scholarly journals The Pyroptosis-Related Signature Predicts Prognosis in Uterine Corpus Endometrial Carcinoma

2021 ◽  
Author(s):  
Mengjun Zhang ◽  
Siyu Hou ◽  
Jialin Wang ◽  
Haodi Yue
Keyword(s):  
Gene Expression ◽  
Endometrial Carcinoma ◽  
Risk Score ◽  
Clinical Characteristics ◽  
Molecular Mechanisms ◽  
Evaluation Model ◽  
Clinical Prognosis ◽  
Prognostic Evaluation ◽  
Uterine Corpus ◽  
Model Based

Abstract Background: Uterine Corpus Endometrial Carcinoma (UCEC) is difficult to evaluate the prognosis. The prognostic evaluation model based on pyroptosis-related genes (PRGs) has shown good predictive power for prognosis in tumors, but there is no relevant research in UCEC. Methods: Based on the gene expression data and clinical prognosis information of UCEC patients from TCGA database, PRGs related to the prognosis were screened out. Based on PRGs, a prognostic evaluation model related was established. Comprehensive analysis of clinical characteristics and prognosis was performed. The potential molecular mechanisms of the prognostic evaluation model was explored by GSEA. The relationship between the prognostic evaluation model and the tumor immune microenvironment (TIME) was delved. Results: 4 key PRGs related to the prognosis (NLRP2, GSDME, NOD2, GPX4) were identified. A prognostic evaluation model based on these 4 key PRGs was established: Riskscore= (0.4323) * GPX4 + (0.2385) * GSDME + (0.0525) * NLRP2 + (-0.3299) * NOD2. A higher risk score was an independent risk factor for the prognosis and closely related to clinical characteristics. The gene expression of the high-risk group was mainly enriched in immune response. The higher risk score was closely related to the degree of immune cell infiltration and the gene expression level of immune checkpoints. Conclusion: The prognostic evaluation model based on 4 key PRGs (NLRP2, GSDME, NOD2 and GPX4) has certain value for the prognosis evaluation and treatment selection of UCEC patients and may affect the prognosis by regulating the TIME.

scholarly journals Establishment of an Autophagy-Related Clinical Prognosis Model for Predicting the Overall Survival of Osteosarcoma

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Jianyi Li ◽  
Xiaojie Tang ◽  
Yukun Du ◽  
Jun Dong ◽  
Zheng Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Molecular Mechanisms ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Data Set ◽  
Primary Tumor Site ◽  
Clinical Prognosis

Purpose. Osteosarcoma is the most common primary and highly invasive bone tumor in children and adolescents. The purpose of this study is to construct a multi-gene expression feature related to autophagy, which can be used to predict the prognosis of patients with osteosarcoma. Materials and methods. The clinical and gene expression data of patients with osteosarcoma were obtained from the target database. Enrichment analysis of autophagy-related genes related to overall survival (OS-related ARGs) screened by univariate Cox regression was used to determine OS-related ARGs function and signal pathway. In addition, the selected OS-related ARGs were incorporated into multivariate Cox regression to construct prognostic signature for the overall survival (OS) of osteosarcoma. Use the dataset obtained from the GEO database to verify the signature. Besides, gene set enrichment analysis (GSEA) were applied to further elucidate the molecular mechanisms. Finally, the nomogram is established by combining the risk signature with the clinical characteristics. Results. Our study eventually included 85 patients. Survival analysis showed that patients with low riskScore had better OS. In addition, 16 genes were included in OS-related ARGs. We also generate a prognosis signature based on two OS-related ARGs. The signature can significantly divide patients into low-risk groups and high-risk groups, and has been verified in the data set of GEO. Subsequently, the riskScore, primary tumor site and metastasis status were identified as independent prognostic factors for OS and a nomogram were generated. The C-index of nomogram is 0.789 (95% CI: 0.703~0.875), ROC curve and calibration chart shows that nomogram has a good consistency between prediction and observation of patients. Conclusions. ARGs was related to the prognosis of osteosarcoma and can be used as a biomarker of prognosis in patients with osteosarcoma. Nomogram can be used to predict OS of patients and improve treatment strategies.

scholarly journals Comprehensive analyses reveal three-gene signatures in ovarian cancer

2020 ◽  
Author(s):  
Chuang Li ◽  
Yuan Lyu ◽  
Caixia Liu
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Molecular Mechanisms ◽  
Hub Genes ◽  
Clinical Prognosis ◽  
Gene Signatures ◽  
Cancer Tissues ◽  
Differently Expressed Genes

