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Uterine corpus endometrial carcinoma (UCEC) is one of the most common tumours of the female reproductive system. CCAAT enhancer-binding protein alpha (CEBPA) is a member of the transcription factor family involved in regulating processes such as cell proliferation, differentiation, metabolism, and the immune response. However, the role of CEBPA in UCEC has not been clarified. Here, we performed a comprehensive analysis to explore the expression level, prognostic value, immune infiltration and biological function of CEBPA in UCEC. In this study, we found that CEBPA expression was upregulated and associated with poor prognosis in UCEC patients. KEGG and GO analyses revealed that the genes positively correlated with CEBPA were enriched primarily in immune regulation and oxidative phosphorylation. Immune infiltration analysis revealed that CEBPA is strongly correlated with immune cell infiltration in UCEC. RT-qPCR indicated that CEBPA may regulate the OXPHOS level in Ishikawa cells. CCK-8, cell cycle, Transwell and scratch wound healing assays revealed that CEBPA promoted Ishikawa cell proliferation, invasion and migration. In addition, PPI and survival analyses suggested that CEBPG may be a potential target of CEBPA in UCEC. These results demonstrated that CEBPA may be a potential therapeutic target in UCEC. [ABSTRACT FROM AUTHOR]

Abstract Uterine corpus endometrial carcinoma (UCEC) is one of the most common tumours of the female reproductive system. CCAAT enhancer-binding protein alpha (CEBPA) is a member of the transcription factor family involved in regulating processes such as cell proliferation, differentiation, metabolism, and the immune response. However, the role of CEBPA in UCEC has not been clarified. Here, we performed a comprehensive analysis to explore the expression level, prognostic value, immune infiltration and biological function of CEBPA in UCEC. In this study, we found that CEBPA expression was upregulated and associated with poor prognosis in UCEC patients. KEGG and GO analyses revealed that the genes positively correlated with CEBPA were enriched primarily in immune regulation and oxidative phosphorylation. Immune infiltration analysis revealed that CEBPA is strongly correlated with immune cell infiltration in UCEC. RT-qPCR indicated that CEBPA may regulate the OXPHOS level in Ishikawa cells. CCK-8, cell cycle, Transwell and scratch wound healing assays revealed that CEBPA promoted Ishikawa cell proliferation, invasion and migration. In addition, PPI and survival analyses suggested that CEBPG may be a potential target of CEBPA in UCEC. These results demonstrated that CEBPA may be a potential therapeutic target in UCEC.

Abstract Background Dachsous cadherin related 1 (DCHS1) is one of calcium-dependent adhesion membrane proteins and is mainly involved in the development of mammalian tissues. There is a lack of more detailed research on the biological function of DCHS1 in pan-cancer. Materials and methods We evaluated the expression, the prognostic value, the diagnostic value and genomic alterations of DCHS1 by using the databases, including TCGA, UALCAN, HPA, GEPIA2.0 and GSCA. We employed the databases of UCSC, TIMER2.0, TISIDB, GSCA to analyze the association between DCHS1 expression and the immune microenvironment, stemness, TMB, MSI and anticancer drug sensitivity. BioGRID, STRING and GEPIA2.0 were used to perform protein interaction and functional enrichment analysis. Real-time quantitative PCR, CCK8, Transwell assay and Western blot were performed to determine the function of DCHS1 in UCEC. Results DCHS1 is differentially expressed in many cancers and its expression is significantly associated with tumor prognosis and diagnosis. DCHS1 expression was significantly correlated with the infiltration of cancer-associated fibroblasts (CAFs), Endothelial cell (ECs), and Hematopoietic stem cell in most cancers. In addition, DCHS1 was significantly associated with sensitivity to many antitumor drugs. Functional enrichment analysis revealed that DCHS1-related proteins were involved in Focal adhesion, Endometrial cancer and Wnt signaling pathway. GSEA results showed that DCHS1 was related to epithelial-mesenchymal transition (EMT) in many cancers. In vitro experiments in UCEC showed that DCHS1 regulated cell proliferation, migration and EMT. Conclusions Our findings indicated that DCHS1 might be a novel prognostic and diagnostic biomarker and immunotherapy target, and plays an important role in the proliferation, migration and EMT in UCEC.

