A novel necroptosis-related lncRNA signature for predicting prognosis and anti-cancer treatment response in endometrial cancer.

Background: Necroptosis, a form of programmed cell death, underlies tumorigenesis and the progression of cancers. Anti-cancer strategies targeting necroptosis have increasingly been shown to present a potential cancer therapy. However, the predictive utility and anticancer sensitivity value of necroptosis-related lncRNAs (NRLs) for endometrial cancer (EC) are currently unknown. Methods: EC patient gene expression profiles and the corresponding clinical information collected from The Cancer Genome Atlas were used to identify NRLs that constituted a predictive signature for EC. The functional pathways, immune status, clinicopathological correlation, and anticancer drug sensitivity of the patients relative to the NRLs signatures were analyzed. Results: A signature composed of 7 NRLs (AC019080.5, BOLA3-AS1, AC022144.1, AP000345.2, LEF1-AS1, AC010503.4, and RPARP-AS1) was identified. The high-risk patient group with this signature exhibited a poorer prognosis and lower survival rate than low-risk group lacking this signature. This necroptosis-related lncRNA signature had a higher predictive accuracy compared with other clinicopathological variables (area under the receiver operating characteristic curve of the risk score: 0.717). Additionally, when patients were stratified based on other clinicopathological variables, the overall survival was significantly shorter in the high-risk versus low-risk group across all cohorts. Gene set enrichment analysis (GSEA) revealed that immune- and tumor-related signaling pathways and biological processes were enriched in the high-risk group compared to the low-risk group. Single-sample gene set enrichment analysis (ssGSEA) additionally showed that the resulting risk score was strongly correlated with EC patient immune status. Finally, patients with high-risk scores were more sensitive to the anti-cancer drugs such as Docetaxel, Mitomycin.C, Vinblastine, AZD.2281 (olaparib), AZD6244, and PD.0332991 (Palbociclib). Conclusion: These findings reveal a novel necroptosis-related lncRNA signature for predicting EC patient prognosis and shed new light on anticancer therapy strategies for EC.

Maelstrom promotes tumor metastasis through regulation of FGFR4 and epithelial-mesenchymal transition in epithelial ovarian cancer.

BACKGROUND: Increasing evidence has indicated that Maelstrom (MAEL) plays an oncogenic role in various human carcinomas. However, the exact function and mechanisms by which MAEL acts in epithelial ovarian cancer (EOC) remain unclear. RESULTS: This study demonstrated that MAEL was frequently overexpressed in EOC tissues and cell lines. Overexpression of MAEL was positively correlated with the histological grade of tumors, FIGO stage, and pT/pN/pM status (p < 0.05), and it also acted as an independent predictor of poor patient survival (p < 0.001). Ectopic overexpression of MAEL substantially promoted invasiveness/metastasis and induced epithelial-mesenchymal transition (EMT), whereas silencing MAEL by short hairpin RNA effectively inhibited its oncogenic function and attenuated EMT. Further study demonstrated that fibroblast growth factor receptor 4 (FGFR4) was a critical downstream target of MAEL in EOC, and the expression levels of FGFR4 were significantly associated with MAEL. (P < 0.05). CONCLUSION: Our findings suggest that overexpression of MAEL plays a crucial oncogenic role in the development and progression of EOC through the upregulation of FGFR4 and subsequent induction of EMT, and also provide new insights on its potential as a therapeutic target for EOC.

DeepEBV: a deep learning model to predict Epstein-Barr virus (EBV) integration sites.

MOTIVATION: Epstein-Barr virus (EBV) is one of the most prevalent DNA oncogenic viruses. The integration of EBV into the host genome has been reported to play an important role in cancer development. The preference of EBV integration showed strong dependence on the local genomic environment, which enables the prediction of EBV integration sites. RESULTS: An attention-based deep learning model, DeepEBV, was developed to predict EBV integration sites by learning local genomic features automatically. First, DeepEBV was trained and tested using the data from the dsVIS database. The results showed that DeepEBV with EBV integration sequences plus Repeat peaks and 2-fold data augmentation performed the best on the training dataset. Furthermore, the performance of the model was validated in an independent dataset. In addition, the motifs of DNA-binding proteins could influence the selection preference of viral insertional mutagenesis. Furthermore, the results showed that DeepEBV can predict EBV integration hotspot genes accurately. In summary, DeepEBV is a robust, accurate and explainable deep learning model, providing novel insights into EBV integration preferences and mechanisms. AVAILABILITYAND IMPLEMENTATION: DeepEBV is available as open-source software and can be downloaded from https://github.com/JiuxingLiang/DeepEBV.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PTOV1 promotes cisplatin-induced chemotherapy resistance by activating the nuclear factor kappa B pathway in ovarian cancer.

