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We aimed to identify differentially expressed pseudogenes and explore their potential functions in four types of common gynecological malignancies (e.g., cervical squamous cell carcinoma, ovarian serous cystadenocarcinoma, uterine corpus endometrial carcinoma, and uterine carcinosarcoma) using bioinformatics technology.
Mucinous cystadenocarcinoma of appendix is a rare entity. Differentiating mucinous cystadenocarcinoma from mucinous cystadenoma is very challenging and depends on establishing the presence of malignant cells in the appendix wall. The invasion may be very difficult to assess in some cases, especially in early stages of the disease, which could have devastating prognostic effects on patients. Therefore, it is necessary to develop an ancillary test that can differentiate the mucinous cystadenocarcinoma from mucinous cystadenoma. So far, there is no report available about the role of differentially expressed miRNAs in the diagnosis of appendiceal mucinous cystadenocarcinoma.
Ovarian serous cystadenocarcinoma is a common malignant tumor of female genital organs. Treatment is generally less effective as patients are usually diagnosed in the late stage. Therefore, a well-designed prognostic marker provides valuable data for optimizing therapy. In this study, we analyzed 303 samples of ovarian serous cystadenocarcinoma and the corresponding RNA-seq data. We observed the correlation between gene expression and patients' survival and eventually established a risk assessment model of five factors using Cox proportional hazards regression analysis. We found that the survival time in high-risk patients was significantly shorter than in low-risk patients in both training and testing sets after Kaplan-Meier analysis. The AUROC value was 0.67 when predicting the survival time in testing set, which indicates a relatively high specificity and sensitivity. The results suggest diagnostic and therapeutic applications of our five-gene model for ovarian serous cystadenocarcinoma.
Lymphatic invasion (LI) is regarded as a predictor of the aggressiveness of ovarian cancer (OC). However, LI is not always the major determinant of long-term patient survival. To establish proper diagnosis and treatment for OC, we analyzed differentially expressed genes (DEGs) for patients with serous epithelial OC, with or without LI, who did or did not survive for 5 years.
Serous ovarian cancer is the most common and primary death type in ovarian cancer. In recent studies, tumor microenvironment and tumor immune infiltration significantly affect the prognosis of ovarian cancer. This study analyzed the four gene expression types of ovarian cancer in TCGA database to extract differentially expressed genes and verify the prognostic significance. Meanwhile, functional enrichment and protein interaction network analysis exposed that these genes were related to immune response and immune infiltration. Subsequently, we proved these prognostic genes in an independent data set from the GEO database. Finally, multivariate cox regression analysis revealed the prognostic significance of TAP1 and CXCL13. The genetic alteration and interaction network of these two genes were shown. Then, we established a nomogram model related to the two genes and clinical risk factors. This model performed well in Calibration plot and Decision Curve Analysis. In conclusion, we have obtained a list of genes related to the immune microenvironment with a better prognosis for serous ovarian cancer, and based on this, we have tried to establish a clinical prognosis model.
Yes-associated protein 1 (YAP1) is a key transcriptional regulator in the Hippo signaling pathway that plays a critical role in the development and progression of several types of malignancies, including ovarian cancer. Herein, we investigated the expression of YAP1 and its clinical significance in a large population of patients with ovarian serous cystadenocarcinoma (OSC), which is the most common form of epithelial ovarian neoplasm, using the TCGA database. Surprisingly, cross-cancer mRNA expression and alterations in YAP1 were higher in OSC than in those of other types of cancers in the TCGA database. YAP1 mRNA expression was significantly higher in OSC compared with normal ovarian samples, and was higher in stages III and IV, than stages I and II. The level of YAP1 protein, which is mainly localized to the nucleus, was also higher in stage IV as compared with stages I, II and III. However, the protein level of pYAP1, which is inactive and is localized to the cytoplasm, was not significantly different between stages. The ratio of pYAP/YAP, which shows higher activity at a low ratio, was lower in stage III than in stages I and II. High YAP and low pYAP levels were significantly correlated with a poor prognosis in patients with OSC. The mRNA and protein expression of YAP1 were significantly increased in the proliferative subtype as compared to the differentiated, immunoreactive and mesenchymal subtypes. According to bioinformatics analysis, YAP1 is most highly correlated with the cell cycle. TGF-β signaling and WNT signaling were significantly increased in the high YAP1 group according to gene set enrichment analysis. Taken together, our results suggest that not only high YAP1 expression but also its subcellular distribution may be associated with poor overall survival in patients with OSC.