Abstract Background Given the significant role of immune-related genes in uterine corpus endometrial carcinoma (UCEC) and the long-term outcomes of patients, our objective was to develop a prognostic risk prediction model using immune-related genes to improve the accuracy of UCEC prognosis prediction. Methods The Limma, ESTIMATE, and CIBERSORT methods were used for cluster analysis, immune score calculation, and estimation of immune cell proportions. Univariate and multivariate analyses were utilized to develop a prognostic risk model for UCEC. Risk model scores and nomograms were used to evaluate the models. String constructs a protein-protein interaction (PPI) network of genes. The qRT-PCR, immunofluorescence, and immunohistochemistry (IHC) all confirmed the genes. Results Cluster analysis divided the immune-related genes into four subtypes. 33 immune-related genes were used to independently predict the prognosis of UCEC and construct the prognosis model and risk score. The analysis of the survival nomogram indicated that the model has excellent predictive ability and strong reliability for predicting the survival of patients with UCEC. The protein-protein interaction network analysis of key genes indicates that four genes play a pivotal role in interactions: GZMK, IL7, GIMAP, and UBD. The quantitative real-time polymerase chain reaction (qRT-PCR), immunofluorescence, and immunohistochemistry (IHC) all confirmed the expression of the aforementioned genes and their correlation with immune cell levels. This further revealed that GZMK, IL7, GIMAP, and UBD could potentially serve as biomarkers associated with immune levels in endometrial cancer. Conclusion The study identified genes related to immune response in UCEC, including GZMK, IL7, GIMAP, and UBD, which may serve as new biomarkers and therapeutic targets for evaluating immune levels in the future.

Background: Dachsous cadherin related 1 (DCHS1) is one of calcium-dependent adhesion membrane proteins and is mainly involved in the development of mammalian tissues. There is a lack of more detailed research on the biological function of DCHS1 in pan-cancer. Materials and methods: We evaluated the expression, the prognostic value, the diagnostic value and genomic alterations of DCHS1 by using the databases, including TCGA, UALCAN, HPA, GEPIA2.0 and GSCA. We employed the databases of UCSC, TIMER2.0, TISIDB, GSCA to analyze the association between DCHS1 expression and the immune microenvironment, stemness, TMB, MSI and anticancer drug sensitivity. BioGRID, STRING and GEPIA2.0 were used to perform protein interaction and functional enrichment analysis. Real-time quantitative PCR, CCK8, Transwell assay and Western blot were performed to determine the function of DCHS1 in UCEC. Results: DCHS1 is differentially expressed in many cancers and its expression is significantly associated with tumor prognosis and diagnosis. DCHS1 expression was significantly correlated with the infiltration of cancer-associated fibroblasts (CAFs), Endothelial cell (ECs), and Hematopoietic stem cell in most cancers. In addition, DCHS1 was significantly associated with sensitivity to many antitumor drugs. Functional enrichment analysis revealed that DCHS1-related proteins were involved in Focal adhesion, Endometrial cancer and Wnt signaling pathway. GSEA results showed that DCHS1 was related to epithelial-mesenchymal transition (EMT) in many cancers. In vitro experiments in UCEC showed that DCHS1 regulated cell proliferation, migration and EMT. Conclusions: Our findings indicated that DCHS1 might be a novel prognostic and diagnostic biomarker and immunotherapy target, and plays an important role in the proliferation, migration and EMT in UCEC. [ABSTRACT FROM AUTHOR]

Background: Given the significant role of immune-related genes in uterine corpus endometrial carcinoma (UCEC) and the long-term outcomes of patients, our objective was to develop a prognostic risk prediction model using immune-related genes to improve the accuracy of UCEC prognosis prediction. Methods: The Limma, ESTIMATE, and CIBERSORT methods were used for cluster analysis, immune score calculation, and estimation of immune cell proportions. Univariate and multivariate analyses were utilized to develop a prognostic risk model for UCEC. Risk model scores and nomograms were used to evaluate the models. String constructs a protein-protein interaction (PPI) network of genes. The qRT-PCR, immunofluorescence, and immunohistochemistry (IHC) all confirmed the genes. Results: Cluster analysis divided the immune-related genes into four subtypes. 33 immune-related genes were used to independently predict the prognosis of UCEC and construct the prognosis model and risk score. The analysis of the survival nomogram indicated that the model has excellent predictive ability and strong reliability for predicting the survival of patients with UCEC. The protein-protein interaction network analysis of key genes indicates that four genes play a pivotal role in interactions: GZMK, IL7, GIMAP, and UBD. The quantitative real-time polymerase chain reaction (qRT-PCR), immunofluorescence, and immunohistochemistry (IHC) all confirmed the expression of the aforementioned genes and their correlation with immune cell levels. This further revealed that GZMK, IL7, GIMAP, and UBD could potentially serve as biomarkers associated with immune levels in endometrial cancer. Conclusion: The study identified genes related to immune response in UCEC, including GZMK, IL7, GIMAP, and UBD, which may serve as new biomarkers and therapeutic targets for evaluating immune levels in the future. [ABSTRACT FROM AUTHOR]

