosis of ovarian cancer, a disease that originates in the ovaries and spreads to the peritoneal cavity, lowers 5-year survival rate from 90% to 30%. Early screening tools that can: i) detect with high specificity and sensitivity before conventional tools such as transvaginal ultrasound and CA-125, ii) use non-invasive sampling methods and iii) longitudinally significantly increase survival rates in ovarian cancer are needed. Studies that employ blood-based screening tools using circulating tumor-cells, -DNA, and most recently tumor-derived small extracellular vesicles (sEVs) have shown promise in non-invasive detection of cancer before standard of care. Our findings in this study show the promise of a sEV-derived signature as a non-invasive longitudinal screening tool in ovarian cancer.

METHODS

Human serum samples as well as plasma and ascites from a mouse model of ovarian cancer were collected at various disease stages. Small extracellular vesicles (sEVs) were extracted using a commercially available kit. RNA was isolated from lysed sEVs, and quantitative RT-PCR was performed to identify specific metastatic gene expression.

CONCLUSION

This paper highlights the potential of sEVs in monitoring ovarian cancer progression and metastatic development. We identified a 7-gene panel in sEVs derived from plasma, serum, and ascites that overlapped with an established metastatic ovarian carcinoma signature. We found the 7-gene panel to be differentially expressed with tumor development and metastatic spread in a mouse model of ovarian cancer. The most notable finding was a significant change in the ascites-derived sEV gene signature that overlapped with that of the plasma-derived sEV signature at varying stages of disease progression. While there were quantifiable changes in genes from the 7-gene panel in serum-derived sEVs from ovarian cancer patients, we were unable to establish a definitive signature due to low sample number. Taken together our findings show that differential expression of metastatic genes derived from circulating sEVs present a minimally invasive screening tool for ovarian cancer detection and longitudinal monitoring of molecular changes associated with progression and metastatic spread.

Deubiquitinase UCHL1 Maintains Protein Homeostasis through the PSMA7-APEH-Proteasome Axis in High-grade Serous Ovarian Carcinoma

High-grade serous ovarian cancer (HGSOC) is characterized by chromosomal instability, DNA damage, oxidative stress, and high metabolic demand that exacerbate misfolded, unfolded, and damaged protein burden resulting in increased proteotoxicity. However, the underlying mechanisms that maintain protein homeostasis to promote HGSOC growth remain poorly understood. This study reports that the neuronal deubiquitinating enzyme, ubiquitin carboxyl-terminal hydrolase L1 (UCHL1), is overexpressed in HGSOC and maintains protein homeostasis. UCHL1 expression was markedly increased in HGSOC patient tumors and serous tubal intraepithelial carcinoma (HGSOC precursor lesions). High UCHL1 levels correlated with higher tumor grade and poor patient survival. UCHL1 inhibition reduced HGSOC cell proliferation and invasion, as well as significantly decreased the in vivo metastatic growth of ovarian cancer xenografts. Transcriptional profiling of UCHL1-silenced HGSOC cells revealed downregulation of genes implicated with proteasome activity along with upregulation of endoplasmic reticulum stress-induced genes. Reduced expression of proteasome subunit alpha 7 (PSMA7) and acylaminoacyl peptide hydrolase (APEH), upon silencing of UCHL1, resulted in a significant decrease in proteasome activity, impaired protein degradation, and abrogated HGSOC growth. Furthermore, the accumulation of polyubiquitinated proteins in the UCHL1-silenced cells led to attenuation of mTORC1 activity and protein synthesis, and induction of terminal unfolded protein response. Collectively, these results indicate that UCHL1 promotes HGSOC growth by mediating protein homeostasis through the PSMA7-APEH-proteasome axis. IMPLICATIONS: This study identifies the novel links in the proteostasis network to target protein homeostasis in HGSOC and recognizes the potential of inhibiting UCHL1 and APEH to sensitize cancer cells to proteotoxic stress in solid tumors.

Positron Emission Tomography for Response Evaluation in Microenvironment-Targeted Anti-Cancer Therapy

Therapeutic response is evaluated using the diameter of tumors and quantitative parameters of 2-[¹⁸F] fluoro-2-deoxy-d-glucose positron emission tomography (FDG-PET). Tumor response to molecular-targeted drugs and immune checkpoint inhibitors is different from conventional chemotherapy in terms of temporal metabolic alteration and morphological change after the therapy. Cancer stem cells, immunologically competent cells, and metabolism of cancer are considered targets of novel therapy. Accumulation of FDG reflects the glucose metabolism of cancer cells as well as immune cells in the tumor microenvironment, which differs among patients according to the individual immune function; however, FDG-PET could evaluate the viability of the tumor as a whole. On the other hand, specific imaging and cell tracking of cancer cell or immunological cell subsets does not elucidate tumor response in a complexed interaction in the tumor microenvironment. Considering tumor heterogeneity and individual variation in therapeutic response, a radiomics approach with quantitative features of multimodal images and deep learning algorithm with reference to pathologic and genetic data has the potential to improve response assessment for emerging cancer therapy.