Abstract Background: Ovarian cancer is a common cancer that affects the quality of women’s life. With the limitation of the early diagnosis of the disease, ovarian cancer has a high mortality rate worldwide. However, the molecular mechanisms underlying tumor invasion, proliferation, and metastasis in ovarian cancer remain unclear. We aimed to identify, using bioinformatics, important genes and pathways that may serve crucial roles in the prevention, diagnosis, and treatment of ovarian cancer. Methods: Three microarray datasets (GSE14407, GSE36668, and GSE26712) were selected for whole-genome gene expression profiling , and differentially expressed genes were identified between normal and ovarian cancer tissues. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using DAVID. Additionally, a protein-protein interaction network was constructed to reveal possible interactions among the differently expressed genes. The prognostic values of the hub genes were investigated using Gene Expression Profiling Interactive Analysis (GEPIA) and the KM plotter database. Meanwhile, the mRNA expression analysis of the hub genes was performed using the GEPIA database. Results: We obtained 247 upregulated and 530 downregulated differently expressed genes, and 52 hub genes in the significant gene modules. Enrichment analysis revealed that the hub genes were significantly ( P < 0.05) associated with proliferation. Additionally, BIRC5, CXCL13, and PBK were revealed to be significantly associated with the clinical prognosis of patients with ovarian cancer. Immunohistochemical staining results obtained from the Human Protein Atlas revealed that BIRC5, PBK, and CXCL13 were highly expressed in ovaria cancer tissues. Conclusion Three-gene signatures ( BIRC5, CXCL13 , and PBK ) are associated with the occurrence, development, and prognosis of OC, and may therefore serve as biological markers of the disease.

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 ◽  
Risk Score ◽  
Prognostic Model ◽  
Immune Cell ◽  
Gene Signature ◽  
Cancer Genome ◽  
Functional Enrichment ◽  
Immune Gene ◽  
Uterine Corpus ◽  
Immune Genes

Abstract Background: Uterine corpus endometrial carcinoma (UCEC) is a frequent gynecological malignancy with a poor prognosis especially when at an advanced stage. In the present study, we explored the potential of an immune-related gene signature to predict overall survival in UCEC patients.Methods: We analyzed expression data of 616 UCEC patients from The Cancer Genome Atlas database and the International Cancer Genome Consortium as well as immune genes from the ImmPort database and identified the signature. We constructed a transcription factor regulatory network based on Cistrome databases and performed functional enrichment and pathway analyses for the differentially expressed immune genes. Moreover, the prognostic value of 410 immune genes was determined using Cox regression analysis then constructed a prognostic model. Finally, we performed immune infiltration analysis using TIMER-generating immune cell content.Results: Results indicated that the immune cell microenvironment as well as the PI3K-Akt, and MARK signaling pathways were involved in UCEC development. The established prognostic model revealed a ten-gene prognosis signature , comprising PDIA3, LTA, PSMC4, TNF, SBDS, HDGF, HTR3E, NR3C1, PGR, and CBLC . This can be used as an independent tool to predict the prognosis of UCEC owing to the observed risk-score. In addition, levels of B cells and neutrophils were significantly correlated with the patient's risk score, and the expression of ten genes is associated with immune cell infiltrates.Conclusions: In summary, we present a 10-gene signature with the potential to predict the prognosis of UCEC. This is expected to guide future development of individualized treatment approaches.

scholarly journals RNF183 Is a Prognostic Biomarker and Correlates With Tumor Purity, Immune Infiltrates in Uterine Corpus Endometrial Carcinoma

2020 ◽  
Vol 11 ◽  
Author(s):  
Rong Geng ◽  
Yuhua Zheng ◽  
Lijie Zhao ◽  
Xiaobin Huang ◽  
Rong Qiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Endometrial Cancer ◽  
Endometrial Carcinoma ◽  
Progression Free Survival ◽  
M2 Macrophage ◽  
Free Survival ◽  
Uterine Corpus ◽  
Immune Infiltration ◽  
Tumor Purity ◽  
High Level