Background: Uterine Corpus Endometrial Carcinoma (UCEC) stands as one of the prevalent malignancies impacting women globally. Given its heterogeneous nature, personalized therapeutic approaches are increasingly significant for optimizing patient outcomes. This study investigated the prognostic potential of cellular senescence genes(CSGs) in UCEC, utilizing machine learning techniques integrated with large-scale genomic data. Methods: A comprehensive analysis was conducted using transcriptomic and clinical data from 579 endometrial cancer patients sourced from the Cancer Genome Atlas (TCGA). A subset of 503 CSGs was assessed through weighted gene co-expression network analysis (WGCNA) alongside machine learning algorithms, including Gaussian Mixture Model (GMM), support vector machine - recursive feature elimination (SVM-RFE), Random Forest, and eXtreme Gradient Boosting (XGBoost), to identify key differentially expressed cellular senescence genes. These genes underwent further analysis to construct a prognostic model. Results: Our analysis revealed two distinct molecular clusters of UCEC with significant differences in tumor microenvironment and survival outcomes. Utilizing cellular senescence genes, a prognostic model effectively stratified patients into high-risk and low-risk categories. Patients in the high-risk group exhibited compromised overall survival and presented distinct molecular and immune profiles indicative of tumor progression. Crucially, the prognostic model demonstrated robust predictive performance and underwent validation in an independent patient cohort. Conclusion: The study emphasized the significance of cellular senescence genes in UCEC progression and underscored the efficacy of machine learning in developing reliable prognostic models. Our findings suggested that targeting cellular senescence holds promise as a strategy in personalized UCEC treatment, thus warranting further clinical investigation. [ABSTRACT FROM AUTHOR]

Abstract We aimed to find new therapeutic targets related to Cancer Stem Cell alterations in recurrent patients from two TCGA cohorts: Testicular Germ Cell Tumor (TGCT) and Uterine Corpus Endometrial Carcinoma (UCEC). Raw sequencing data were downloaded from the TCGA database. Datasets containing RNA expression and Methylation files were directly downloaded from cBioportal. Variant Call Format files (VCFs) were downloaded from the GDC portal. Gene enrichment analysis was performed using GSEA (Gene Set Enrichment Analysis) software. Transcriptome profiling, coexpression co-occurrence, networks, and survival analyses were performed using cBioportal tools, while mutational analysis of patients was processed using UNIX scripts. We found that cancer stem cell transcription factors were highly expressed in Testicular Germ Cell Tumor (TGCT) and Uterine Corpus Endometrial Carcinoma (UCEC) cohorts, compared to the other 29 cancer cohorts in TCGA. Patients presented a poorer diagnosis when the genes (POU5F1, NANOG, SOX2, SALL4, ABCB1, ABCC1, and ABCG2) were altered. In UCEC cohorts, recurrent patients showed the ABCG2 potentially phosphorylated by the PIM1 kinase. In the TGCT cohort, genes ABCB1 and ABCG2 only appeared in the phosphonetwork in recurrent patients potentially phosphorylated by the same kinase, PIM1, but also by PRKACA. Our data indicate that PRKACA and PIM1 may modulate POU5F1 phosphorylation.

Background: The field of gynaecological immunology has increasingly focused on recurrent spontaneous abortion (RSA). The complex mechanisms underlying the interaction between RSA and cancer are not well understood. Methods: Weighted gene coexpression network analysis (WGCNA), single-cell RNA sequencing (scRNA-seq), and machine learning algorithms were used for the analysis of RSA decidua samples to identify the hub genes. The expression and distribution of the hub genes were subsequently investigated via the pancancer database TCGA. A prognostic prediction was made to assess the impact of the hub genes on the cancer response, mutation burden, immune microenvironment, immune checkpoint, and chemotherapy. In vitro assays were performed to determine whether SLC8A1 influences HTR-8/SVneo cell proliferation, apoptosis and the concentration of calcium ions. Results: SLC8A1 was identified as a hub gene within RSA and was highly expressed in uterine corpus endometrial carcinoma (UCEC). The efficacy of SLC8A1 as a predictive marker was substantiated by calibration curves and the concordance index. The mutation rate of SLC8A1 was found to be 6 % on the basis of the waterfall plot. Immune analysis revealed notable differences in the fractions of T cells and macrophages between the high- and low-expression groups. Patients classified in the low-risk group exhibited enhanced responsiveness to osimertinib, dasatinib, and ibrutinib. The results of in vitro experiments revealed that SLC8A1 promotes proliferation and inhibits the apoptosis and concentration of calcium ions in HTR-8/SVneo cells. Conclusion: These findings suggest that SLC8A1 may serve as a promising prognostic biomarker and potential target for immunotherapy in the context of RSA and UCEC.

Abstract Uterine corpus endometrial carcinoma (UCEC) is becoming a main malignant cancer that threaten to women's health. Thymidine kinase 1 (TK1) is considering to be associated with tumorigenesis and development. Nevertheless, the function of TK1 in UCEC is still unclear. Herein, we analyzed the TK1 expression level in pan-cancer and found that TK1 was upregulated in a variety of cancers including UCEC. Patients of UCEC with high expression of TK1 were related to poor outcome. TK1 was also related to clinical stage, histologic grade and lymph node metastasis. Abnormal expression of TK1 in UCEC was related to promoter methylation while gene mutation was not frequent. TK1 and its associated genes appeared to be prominent in cell cycle and DNA replication, according to GO and KEGG analysis. Analysis of immune infiltration revealed a negative correlation between TK1 and CD8 + T cells, macrophages, and dendritic cells. In vitro experiments, TK1 knockdown resulted in the inhibition of proliferation, migration, invasion and EMT in UCEC cell lines.