Prognostic values of SNAI family members in breast cancer patients

Background

Breast cancer (BC) is one of the most lethal malignant tumors and the leading cause of cancer-related death worldwide. Although early diagnostic techniques for BC have been well developed, 40% of cases are still diagnosed at the advanced stage, while for BC patients with distant metastases, the 5-year survival rate is usually lower than 30%. The Snail family, generally regarded as transcriptional repressors, has been indicated to be an essential prognostic factor in malignant tumors. However, limited data exist on public databases concerning the prognostic value of individual Snail family members in BC, especially SNAI3.

Methods

Data from public databases including cBioPortal for Cancer Genomics, Gene Expression Omnibus, UCSC Xena Browser, and Human Protein Atlas (HPA) were downloaded. Based on the Kaplan¬–Meier plotter platform, correlation of the three members of the Snail family and prognosis in BC were analyzed. Individual Snail family members and their co-expressed genes were respectively enriched on different pathways and biological processes via the functional enrichment analysis (FunRich) tool.

Results

High SNAI1 mRNA expression was associated with shorter distant metastasis-free survival (DMFS) in all BC patients regardless of PAM50 subtype. Conversely, high SNAI3 mRNA expression was associated with longer DMFS. Although the presence of SNAI2 expression was significantly associated with DMFS in the whole cohort, no significant correlation was found in patients with luminal A or HER2 subtype. For patients with the most diverse clinicopathological features, high SNAI1 expression was associated with poor survival, with the converse being true for SNAI3. However, the impact on prognosis of patients with different clinicopathological features produced by SNAI2 expression was inconclusive. Furthermore, we discovered that SNAI1 or SNAI2 and their co-expressed genes frequently enriched receptor tyrosine kinase (RTK) signaling and integrin-related pathways which mainly functioned on epithelial-mesenchymal transition and were further involved in several processes of signal transduction and cell communication. Furthermore, as SNAI3, along with its co-expressed genes, enriched immune-related pathways, it may thus play a role in mediating the immune system.

Conclusions

Our analysis revealed that SNAI1 mRNA expression may potentially be a negative prognostic factor, whereas SNAI3 mRNA was associated with positive prognosis in BC. Therefore, the assessment of SNAI1 and SNAI3 expression may be valuable for predicting prognosis in BC patients.

Comprehensive Review of Web Servers and Bioinformatics Tools for Cancer Prognosis Analysis

Prognostic biomarkers are of great significance to predict the outcome of patients with cancer, to guide the clinical treatments, to elucidate tumorigenesis mechanisms, and offer the opportunity of identifying therapeutic targets. To screen and develop prognostic biomarkers, high throughput profiling methods including gene microarray and next-generation sequencing have been widely applied and shown great success. However, due to the lack of independent validation, only very few prognostic biomarkers have been applied for clinical practice. In order to cross-validate the reliability of potential prognostic biomarkers, some groups have collected the omics datasets (i.e., epigenetics/transcriptome/proteome) with relative follow-up data (such as OS/DSS/PFS) of clinical samples from different cohorts, and developed the easy-to-use online bioinformatics tools and web servers to assist the biomarker screening and validation. These tools and web servers provide great convenience for the development of prognostic biomarkers, for the study of molecular mechanisms of tumorigenesis and progression, and even for the discovery of important therapeutic targets. Aim to help researchers to get a quick learning and understand the function of these tools, the current review delves into the introduction of the usage, characteristics and algorithms of tools, and web servers, such as LOGpc, KM plotter, GEPIA, TCPA, OncoLnc, PrognoScan, MethSurv, SurvExpress, UALCAN, etc., and further help researchers to select more suitable tools for their own research. In addition, all the tools introduced in this review can be reached at http://bioinfo.henu.edu.cn/WebServiceList.html.

MetaGxData: Clinically Annotated Breast, Ovarian and Pancreatic Cancer Datasets and their Use in Generating a Multi-Cancer Gene Signature

A wealth of transcriptomic and clinical data on solid tumours are under-utilized due to unharmonized data storage and format. We have developed the MetaGxData package compendium, which includes manually-curated and standardized clinical, pathological, survival, and treatment metadata across breast, ovarian, and pancreatic cancer data. MetaGxData is the largest compendium of curated transcriptomic data for these cancer types to date, spanning 86 datasets and encompassing 15,249 samples. Open access to standardized metadata across cancer types promotes use of their transcriptomic and clinical data in a variety of cross-tumour analyses, including identification of common biomarkers, and assessing the validity of prognostic signatures. Here, we demonstrate that MetaGxData is a flexible framework that facilitates meta-analyses by using it to identify common prognostic genes in ovarian and breast cancer. Furthermore, we use the data compendium to create the first gene signature that is prognostic in a meta-analysis across 3 cancer types. These findings demonstrate the potential of MetaGxData to serve as an important resource in oncology research, and provide a foundation for future development of cancer-specific compendia.

