Prognosis Of Endometrial Cancer Patients Research Articles

Identification of autophagy-related long non-coding RNAs in endometrial cancer via comprehensive bioinformatics analysis

BackgroundEndometrial cancer is a common gynaecological malignancy with an increasing incidence. It is of great importance and value to uncover its effective and accurate prognostic indicators of disease outcomes.MethodsThe sequencing data and clinical information of endometrial cancer patients in the TCGA database were downloaded, and autophagy-related genes in the human autophagy database were downloaded. R software was used to perform a Pearson correlation analysis on autophagy-related genes and long non-coding RNAs (lncRNAs) to screen autophagy-related lncRNAs. Next, univariate and multivariate Cox regression analyses were performed to select autophagy-related lncRNAs and construct the prognostic model. Finally, the accuracy of the prognostic prediction of the model was evaluated, the lncRNA–mRNA network was constructed and visualized by Cytoscape, and the gene expression profile of endometrial cancer patients was analysed by GSEA.ResultsA total of 10 autophagy-related lncRNAs were screened to construct the prognostic model. The risk factors were AC084117.1, SOS1-IT1, AC019080.5, FIRRE and MCCC1-AS, and the protective factors were AC034236.2, POC1B-AS1, AC137630.1, AC083799.1 and AL133243.2. This prognostic model could independently predict the prognosis of endometrial cancer patients and had better predictive performance than that of using age and tumour grade. In addition, after classifying patients as high-risk or low-risk based on the prognostic model, we found that the enrichment of the JAK-STAT and MAPK pathways was significantly higher in the high-risk group than that in the low-risk group.ConclusionsThe 10 autophagy-related lncRNAs are potential prognostic biomarkers. Compared with using age and tumour grade, this prognostic model is more predictive for the prognosis of endometrial cancer patients.

Tertiary lymphoid structures critical for prognosis in endometrial cancer patients

B-cells play a key role in cancer suppression, particularly when aggregated in tertiary lymphoid structures (TLS). Here, we investigate the role of B-cells and TLS in endometrial cancer (EC). Single cell RNA-sequencing of B-cells shows presence of naïve B-cells, cycling/germinal center B-cells and antibody-secreting cells. Differential gene expression analysis shows association of TLS with L1CAM overexpression. Immunohistochemistry and co-immunofluorescence show L1CAM expression in mature TLS, independent of L1CAM expression in the tumor. Using L1CAM as a marker, 378 of the 411 molecularly classified ECs from the PORTEC-3 biobank are evaluated, TLS are found in 19%. L1CAM expressing TLS are most common in mismatch-repair deficient (29/127, 23%) and polymerase-epsilon mutant EC (24/47, 51%). Multivariable Cox regression analysis shows strong favorable prognostic impact of TLS, independent of clinicopathological and molecular factors. Our data suggests a pivotal role of TLS in outcome of EC patients, and establishes L1CAM as a simple biomarker.

Establishing a Prognostic Signature Based on Epithelial-Mesenchymal Transition-Related Genes for Endometrial Cancer Patients.

BackgroundsEpithelial–mesenchymal transition (EMT) is a sequential process where tumor cells develop from the epithelial state to the mesenchymal state. EMT contributes to various tumor functions including initiation, propagating potential, and resistance to therapy, thus affecting the survival time of patients. The aim of this research is to set up an EMT-related prognostic signature for endometrial cancer (EC).MethodsEMT-related gene (ERG) expression and clinical data were acquired from The Cancer Genome Atlas (TCGA). The entire set was randomly divided into two sets, one for contributing the risk model (risk score) and the other for validating. Univariate and multivariate Cox proportional hazards regression analyses were applied to the training set to select the prognostic ERGs. The expression of 10 ERGs was confirmed by qRT-PCR in clinical samples. Then, we developed a nomogram predicting 1-/3-/5-year survival possibility combining the risk score and clinical factors. The entire set was stratified into the high- and low-risk groups, which was used to analyze the immune infiltrating, tumorigenesis pathways, and response to drugs.ResultsA total of 220 genes were screened out from 1,316 ERGs for their differential expression in tumor versus normal. Next, 10 genes were found to be associated with overall survival (OS) in EC, and the expression was validated by qRT-PCR using clinical samples, so we constructed a 10-ERG-based risk score to distinguish high-/low-risk patients and a nomogram to predict survival rate. The calibration plots proved the predictive value of our model. Gene Set Enrichment Analysis (GSEA) discovered that in the low-risk group, immune-related pathways were enriched; in the high-risk group, tumorigenesis pathways were enriched. The low-risk group showed more immune activities, higher tumor mutational burden (TMB), and higher CTAL4/PD1 expression, which was in line with a better response to immune checkpoint inhibitors. Nevertheless, response to chemotherapeutic drugs turned out better in the high-risk group. The high-risk group had higher N 6-methyladenosine (m6A) RNA expression, microsatellite instability level, and stemness indices.ConclusionWe constructed the ERG-related signature model to predict the prognosis of EC patients. What is more, it might offer a reference for predicting individualized response to immune checkpoint inhibitors and chemotherapeutic drugs.