Background: Uterine corpus endometrial carcinoma (UCEC), derived from the endometrium, is the most common type of endometrial malignasis. This gynecological malignancy is very common all over the world, especially in developed countries and shows a potentially rising trend correlated with the increase in obese women. Methods: Differentially Expressed Genes (DEGs) analysis was conducted on GSE7305 and GSE25628 datasets from the Gene Expression Omnibus (GEO). DEGs were identified using GEO2R (adjusted p-value 1). Pathway analysis employed KEGG and Gene Ontology databases, while protein-protein interactions were analyzed using Cytoscape and Gephi. GEPIA was used for target gene validation. Results: We have identified 304 common DEGs and 78 hub genes using GEO and PPI analysis, respectively. The GO and KEGG pathways analysis revealed enrichment of DEGs in extracellular matrix structural constituent, extracellular space, cell adhesion, and ECM-receptor interaction. GEPIA analysis identified three genes, ENG, GNG4, and ECT2, whose expression significantly differed between normal and tumor samples. Conclusion: This analysis study identified the hub genes and associated pathways involved in the pathogenesis of UCEC. The identified hub genes exhibit remarkable potential as diagnostic biomarkers, providing a significant opportunity for early diagnosis and more effective therapeutic approaches for UCEC.

BackgroundUterine Corpus Endometrial Carcinoma (UCEC) stands as one of the prevalent malignancies impacting women globally. Given its heterogeneous nature, personalized therapeutic approaches are increasingly significant for optimizing patient outcomes. This study investigated the prognostic potential of cellular senescence genes(CSGs) in UCEC, utilizing machine learning techniques integrated with large-scale genomic data.MethodsA comprehensive analysis was conducted using transcriptomic and clinical data from 579 endometrial cancer patients sourced from the Cancer Genome Atlas (TCGA). A subset of 503 CSGs was assessed through weighted gene co-expression network analysis (WGCNA) alongside machine learning algorithms, including Gaussian Mixture Model (GMM), support vector machine - recursive feature elimination (SVM-RFE), Random Forest, and eXtreme Gradient Boosting (XGBoost), to identify key differentially expressed cellular senescence genes. These genes underwent further analysis to construct a prognostic model.ResultsOur analysis revealed two distinct molecular clusters of UCEC with significant differences in tumor microenvironment and survival outcomes. Utilizing cellular senescence genes, a prognostic model effectively stratified patients into high-risk and low-risk categories. Patients in the high-risk group exhibited compromised overall survival and presented distinct molecular and immune profiles indicative of tumor progression. Crucially, the prognostic model demonstrated robust predictive performance and underwent validation in an independent patient cohort.ConclusionThe study emphasized the significance of cellular senescence genes in UCEC progression and underscored the efficacy of machine learning in developing reliable prognostic models. Our findings suggested that targeting cellular senescence holds promise as a strategy in personalized UCEC treatment, thus warranting further clinical investigation.

Abstract Background CCNE1 plays an important oncogenic role in several tumors, especially high-stage serous ovarian cancer and endometrial cancer. Nevertheless, the fundamental function of CCNE1 has not been explored in multiple cancers. Therefore, bioinformatics analyses of pan-cancer datasets were carried out to explore how CCNE1 regulates tumorigenesis. Methods A variety of online tools and cancer databases, including GEPIA2, SangerBox, LinkedOmics and cBioPortal, were applied to investigate the expression of CCNE1 across cancers. The pan-cancer datasets were used to search for links between CCNE1 expression and prognosis, DNA methylation, m6A level, genetic alterations, CCNE1-related genes, and tumor immunity. We verified that CCNE1 has biological functions in UCEC cell lines using CCK-8, EdU, and Transwell assays. Results In patients with different tumor types, a high mRNA expression level of CCNE1 was related to a poor prognosis. Genes related to CCNE1 were connected to the cell cycle, metabolism, and DNA damage repair, according to GO and KEGG enrichment analyses. Genetic alterations of CCNE1, including duplications and deep mutations, have been observed in various cancers. Immune analysis revealed that CCNE1 had a strong correlation with TMB, MSI, neoantigen, and ICP in a variety of tumor types, and this correlation may have an impact on the sensitivity of various cancers to immunotherapy. CCK-8, EdU and Transwell assays suggested that CCNE1 knockdown can suppress UCEC cell proliferation, migration and invasion. Conclusion Our study demonstrated that CCNE1 is upregulated in multiple cancers in the TCGA database and may be a promising predictive biomarker for the immunotherapy response in some types of cancers. Moreover, CCNE1 knockdown can suppress the proliferation, migration and invasion of UCEC cells.