RNF183, a member of the E3 ubiquitin ligase, has been shown to involve in carcinogenesis and proposed as one of the biomarkers in Uterine Corpus Endometrial Carcinoma (UCEC). However, no research focused on the role of RNF183 in UCEC. We analyzed the expression and immune infiltration of RNF183 in UCEC. TIMER, UALCAN, and GEPIA were used to analyze the gene expression of RNF183. We emplored Kaplan-Meier Plotter to examine the overall survival and progression-free survival of RNF183, and applied GeneMANIA to identify RNF183-related functional networks. LinkedOmics was helpful to identify the differential gene expression of RNF183, and to further analyze gene ontology and the genome pathways in the Kyoto Protocol. Finally, we used TIMER to investigate the immune infiltration of RNF183 in UCEC. Otherwise, we partly verified the results of bioinformatics analysis that RNF183 controlled ERα expression in ERα-positive Ishikawa cells dependent on its RING finger domain. We also found that ERα increased the stability of RNF183 through the post-translational mechanism. Together, patients with a high level of RNF183 harbor favorable overall and progression-free survival. High expression of RNF183 was associated with a low stage, endometrioid, and TP53 Non-Mutant status in endometrial cancer. The RNF183 expression was greater at higher expression and the tumor stage was greater at the lower level. On the side of immunization, high level of RNF183 in UCEC is negatively related to tumor purity, infiltrating levels of CD4 + T cells, neutrophils, and dendritic cells. Besides, the expression of RNF183 in UCEC is significantly correlated with the expression of several immune cell markers, including B cell, M1 macrophage marker, M2 Macrophage, Dendritic cell, Th1 markers, Th2 markers, Treg markers, and T cell exhaustion markers, indicating its role in regulating tumor immunity. These results suggested that RNF183 may be considered as a novel prognostic factor in endometrial cancer and an early diagnostic indicator for patients with UCEC.

scholarly journals Identification of the prognostic value of a 2-gene signature of the WNT gene family in UCEC using bioinformatics and real-world data

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuexin Hu ◽  
Mingjun Zheng ◽  
Dandan Zhang ◽  
Rui Gou ◽  
Ouxuan Liu ◽  
...  
Keyword(s):  
Gene Family ◽  
Endometrial Carcinoma ◽  
Clinical Features ◽  
Risk Score ◽  
Real World ◽  
Prognostic Value ◽  
Gene Signature ◽  
Real World Data ◽  
Uterine Corpus ◽  
World Data

Abstract Background The WNT gene family plays an important role in the occurrence and development of malignant tumors, but its involvement has not been systematically analyzed in uterine corpus endometrial carcinoma (UCEC). This study aimed to evaluate the prognostic value of the WNT gene family in UCEC. Methods Pan-cancer transcriptome data of the UCSC Xena database and Genotype-Tissue Expression (GTEx) normal tissue data were downloaded to analyze the expression and prognosis of 19 WNT family genes in UCEC. A cohort from The Cancer Genome Atlas-Uterine Corpus Endometrial Carcinoma (TCGA-UCEC) was used to analyze the expression of the WNT gene family in different immune subtypes and clinical subgroups. The STRING database was used to analyze the interaction of the WNT gene family and its biological function. Univariate Cox regression analysis and Lasso cox analysis were used to identify the genes associated with significant prognosis and to construct multi signature prognosis model. An immunohistochemical assay was used to verify the predictive ability of the model. Risk score and the related clinical features were used to construct a nomogram. Results The expression levels of WNT2, WNT3, WNT3A, WNT5A, WNT7A, and WNT10A were significantly different among different immune subtypes and correlated with TP53 mutation. According to the WNT family genes related to the prognosis of UCEC, UCEC was classified into two subtypes (C1, C2). The prognosis of subtype C1 was significantly better than that of subtype C2. A 2-gene signature (WNT2 and WNT10A) was constructed and the two significantly prognostic groups can be divided based on median Risk score. These results were verified using real-world data, and the nomogram constructed using clinical features and Risk score had good prognostic ability. Conclusions The 2-gene signature including WNT2 and WNT10A can be used to predict the prognosis of patients with UCEC, which is important for clinical decision-making and individualized therapy for patients with UCEC.

scholarly journals Mesonephric Adenocarcinoma Arising From The Uterine Corpus：Case Reports and Literature Review

2020 ◽  
Author(s):  
Qian HU ◽  
Qin Xu ◽  
Yan Chun Deng ◽  
Tao Guo ◽  
Li Xiu Wu
Keyword(s):  
Clinical Characteristics ◽  
Uterine Wall ◽  
University Hospital ◽  
Molecular Characteristics ◽  
Clinical Prognosis ◽  
Uterine Corpus ◽  
Kaplan Meier ◽  
Mesonephric Adenocarcinoma ◽  
The One ◽  
Mesonephric Carcinoma

