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Borderline ovarian tumors are a special class of ovarian tumors between benign and malignant, which are not sensitive to traditional chemotherapy regimens, and the development of target drugs is limited due to the lack of cell lines. Tumor organoids can well preserve the genetic characteristics of the primary tumor, but there are only a few reports of application in borderline tumors. In this study, we successfully generated 13 ovarian borderline tumor organoids and tested the antitumor activity of Bractoppin, a BRCA1 carboxy-terminal domain (BRCT) inhibitor. Bractoppin promotes organoid apoptosis. Mechanistically, Bractoppin can inhibit organoid cell cycle progression, inhibit the repair of DSB damage and promote tumor cell apoptosis. In addition, Bractoppin can also promote the apoptosis of ovarian cancer cell lines and inhibit the HR and NHEJ repair ability of tumor cells. We demonstrate the value of ovarian borderline tumor organoids in the exploration of molecular therapy drugs, and Bractoppin may be a valuable small molecule drug in the treatment of BOT. • Borderline ovarian tumor organoids can recapitulate the characteristics of borderline tumor in vitro. • Bractoppin can effectively inhibit the progression of borderline ovarian tumors and ovarian cancer cells. • Bractoppin can promote DNA damage in tumor cells. [ABSTRACT FROM AUTHOR]

Cervical cancer (CC) is the fourth commonest cancer in women worldwide. Increasing evidence proves that microRNA (miRNA)–messenger RNA (mRNA) network is involved in CC. In this study, miRNA and mRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. Differently expressed miRNAs (DE-miRNAs) and mRNAs (DE-mRNAs) were obtained by "Empirical Analysis of Digital Gene Expression Data in R (EdgeR)" package. Then, functional analyses were conducted. With Cytoscape software, a protein–protein interaction (PPI) network was established to identify hub genes that were used for building an miRNA-hub gene network. Next, a prognostic signature based on hub genes was constructed by Cox regression analysis, and its prognostic value was assessed by a nomogram. Finally, the relationship between immune cell infiltration and the three genes in the prognostic model was investigated by using the CIBERSORT algorithm. We screened out 5096 DE-mRNAs and 114 DE-miRNAs between healthy cervical and CC tissues. Then, 102 target DE-mRNAs of upregulated DE-miRNAs and 150 target DE-mRNAs of downregulated DE-miRNAs were obtained. PPI network demonstrated 20 hub nodes with higher connectivity. DE-mRNAs were mostly enriched in pathways in cancer, cell cycle, and proteoglycans in cancer. The miRNA-hub gene network showed that most hub genes could be potentially modulated by miR-200c-3p, miR-23b-3p, and miR-106b-5p. Quantitative real-time PCR proved that 10 miRNAs were downregulated and 6 mRNAs were upregulated markedly in CC tissues. Furthermore, a prognostic signature was established based on enhancer of zeste homolog 2 (EZH2), Fms-related tyrosine kinase 1 (FLT1), and glyceraldehyde 3-phosphate dehydrogenase (GAPDH). The area under the curve value of the 5-year receiver operating characteristic curve was 0.609. The three genes were also found to be related to the infiltration of six types of immune cells, including dendritic cells, macrophages M0 and M1, mast cells, and monocytes. In conclusion, the development of CC is regulated by the miRNA–mRNA network we proposed in this study. [ABSTRACT FROM AUTHOR]

Methylation is the main form of RNA modification. N6‐methyladenine (m6A) regulates the splicing and translation of mRNA. Alk B homologue 5 (ALKBH5) participates in the biological regulation of various cancers. However, its role in ovarian carcinogenesis has not been unveiled. In the present study, ALKBH5 showed higher expression in ovarian cancer tissue than in normal ovarian tissue, but lower expression in ovarian cancer cell lines than in normal ovarian cell lines. Interestingly, Toll‐like receptor (TLR4), a molecular functioning in tumour microenvironment (TME), demonstrated the same expression trend. To investigate the effect of abnormal TME on ovarian carcinogenesis, we established an in vitro model in which macrophages and ovarian cancer cells were co‐cultured. In the ovarian cancer cells co‐cultured with M2 macrophages, the expression of ALKBH5 and TLR4 increased. We also verified that TLR4 up‐regulated ALKBH5 expression via activating NF‐κB pathway. Depending on transcriptome sequencing, m6A‐Seq and m6A MeRIP, we found that NANOG served as a target in ALKBH5‐mediated m6A modification. NANOG expression increased after mRNA demethylation, consequently enhancing the aggressiveness of ovarian cancer cells. In conclusion, highly expressed TLR4 activated NF‐κB pathway, up‐regulated ALKBH5 expression and increased m6A level and NANOG expression, all contributing to ovarian carcinogenesis. Our study revealed the role of m6A in ovarian carcinogenesis, providing a clue for inventing new target therapy. [ABSTRACT FROM AUTHOR]