Ribonucleic acid-binding proteins (RBPs) are reportedly involved in tumor progression and recurrence; however, the functions and mechanisms of action of RBPs in ovarian serous cystadenocarcinoma (OSC) are not known. To address these issues, gene expression profiles of OSC tissues from The Cancer Genome Atlas (TCGA) and normal tissues from the Genotype-Tissue Expression database were compared in order to identify RBPs that are differentially expressed in OSC. We also analyzed the biological functions of these RBPs and their relationship to clinical outcome. There were 190 RBPs that were differentially expressed between OSC and normal tissues, including 93 that were upregulated and 97 that were downregulated. Five of the RBPs were used to construct a prediction model that was evaluated by univariate and multivariate Cox regression analyses. TCGA data were randomly divided into training and test cohorts, and further categorized into high- and low-risk groups according to risk score in the model. The overall survival (OS) of the high-risk group was shorter than that of the low-risk group (training cohort P = 0.0007596; test cohort P = 0.002219). The area under the receiver operating characteristic curve of the training and test cohorts was 0.701 and 0.638, respectively, demonstrating that the model had good predictive power. A nomogram was established to quantitatively describe the relationship between the five prognostic RBPs and OS in OSC, which can be useful for developing individualized management strategies for patients.
Ovarian serous cystadenocarcinoma is one of the most serious gynecological malignancies. Circular RNA (circRNA) is a type of noncoding RNA with a covalently closed continuous loop structure. Abnormal circRNA expression might be associated with tumorigenesis because of its complex biological mechanisms by, for example, functioning as a microRNA (miRNA) sponge. However, the circRNA expression profile in ovarian serous cystadenocarcinoma and their associations with other RNAs have not yet been characterized. The main purpose of this study was to reveal the circRNA expression profile in ovarian serous cystadenocarcinoma.
Ovarian cancer (OV) is a common type of carcinoma in females. Many studies have reported that ferroptosis is associated with the prognosis of OV patients. However, the mechanism by which this occurs is not well understood. We utilized Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) to identify ferroptosis-related genes in OV. In the present study, we applied Cox regression analysis to select hub genes and used the least absolute shrinkage and selection operator to construct a prognosis prediction model with mRNA expression profiles and clinical data from TCGA. A series of analyses for this signature was performed in TCGA. We then verified the identified signature using International Cancer Genome Consortium (ICGC) data. After a series of analyses, we identified six hub genes (DNAJB6, RB1, VIMP/ SELENOS, STEAP3, BACH1, and ALOX12) that were then used to construct a model using a training data set. The model was then tested using a validation data set and was found to have high sensitivity and specificity. The identified ferroptosis-related hub genes might play a critical role in the mechanism of OV development. The gene signature we identified may be useful for future clinical applications.
Ovarian serous cystadenocarcinoma (OSC) is the most common and lethal gynecological cancer in women worldwide; however, biomarkers to diagnose and predict prognosis of OSC remain limited. Therefore, the present study aimed to investigate whether sodium/potassium adenosine triphosphate (Na+/K+-ATP)ase α-subunits (ATP1As) are helpful diagnostic and prognostic markers of OSC.