Prognostic Values From Integrated Analysis of the Nomogram Based on RNA-Binding Proteins and Clinical Factors in Endometrial Cancer.

Background:Endometrial cancer (EC) is a common gynecological malignancy, and the prognosis of advanced EC is unsatisfactory. The deregulated expression of RNA-binding proteins (RBPs) is closely associated with the occurrence and development of cancer. However, the role of RBPs in EC remains unclear. The aim of this study was to validate the prognostic values of RBPs combined with clinical factors.Methods:We downloaded the RNA sequencing and clinical data for EC from The Cancer Genome Atlas (TCGA) database. R software was used to identify the differentially expressed RBPs. Univariate and multivariate Cox proportional hazards regression analyses were performed to predict the 4 overall survival (OS)-related RBPs. We then constructed a nomogram combining the 4-RBP signature with clinical risk factors to assess the prognostic power. Furthermore, we validated the expression of 4 RBPs in our patient samples using quantitative real-time polymerase chain reaction (qRT-PCR) and explored the effect of cold-inducible RNA-binding protein (CIRBP) on EC tumor growth using cell proliferation experiments.Results:It is found that Shwachman-Bodian-Diamond syndrome (SBDS), CIRBP, MRPL15, and CELF4 were significantly related to the prognosis of EC patients. In addition, the nomogram showed better performance in OS predictions than the International Federation of Gynecology and Obstetrics (FIGO) stage. The qRT-PCR results showed that low CIRBP expression was associated with cell proliferation.Conclusions:In our study, we constructed a 4-RBP signature-based nomogram combined with clinical factors in EC that could effectively predict the prognosis of EC patients. The results provide novel insights into the development of treatment targets and prognostic molecular markers in EC.

Artemin affects the survival and prognosis of endometrial cancer patients via regulating tumor cell proliferation

The main aim of the study is to analyze the impact of Artemin on survival and prognosis in endometrial cancer (EC) patients by bioinformatics methods. As a member of the glial-derived neurotrophic factor (GDNF) family, Artemin is not only important in the repair process of nerve damage, but also involved in tumorigenesis and metastasis. In this study, we demonstrated that Artemin mRNA was overexpressed in EC tissues. Artemin expression was closely related to the FIGO stage, pathologic differentiation, deep myometrial infiltration, lymphatic metastasis, and survival status. Univariate and multivariate Cox regression analysis showed that ectopic overexpression of Artemin predicted poor survival prognosis. Artemin expression could be used as an independent risk factor for the prognosis of EC patients. The proliferation of EC cells was significantly downregulated by silencing of Artemin. Artemin promotes tumor progression by regulating the proliferation of EC cells, thereby affecting the prognosis of EC patients.

An analysis of the significance of the lymph node ratio and extracapsular involvement in the prognosis of endometrial cancer patients.

IntroductionThe primary aim of our study was to analyse the impact of the lymph node ratio (LNR) and extracapsular involvement (ECI) on the prognosis of endometrial cancer (EC) patients.Material and methodsWe carried out a retrospective analysis of 886 patients surgically treated for EC between 2000 and 2015. In the subgroup of patients with lymph node metastases (LNM), we evaluated the impact of the number and localization of the LNM, LNR, and ECI on patients’ overall survival (OS).ResultsIn the group of patients with LNM, 0.3 was the optimal LNR cut-off for differentiating between short- and long-term survivors [HR = 2.94 (95% CI: 1.49–5.80)]. Patients with a LNR ≥ 0.3 had a significantly shorter OS period (35.0 months, range 0.2–175 months) compared to patients with a LNR < 0.3 [median OS – mOS, was 143, range 15–169 months; (p = 0.003]. We observed significant differences in the mOS of EC patients without LNM compared to patients with LNM, as well as those with both LNM and ECI (p < 0.0001). In the group of patients with LNM, we also found that a poorer prognosis depended on the extension of the primary tumour.ConclusionsOur results suggest that when LNM are found, the long-term outcomes of EC patients are worse in those who have a LNR ≥ 0.3, the presence of ECI, and a more advanced extension of the primary tumour.