Endometrial cancer (EC) is a fatal female reproductive tumor. Bioinformatic tools are increasingly developed to screen out molecular targets related to EC. In this study, GSE17025 and GSE40032 were obtained from Gene Expression Omnibus (GEO). "limma" package and Venn diagram tool were used to identify hub genes. FunRich was used for functional analysis. Retrieval of Interacting Genes Database (STRING) was used to analyze protein‐protein interaction (PPI) complex. Cancer Genome Atlas (TCGA), GEPIA, immunohistochemistry staining, and ROC curve analysis were carried out for validation. Univariate and multivariate regression analyses were performed to predict the risk score. Compound muscle action potential (CMap) was used to find potential drugs. GSEA was also done. We retrieved seven oncogenes which were upregulated and hypomethylated and 12 tumor suppressor genes (TSGs) which were downregulated and hypermethylated. The upregulated and hypomethylated genes were strikingly enriched in term "immune response" while the downregulated and hypermethylated genes were mainly focused on term "aromatic compound catabolic process." TCGA and GEPIA were used to screen out EDNRB, CDO1, NDN, PLCD1, ROR2, ESPL1, PRAME, and PTTG1. Among them, ESPL1 and ROR2 were identified by Cox regression analysis and were used to construct prognostic risk model. The result showed that ESPL1 was a negative independent prognostic factor. Cmap identified aminoglutethimide, luteolin, sulfadimethoxine, and maprotiline had correlation with EC. GSEA results showed that "hedgehog signaling pathway" was enriched. This research inferred potential aberrantly methylated DEGs and dysregulated pathways may participate in EC development and firstly reported eight hub genes, including EDNRB, CDO1, NDN, PLCD1, ROR2, ESPL1, PRAME, and PTTG1 that could be used to predict EC prognosis. Aminoglutethimide and luteolin may be used to fight against EC. [ABSTRACT FROM AUTHOR]

Cervical cancer remains a primary cause of female death in developing countries, but its prognosis can be greatly improved if patients are diagnosed earlier. In the present study, we screened the common differentially expressed genes (DEGs) of cervical squamous cell carcinoma (CESC) from dataset GSE7803, Gene Expression Omnibus, and The Cancer Genome Atlas databases. An integrated bioinformatics analysis was performed based on these DEGs for their enrichment in functions and pathways, interaction network, prognostic signature, and candidate molecular drugs. As a result, 164 (114 upregulated and 47 downregulated) DEGs of CESC were identified for further investigation. We then conducted the gene ontology term enrichment and Kyoto Encyclopedia of Genes and Genomes Pathway analyses to reveal the underlying functions and pathways of these DEGs. In the protein–protein interaction network, hub module and hub genes were identified. Five genes of significant prognostic value—DSG2, ITM2A, CENPM, RIBC2, and MEIS2—were identified by prognostic signature analysis and used to construct a risk linear model. Further validation and investigation suggested DSG2 might be a key gene in CESC prognosis. We then identified two candidate small molecules (trichostatin A and tanespimycin) against CESC. Further validation and exploration of these hub genes are warranted for future prospect in clinical applications. [ABSTRACT FROM AUTHOR]