Chemotherapy resistance is a bottleneck for ovarian cancer treatment; therefore, revealing its regulatory mechanism is critical. In the present study, we found that prostate tumor overexpressed-1 (PTOV1) was upregulated significantly in ovarian cancer cells and tissues. Patients with high PTOV1 levels had a poor outcome. In addition, PTOV1 overexpression increased CDDP (cisplatin) resistance, while PTOV1 knockdown inhibited CDDP resistance, as determined using cell viability assays, apoptosis assays, and an animal model. Mechanistic analysis showed that PTOV1 increased nuclear factor kappa B (NF-κB) pathway activity, reflected by increased nuclear translocation of its p65 subunit and the phosphorylation of inhibitor of nuclear factor kappa-B kinase subunits alpha and beta, which are markers of NF-κB pathway activation. Inhibition of the NF-κB pathway in PTOV1-overexpressing ovarian cancer cells increased CDDP-induced apoptosis, suggesting that PTOV1 promoted chemotherapy resistance by activating the NF-κB pathway. In summary, we identified PTOV1 as a prognostic factor for patients with ovarian cancer. PTOV1 might be a target for inhibition of chemotherapy resistance.

FAM83B inhibits ovarian cancer cisplatin resistance through inhibiting Wnt pathway.

Cisplatin resistance is frequently occurred in ovarian cancer therapy, understanding its regulatory mechanisms is critical for developing novel treatment methods and drugs. Here, we found ovarian cancer patients with low FAM83B levels had shorter survival time, tissues with cisplatin resistance also had low FAM83B levels, suggesting FAM83B might inhibit cisplatin resistance. FAM83B overexpression inhibits cisplatin resistance showed in increased ovarian cancer cell proliferation and growth rate, and reduced apoptosis rate, while FAM83B knockdown promotes cisplatin resistance. Mechanism analysis showed FAM83B interacted with APC to inhibit Wnt pathway activity, causing ovarian cancer cisplatin resistance. We also found FAM83B levels were negative with Wnt pathway activity in clinic samples, confirming FAM83B inhibited Wnt pathway activity. In summary, we found FAM83B inhibits ovarian cancer cisplatin resistance through inhibiting Wnt pathway, providing a new target for ovarian cancer therapy.

DeepHPV: a deep learning model to predict human papillomavirus integration sites.

Human papillomavirus (HPV) integrating into human genome is the main cause of cervical carcinogenesis. HPV integration selection preference shows strong dependence on local genomic environment. Due to this theory, it is possible to predict HPV integration sites. However, a published bioinformatic tool is not available to date. Thus, we developed an attention-based deep learning model DeepHPV to predict HPV integration sites by learning environment features automatically. In total, 3608 known HPV integration sites were applied to train the model, and 584 reviewed HPV integration sites were used as the testing dataset. DeepHPV showed an area under the receiver-operating characteristic (AUROC) of 0.6336 and an area under the precision recall (AUPR) of 0.5670. Adding RepeatMasker and TCGA Pan Cancer peaks improved the model performance to 0.8464 and 0.8501 in AUROC and 0.7985 and 0.8106 in AUPR, respectively. Next, we tested these trained models on independent database VISDB and found the model adding TCGA Pan Cancer performed better (AUROC: 0.7175, AUPR: 0.6284) than the model adding RepeatMasker peaks (AUROC: 0.6102, AUPR: 0.5577). Moreover, we introduced attention mechanism in DeepHPV and enriched the transcription factor binding sites including BHLHA15, CHR, COUP-TFII, DMRTA2, E2A, HIC1, INR, NPAS, Nr5a2, RARa, SCL, Snail1, Sox10, Sox3, Sox4, Sox6, STAT6, Tbet, Tbx5, TEAD, Tgif2, ZNF189, ZNF416 near attention intensive sites. Together, DeepHPV is a robust and explainable deep learning model, providing new insights into HPV integration preference and mechanism. Availability: DeepHPV is available as an open-source software and can be downloaded from https://github.com/JiuxingLiang/DeepHPV.git, Contact: huzheng1998@163.com, liangjiuxing@m.scnu.edu.cn, lizheyzy@163.com.