Uterus corpus endometrial cancer (UCEC) is associated with a high mortality rate. In this study, we examined the impact of long intergenic non-protein coding RNA 01234 (LINC01234) in the diagnosis and survival of UCEC using an open high-throughput sequencing database. The association between LINC01234 expression and UCEC clinical features was determined using the Wilcoxon rank sum test, logistic regression and Cox regression. To assess the classification effectiveness of LINC01234 in UCEC, the area under the receiver operating characteristic (ROC) curve (AUC) was performed. Then, Kaplan-Meier analysis was performed to determine the prognostic significance of LINC01234 in UCEC. The underlying regulatory mechanisms of LIN01234 were assessed using the Gene set enrichment analysis (GSEA), and the influence on immune infiltration cells was tested by the Spearman correlation method. Datebases showed LINC01234 was up-regulated in UCEC and associated with poor clinicopathologic characteristics. What's more quantitative real time polymerase chain reaction (qRTPCR) analyse of clinical tissue specimens, LINC01234 was actually high expression in UCEC. The results showed an AUC of 0.726, indicating that LINC01234 had a significant diagnostic value. Further, Kaplan-Meier analysis showed that high LINC01234 expression was associated with poorer progress free interval (PFI) (hazard ratio (HR): 1.68, 95% confidence interval (CI): 1.18-2.39, p = 0.004), diseasespecific survival (DSS) (HR: 2.17, 95% CI: 1.29-3.67, p = 0.004), overall survival (OS) (HR: 1.81, 95% CI: 1.19-2.75, p = 0.005). Cox regression analysis showed LINC01234 expression was an independent factor for DSS. Pathway enrichment and immune infiltration analysis showed the most likely mechanisms that LINC01234 promoted tumor progression. LINC01234 demonstrated diagnostic and prognostic potential in UCEC and was shown to exert its effects via various mechanisms, including cell proliferation, spermatogenesis, angiogenesis and immune response in the tumor microenvironment, to promote tumor progression; thus, indicating that it could be a target for treating UCEC. [ABSTRACT FROM AUTHOR]

Abstract Background Uterine corpus endometrial carcinoma (UCEC) is the most common female pelvic malignancy worldwide. N6-methyladenosine (m6A) plays an important role in various cellular responses, especially in cancer progression. However, the correlation between prognostic UCEC and m6A RNA methylation regulators remains unclear. Methods We used The Cancer Genome Atlas (TCGA) to provide a gene signature that could improve the prognostic evaluation of UCEC patients according to the distinct genetic trait of m6A RNA methylation regulators from a bioinformatics perspective. After comparing UCEC subgroups with different genetic profiles of m6A regulators, we identified 71 differentially expressed genes associated with overall survival (OS) and generated a nine-gene signature through least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Finally, we used in vitro and in vivo tumor cell experiments as well as the immune correlation analysis to verify the function of each gene in the proposed gene signature. Results Time-dependent receiver operating characteristic (ROC) curves revealed that the proposed gene signature could predict the outcome of UCEC patients accurately. We found that CDKN2A mainly acted from the perspective of tumor cells, while COL4A4, PXDN, TIGIT, CHODL, LMO3, KCNJ12, L1CAM, and EPHB1 might play a role in UCEC from an immunological point of view. Conclusions From an epigenetics perspective, the m6A RNA methylation regulator-based gene signature can predict the prognosis of UCEC patients and immune therapeutic efficacy.

Background: CCNE1 plays an important oncogenic role in several tumors, especially high-stage serous ovarian cancer and endometrial cancer. Nevertheless, the fundamental function of CCNE1 has not been explored in multiple cancers. Therefore, bioinformatics analyses of pan-cancer datasets were carried out to explore how CCNE1 regulates tumorigenesis. Methods: A variety of online tools and cancer databases, including GEPIA2, SangerBox, LinkedOmics and cBioPortal, were applied to investigate the expression of CCNE1 across cancers. The pan-cancer datasets were used to search for links between CCNE1 expression and prognosis, DNA methylation, m6A level, genetic alterations, CCNE1-related genes, and tumor immunity. We verified that CCNE1 has biological functions in UCEC cell lines using CCK-8, EdU, and Transwell assays. Results: In patients with different tumor types, a high mRNA expression level of CCNE1 was related to a poor prognosis. Genes related to CCNE1 were connected to the cell cycle, metabolism, and DNA damage repair, according to GO and KEGG enrichment analyses. Genetic alterations of CCNE1, including duplications and deep mutations, have been observed in various cancers. Immune analysis revealed that CCNE1 had a strong correlation with TMB, MSI, neoantigen, and ICP in a variety of tumor types, and this correlation may have an impact on the sensitivity of various cancers to immunotherapy. CCK-8, EdU and Transwell assays suggested that CCNE1 knockdown can suppress UCEC cell proliferation, migration and invasion. Conclusion: Our study demonstrated that CCNE1 is upregulated in multiple cancers in the TCGA database and may be a promising predictive biomarker for the immunotherapy response in some types of cancers. Moreover, CCNE1 knockdown can suppress the proliferation, migration and invasion of UCEC cells. [ABSTRACT FROM AUTHOR]