Cervical cancer (CC) is one kind of female cancer. With the development of bioinformatics, targeted specific biomarkers therapy has become much more valuable. GSE26511 was obtained from gene expression omnibus (GEO). We utilized a package called "WGCNA" to build co-expression network and choose the hub module. Search Tool for the Retrieval of Interacting Genes Database (STRING) was used to analyze protein-protein interaction (PPI) information of those genes in the hub module. A Plug-in called MCODE was utilized to choose hub clusters of PPI network, which was visualized in Cytoscape. Clusterprofiler was used to do functional analysis. Univariate and multivariate cox proportional hazards regression analysis were both conducted to predict the risk score of CC patients. Kaplan-Meier curve analysis was done to show the overall survival. Receiver operating characteristic (ROC) curve analysis was utilized to evaluate the predictive value of the patient outcome. Validation of the hub gene in databases, Gene set enrichment analysis (GSEA) and GEPIA were completed. We built co-expression network based on GSE26511 and one CC-related module was identified. Functional analysis of this module showed that extracellular space and Signaling pathways regulating pluripotency of stem cells were most related pathways. PPI network screened GNG11 as the most valuable protein. Cox analysis showed that ACKR1 was negatively correlated with CC progression, which was validated in Gene Expression Profiling Interactive Analysis (GEPIA) and datasets. Survival analysis was performed and showed the consistent result. GSEA set enrichment analysis was also completed. This study showed hub functional terms and gene participated in CC and then speculated that ACKR1 might be tumor suppressor for CC. [ABSTRACT FROM AUTHOR]

Background: Long noncoding RNAs (lncRNAs) have been identified to participate in tumorigenesis. However, the underlying mechanisms of differentially expressed lncRNAs engaged in diseases remain indistinct and need further exploration. Methods: Raw data files downloaded from TCGA and GEO dataset were used to analyze the differentially expressed lncRNAs and LINC00565 was picked out as the potential oncogene. qRT-PCR was used to analyze the LINC00565 level in ovarian tissues and cell lines. Subsequently, the selected ovarian tumor cells were then transfected with LINC00565 siRNA by Lipofectamine 2000 and the cell cycle was detected by flow cytometry. Effect of LINC00565 on tumor growth and cell cycle was verified by tumor formation assay in nude mice. The mechanism of LINC00565 involving in cell cycle regulation was further explored by Western blot. Results: In this research, we discovered that LINC00565, a novel lncRNA, was highly expressed in ovarian cancer (OC). LINC00565 expression level was negatively associated with outcomes of OC patients. Further analysis showed that LINC00565 expression was closely correlated to tumor size, FIGO stage, but not related to other clinical features. In vitro experiments indicated that knockdown of LINC00565 significantly inhibited proliferative, invasive and migratory abilities of ovarian cancer cells. Besides, knockdown of LINC00565 can induce cell cycle arrest in G0/G1 phase. In addition, in vivo assay showed that low expression of LINC00565 inhibited the growth of OC. Further study found that LINC00565 knockdown markedly downregulated the protein expressions of CyclinD1, CyclinE1 and CDK4, but upregulated the expression of P16 and P21. Subsequently, we confirmed that LINC00565 promoted the progression of OC via upregulating GAS6, which has been confirmed to promote tumor progression. Conclusion: In summary, our study firstly reported that the LINC00565 functioned as an oncogene to promote the progression of OC by interacting with GAS6. [ABSTRACT FROM AUTHOR]

Cervical cancer is the fourth most common malignancy in women worldwide and cervical squamous cell carcinoma (CESC) is the most common histological type of cervical cancer. The dysregulation of genes plays a significant role in cancer. In the present study, we screened out differentially expressed genes (DEGs) of CESC in the GSE63514 data set from the Gene Expression Omnibus database. An integrated bioinformatics analysis was used to select hub genes, as well as to investigate their related prognostic signature, functional annotation, methylation mechanism, and candidate molecular drugs. As a result, a total of 1907 DEGs were identified (944 were upregulated and 963 were downregulated). In the protein–protein interaction network, three hub modules and 30 hub genes were identified. And two hub modules and 116 hub genes were screened out from four CESC‐related modules by the weighted gene coexpression network analysis. The gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to better understand functions and pathways. Genes with a significant prognostic value were found by prognostic signature analysis. And there were five genes (EPHX2, CHAF1B, KIAA1524, CDC45, and RMI2) identified as significant CESC‐associated genes after expression validation and survival analysis. Among them, EPHX2 and RMI2 were noted as two novel key genes for the CESC‐associated methylation and expression. In addition, four candidate small molecule drugs for CESC (camptothecin, resveratrol, vorinostat, and trichostatin A) were defined. Further studies are required to explore these significant CESC‐associated genes for their potentiality in diagnosis, prognosis, and targeted therapy. [ABSTRACT FROM AUTHOR]