A novel diagnostic nomogram based on serological and ultrasound findings for preoperative prediction of malignancy in patients with ovarian masses.

OBJECTIVE: To develop a novel diagnostic nomogram model to predict malignancy in patients with ovarian masses. METHODS: In total, 1277 patients with ovarian masses were retrospectively analyzed. Receiver operating characteristic (ROC) analysis was performed to identify valuable predictive factors. Univariate and multivariate logistic regression analyses were used to identify risk factors for ovarian cancer. Subsequently, a predictive nomogram model was developed. The performance of the nomogram model was assessed by its calibration and discrimination in a validation cohort. Decision curve analysis (DCA) was applied to assess the clinical net benefit of the model. RESULTS: Overall, 496 patients (38.8%) had ovarian cancer. Eighteen parameters were significantly different between the malignant and benign groups. Five parameters were identified as being most optimal for predicting malignancy, including age, carbohydrate antigen 125, fibrinogen-to-albumin ratio, monocyte-to-lymphocyte ratio, and ultrasound result. These parameters were incorporated to establish a nomogram model, and this model exhibited an area under the ROC curve (AUC) of 0.937 (95% confidence interval [CI], 0.920-0.954). The model was also well calibrated in the validation cohort and showed an AUC of 0.925 (95%CI, 0.896-0.953) at the cut-off point of 0.298. DCA confirmed that the nomogram model achieved the best clinical utility with almost the entire range of threshold probabilities. The model has demonstrated superior efficacy in predicting malignancy compared to currently available models, including the risk of ovarian malignancy algorithm, copenhagen index, and the risk of malignancy index. More importantly, the nomogram established here showed potential value in identification of early-stage ovarian cancer. CONCLUSION: The cost-effective and easily accessible nomogram model exhibited favorable accuracy for preoperative prediction of malignancy in patients with ovarian masses, even at early stages.

CHD1L promotes EOC cell invasiveness and metastasis via the regulation of METAP2.

Chromodomain helicase DNA binding protein 1-like (CHD1L) gene has been proposed to play an oncogenic role in human hepatocellular carcinoma. Previously we reported that CHD1L overexpression is significantly associated with the metastasis proceeding of epithelial ovarian cancer (EOC), and may predict a poor prognosis in EOC patients. However, the potential oncogenic mechanisms by which CHD1L acts in EOC remain unclear. To elucidate the oncogenic function of CHD1L, we carried out a series of in vitro assays, with effects of CHD1L ectogenic overexpression and silencing being determined in EOC cell lines (HO8910, A2780 and ES2). Real-time PCR and Western blotting analyses were used to identify potential downstream targets of CHD1L in the process of EOC invasion and metastasis. In ovarian carcinoma HO8910 cell lines, ectopic overexpression of CHD1L substantially induced the invasive and metastasis ability of the cancer cells in vitro. In contrast, knockdown of CHD1L using shRNA inhibited cell invasion in vitro in ovarian carcinoma A2780 and ES2 cell lines. We also demonstrated that methionyl aminopeptidase 2 (METAP2) was a downstream target of CHD1L in EOC, and we found a significant, positive correlation between the expression of CHD1L and METAP2 in EOC tissues (P<0.05). Our findings indicate that CHD1L plays a potential role in the inducement of EOC cancer cell invasion and/or metastasis via the regulation of METAP2 expression and suggests that CHD1L inhibition may provide a potential target for therapeutic intervention in human EOC.

An effective vaginal gel to deliver CRISPR/Cas9 system encapsulated in poly (ß-amino ester) nanoparticles for vaginal gene therapy.

