scholarly journals A seven-m6A regulator-related CpG site-based prognostic signature for endometrial carcinoma

Medicine ◽  
2021 ◽  
Vol 100 (29) ◽  
pp. e26648
Author(s):  
Xiang Zhang ◽  
Xuecheng Pang ◽  
Yue Huang ◽  
Sumin Qian
Keyword(s):  
Endometrial Carcinoma ◽  
Prognostic Signature ◽  
Cpg Site

A bioinformatics study of autophagy biomarkers associated with the prognosis of endometrial carcinoma

2020 ◽  
Author(s):  
Wei Liu ◽  
Rui Sun ◽  
Yixuan Bai ◽  
Yunkai Xie ◽  
Changzhong Li
Keyword(s):  
Functional Analysis ◽  
Endometrial Carcinoma ◽  
Expression Analysis ◽  
Critical Role ◽  
Curve Analysis ◽  
Gene Set Enrichment Analysis ◽  
Ppi Network ◽  
Prognostic Signature ◽  
Roc Curve Analysis ◽  
Limma Package

Abstract Background: Autophagy plays a critical role in endometrial carcinoma (EC), but prognosis studies of differentially expressed autophagy-related genes (DEARGs) in EC are lacking. This study aimed to access the prognostic value of autophagy-related genes (ARGs) in EC and to identify the potential characteristics of ARGs in predicting patient survival and guiding treatment.Methods: The RNA-Seq data and clinical data were obtained from TCGA databases. The DEARGs were identified by “limma” package in R software. Clusterprofler was used for functional analysis. Using STRING databases to construct a protein-protein interaction (PPI) network and plug-in MCODE to screen hub modules in Cytoscape. The degrees method of cytoHubba was used to select important hub genes. Co-expression analysis was performed using “limma” package and Metascape for functional analysis. Univariate and multivariate Cox proportional hazards regression analyses were performed to construct a prognostic signature. Kaplan–Meier curve analysis, ROC curve analysis and Gene set enrichment analysis (GSEA) were also performed. Validation was executed by UALCAN, CCLE and HPA databases.Results: In total, 45 DEARGs were identified. Functional analysis showed that DEARGs were strikingly enriched in autophagy pathway. PPI network showed that CASP3 was the most central protein. CASP3 co-expression analysis revealed that co-expressed genes were mostly enriched in cell cycle. We identified a novel prognostic signature consisting of 3 genes (CDKN2A, PTK6 and GRID2). The risk score based on the prognostic signature was able to classify patients into high-risk and low-risk groups with significantly different overall survival. Furthermore, the prognostic signature is an independent prognostic predictor of survival and demonstrates superior prognostic performance compared with the clinicopathologic features for predicting 5-year survival. CDKN2A and PTK6 were further validated in UALCAN. GSEA suggested that the two genes played crucial roles in drug metabolism.Conclusion: Using bioinformatics analyses, we identified DEARGs and determined CDKN2A, PTK6 and DRID2 are tumor-associated genes and can be utilized as possible biomarkers in EC treatment.

scholarly journals Development of an Oxidative Phosphorylation-Related and Immune Microenvironment Prognostic Signature in Uterine Corpus Endometrial Carcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Jinhui Liu ◽  
Tian Chen ◽  
Min Yang ◽  
Zihang Zhong ◽  
Senmiao Ni ◽  
...  
Keyword(s):  
Overall Survival ◽  
Oxidative Phosphorylation ◽  
Endometrial Carcinoma ◽  
Cox Regression ◽  
Prognostic Signature ◽  
Immune Microenvironment ◽  
Uterine Corpus ◽  
Chemotherapy Drugs ◽  
Specific Subset ◽  
Lower Expression