The expression of homeobox gene DLX4 has been verified in some tumors, but not in endometrial cancer. We found that expression of DLX7 , a splicing isoform of DLX4 , did not show any significant difference in expression between endometrial cancer and endometrium. However, BP1 , another splicing isoform of DLX4 , was highly expressed in endometrial cancer, and its expression was positively correlated with patient prognosis, cancer pathological grade, tumor invasion and metastasis. Lentiviral-mediated expression of BP1 in HEC-1-B cells accelerated the cell cycle progression from G0/G1 into S phase, and promoted cell proliferation and migration both in vitro and in vivo. Real-time PCR and western blotting showed that the expression levels of p15, p21 and E-cadherin significantly decreased, and levels of cyclinD1 and MMP-2 increased in endometrial cancer cells. In conclusion, our results demonstrate that high expression of BP1 is associated with poor prognosis in patients with endometrial cancer and promotes cell proliferation and migration. • BP1 is significantly overexpressed in endometrial cancer. • BP1 expression correlates with cancer pathological grade, tumor invasion and metastasis, and prognosis. • BP1 overexpression reduced G0/G1 cells and promoted proliferation and migration. • BP1 expression promoted cyclinD1 and MMP-2 expression and reduced p15, p21 and E-cadherin expression. [ABSTRACT FROM AUTHOR]

Background: Epithelial ovarian cancer (EOC) is a female malignant tumor. Bioinformatics has been widely utilized to analyze genes related to cancer progression. Targeted therapy for specific biological factors has become more valuable. Materials and methods: Gene expression profiles of GSE18520 and GSE27651 were downloaded from Gene Expression Omnibus. We used the "limma" package to screen differentially expressed genes (DEGs) between EOC and normal ovarian tissue samples and then used Clusterprofiler to do functional and pathway enrichment analyses. We utilized Search Tool for the Retrieval of Interacting Genes Database to assess protein–protein interaction (PPI) information and the plug-in Molecular Complex Detection to screen hub modules of PPI network in Cytoscape, and then performed functional analysis on the genes in the hub module. Next, we utilized the Weighted Gene Expression Network Analysis package to establish a co-expression network. Validation of the key genes in databases and Gene Expression Profiling Interactive Analysis (GEPIA) were completed. Finally, we used quantitative real-time PCR to validate hub gene expression in clinical tissue samples. Results: We analyzed the DEGs (96 samples of EOC tissue and 16 samples of normal ovarian tissue) for functional analysis, which showed that upregulated DEGs were strikingly enriched in phosphate ion binding and the downregulated DEGs were significantly enriched in glycosaminoglycan binding. In the PPI network, CDK1 was screened as the most relevant protein. In the co-expression network, one EOC-related module was identified. For survival analysis, database and clinical sample validation of genes in the turquoise module, we found that ITLN1 was positively correlated with EOC prognosis and had lower level in EOC than in normal tissues, which was consistent with the results predicted in GEPIA. Conclusion: In this study, we exhibited the key genes and pathways involved in EOC and speculated that ITLN1 was a tumor suppressor which could be used as a potential biomarker for treating EOC, Gene Expression Omnibus, prognosis. [ABSTRACT FROM AUTHOR]

Ovarian cancer is the most lethal gynecological cancer and its metastasis leads to a poor prognosis. The present study was designed to elucidate how microRNA (miR)-665 regulates the proliferation and migration of ovarian tumor cells. Reverse transcription-polymerase chain reaction (RT-PCR) demonstrated that miR-665 expression was decreased in ovarian cancer tissues. Increased expression of miR-665 suppressed the growth and migration of ovarian cancer cells, whereas the downregulated expression of miR-665 led to the opposite results. Bioinformatics tools identified homeobox A10 (HOXA10) as a target of miR-665. Following miR-665 overexpression, HOXA10 protein expression was significantly reduced. A dual luciferase assay revealed that miR-665 bound to the 3′-untranslated region of HOXA10. Immunohistochemistry and RT-PCR revealed that the expression of HOXA10 was negatively correlated with the expression of miR-665. It was concluded that miR-665 targets HOXA10 and may act as a tumor-suppressing gene in ovarian cancer. This pathway may be involved in the development and metastasis of ovarian cancer. [ABSTRACT FROM AUTHOR]