Abstract Background Mesonephric adenocarcinoma (MNAC) is a rare carcinoma which arises from the mesonephric remnant of the gynecologic tract. It mainly occurs in the uterine cervix, barely locates in the uterine corpus, ovarian and vagina. To date, only a few cases of MNAC arising from of the uterine body (UB-MNAC) have been reported, and the clinicopathologic and molecular characteristics of UB-MNAC remain limited. A recent report suggested that series of UB-MNAC should be defined as Mesonephric-like adenocarcinoma carcinomas (MLAC), for they exhibited the classic morphologic features and immunophenotype of mesonephric carcinoma, but occurring outside of the cervix and without convincing mesonephric remnants. Thus, the histogenesis of UB-MNAC is not yet clear, they may originate in Müllerian tissue and exhibits the mesonephric differentiation phenotype, or arise from the mesonephric remnants in the uterine wall.Case presentation To better understand the histogenesis of UB-MNAC, we presented three UB-MNAC cases from west china second university hospital, which exhibited typical morphologic, histologic as well as the immunohistochemical characteristics of MNAC. Notably, among the three cases, two cases arising from the myometrium layer of the uterine corpus found mesonephric remnants around the tumor. By reviewing the published UB-MNAC and UB-MLAC, we found that to our knowledge ,it is the first time finding mesonephric remnants around the MNAC cells in the reported literature, except one case that found mesonephric remnants in the cervix, and the tumors of the three cases were all arising from the myometrium layer, without endometrium involved. Then we compared the clinical characteristics of the UB-MNAC cases arising from the myometrium and endometrium, and the results showed that the two subgroups had most in common in the clinical characteristics except the myometrium subgroup had a higher elevated CA125 level, and this result was in consistent with the Kaplan-Meier survival analysis, which indicated that the myometrium subgroup had a poorer prognosis than the endometrium group. But this need more data and further study such as the molecular analysis.Conclusion Though the pathogenesis of MLAC or MNAC of the uterine corpus is still under debate, according to our cases and the published literatures, We hypothesize two different pathways involved: the MNAC arising from the myometrium not affecting the endometrium may directly develop from the mesonephric remnant, the one occurred in the endometrium may not real mesonephric adenocarcinoma, but more likely arising from mesonephric transformation of Müllerian adenocarcinoma, and is better referred as MLAC. Besides, the two kinds of adenocarcinomas may have different clinical prognosis, while the MNAC arising from the myometrium may have a poorer prognosis than the MLAC originating from the endometrium, although they have identical morphologic and histologic characteristics.

scholarly journals Analysis of the Expression and Prognostic Potential of a Novel Metabolic Regulator ANGPTL8/Betatrophin in Human Cancers

2021 ◽  
Vol 27 ◽  
Author(s):  
Fangfang Xu ◽  
Dandan Tian ◽  
Xiaoyang Shi ◽  
Kai Sun ◽  
Yuqing Chen
Keyword(s):  
Gene Expression ◽  
Cell Carcinoma ◽  
Endometrial Carcinoma ◽  
Signaling Pathway ◽  
Glucose Homeostasis ◽  
Prognostic Value ◽  
Clear Cell ◽  
Cholesterol Metabolism ◽  
Uterine Corpus ◽  
Human Cancers