Background: As the fourth most common malignant tumors in women, uterine corpus endometrial carcinoma (UCEC) requires novel and reliable biomarkers for prognosis prediction to improve the overall survival. Oxidative phosphorylation (OXPHOS) is found to be strongly correlated with the progression of tumor. Here, we aimed to construct an OXPHOS-related and immune microenvironment prognostic signature to stratify UCEC patients for optimization of treatment strategies.Method: Prognosis-associated OXPHOS-related differentially expressed genes were identified by multivariable Cox regression from TCGA–UCEC cohort. Based on the candidate genes, an OXPHOS-related prognostic signature was constructed by the train set data and verified by the entire set. When integrated with relevant clinical characteristics, a nomogram was also created for clinical application. Through comparison of tumor microenvironment between different risk groups, the underlying mechanism of the model and the inner correlation between immune microenvironment and energy metabolism were further investigated.Results: An OXPHOS-related signature containing ATP5IF1, COX6B1, FOXP3, and NDUFB11 was constructed and had better predictive ability compared with other recently published signatures in UCEC. Patients with lower risk score showed higher immune cell infiltration, higher ESTIMATE score (p = 2.808E−18), lower tumor purity (p = 2.808E−18), higher immunophenoscores (IPSs) (p < 0.05), lower expression of mismatch repair (MMR) proteins (p < 0.05), higher microsatellite instability (MSI), lower expression of markers of N6-methyladenosine (m6A) mRNA methylation regulators, higher tumor mutation burden (TMB) (p = 1.278E−9), and more sensitivity to immune checkpoint blockade (ICB) (p < 0.001) and chemotherapy drugs, thus, possessing improved prognosis.Conclusion: An OXPHOS-related and immune microenvironment prognostic signature classifying EC patients into different risk subsets was constructed in our study, which could be used to predict the prognosis of patients and help to select a specific subset of patients who might benefit from immunotherapy and chemotherapy, thus, improving the overall survival rate of UCEC. These findings may contribute to the discovery of novel and robust biomarkers or target therapy in UCEC and give new insights into the molecular mechanism of tumorigenesis and progression of UCEC.

scholarly journals Identification of an immune gene signature for predicting the prognosis of patients with uterine corpus endometrial carcinoma

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Cankun Zhou ◽  
Chaomei Li ◽  
Fangli Yan ◽  
Yuhua Zheng
Keyword(s):  
Endometrial Carcinoma ◽  
Immune Cell ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Immune Gene ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Uterine Corpus ◽  
Immune Genes

Abstract Background Uterine corpus endometrial carcinoma (UCEC) is a frequent gynecological malignancy with a poor prognosis particularly at an advanced stage. Herein, this study aims to construct prognostic markers of UCEC based on immune-related genes to predict the prognosis of UCEC. Methods We analyzed expression data of 575 UCEC patients from The Cancer Genome Atlas database and immune genes from the ImmPort database, which were used for generation and validation of the signature. We constructed a transcription factor regulatory network based on Cistrome databases, and also performed functional enrichment and pathway analyses for the differentially expressed immune genes. Moreover, the prognostic value of 410 immune genes was determined using the Cox regression analysis. We then constructed and verified a prognostic signature. Finally, we performed immune infiltration analysis using TIMER-generating immune cell content. Results The immune cell microenvironment as well as the PI3K-Akt, and MARK signaling pathways were involved in UCEC development. The established prognostic signature revealed a ten-gene prognostic signature, comprising of PDIA3, LTA, PSMC4, TNF, SBDS, HDGF, HTR3E, NR3C1, PGR, and CBLC. This signature showed a strong prognostic ability in both the training and testing sets and thus can be used as an independent tool to predict the prognosis of UCEC. In addition, levels of B cells and neutrophils were significantly correlated with the patient’s risk score, while the expression of ten genes was associated with immune cell infiltrates. Conclusions In summary, the ten-gene prognostic signature may guide the selection of the immunotherapy for UCEC.

scholarly journals Development and Clinical Validation of Novel 8-Gene Prognostic Signature Associated With the Proportion of Regulatory T Cells by Weighted Gene Co-Expression Network Analysis in Uterine Corpus Endometrial Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Jinhui Liu ◽  
Rui Geng ◽  
Sheng Yang ◽  
Fang Shao ◽  
Zihang Zhong ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Network Analysis ◽  
Endometrial Carcinoma ◽  
Risk Score ◽  
Immune Status ◽  
Low Risk ◽  
Prognostic Signature ◽  
Uterine Corpus ◽  
Risk Patients

BackgroundUterine corpus endometrial carcinoma (UCEC) is a gynecological malignant tumor with low survival rate and poor prognosis. The traditional clinicopathological staging is insufficient to estimate the prognosis of UCEC. It is necessary to select a more effective prognostic signature of UCEC to predict the prognosis and immunotherapy effect of UCEC.MethodsCIBERSORT and weighted correlation network analysis (WGCNA) algorithms were combined to screen modules related to regulatory T (Treg) cells. Subsequently, univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were used to identify the genes in key modules. The difference in overall survival (OS) between high- and low-risk patients was analyzed by Kaplan–Meier analysis. The Tregs-related risk signature (TRRS) was screened by uni- and multivariate Cox analyses. Afterward, we analyzed the expression difference of TRRS and verified its ability to predict the prognosis of UCEC and the effect of immunotherapy.ResultsRed module has the highest correlation with Tregs among all clustered modules. Pathways enrichment indicated that the related processes of UCEC were primarily associated to the immune system. Eight genes (ZSWIM1, NPRL3, GOLGA7, ST6GALNAC4, CDC16, ITPK1, PCSK4, and CORO1B) were selected to construct TRRS. We found that this TRRS is a significantly independent prognostic factor of UCEC. Low-risk patients have higher overall survival than high-risk patients. The immune status of different groups was different, and tumor-related pathways were enriched in patients with higher risk score. Low-risk patients are more likely take higher tumor mutation burden (TMB). Meanwhile, they are more sensitive to chemotherapy than patients with high-risk score, which indicated a superior prognosis. Immune checkpoints such as PD-1, CTLA4, PD-L1, and PD-L2 all had a higher expression level in low-risk group. TRRS expression really has a relevance with the sensitivity of UCEC patients to chemotherapeutic drugs.ConclusionWe developed and validated a TRRS to estimate the prognosis and reflect the immune status of UCEC, which could accurately assess the prognosis of patients with UCEC and supply personalized treatments for them.