Pancreatic mucinous cystadenocarcinoma (MCC) is a rare malignant tumor, with a limited number of studies. The present study aimed to investigate the function and mechanism of microRNA (miR)‑224‑5p on proliferation, migration and invasion of MCC of the pancreas. Reverse transcription‑quantitative PCR was used to explorethe expression of miR‑224‑5p and the PTEN gene. MTT, wound healing, Transwell and tumorigenesis assays were conducted to investigate the proliferation, migration and invasion of MCC1 cells in vitro and in vivo. Western blot analysis was employed to test the protein expression of PTEN. The target gene of miR‑224‑5p was assessed and verified by luciferase assay. miR‑224‑5p expression was notably higher, while PTEN expression was lower, in MCC1 cells compared with normal tissues and cells. Overexpression of miR‑224‑5p promoted the proliferation, migration and invasion of MCC and knockdown of miR‑224‑5p inhibited these functions. Bioinformatics analysis and luciferase assay indicated that PTEN was the direct target gene of miR‑224‑5p. The negative correlation between miR‑224‑5p and PTEN was confirmed both in vitro and in vivo. PTEN reversed the effects of miR‑224‑5p on proliferation, migration and invasion of MCC1 cells. The present study revealed for the first time, to the best of the authors' knowledge, that miR‑224‑5p was highly expressed and served an oncogenic role in MCC. miR‑224‑5p not only regulated the proliferation, migration and invasion of pancreatic MCC but may also be a potential therapeutic target for MCC.
The pharmacologic modulatory effects of the antibiotic, tunicamycin (TM), on multidrug-resistant human UWOV2 ovarian cancer cells are reported. The UWOV2 cell line was derived from a cystadenocarcinoma in a patient refractory to combination chemotherapy with actinomycin D, vincristine (VCR), cis-diaminedichloroplatinum (II) (CDDP) and doxorubicin (DXR). In an attempt to explain drug resistance in this cell line, we examined the effects of TM on their sensitivity to various anticancer drugs, the uptake, efflux and retention of [3H]VCR, and their ability to bind [14C]DXR and [3H]azidopine (AZD), a photoaffinity label of the multidrug transporter, P-glycoprotein (Pgp).
Ovarian cancer patients with homologous recombination deficiency (HRD) tumors would benefit from PARP inhibitor (PARPi) therapy. However, patients with HRD tumors account for less than 50% of the whole cohort, so new biomarkers still need to be developed. Based on the data from the SNP array and somatic mutation profiles in the ovarian cancer genome, we found that high frequency of actionable mutations existed in patients with non-HRD tumors. Through transcriptome analysis, we identified that a downstream target of the cGAS-STING pathway, CXCL11, was upregulated in HRD tumors and could be used as a predictor of survival outcome. Further comprehensive analysis of the tumor immune microenvironment (TIME) revealed that CXCL11 expression signature was closely correlated with cytotoxic cells, neoantigen load and immune checkpoint blockade (ICB). Clinical trial data confirmed that the expression of CXCL11 could be used as a biomarker for anti-PD-1/PD-L1 therapy. Finally, in vivo and in vitro experiments showed that cancer cells with PARPi treatment increased the expression of CXCL11. Collectively, our study not only provides biomarkers of ovarian cancer complementary to the HRD score but also introduces a potential new perspective for identifying prognostic biomarkers of immunotherapy.
The prognosis of invasive pancreatic mucinous cystadenocarcinoma (MCC) is poor, and the molecular mechanism underlying its development remains unclear. The present study aimed to explore the potential role of autophagy in pancreatic MCC. The results demonstrated an increase in autophagy signaling in pancreatic MCC tissues and the MCC1 cell line compared with adjacent tissues and normal human pancreatic ductal epithelium (HPDE) cells. In addition, abnormal autophagy activation facilitated the migration and invasion of MCC1 cells. MicroRNA (miR)-224-5p expression levels were significantly higher in MCC1 cells compared with those in HPDE cells. Treatment with rapamycin further demonstrated that high levels of autophagy elevated miR-224-5p expression in MCC1 cells in a time-dependent manner. BCL2 was identified as a downstream target gene of miR-224-5p, which binds to the 3'-untranslated region of BCL2. In addition, the results of the present study demonstrated that BCL2 knockdown reversed the inhibition of autophagy mediated by the miR-224-5p inhibitor. To the best of our knowledge, this is the first study to evaluate the role of autophagy in pancreatic MCC. Thus, these results suggested that autophagy may be hyperactivated in pancreatic MCC. In addition, the present study identified a positive feedback loop between autophagy signaling and miR-224-5p, which may promote the aggressive migration and invasion of MCC1. These results may provide a new insight into the relationship between autophagy and tumor metastasis in pancreatic MCC.
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