Background: Most tumor tissues expressed spindle pole body component 25 (SPC25), one of the four subunits of the NDC80 complex, at greater levels compared to surrounding normal tissues. According to earlier researches, this subunit strongly encouraged tumor cell proliferation and tumor growth, which resulted in worse prognoses in patients with hepatocellular, breast, lung, and prostate cancer. Precisely because SPC25’s role in uterine corpus endometrial carcinoma (UCEC) is understudied, we chose to concentrate on UCEC for gaining a more scientific and thorough understanding of SPC25. Methods: Along with examining SPC25’s differential expression, prognostic significance, and biological function in UCEC, our research sought to clarify the underlying mechanism by which SPC25 influences the course of UCEC and patient prognosis from the viewpoints of methylation and immune infiltration. Results: We observed differential expression of SPC25 gene in different clinicopathological features of UCEC and identified SPC25 as a hazard factor for poorer overall survival (OS), disease-specific survival (DSS), and progress free interval (PFI) in UCEC, particularly in its multiple clinical subtypes. In addition, we also discovered that SPC25 and its co-expressed genes mostly engaged in biological processes and signal transduction routes linked to cell cycle and cell division in UCEC. After investigating SPC25’s methylation status, we discovered that patients with UCEC had elevated SPC25 expression and a poor prognosis due to hypomethylation of CpG sites in the SPC25 gene sequence. Finally, we investigated SPC25’s potential role in immunotherapy and discovered that SPC25 might alter the major immune cell infiltration levels in the tumor microenvironment (TME) by regulating the expression of immunoregulatory molecules and chemokines, which would be beneficial for SPC25 to control the progression of UCEC. Conclusions: In conclusion, SPC25 was a useful predictive biomarker as well as a possible therapeutic target for UCEC.

Abstract Background Long non-coding RNAs (lncRNA) have been implicated in a hand of studies that supported an involvement and co-operation in Uterine Corpus Endometrial Carcinoma (UCEC). Enhancer RNAs (eRNA), a functional subtype of lncRNA, have a key role throughout the genome to guide protein production, thus potentially associated with diseases. Methods In this study, we mainly applied the Cancer Genome Atlas (TCGA) dataset to systematically discover crucial eRNAs involving UCEC. For the key eRNAs in UCEC, we employed RT-qPCR to compare eRNA expression levels in tumor tissues and paired normal adjacent tissues from UCEC patients for validation. Furthermore, the relationships between the key eRNAs and immune activities were measured from several aspects, including the analysis for tumor microenvironment, immune infiltration cells, immune check point genes, tumor mutation burden, and microsatellite instability, as well as m6A related genes. Finally, the key eRNAs were verified by a comprehensive pan-cancer analysis. Results IGFBP7 Antisense RNA 1 (IGFBP7-AS1) was identified as the key eRNA for its expression patterns of low levels in tumor tissues and favorable prognostic value in UCEC correlated with its target gene IGFBP7. In RT-qPCR analysis, IGFBP7-AS1 and IGFBP7 had down-regulated expression in tumor tissues, which was consistent with previous analysis. Moreover, IGFBP7-AS1 was found closely related with immune response in relevant immune analyses. Besides, IGFBP7-AS1 and its target gene IGFBP7 correlated with a multi-omics pan-cancer analysis. Conclusions Finally, we suggested that IGFBP7-AS1 played a key role in impacting on clinical outcomes of UCEC patients for its possible influence on immune activity.

Abstract Endometrial carcinoma is one of the two cancers with rising mortality and morbidity in recent years. In the light of many controversies about its treatment, it is urgent to construct a new prognostic model and to find out new therapeutic directions. As a small drug molecule widely used in clinical treatment and experimental research in China, puerarin has recently been proven to have obvious anti-cancer effects in multiple cancer cells. In this study, bioinformatics analysis and experimental validation were used to explore the potential mechanism of puerarin for endometrial carcinoma and construct a prognostic model. A total of 22 drug-related differential genes were found by constructing a database of drug targets and disease genes. The protein–protein interaction network was constructed for GO and KEGG enrichment analysis to initially explore the potential mechanism of its therapeutic effects. To construct the prognostic model, validation was performed by risk regression analysis and LASSO analysis. Finally, two prognostic genes—PIM1 and BIRC5 were determined to establish high and low risk groups. Kaplan–Meier analysis displayed a higher survival rate in the low-risk group than in the high-risk group. ROC curves indicated the stable and good effect in prediction (one-year AUC is 0.626; two-year AUC is 0.620; three-year AUC is 0.623). The interrelationship between immunity and its disease was explored by immune infiltration analysis. Finally, the potential effect of puerarin on endometrial carcinoma cells was further verified by experiments.