scholarly journals Identification of an immune gene signature for predicting the prognosis of patients with uterine corpus endometrial carcinoma

2020 ◽  
Author(s):  
Cankun Zhou ◽  
Chaomei Li ◽  
Fangli Yan ◽  
Yuhua Zheng
Keyword(s):  
Endometrial Carcinoma ◽  
Immune Cell ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Immune Gene ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Uterine Corpus ◽  
Immune Genes

Abstract Background: Uterine corpus endometrial carcinoma (UCEC) is a frequent gynecological malignancy with a poor prognosis particularly at an advanced stage. Herein, this study aims to construct prognostic markers of UCEC based on immune-related genes to predict the prognosis of UCEC.Methods: We analyzed expression data of 575 UCEC patients from The Cancer Genome Atlas database and immune genes from the ImmPort database, which were used for generation and validation of the signature. We constructed a transcription factor regulatory network based on Cistrome databases, and also performed functional enrichment and pathway analyses for the differentially expressed immune genes. Moreover, the prognostic value of 410 immune genes was determined using the Cox regression analysis. We then constructed and verified a prognostic signature. Finally, we performed immune infiltration analysis using TIMER-generating immune cell content.Results: The immune cell microenvironment as well as the PI3K-Akt, and MARK signaling pathways were involved in UCEC development. The established prognostic signature revealed a ten-gene prognostic signature, comprising of PDIA3, LTA, PSMC4, TNF, SBDS, HDGF, HTR3E, NR3C1, PGR, and CBLC. This signature showed a strong prognostic ability in both the training and testing sets and thus can be used as an independent tool to predict the prognosis of UCEC. In addition, levels of B cells and neutrophils were significantly correlated with the patient's risk score, while the expression of ten genes was associated with immune cell infiltrates.Conclusions: In summary, the ten-gene prognostic signature may guide the selection of the immunotherapy for UCEC.

Immunocytochemical localization of β1-4 galactosyltransferase in endometrial carcinoma cells

1990 ◽  
Vol 48 (3) ◽  
pp. 944-945
Author(s):  
Ichiro Yamamoto ◽  
Toshiaki Tachibana ◽  
Hiroko Maruyama ◽  
Noriyuki Komatsu ◽  
Hiroyuki Kuramoto ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Cell Lines ◽  
Endometrial Adenocarcinoma ◽  
Protein A ◽  
Rabbit Antiserum ◽  
Carcinoma Cells ◽  
Affinity Column ◽  
Antibody Technique ◽  
Galactosyl Transferase ◽  
C Terminus

We have paid attention to the alteration of glycosyltransferase in carcinoma cells, because it might be related to the malignancy of the cells. In this connection, localization of β1-4 galactosyl transferase (β1-4 Gal T) in human endometrial carcinoma cells was examined immunocytochemically using two kinds of cell lines, each of which showed different degree of differentiation.An antibody was purified from the rabbit antiserum against the synthetic peptide, IFNRLVFRGMSC (W89) of human β1-4 Gal T coupled with KLH (keyhole limpet hemocyanine) by protein A column and peptide-affinity column chromatography. The anti-W89 serum reacts to the C-terminus of human β 1-4 Gal T and to both membrane-bound and soluble forms of the enzyme. Cell line of well differentiated endometrial adenocarcinoma (I) and that of poorly differentiated endometrial adenocarcinoma (50B) were cultivated respectively in MEM medium containing 15% FCS and 2 mM glutamine for 4 d at 37°C under 5% CO2. The cells were fixed in a mixture of 4% paraformaldehyde and 0.1% glutaraldehyde in 0.1 M Soerensen’s phosphate buffer (pH 7.4) at 4°C for 30 min, washed with PBS, then freezed and thawed. The indirect method of the peroxidase- labeled antibody technique was used for immunocytochemistry of both LM and TEM on the cell lines. The cells were dehydrated in ethanol and embedded in TAAB 812. Ultrathin sections were observed under a TEM, JEM-100S.

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