Transcriptomic and genomic profiling of early-stage ovarian carcinomas associated with histotype and overall survival

Ovarian cancer is the most lethal gynecological malignancy in the western world. Despite recent efforts to characterize ovarian cancer using molecular profiling, few targeted treatment options are currently available. Here, we examined genetic variants, fusion transcripts, SNP genotyping, and gene expression patterns for early-stage (I and II) ovarian carcinomas (n=96) in relation to clinicopathological characteristics and clinical outcome, thereby identifying novel genetic features of ovarian carcinomas. Furthermore, mutation frequencies of specific genetic variants and/or their gene expression patterns were associated with histotype and overall survival, e.g. SLC28A2 (mucinous ovarian carcinoma histotype), ARCN1 (low expression in 0-2 year survival group), and tumor suppressor MTUS1 (mutation status and overall survival). The long non-coding RNA MALAT1 was identified as a highly promiscuous fusion transcript in ovarian carcinoma. Moreover, gene expression deregulation for 23 genes was associated with tumor aggressiveness. Taken together, the novel biomarkers identified here may improve ovarian carcinoma subclassification and patient stratification according to histotype and overall survival.

Activin A stimulates migration of the fallopian tube epithelium, an origin of high-grade serous ovarian cancer, through non-canonical signaling

Factors that stimulate the migration of fallopian tube epithelial (FTE)-derived high-grade serous ovarian cancer (HGSOC) to the ovary are poorly elucidated. This study characterized the effect of the ovarian hormone, activin A, on normal FTE and HGSOC. Activin A and TGFβ1 induced an epithelial-to-mesenchymal transition in murine oviductal epithelial (MOE) cells, but only activin A increased migration. The migratory effect of activin A was independent of Smad2/3 and required phospho-AKT, phospho-ERK, and Rac1. Exogenous activin A stimulated migration of the HGSOC cell line OVCAR3 through a similar mechanism. Activin A signaling inhibitors, SB431542 and follistatin, reduced migration in OVCAR4 cells, which expressed activin A subunits (encoded by INHBA). Murine superovulation increased phospho-Smad2/3 immunostaining in the FTE. In Oncomine, transcripts for the activin A receptors (ACVR1B and ACVR2A) were higher in serous tumors relative to the normal ovary, while inhibitors of activin A signaling (INHA and TGFB3) were lower. High expression of both INHBA and ACVR2A, but not TGFβ receptors or co-receptors, was associated with shorter disease-free survival in serous cancer patients. These results suggest activin A stimulates migration of FTE-derived tumors to the ovary.

CSIOVDB: a microarray gene expression database of epithelial ovarian cancer subtype

Databases pertaining to various diseases provide valuable resources on particular genes of interest but lack the molecular subtype and epithelial-mesenchymal transition status. CSIOVDB is a transcriptomic microarray database of 3,431 human ovarian cancers, including carcinoma of the ovary, fallopian tube, and peritoneum, and metastasis to the ovary. The database also comprises stroma and ovarian surface epithelium from normal ovary tissue, as well as over 400 early-stage ovarian cancers. This unique database presents the molecular subtype and epithelial-mesenchymal transition status for each ovarian cancer sample, with major ovarian cancer histologies (clear cell, endometrioid, mucinous, low-grade serous, serous) represented. Clinico-pathological parameters available include tumor grade, surgical debulking status, clinical response and age. The database has 1,868 and 1,516 samples with information pertaining to overall and disease-free survival rates, respectively. The database also provides integration with the copy number, DNA methylation and mutation data from TCGA. CSIOVDB seeks to provide a resource for biomarker and therapeutic target exploration for ovarian cancer research.

A genome-scale screen reveals context-dependent ovarian cancer sensitivity to miRNA overexpression

Large‐scale molecular annotation of epithelial ovarian cancer (EOC) indicates remarkable heterogeneity in the etiology of that disease. This diversity presents a significant obstacle against intervention target discovery. However, inactivation of miRNA biogenesis is commonly associated with advanced disease. Thus, restoration of miRNA activity may represent a common vulnerability among diverse EOC oncogenotypes. To test this, we employed genome‐scale, gain‐of‐function, miRNA mimic toxicity screens in a large, diverse spectrum of EOC cell lines. We found that all cell lines responded to at least some miRNA mimics, but that the nature of the miRNA mimics provoking a response was highly selective within the panel. These selective toxicity profiles were leveraged to define modes of action and molecular response indicators for miRNA mimics with tumor‐suppressive characteristics in vivo. A mechanistic principle emerging from this analysis was sensitivity of EOC to miRNA‐mediated release of cell fate specification programs, loss of which may be a prerequisite for development of this disease.