Effects of Metabolic Syndrome and Its Components on the Prognosis of Endometrial Cancer.

ObjectiveTo explore the effects of metabolic syndrome (MetS) on the prognosis of endometrial cancer (EC) and to identify key components of MetS associated with EC.MethodsA total of 506 patients surgically diagnosed with EC were analyzed in this study. These patients were diagnosed with EC in the Department of Obstetrics and Gynecology at the People’s Hospital of Peking University between 2010 and 2016. The follow-up time was cut off at December 2019. MetS was characterized based on standards provided by the Chinese Diabetes Society in 2004.ResultsAmong the 506 EC patients analyzed, 153 patients were diagnosed with MetS. MetS patients were more likely to be older and postmenopausal. MetS was positively related to tumor grade, stage, LNM, LVSI, and MI. The univariate analysis showed that MetS was closely related to the OS (HR = 2.14; P = 0.032) and RFS (HR = 1.80; P = 0.045) of EC patients. K–M analysis also indicated that EC patients with MetS had shorter OS and RFS than EC patients without MetS. More specifically, patients that had ≥3 components showed a worse outcome compared with patients only having 0 or 1–2 components (P <0.05). In the multivariate-adjust model, after adjusting for age, histotype, tumor grade, and stage, HDL-C was found to be associated with increased risk of death related to EC (HR = 2.2, P = 0.034). However, MetS did not significantly correlate with this. ROC analysis revealed that the area under the ROC curve of combined factors (HDL-C + grade + stage) was better than traditional stage or grade at 1-, 3-, and 5-year survival rates. From this, a nomogram based on HDL-C, grade, and stage was constructed to predict survival of EC patients. Calibration curve analysis and decision curve analysis (DCA) showed the nomogram we constructed could better predict the survival of EC patients.ConclusionMetS is closely related to poor prognosis in EC patients. The prevalence of individual MetS components increase with worse outcomes in EC patients. A nomogram based on HDL-C, grade, and stage has good ability to predict survival of EC patients.

A Novel miR-98 Negatively Regulates the Resistance of Endometrial Cancer Cells to Paclitaxel by Suppressing ABCC10/MRP-7.

Endometrial cancer (EC) is one of the most frequent gynecological tumors, and chemoresistance is a major obstacle to improving the prognosis of EC patients. MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) have recently emerged as crucial chemoresistance regulators that alter the levels of downstream target genes. Multidrug Resistance Protein 7 (MRP-7/ABCC10) is an ATP-binding cassette transporter that causes the resistance to anti-cancer drugs. The purpose of this research is to determine whether MRP-7 has a role in mediating the sensitivity of EC cells to paclitaxel and whether the expression of MRP-7 is regulated by miR-98 and lncRNA NEAT1. We reported that the levels of MRP-7 were significantly increased in EC tissues and associated with an unfavorable prognosis. Downregulation of MRP-7 in EC cells sensitized these cells to paclitaxel and reduced cell invasion. PLAUR serves as a downstream molecule of MRP-7 and facilitates paclitaxel resistance and EC cell invasiveness. Moreover, miR-98 serves as a tumor suppressor to inhibit MRP-7 expression, leading to the repression of paclitaxel resistance. Furthermore, a novel lncRNA, NEAT1, was identified as a suppressor of miR-98, and NEAT1 could upregulate MRP-7 levels by reducing the expression of miR-98. Taken together, these findings demonstrate that upregulation of MRP-7 and NEAT1, and downregulation of miR-98 have important roles in conferring paclitaxel resistance to EC cells. The modulation of these molecules may help overcome the chemoresistance against paclitaxel in EC cells.

KIF2C Is a Novel Prognostic Biomarker and Correlated with Immune Infiltration in Endometrial Cancer.