BACKGROUND: Gene therapy has held promises for treating specific genetic diseases. However, the key to clinical application depends on effective gene delivery. METHODS: Using a large animal model, we developed two pharmaceutical formulations for gene delivery in the pigs' vagina, which were made up of poly (ß-amino ester) (PBAE)-plasmid polyplex nanoparticles (NPs) based two gel materials, modified montmorillonite (mMMT) and hectorite (HTT). FINDINGS: By conducting flow cytometry of the cervical cells, we found that PBAE-GFP-NPs-mMMT gel was more efficient than PBAE-GFP-NPs-HTT gel in delivering exogenous DNA intravaginally. Next, we designed specific CRISPR/SpCas9 sgRNAs targeting porcine endogenous retroviruses (PERVs) and evaluated the genome editing efficacy in vivo. We discovered that PERV copy number in vaginal epithelium could be significantly reduced by the local delivery of the PBAE-SpCas9/sgRNA NPs-mMMT gel. Comparable genome editing results were also obtained by high-fidelity version of SpCas9, SpCas9-HF1 and eSpCas9, in the mMMT gel. Further, we confirmed that the expression of topically delivered SpCas9 was limited to the vagina/cervix and did not diffuse to nearby organs, which was relatively safe with low toxicity. INTERPRETATION: Our data suggested that the PBAE-NPs mMMT vaginal gel is an effective preparation for local gene therapy, yielding insights into novel therapeutic approaches to sexually transmitted disease in the genital tract. FUNDING: This work was supported by the National Science and Technology Major Project of the Ministry of science and technology of China (No. 2018ZX10301402); the National Natural Science Foundation of China (81761148025, 81871473 and 81402158); Guangzhou Science and Technology Programme (No. 201704020093); National Ten Thousand Plan-Young Top Talents of China, Fundamental Research Funds for the Central Universities (17ykzd15 and 19ykyjs07); Three Big Constructions-Supercomputing Application Cultivation Projects sponsored by National Supercomputer Center In Guangzhou; the National Research FFoundation (NRF) South Africa under BRICS Multilateral Joint Call for Proposals; grant 17-54-80078 from the Russian Foundation for Basic Research.

In vitro and in vivo growth inhibition of human cervical cancer cells via human papillomavirus E6/E7 mRNAs' cleavage by CRISPR/Cas13a system.

Sustained infection of high-risk human papillomavirus (HR-HPVs), especially HPV16 and HPV18, is a major cause of cervical cancer. E6 and E7 oncoproteins, encoded by the HPV genome, are critical for transformation and maintenance of malignant phenotypes of cervical cancer. Here, we used an emerging programmable clustered regularly interspaced short palindromic repeat (CRISPR)/Cas13a system to cleave HPV 16/18 E6/E7 messenger RNAs (mRNAs). The results showed that customized CRISPR/Cas13a system effectively and specifically knocked down HPV 16/18 E6/E7 mRNAs, inducing growth inhibition and apoptosis in HPV16-positive SiHa and HPV18-positive HeLa Cell lines, but not in HPV-negative C33A cell line. Simultaneously, we detected downregulation of E6/E7 oncoproteins and upregulation of tumor suppressor P53 and RB proteins. In addition, we used subcutaneous xenograft tumor growth assays to find that the weight and volume of tumors in the SiHa-16E6CR1 group knocked down by the CRISPR/Cas13a system were significantly lower than those in the SiHa-VECTOR group lacking crRNA. Our study demonstrated that targeting HPV E6/E7 mRNAs by the CRISPR/Cas13a system may be a candidate therapeutic strategy for HPV-related cervical cancer.

Non-target genetic manipulation induces rhabdomyosarcoma in KrasPten-driven mouse model of ovarian cancer.

BACKGROUND: Genetically engineered mice are ideal models to advance our understanding the tumorigenesis of ovarian cancer. Our original objective was to establish an ovarian cancer model induced by Kras activation and Pten deletion. However, proficiently establishing the model remains a technical problem, which limits its application. METHODS: We established the Kras activation/Pten deletion-induced mouse model of ovarian cancer by injecting Cre recombinase-expressing adenovirus in the ovarian bursa. PCR analysis, Western blotting, and immunohistochemistry staining were performed to verify the alteration of conditional genes. We detected expression of canonical molecular markers in order to examine the origin of the tumors. RESULTS: Subcutaneous lumps developed accidentally in mice with ovarian cancer, as early as 2 weeks post in vivo genetic manipulation, far before the destructive growth of ovarian cancer. PCR analysis confirmed the efficient Cre-mediated recombination of Kras and Pten in tumor tissues, which are consistent with the activation of the MAPK and PI3K/Akt/mTOR pathways. Histomorphological and histological analysis showed that the lumps were actually rhabdomyosarcoma (RMS). We confirmed that the leakage of adenovirus transformed healthy adjacent tissues into RMS. CONCLUSIONS: Avoiding accidental exposure of non-target tissues to adenovirus is crucial to successfully establish the ovarian cancer mouse model. Moreover, non-specific genetic manipulations can induce the development of RMS.