Background: p16 INK4A (p16) functions as a tumor suppressor gene in various malignancies. Aberrant p16 methylation has been proposed to be essential in ovarian carcinogenesis. However, it is unclear whether p16 can be used as a diagnostic marker owing to the small sample sizes in previous studies.Methods: To determine whether p16 promoter methylation is associated with epithelial ovarian cancer and can thus be used as a diagnostic marker, we performed a meta-analysis of published studies. The following databases were searched using a systematic search method: PubMed, Web of Science, EMBASE, and Chinese National Knowledge Infrastructure. We used a random-effects model to analyze the relative risk (RR); we also evaluated between-study heterogeneity, subgroup heterogeneity, and publication bias.Results: Our meta-analysis included eight eligible studies, with 428 ovarian cancers and 278 normal tissue samples and benign neoplasms. p16 promoter methylation was identified in 5.4 to 43.2% (median 27.86%) of ovarian cancers and 0 to 37.5% (median 15.8%) of normal tissue and benign neoplasms indicating that no significant association exists between p16 promoter methylation and epithelial ovarian cancer. However, the pooled results also showed that the RR was 1.52 (95% CI 0.80-2.87) in the ovarian cancer cases versus the corresponding normal and benign cases under the random-effects model. Between-study heterogeneity was determined through a sensitivity analysis; the I 2 value did not change when one study was excluded.Conclusions: Our study showed that p16 promoter methylation cannot be used to differentiate benign from malignant epithelial ovarian tumors. Therefore, p16 promoter methylation cannot be used as a marker for diagnosing the early stage of ovarian cancer. [ABSTRACT FROM AUTHOR]

Urothelial cancer associated 1 (UCA1) is an example of functional long noncoding RNAs involved in many biologic processes. However, little is known about the association between UCA1 expression and metastasis in epithelial ovarian cancer (EOC). Findings of this study confirmed that not only UCA1 was aberrantly upregulated in EOC tissues and cells, but also correlated with status of lymph node metastasis and FIGO stage. Furthermore, univariate and multivariate analyses showed that UCA1 was a prognostic factor for overall survival in EOC patients. In vitro, knockdown of UCA1 reduced the invasion and migration ability of EOC cells. The results showed that UCA1 could function as an endogenous sponge by directly binding to miR-485-5p. Depletion of UCA1 was involved in the downregulation of matrix metallopeptidase 14 (MMP14) expression, a target gene of miR-485-5p. In conclusion, our work indicates that UCA1 is a new prognostic biomarker for EOC, establishing a novel connection among UCA1, miR-485-5p, and MMP14 in EOC metastasis. [ABSTRACT FROM AUTHOR]

In this study, we devoted to investigate immune-related genes and tumor microenvironment (TME) in EC based on The Cancer Genome Atlas (TCGA) database. In total 799 up-regulated and 139 down-regulated immune-related and differentially expressed genes in EC were investigated for functional annotations and prognosis. By a conjoint Cox regression analysis, we built two risk models for OS and DFS, as well as the consistent nomograms. Immune-related pathways were revealed mostly enriched in the low-risk group. By further analyzing TME based on the risk signatures, the higher immune cell infiltration and activation, lower tumor purity and higher tumor mutational burden were found in low-risk group, which presented a better prognosis. Both the expression and immunophenoscore of immune checkpoints PD-1, CTLA4, PD-L1 and PD-L2 increased significantly in low-risk group. These findings may provide new ideas for novel biomarkers and immunotherapy targets in EC. • Our present study investigated the immune-related genes and TME in EC based on TCGA database. • We built two prognostic risk models for OS and DFS based on immune-related genes of EC patients. • The higher immune status, tumor mutational burden and immune checkpoints expression was found in the low-risk group patients. [ABSTRACT FROM AUTHOR]