Endometrial cancer (EC) is commonly diagnosed cancer in women, and the prognosis of advanced types of EC is extremely poor. Kinesin family member 2C (KIF2C) has been reported as an oncogene in cancers. However, its pathophysiological roles and the correlation with tumor-infiltrating lymphocytes in EC remain unclear. The mRNA and protein levels of KIF2C in EC tissues were detected by qRT-PCR, Western blot (WB), and IHC. CCK8, Transwell, and colony formation assay were applied to assess the effects of KIF2C on cell proliferation, migration, and invasion. Cell apoptosis and cell cycle were analyzed by flow cytometry. The antitumor effect was further validated in the nude mouse xenograft cancer model and humanized mouse model. KIF2C expression was higher in EC. Knockdown of KIF2C prolonged the G1 phases and inhibited EC cell proliferation, migration, and invasion in vitro. Bioinformatics analysis indicated that KIF2C is negatively correlated with the infiltration level of CD8+ T cells but positively with the poor prognosis of EC patients. The apoptosis of CD8+ T cell was inhibited after the knockdown of KIF2C and was further inhibited when it is combined with anti-PD1. Conversely, compared to the knockdown of KIF2C expression alone, the combination of anti-PD1 further promoted the apoptosis of Ishikawa and RL95-2 cells. Moreover, the knockdown of KIF2C inhibited the expression of Ki-67 and the growth of tumors in the nude mouse xenograft cancer model. Our study found that the antitumor efficacy was further evaluated by the combination of anti-PD1 and KIF2C knockdown in a humanized mouse model. This study indicated that KIF2C is a novel prognostic biomarker that determines cancer progression and also a target for the therapy of EC and correlated with tumor immune cells infiltration in EC.

Abstract 1989: LSR is a novel prognostic factor by regulating cell proliferation via MEK/ERK pathway in endometrial cancer:Analysis of signal transduction, bioinformatics, and in vitro/in vivo study

Abstract Introduction: Advanced endometrial cancer (EC) still has poor prognosis and requires the development of new therapeutic agents. In ovarian and gastric cancer, we revealed that high expression of lipolysis-stimulated lipoprotein receptor (LSR), a cell-surface membrane protein, was associated with poor prognosis and LSR could be a new therapeutic target. However, in EC, the clinical and cell biological role of LSR is still unclear. We aimed to investigate the functions of LSR in EC. Methods: We evaluated LSR expression by immunohistochemistry and analyzed overall survival (OS) and clinicopathological factors in 228 EC patients. To investigate the mechanism by which LSR affects the prognosis of EC patients, the pathway enrichment analysis and gene ontology analysis were conducted using the publicly available proteogenomic dataset of EC. Cell proliferation was analyzed by WST-8 assay using two LSR-knockdown cell lines (HEC1 and HEC116) developed by transfection of LSR-siRNA, and the activity of several signaling pathways were examined by Western blotting. Results: Patients were divided into two groups based on LSR expression; High (darkly stained cells in ≥25% of the area, n=153) and Low (darkly stained cells in &amp;lt;25% of the area, n=75) groups. 5-year OS rate in High group was significantly lower than Low group (hazard ratio: 3.53, 95% confidence interval: 1.35 - 9.24, p=0.01). Stage III-IV, deep myometrial invasion (≥75% of uterine myometrium), tumor involvement of adnexa or serosa, and distant metastasis were more frequently observed in High group than in Low group (p&amp;lt;0.05, respectively). The pathway analysis demonstrated that genes correlated with high LSR expression were enriched in MAPK signaling pathway. In gene ontology analysis, these genes were enriched in regulation of ERK1/2 and MAPK cascade. In vitro, LSR-knockdown suppressed cell proliferation (p&amp;lt;0.01) and phosphorylation of MEK1/2, ERK1/2, and p90RSK, suggesting that LSR promoted cell proliferation via MEK/ERK pathway. However, LSR did not regulate the other signaling pathways (SAPK/JNK, p38-MAPK, JAK/STAT3, and PI3K/AKT/mTOR pathway). Conclusion: LSR regulated cell proliferation via MEK/ERK pathway, and contributed poor prognosis in EC. LSR may be a new therapeutic target of advanced EC. Citation Format: Yoshikazu Nagase, Kosuke Hiramatsu, Satoshi Nakagawa, Shinya Matsuzaki, Toshihiro Kimura, Satoshi Serada, Yutaka Ueda, Tetsuji Naka, Tadashi Kimura. LSR is a novel prognostic factor by regulating cell proliferation via MEK/ERK pathway in endometrial cancer:Analysis of signal transduction, bioinformatics, and in vitro/in vivo study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1989.