Overexpression of SLC12A5 is associated with tumor progression and poor survival in ovarian carcinoma.

INTRODUCTION: The solute carrier family 12 member 5 (SLC12A5) gene is playing a putative oncogenic role in colorectal carcinoma. However, the status of SLC12A5 amplification and expression in ovarian carcinoma and its potential clinical and/or prognostic significance has not yet been investigated. METHODS: In the present study, semi-quantitative staining and fluorescence in situ hybridization were used to investigate SLC12A5 protein expression and gene amplification levels. Samples were obtained from archival, formalin-fixed, paraffin-embedded pathological specimens consisting of 30 normal ovaries, 30 ovarian cystadenomas, 30 borderline ovarian tumors, and 147 invasive ovarian carcinomas. SLC12A5 immunohistochemical staining results, pathological parameters, and patient prognosis were then evaluated using various statistical models. Patient survival rate was also assessed using receiver-operator curve analysis. RESULTS: Our results revealed no SLC12A5 protein overexpression in normal ovaries. However, 7% of cystadenomas had SLC12A5 protein overexpression along with 17% of borderline tumors and 37% of ovarian carcinomas (P<0.01). Amplification of SLC12A5 was detected in 10.3% of ovarian carcinomas. Further correlational analyses showed that SLC12A5 protein overexpression in ovarian carcinomas was significantly associated with ascending histological grade, pT/pN/pM status, as well as FIGO stage (P<0.05). A subsequent univariate survival analysis of our ovarian carcinoma cohorts resulted in a significant association between SLC12A5 protein overexpression and decreased patient survival (44.3 and 85.9 months for high and low SLC12A5 protein expression, respectively; P<0.001). Importantly, additional multivariate analysis revealed that SLC12A5 protein expression was a significant, independent prognostic factor for overall survival in ovarian carcinoma patients (P=0.003). CONCLUSIONS: Collectively, these findings support the conclusion that SLC12A5 protein overexpression could indicate an invasive and/or aggressive phenotype of ovarian carcinoma. Future work will need to investigate whether SLC12A5 protein can serve as an independent prognostic molecular marker in patients with ovarian carcinoma.

Cytological Immunostaining of HMGA2, LRP1B, and TP63 as Potential Biomarkers for Triaging Human Papillomavirus-Positive Women.

BACKGROUND: Since human papillomavirus (HPV) DNA testing has been promoted as primary screening strategy, the triage method has also evolved from morphological testing to a molecular biomarker detection to improve screening efficiency. In this study, we investigated the performance of three HPV integration hot-spots, HMGA2, LRP1B, and TP63, as potential triage markers in HPV screening tests. MATERIALS AND METHODS: This cross-sectional study was conducted from November 2016 to December 2017 in the First Affiliated Hospital of Sun Yat-sen University. Immunocytochemistry was carried out using residual cervical cell samples from 121 HPV-positive cases (23 normal, 24 cervical intraepithelial neoplasia (CIN) 1, and 74 CIN2+). RESULTS: Of the 121 cases, 77 showed completely paired for the three biomarkers. In these 77 cases, receiver operating characteristic (ROC) analysis of HMGA2 showed the best potential for detecting CIN2+ among HPV+ cases (sensitivity 70%; specificity 91.89%; AUC 0.839). TP63 was second most effective biomarker (AUC 0.838; sensitivity 80%; specificity 81.08%). In contrast, LRP1B had the smallest AUC (0.801) among the three biomarkers but had the highest sensitivity (90%) and specificity (56.76%). To test the triage value of combining the three biomarkers, logistic regression was conducted followed by ROC comparison analysis. Promisingly, the combination of the three biomarkers gave the largest AUC of 0.951 with 92.5% sensitivity and 89.1% specificity (P < .0001 compared to liquid-based cytology test by Z-test). CONCLUSIONS: A combination of HMGA2, LRP1B, and TP63 as potential biomarkers may be useful for screening during triage of HPV-positive patients, particularly for detecting CIN2 + .

LncRNA GAS5 suppresses ovarian cancer by inducing inflammasome formation.