The angiopoietin-like protein (ANGPTL) family members, except for the novel atypical member ANGPTL8/betatrophin, have been reported to participate in angiogenesis, inflammation and cancer. ANGPTL8/betatrophin is a metabolic regulator that is involved in lipid metabolism and glucose homeostasis. However, little is known about the expression and prognostic value of ANGPTL8/betatrophin in human cancers. In this study, we first conducted detailed analyses of ANGPTL8/betatrophin expression in cancer/normal samples via the Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA), DriverDBv3, ENCORI and UALCAN databases. ANGPTL8/betatrophin showed high tissue specificity (enriched in the liver) and cell-type specificity (enriched in HepG2 and MCF7 cell lines). More than one databases demonstrated that the gene expression of ANGPTL8/betatrophin was significantly lower in cholangiocarcinoma (CHOL), breast invasive carcinoma (BRCA), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), uterine corpus endometrial carcinoma (UCEC), and significantly higher in kidney renal clear cell carcinoma (KIRC) compared with that in normal samples. However, the protein expression of ANGPTL8/betatrophin displayed opposite results in clear cell renal cell carcinoma (ccRCC)/KIRC. Based on the expression profiles, the prognostic value was evaluated with the GEPIA, DriverDBv3, Kaplan Meier plotter and ENCORI databases. Two or more databases demonstrated that ANGPTL8/betatrophin significantly affected the survival of KIRC, uterine corpus endometrial carcinoma (UCEC), pheochromocytoma and paraganglioma (PCPG) and sarcoma (SARC); patients with PCPG and SARC may benifit from high ANGPTL8/betatrophin expression while high ANGPTL8/betatrophin expression was associated with poor prognosis in KIRC and UCEC. Functional analyses with the GeneMANIA, Metascape and STRING databases suggested that ANGPTL8/betatrophin was mainly involved in lipid homeostasis, especially triglyceride and cholesterol metabolism; glucose homeostasis, especially insulin resistance; AMPK signaling pathway; PI3K/Akt signaling pathway; PPAR signaling pathway; mTOR signaling pathway; HIF-1 signaling pathway; autophagy; regulation of inflammatory response. ANGPTL8/betatrophin may be a promising prognostic biomarker and therapeutic target, thus providing evidence to support further exploration of its role in defined human cancers.

scholarly journals Identification of the Prognostic LncRNA Biomarkers and Comprehensive Analysis of LncRNA-Mediated ceRNA Network for Uterine Corpus Endometrial Carcinoma

2021 ◽  
Author(s):  
Yiran Cai ◽  
Jin Cui ◽  
Huiqun Wu
Keyword(s):  
Regression Analysis ◽  
Endometrial Carcinoma ◽  
Noncoding Rna ◽  
Molecular Mechanisms ◽  
Cox Regression ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis ◽  
Uterine Corpus ◽  
Cerna Network

Abstract Background Given that long non-coding RNAs (lncRNAs) involved in the tumor initiation or progression of the endometrium and that competing endogenous RNA (ceRNA) plays an important role in increasingly more biological processes, lncRNA-mediated ceRNA is likely to function in the pathogenesis of uterine corpus endometrial carcinoma (UCEC). Our present study aimed to explore the potential molecular mechanisms for the prognosis of UCEC through an lncRNA-mediated ceRNA network. Methods The transcriptome profiles and corresponding clinical profiles of UCEC dataset were retrieved from CPTAC and TCGA databases respectively. Differentially expressed genes (DEGs) in UCEC samples were identified via “Edge R” package. Then, an integrated bioinformatics analysis including functional enrichment analysis, tumor infiltrating immune cell(TIIC) analysis, Kaplan-Meier curve, Cox regression analysis were conducted to analyze the prognostic biomarkers. Results In the CPTAC dataset of UCEC, a ceRNA network comprised of 36 miRNAs, 123 lncRNAs and 124 targeted mRNAs was established, and 8 of 123 prognostic-related DElncRNAs(Differentially Expressed long noncoding RNA) were identified. While in the TCGA dataset, a ceRNA network comprised of 38 miRNAs, 83 lncRNAs and 110 targeted mRNAs was established, and 2 of 83 prognostic-related DElncRNAs were identified. After filtered by risk grouping and Cox regression analysis, 10 prognostic-related lncRNAs including LINC00443, LINC00483, C2orf48, TRBV11-2, MEG-8 were identified. In addition, 33 survival-related DEmRNAs(Differentially Expressed messager RNA) in two ceRNA networks were further validated in the HPA database. Finally, six lncRNA/miRNA/mRNA axes were established to elucidate prognostic regulatory roles in UCEC. Conclusion Several prognostic lncRNAs are identified and prognostic model of lncRNA-mediated ceRNA network is constructed, which promotes the understanding of UCEC development mechanisms and potential therapeutic targets.

scholarly journals Genetic expression and mutation profile analysis in different pathologic stages of hepatocellular carcinoma patients

2020 ◽  
Author(s):  
Xingjie Gao ◽  
Chunyan Zhao ◽  
Xiaoteng Cui ◽  
Nan Zhang ◽  
Yuanyuan Ren ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Molecular Mechanisms ◽  
Cohort Analysis ◽  
Interaction Network ◽  
Principal Component ◽  
High Expression ◽  
Clinical Prognosis ◽  
Synonymous Mutations ◽  
Mutation Profile