LINC00470 Stimulates Methylation of PTEN to Facilitate the Progression of Endometrial Cancer by Recruiting DNMT3a Through MYC.

ObjectivesIncreasing researches emphasize the importance of long non-coding RNAs (lncRNAs) in the development of endometrial cancer (EC). There is wide recognition that LINC00470 is a critical participant in the tumorigenesis of cancers such as gastric cancer and glioblastoma, but its possible effects on EC progression remain to be explored.MethodsWe collected EC tissues and cells, where the expression of LINC00470 was determined, and followed by the Kaplan-Meier analysis of EC patient survival. We next examined the effect of LINC00470 and phosphatase and tensin homolog (PTEN) on EC cell migration, invasion, tube formation in vitro, and angiogenesis in mice xenografted with tumor after gain- or loss-of-function treatments. RNA pull-down, Co-IP, and ChIP experiments were performed to analyze the targeting relationships among LINC00470, MYC and DNMT3a.ResultsLINC00470 was aberrantly upregulated in EC and its high expression correlated to prognosis of EC patients. LINC00470 promoted invasiveness, migration, and angiogenesis of EC cells, and facilitated tumorigenesis and metastasis in vivo, but those effects were reversed by up-regulating PTEN. Functionally, LINC00470 bound to MYC in EC and that LINC00470 stimulated the binding of MYC to DNMT3a, and thus recruited DNMT3a through MYC to promote PTEN methylation.ConclusionsOur findings revealed that LINC00470 stimulated PTEN methylation to inhibit its expression by MYC-induced recruitment of DNMT3a, thus aggravating EC.

Immune infiltration and a ferroptosis-associated gene signature for predicting the prognosis of patients with endometrial cancer.

Ferroptosis, a form of programmed cell death induced by excess iron-dependent lipid peroxidation product accumulation, plays a critical role in cancer. However, there are few reports about ferroptosis in endometrial cancer (EC). This article explores the relationship between ferroptosis-related gene (FRG) expression and prognosis in EC patients. One hundred thirty-five FRGs were obtained by mining the literature, retrieving GeneCards and analyzing 552 malignant uterine corpus endometrial carcinoma (UCEC) samples, which were randomly assigned to training and testing groups (1:1 ratio), and 23 normal samples from The Cancer Genome Atlas (TCGA). We established a signature using eight screened FRGs (MDM2, GPX4, PRKAA2, PRNP, SLC11A2, ATP5MC3, PHKG2 and ACO1) related to overall survival using LASSO regression analysis. The samples were divided into low- and high-risk subgroups according to the median risk score. Kaplan-Meier survival curves showed that the low-risk group had better OS. ROC curves showed that this signature performed well in predicting OS (1-, 2-, 3-, and 5-year AUCs of 0.676, 0.775, 0.797, and 0.826, respectively). We systematically analyzed the immune infiltrating profile in UCEC samples from TCGA. Overall, our study identified a novel prognostic signature of 8 FRGs that can potentially predict the prognosis of EC.

Clinical study of the clinical characteristics and prognosis of 1219 cases of endometrial cancer with lymph node metastasis.

To analyze the clinical characteristics and prognosis of endometrial cancer patients with lymph node metastasis to provide a reference for lymphadenectomy in endometrial cancer. The data used in this study were extracted from a tertiary hospital in Guangxi, China based on the hospital information system. 1219 patients with endometrial malignancy who were treated in our hospital. The lymph node metastasis rate was 9.8%. The metastasis rate of the abdominal aorta + pelvic lymph nodes (56.7%) was significantly higher than that of the pelvic (24.2%) or para-aortic (19.2%) lymph nodes alone. The proportion of postmenopausal patients with lymph node metastasis was higher than that of premenopausal patients. The proportion of patients with lymph node metastasis with vaginal and uterus involvement, HPV detection, Thinprep Cytologic Testresults, CRP level <10 ug/mL, G3 tumor grade, postoperative pathology indicating cervical invasion, lymphovascular invasion, and muscular infiltration depth > 1/2 was higher than that of patients without lymph node metastasis. The proportion of endometrial cancer patients with lymph node metastasis with CA125 ≥ 35 U/ml was higher than that of those with CA125 < 35 U/ml. The lymph node-positive rate is related to tissue differentiation, lymphangitic infiltration, cervical invasion, muscle infiltration depth > 1/2, and CA125 level. The metastasis rate of pelvic and para-aortic lymph nodes is higher than that of pelvic lymph nodes or para-aortic lymph nodes alone. There was no statistically significant difference in the overall survival rate among the three groups.