OBJECTIVE: Long non-coding RNA growth arrest-specific transcript 5 (lncRNA GAS5) is involved in various kinds of cancer. However, the role of lncGAS5 in the development of ovarian cancer remains unclear. In the current study, we explored the cellular mechanism and clinical value of lncRNA GAS5 in ovarian cancer. METHODS: Quantitative real-time PCR was used to detect mRNA level of LncRNA GAS5 in 20 ovarian cancer tissues. The effect of lncRNA GAS5 on cell proliferation was performed using CCK-8 assay. Cell apoptosis was evaluated by flow cytometry. Western blotting was used to detect the protein level of lncRNA GAS5 potential target. Standard sandwich ELISA was used to quantify the level of inflammatory cytokines. The cells with stable expression of lncRNA GAS5 were injected into nude mice to study the effect of lncRNA GAS5 on tumorigenesis in vivo. Results: The expression of lncRNA GAS5 was significantly decreased in ovarian cancer tissues. Decrease in lncRNA GAS5 expression resulted in increased cell proliferation and colony formation and reduced ovarian cancer cell apoptosis. In contrast, exogenous overexpression of lncRNA GAS5 in ovarian cancer cells inhibited proliferation, colony formation and apoptosis in ovarian cancer cells. In addition, the role of lncRNA GAS5 in ovarian cancer was associated with inflammasome formation and pyroptosis. CONCLUSION: These results suggested that lncRNA GAS5 acts as tumor suppressor and could be used as a potential treatment target for diagnosis and therapy of ovarian cancer.

The oncogenic Golgi phosphoprotein 3 like overexpression is associated with cisplatin resistance in ovarian carcinoma and activating the NF-κB signaling pathway.

BACKGROUND: Chemo-resistance is a leading cause of tumor relapse and treatment failure in patients with ovarian cancer. The identification of effective strategies to overcome drug resistance will have a significant clinical impact on the disease. METHODS: The protein and mRNA expression of GOLPH3L in ovarian cancer cell lines and patient tissues were determined using Real-time PCR and Western blot, respectively. 177 human ovarian cancer tissue samples were analyzed by IHC to investigate the association between GOLPH3L expression and the clinicopathological characteristics of ovarian cancer patients. Functional assays, such as MTT, FACS, and Tunel assay used to determine the oncogenic role of GOLPH3L in human ovarian cancer progression. Furthermore, western blotting and luciferase assay were used to determine the mechanism of GOLPH3L promotes chemoresistance in ovarian cancer cells. RESULTS: The expression of GOLPH3L was markedly upregulated in ovarian cancer cell lines and tissues, and high GOLPH3L expression was associated with an aggressive phenotype and poor prognosis with ovarian cancer patients. GOLPH3L overexpression confers CDDP resistance on ovarian cancer cells; however, inhibition of GOLPH3L sensitized ovarian cancer cell lines to CDDP cytotoxicity both in vitro and in vivo. Additionally, GOLPH3L upregulated the levels of nuclear p65 and phosphorylated inhibitor of nuclear factor Kappa-B kinase-ß and IκBα, thereby activating canonical nuclear factor-κB (NF-κB) signaling. CONCLUSIONS: Our findings suggest that GOLPH3L is a potential therapeutic target for the treatment of ovarian cancer: targeting GOLPH3L signaling may represent a promising strategy to enhance platinum response in patients with chemoresistant ovarian cancer.

Overexpression of miRNA-221 promotes cell proliferation by targeting the apoptotic protease activating factor-1 and indicates a poor prognosis in ovarian cancer.