Background: Endometrial cancer (UCEC) is a highly heterogeneous gynecologic malignancy that exhibits variable prognostic outcomes and responses to immunotherapy. The Familial sequence similarity (FAM) gene family is known to contribute to the pathogenesis of various malignancies, but the extent of their involvement in UCEC has not been systematically studied. This investigation aimed to develop a robust risk profile based on FAM family genes (FFGs) to predict the prognosis and suitability for immunotherapy in UCEC patients.Methods: Using the TCGA-UCEC cohort from The Cancer Genome Atlas (TCGA) database, we obtained expression profiles of FFGs from 552 UCEC and 35 normal samples, and analyzed the expression patterns and prognostic relevance of 363 FAM family genes. The UCEC samples were randomly divided into training and test sets (1:1), and univariate Cox regression analysis and Lasso Cox regression analysis were conducted to identify the differentially expressed genes (FAM13C, FAM110B, and FAM72A) that were significantly associated with prognosis. A prognostic risk scoring system was constructed based on these three gene characteristics using multivariate Cox proportional risk regression. The clinical potential and immune status of FFGs were analyzed using CiberSort, SSGSEA, and tumor immune dysfunction and rejection (TIDE) algorithms. qRT-PCR and IHC for detecting the expression levels of 3-FFGs.Results: Three FFGs, namely, FAM13C, FAM110B, and FAM72A, were identified as strongly associated with the prognosis of UCEC and effective predictors of UCEC prognosis. Multivariate analysis demonstrated that the developed model was an independent predictor of UCEC, and that patients in the low-risk group had better overall survival than those in the high-risk group. The nomogram constructed from clinical characteristics and risk scores exhibited good prognostic power. Patients in the low-risk group exhibited a higher tumor mutational load (TMB) and were more likely to benefit from immunotherapy.Conclusion: This study successfully developed and validated novel biomarkers based on FFGs for predicting the prognosis and immune status of UCEC patients. The identified FFGs can accurately assess the prognosis of UCEC patients and facilitate the identification of specific subgroups of patients who may benefit from personalized treatment with immunotherapy and chemotherapy.

Cuproptosis is a copper-dependent model of cell death involved in tumor genesis and progression. Its roles in uterine corpus endometrial carcinoma (UCEC) remains elusive. Here, we aimed to explore the expression and prognostic values of cuprotosis-related genes (CRGs) in UCEC. Expression profiles and clinical data of UCEC were downloaded from The Cancer Genome Atlas (TCGA), and randomly divided into testing or training cohort (1:1 ratio). The CRG signature was identified by LASSO regression analysis. The differentially expressed genes and their functional enrichment analysis were performed by the “limma” R package and Metascape, respectively. The immunocytes infiltration was measured by TIMER, and “GSVA” R package. In total, seven differentially expressed prognostic genes of CRGs in UCEC were identified, and four genes (GLS, CDKN2A, PC, and SUCLG1) were selected to construct a predictive model in training cohort. UCEC patients from training and testing cohorts were further divided into high- or low-risk groups according to the median risk score. High-risk group favored poor prognosis compared to low-risk group. Functional enrichment analysis revealed this CRG signature were got involved in the process of cell-cell adhesion and immune activities (e.g., IL-1 signaling pathway, cellular response to cytokine stimulus). Further analyses revealed there were significant differences between high- and low-risk patients regarding immunocytes infiltration, chemokines, and chemokine receptors. Finally, the expression and biological functions of identified CRGs were confirmed by UCEC samples and experimental methods in vitro. In summary, the CRG signature was significantly correlated with patients' overall survival, which could provide insights into the diagnosis and prognosis prediction for UCEC.

Necroptosis is one of the common modes of apoptosis, and it has an intrinsic association with cancer prognosis. However, the role of the necroptosis-related long non-coding RNA LncRNA (NRLncRNAs) in uterine corpora endometrial cancer (UCEC) has not yet been fully elucidated at present. Therefore, the present study is designed to investigate the potential prognostic value of necroptosis-related LncRNAs in UCEC. In the present study, the expression profiles and clinical data of UCEC patients were downloaded from TCGA database to identify the differentially expressed NRLncRNAs associated with overall survival. A LncRNA risk model was constructed via Cox regression analysis, and its prognostic value was evaluated. We have also further evaluated the relationships between the LncRNA features and the related cellular function, related pathways, immune status, and immune checkpoints m6A-related genes. Seven signatures, including PCAT19, CDKN2B-AS1, LINC01936, LINC02178, BMPR1B-DT, LINC00237, and TRPM2-AS, were established to assess the overall survival (OS) of the UCEC in the present study. Survival analysis and ROC curves indicated that the correlated signature has good predictable performance. The normogram could accurately predict the overall survival of the patients with an excellent clinical practical value. Enrichment analysis of gene sets indicated that risk signals were enriched in several immune-related pathways. In addition, the risk characteristics were significantly correlated with immune cells, immune function, immune cell infiltration, immune checkpoints, and some m6A-related genes. This study has identified seven necroptosis-related LncRNA signatures for the first time, providing a valuable basis for a more accurate prognostic prediction of UCEC. [ABSTRACT FROM AUTHOR]