A Novel Transcription Factor-Based Prognostic Signature in Endometrial Cancer: Establishment and Validation.

BackgroundEndometrial cancer (EC) is a common malignancy of the female reproductive system worldwide. Increasing evidence has suggested that many transcription factors are aberrantly expressed in various cancers. This study aimed to develop a transcription factor-based prognostic signature for EC.MethodsGene expression data and clinical data of EC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression and Multivariate Cox regression analysis was used to construct a prognostic signature. Then, the efficacy of the prognostic signature was validated in a training cohort, testing cohort and then the entire cohort. Correlations between clinical features and the model were also analyzed, and a nomogram based on the multivariate Cox analysis was developed. Furthermore, we verified the effect of a key transcription factor, E2F1, on biological functions of EC in vitro.ResultsWe developed a nine-transcription factor (MSX1, HOXB9, E2F1, DLX4, BNC2, DLX2, PDX1, POU3F2, and FOXP3) prognostic signature. Compared with those in the low-risk group, patients in the high-risk group had worse clinical outcomes. The area under the curve (AUC) of this prognostic signature for 5-year survival was 0.806 in the training cohort, 0.710 in the testing cohort and 0.761 in the entire cohort. Gene set enrichment analysis (GSEA) revealed a correlation between the prognostic signature and various cancer signaling pathways, and a hub transcription factor regulatory network was constructed. The prognostic signature was confirmed to have independent predictive value. Finally, a nomogram based on the prognostic signature and clinical independent prognostic factors was also established and performed well according to the calibration curves. Further, knockdown of E2F1 inhibited invasion and metastasis of EC cells.ConclusionOur study developed and validated a transcription factor-based prognostic signature that accurately predicts prognosis of EC patients. Moreover, E2F1 may represent a potential target for the treatment of EC.

A Risk Signature with Nine Stemness Index-Associated Genes for Predicting Survival of Patients with Uterine Corpus Endometrial Carcinoma.

Purpose To identify mRNA expression-based stemness index- (mRNAsi-) related genes and build an mRNAsi-related risk signature for endometrial cancer. Methods We collected mRNAsi data of endometrial cancer samples from The Cancer Genome Atlas (TCGA) and analyzed their relationship with the main clinicopathological characteristics and prognosis of endometrial cancer patients. We screened the top 50% of the genes in TCGA for weighted gene correlation network analysis (WGCNA) to explore mRNAsi-related gene sets. Among these mRNAsi-related genes, we further screened for those related to the prognosis of endometrial cancer patients via univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Using stepwise multivariate Cox regression analysis, a stemness index-related risk signature was constructed. Finally, we identified potential prognostic biomarkers for endometrial cancer by combining the GEO database and immunohistochemical staining. Results The mRNAsi of endometrial cancer samples was significantly higher than that of normal samples and was related to the International Federation of Gynecology and Obstetrics (FIGO) stage, pathological grade, postoperative tumor status, and overall survival of endometrial cancer patients. We identified 21 mRNAsi-related gene modules, and 1,324 genes were obtained from the most relevant module. TCGA samples were divided into training and validation cohorts, and the training cohort was used to construct a nine-mRNAsi-related gene signature (B3GAT2, CD3EAP, DMC1, FRMPD3, LINC01224, LINC02068, LY6H, NR6A1, and TLE2). High-risk and low-risk patients had significant prognostic differences, and the risk signature could accurately predict their 1-, 3-, and 5-year survival. The nomogram composed of risk score and multiple clinicopathological features could accurately predict 1-, 3-, and 5-year survival. Finally, CD3EAP was found to be a novel prognostic biomarker for endometrial cancer. Conclusion Endometrial cancer cell stemness is related to patient prognosis. The nine-gene risk signature is an independent prognostic factor and can accurately predict endometrial cancer patient prognosis.