MicroRNAs are a class of small non-coding, endogenous RNAs involved in cancer development and progression. MicroRNA-221 (mir-221) has been reported to have both an oncogenic and tumor-suppressive role in human tumors, but the role of miR-221 in ovarian cancer is poorly understood. In the present study, the expression levels of miR-221 and the apoptosis protease activating factor 1 (APAF1) protein in 63 samples of ovarian cancer tissues and the cell lines, IOSE25, A2780, OVCAR3, SKOV3 and 3AO were detected by quantitative reverse-transcription polymerase chain reaction (qRT-PCR) and western blot analysis, respectively. Cell proliferation was measured using cell counting kit-8 (CCK-8); cell migration and invasion were detected using a transwell assay; cell apoptosis was evaluated by flow cytometry and hoechst staining, and a luciferase assay was performed to verify a putative target site of miR-221 in the 3'-UTR of APAF1 mRNA. Expression of miR-221 was upregulated in ovarian cancer tissues. Patients with increased miR-221 expression levels had a reduced disease-free survival (P=0.0014) and overall survival (P=0.0058) compared with those with low miR-221 expression. Transfection of SKOV3 and A2780 cell lines with miR-221 inhibitor induced APAF1 protein expression, suppressed cell proliferation and migration and promoted tumor cell apoptosis. In conclusion, the APAF1 gene was confirmed as a direct target of miR-221 and overexpression of APAF1 suppressed ovarian cancer cell proliferation and induced cell apoptosis in vitro. These findings indicate that miR-221-APAF1 should be studied further as a potential new diagnostic or prognostic biomarker for ovarian cancer.

MiR-760 overexpression promotes proliferation in ovarian cancer by downregulation of PHLPP2 expression.

OBJECTIVE: Ovarian cancer is one of the most lethal gynecologic malignancies worldwide and with poor prognosis and survival rate in women. Identifying sensitive and specific molecular in carcinogenesis may improve diagnostic and therapeutic strategies for this malignancy and achieve a better clinical outcome. METHODS: miR-760 expression in ovarian cancer cell lines and patient tissues were determined using Real-time PCR. 145 human ovarian cancer tissue samples were analyzed by RT-PCR to investigate the association between miR-760expression and the clinicopathological characteristics of ovarian cancer patients. Functional assays, such as MTT, anchorage-independent growth, colony formation and BRDU assay were used to determine the oncogenic role of miR-760 in human ovarian cancer progression. Furthermore, western blotting and luciferase assay were used to determine the mechanism of miR-760 promotes proliferation in ovarian cancer cells. RESULT: The expression of miR-760 was markedly upregulated in ovarian cancer cell lines and tissues, and high miR-760 expression was associated with an aggressive phenotype and poor prognosis with ovarian cancer patients. Upregulation of miR-760 promoted, whereas downregulation of miR-760 inhibited the proliferation of ovarian cancer cells in vitro. Additionally, we identified PHLPP2 as a direct target of miR-760, and silencing the expression of PHLPP2 is the essential biological function of miR-760 during ovarian cancer cell proliferation. Finally, we showed a significant correlation between miR-760 and PHLPP2 expression in ovarian cancer tissues. CONCLUSION: Our findings suggest that miR-760 represents a potential onco-miR and participates in ovarian cancer carcinogenesis, which highlight its potential as a target for ovarian cancer therapy.

Decreased expression of long non-coding RNA GAS5 promotes cell proliferation, migration and invasion, and indicates a poor prognosis in ovarian cancer.

Long non-coding RNA growth arrest-specific 5 (GAS5) was reported to be aberrantly expressed in various types of cancers. However, the role of GAS5 in the evolution and progression of ovarian cancer remains elusive. In the present study, we aimed to investigate the cellular function and clinical significance of GAS5 in ovarian cancer. GAS5 expression levels in 63 ovarian cancer tissues were detected by quantitative real-time PCR. Cell Counting Kit-8 (CCK-8) assay was performed to analyze the effect of GAS5 on cell proliferation. The effect of GAS5 on cell migration and invasion was detected using Transwell assay. Cell apoptosis was evaluated by flow cytometry and Hoechst staining. SKOV3 cells with stable expression of GAS5 were injected into nude mice to study the effect of GAS5 on tumorigenesis in vivo. Western blotting was used to determine the protein levels of GAS5 potential targets. The results showed that GAS5 was markedly decreased in tumor tissues and a lower expression of GAS5 was detected in tumors with larger size, deeper invasive depth and higher tumor stage. Patients with low GAS5 expression level had poorer disease-free (P<0.0001) and overall survival (P=0.0016) than those with high GAS5 expression. Moreover, overexpression of GAS5 was demonstrated to suppress ovarian cancer cell proliferation in vitro and in vivo. Finally, we found that GAS5 influenced ovarian cancer cell proliferation, partly via regulating cyclin D1, p21 and apoptosis protease activating factor 1 (APAF1) expression. Our findings suggest that lncRNA GAS5 may represent a novel indicator of poor prognosis in ovarian cancer and may be a potential therapeutic target for diagnosis and therapy.