Abstract Background: The expression and mutation of multiple genes are involved in the complicated mechanism regarding the occurrence and development of hepatocellular carcinoma (HCC). The clinical pathological stage of HCC is closely linked to clinical prognosis of liver cancer. This study aims at analyzing the gene expression and mutation profile of different clinical pathological stages of HCC (stage I, II, III-IV), based on 367 HCC cases included in TCGA cohort.Results: We identified a series of targeting genes with copy number variation (CNV), which is statistically associated with gene expression. For instance, compared withthe normal group, CCNE2 gene is highly expressed in the tumor group and specificstage I group, which are associated withthree CNV types of single deletion, single gain, and amplification mutations. Protein interaction network construction and followed "Molecular Complex Detection" analysis indicated that the high expression of some cell cycle-related genes in HCC, such as TTK, CDC20, ASPM, is positively correlated with CNV. Non-synonymous mutations mainly existed in some genes, such as TTN, TP53, CTNNB1, MUC16, andALB, however, we did not observe the association between thegene mutation frequency and the clinical pathological grade distribution. The rs121913396 and rs121913400 polymorphisms withintheCTNNB1 gene were associated with the high expression of CTNNB1 protein, but not linked to the clinical prognosis of HCC. We performed the random forest and decision tree approachesfor the modeling analysis and identified a group of genes related to different HCC pathological grades, such as the lowly expressed VIPR1, FAM99A, and GNA14 genes, or highly expressed CEP55, SEMA3F, and PRR11. Moreover, we conducted a principal component analysis (PCA) to obtain several genes associated with different pathological grades, including SLC27A5, ADAM17, SNRPA, SNRPD2, and ALDH2. Finally, we confirmed the highly expressed GAS2L3, SNRPA, SNRPD2 genes in the HCC tissues, for the first time, through a Chinese HLivH060PG02 cohort analysis.Conclusions: The identification of the targeting genes, including GAS2L3, SNRPA, SNRPD2, provides insight into the molecular mechanisms associated with different prognosis of HCC.

scholarly journals Identification of TNFRSF4 as a Diagnosis and Prognosis Biomarker Associated with Immune Microenvironment in Uterine Corpus Endometrial Carcinoma

2021 ◽  
Author(s):  
Heng Ma ◽  
Penghui Feng ◽  
Shuangni Yu ◽  
Ruiqin Han ◽  
Zaixin Guo ◽  
...  
Keyword(s):  
T Cells ◽  
Endometrial Carcinoma ◽  
Molecular Mechanisms ◽  
Cox Regression ◽  
Functional Enrichment ◽  
Prognostic Biomarkers ◽  
Clinical Samples ◽  
Immune Microenvironment ◽  
Uterine Corpus ◽  
Diagnosis And Prognosis

Abstract BackgroundThe interaction between tumor microenvironment (TME) and tumors offers various targets in mounting anti-tumor immunotherapies. However, the diagnostic and prognostic biomarkers in uterine corpus endometrial carcinoma (UCEC) are still limited. Here, we aimed to analyze the TME features and identify novel prognostic biomarkers for UCEC. MethodsESTIMATE, CIBERSORT, protein-protein interaction (PPI) network, univariate Cox regression, and functional enrichment analysis were performed to identify immune- and survival-related hub genes as well as possible molecular mechanisms. The limma package and the deconvolution algorithm were adopted to estimate the tumor-infiltrating immune cells (TICs) abundance and their relationship with the target gene. Tissue microarrays (TMAs) of UCEC were evaluated to validate protein expression of the identified immune markers, including TNFRSF4, CD4, and CD8. The receiver operating characteristic (ROC) curve was used to determine the efficacy of TNFRSF4 in diagnosing UCEC. ResultsTwo genes, TNFRSF4 and S1PR4, were screened out from 386 intersection differential expression gene (DEGs) shared by ImmuneScore and StromalScore in UCEC. Highlighted by TNFRSF4, we found that it was not only positively correlated with the TICs (mainly CD4+ T cells, CD8+ T cells, and Tregs) but significantly related to diagnosis and prognosis in patients of UCEC, both verified by data from the TCGA database and clinical samples. ConclusionsCollectively, TNFRSF4 could serve as a high-profile biomarker to robustly predict immune microenvironment, clinical diagnosis and prognosis for UCEC.

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