Zfx-induced upregulation of UBE2J1 facilitates endometrial cancer progression via PI3K/AKT pathway

ABSTRACT Emerging documents revealed that E2 enzyme family has been implicated in regulating the progression of numerous human cancers. Ubiquitin-conjugating enzyme E2 J1 (UBE2J1), a member of E2 enzyme family, has been reported to participate in the biological process of medulloblastoma, while little is known about its functionality in endometrial cancer (EC). Gene expression at the mRNA and protein levels were identified using RT-qPCR and western blot analysis, separately. The alteration on cell proliferation, adhesion, migration, invasion, and epithelial-mesenchymal transition (EMT) process was determined through 5-Ethynyl-2ʹ-deoxyuridine, cell adhesion, wound healing and transwell assays as well as western blot analysis. The role of UBE2J1 in xenograft tumor in mice was determined. Luciferase reporter and chromatin immunoprecipitation assays were conducted to reveal the undering mechanism of UBE2J1. Our results indicated that UBE2J1 displayed high level in EC tissues and cells and predicted poor prognosis of EC patients. In addition, UBE2J1 depletion inhibited cell proliferation, adhesion, motion, EMT process in vitro, and repressed tumor growth in vivo. Rescue assays manifested that ethyl 2-amino-6-chloro-4-(1-cyano-2-ethoxy-2-oxoethyl)-4H-chromene-3-carboxylate treatment reversed the effects of UBE2J1 on PI3K/AKT pathway activation and malignant phenotypes of EC cells. Finally, zinc finger X-chromosomal protein (zfx), with high expression in EC tissues, was verified to activate UBE2J1 transcription by binding to UBE2J1 promoter. In conclusion, all facts signified that zfx-induced upregulation of UBE2J1 accelerated the progression of EC via regulating the PI3K/AKT signaling pathway, which suggested that UBE2J1 might be of great significance in probing into the underlying therapeutic strategies of EC.

Development and validation of nomogram with tumor microenvironment-related genes and clinical factors for predicting overall survival of endometrial cancer.

Background: Tumor microenvironment (TME) has attracted lots of attention with its important role in the tumor development. This study aimed to explore TME- related genes of prognostic value in patients with endometrial cancer (EC) and establish a prediction model for EC.Methods: The RNA-Seq data and clinicopathological characteristics of 521 subjects were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were identified based on the immune and stromal scores, which were calculated by the ESTIMATE algorithm. Hub genes were initially screened using the Cytoscape and further selected through Cox regression. Gene correlation analysis was performed in TIMER database. A nomogram was constructed integrating prognosis-related hub genes and clinical factors and validated in the validation group. Risk stratification was performed based on the nomogram.Results: Three TME-related hub genes (CCR5, FCER1G, and ITGB2) were found with significant prognostic value for EC patients. The expression of CCR5, FCER1G, and ITGB2 were significantly correlated with various immune cells infiltration. Based on the Cox regression, a nomogram was constructed by integrating five predictors (stage, grade, immune score, expression of FCER1G, and ITGB2), with a C-index of 0.765. Discrimination of the model was confirmed in the validation group (C-index: 0.716). The calibration curves for the 3- and 5- year survival indicated good calibration. Patients in high- and low- risk groups presented significantly different survival outcomes (P<0.001) in both discovery and validation group.Conclusion: TME-related hub genes of prognostic value identified in our study may provide references for the mechanisms underlying EC development and the immunotherapy for EC. The prediction model may help assess the prognosis of EC patients.

Clinical Significance, Cellular Function, and Potential Molecular Pathways of CCT7 in Endometrial Cancer.

Objective: Endometrial cancer (EC) is a common gynecologic malignancy; myometrial invasion (MI) is a typical approach of EC spreads and an important index to assess tumor metastasis and outcome in EC patients. CCT7 is a member of the TCP1 chaperone family, involved in cytoskeletal protein folding and unfolding. In this study, the role of CCT7 in EC development was investigated.Methods: Clinical data for 87 EC cases and expression of CCT7 were analyzed. CCT7 was knocked out using siRNA-CCT7 in Ishikawa and RL95-2 cells, and their function about proliferation, apoptosis, and invasion was further tested. Bioinformatics methods were used to predict the potential pathways of CCT7 in EC development.Results: The rates of CCT7-positive cells in EC and adjacent normal endometrium tissues had a significant difference (67.8 vs. 51.4%, p = 0.035), and the expression rate increased from low to high pathological stage (39.7% in the I/II stage, 71.4% in the III/IV stage, p = 0.029). A similar change was found in protein level. CCT7 expression differed significantly between the deep MI group (>1/2) and the superficial MI group (≤1/2) (p = 0.039). However, there were no differences with respect to age, pathological type, and histological grade. CCT7 suppression induced a function loss in both Ishikawa and RL95-2 cells. Bioinformatics analysis demonstrated that EC patients with lower-level CCT7 expression had better overall survival (p = 0.0081). Gene ontology enrichment indicated that “RNA binding,” “Mitochondrion,” “Translation,” and “Spliceosome” were most significantly enriched potential pathways. Five hub genes, PSMA5, PSMD14, SNRPB, SNRPG, and TXNL4A, were all significantly upregulated in EC and had a positive correlation with CCT7.Conclusions: CCT7 may be involved in EC development by excessively activating tumor cell function to promote MI or distant/nodal metastasis, which may contribute to the prognosis of EC patients.

Identification of biomarkers correlated with diagnosis and prognosis of endometrial cancer using bioinformatics analysis.

Endometrial cancer (EC) is one of the most common malignancies in the female genital system, characterized by high mortality and recurrence rates. This study attempted to screen key genes and potential prognostic biomarkers for EC using bioinformatics analysis. Twenty-seven normal endometrial tissues and 135 EC samples were collected from four Gene Expression Omnibus (GEO) databases, then we identified the differentially expressed genes (DEGs) and conducted downstream analyses. Moreover, we screened hub genes by constructing a protein-protein interaction (PPI) network. Finally, we assessed the prognostic values and molecular mechanism of the potential prognostic genes using the Kaplan-Meier curve and Gene Set Enrichment Analysis (GSEA). As a result, 28 upregulated and 94 downregulated genes were determined after gene integration of these four GEO data sets. Gene Ontology analysis indicated that DEGs were mainly involved in transcriptional regulation and cell proliferation. The Kyoto Encyclopedia of Gene and Genome pathway analysis primarily related to transcriptional misregulation and apoptosis. Moreover, the PPI analysis revealed 10 hub genes (JUN, UBE2I, GATA2, WT1, PIAS1, FOXL2, RUNXI, EZR, TCF4, and NR2F2) with a high degree of connectivity, among them, the expression tendency of nine genes except UBE2I were consistent with messenger RNA level from The Cancer Genome Atlas data. Furthermore, only FOXL2, TCF4, and NR2F2 were significantly correlated with prognosis of EC patients, and their low expression associated biological pathways were enriched in the cell cycle and fatty acid metabolism. In conclusion, this study identified three key genes as biomarkers and potential therapeutic targets of EC on the basis of integrated bioinformatics analysis. The findings will improve our comprehension of the molecular mechanisms underlying the pathogenesis and prognosis of EC.

Prognostic significance of immune landscape in tumour microenvironment of endometrial cancer.

Tumour microenvironment (TME) is crucial to tumorigenesis. This study aimed to uncover the differences in immune phenotypes of TME in endometrial cancer (EC) using Uterine Corpus Endometrial Carcinoma (UCEC) cohort and explore the prognostic significance. We employed GVSA enrichment analysis to cluster The Cancer Genome Atlas (TCGA) EC samples into immune signature cluster modelling, evaluated immune cell profiling in UCEC cohort (n = 538) and defined four immune subtypes of EC. Next, we analysed the correlation between immune subtypes and clinical data including patient prognosis. Furthermore, we analysed the expression of immunomodulators and DNA methylation modification. The profiles of immune infiltration in TCGA UCEC cohort showed significant difference among four immune subtypes of EC. Among each immune subtype, natural killer T cells (NKT), dendritic cells (DCs) and CD8+T cells were significantly associated with EC patients survival. Each immune subtype exhibited specific molecular classification, immune cell characterization and immunomodulators expression. Moreover, the expression immunomodulators were significantly related to DNA methylation level. In conclusion, the identification of immune subtypes in EC tissues could reveal unique immune microenvironments in EC and predict the prognosis of EC patients.