Uterine corpus endometrial carcinoma (UCEC) is one of the most common gynecologic malignancies. Currently, for UCEC cancer, molecular classification based on metabolic gene characteristics is rarely established. Here, we describe the molecular subtype features of UCEC by classifying metabolism-related gene profiles. Therefore, integrative analysis was performed on UCEC patients from the TCGA public database. Consensus clustering of RNA expression data on 2,752 previously reported metabolic genes identified two metabolic subtypes, namely, C1 and C2 subtypes. Two metabolic subtypes for prognostic characteristics, immune infiltration, genetic alteration, and responses to immunotherapy existed with distinct differences. Then, differentially expressed genes (DEGs) among the two metabolic subtypes were also clustered into two subclusters, and the aforementioned features were similar to the metabolic subtypes, supporting that the metabolism-relevant molecular classification is reliable. The results showed that the C1 subtype has high metabolic activity, high immunogenicity, high gene mutation, and a good prognosis. The C2 subtype has some features with low metabolic activity, low immunogenicity, high copy number variation (CNV) alteration, and poor prognosis. Finally, a model was identified, with three gene metabolism-related signatures, which can predict the prognosis. These findings of this study demonstrate a new classification in UCEC based on the metabolic pattern, thereby providing valuable information for understanding UCEC's molecular characteristics. [ABSTRACT FROM AUTHOR]

Background: Uterine corpus endometrial carcinoma (UCEC) is the most common female pelvic malignancy worldwide. N6-methyladenosine (m6A) plays an important role in various cellular responses, especially in cancer progression. However, the correlation between prognostic UCEC and m6A RNA methylation regulators remains unclear. Methods: We used The Cancer Genome Atlas (TCGA) to provide a gene signature that could improve the prognostic evaluation of UCEC patients according to the distinct genetic trait of m6A RNA methylation regulators from a bioinformatics perspective. After comparing UCEC subgroups with different genetic profiles of m6A regulators, we identified 71 differentially expressed genes associated with overall survival (OS) and generated a nine-gene signature through least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Finally, we used in vitro and in vivo tumor cell experiments as well as the immune correlation analysis to verify the function of each gene in the proposed gene signature. Results: Time-dependent receiver operating characteristic (ROC) curves revealed that the proposed gene signature could predict the outcome of UCEC patients accurately. We found that CDKN2A mainly acted from the perspective of tumor cells, while COL4A4, PXDN, TIGIT, CHODL, LMO3, KCNJ12, L1CAM, and EPHB1 might play a role in UCEC from an immunological point of view. Conclusions: From an epigenetics perspective, the m6A RNA methylation regulator-based gene signature can predict the prognosis of UCEC patients and immune therapeutic efficacy. [ABSTRACT FROM AUTHOR]

Uterine corpus endometrial carcinoma (UCEC) is a malignant disease globally, and there is no unified prognostic signature at present. In our study, two clusters were identified. Cluster 1 showed better prognosis and higher infiltration level, such as tumor microenvironment (TME), tumor mutation burden (TMB), and immune checkpoint genes expression. Gene set enrichment analysis (GSEA) indicated that some tumor-related pathways and immune-associated pathways were exposed. What is more, six pyroptosis-related long noncoding RNAs (lncRNAs) (PRLs) were applied to establish a prognostic signature through multiple Cox regression analysis. In both training and testing sets, patients with higher risk score had poorer survival than patients with low risk. The area under the curve (AUC) of receiver operating characteristic (ROC) curves performed that the survival probability was better in people with lower risk score. Mechanism analysis revealed that high risk score was correlated with reduced immune infiltration and T cells exhaustion, matching the definition of an “immune-desert” phenotype. Patients with lower risk score were characterized by higher immune checkpoint gene expression and TMB and have a sensitive response to immunotherapy and chemotherapy compared with patients with high risk score. The signature has accurate prediction ability of UCEC and is a promising therapeutic target to improve the effect of immunotherapy.

BackgroundThis study aimed to explore the clinical significance of cellular senescence in uterine corpus endometrial carcinoma (UCEC).MethodsCluster analysis was performed on GEO data and TCGA data based on cellular senescence related genes, and then performed subtype analysis on differentially expressed genes between subtypes. The prognostic model was constructed using Lasso regression. Survival analysis, microenvironment analysis, immune analysis, mutation analysis, and drug susceptibility analysis were performed to evaluate the practical relevance. Ultimately, a clinical nomogram was constructed and cellular senescence-related genes expression was investigated by qRT-PCR.ResultsWe ultimately identified two subtypes. The prognostic model divides patients into high-risk and low-risk groups. There were notable discrepancies in prognosis, tumor microenvironment, immunity, and mutation between the two subtypes and groups. There was a notable connection between drug-sensitive and risk scores. The nomogram has good calibration with AUC values between 0.75-0.8. In addition, cellular senescence-related genes expression was investigated qRT-PCR.ConclusionOur model and nomogram may effectively forecast patient prognosis and serve as a reference for patient management.

Background: Using bioinformatics analysis and experimental operations, we intend to analyze the potential mechanism of action of capsaicin target gene GATA1 in the treatment of uterine corpus endometrial carcinoma (UCEC) and develop a prognostic model for the disease to validate this model. Methods: By obtaining capsaicin and UCEC-related DR-DEGs, the prognosisrelated gene GATA1 was screened. The survival analysis was conducted via establishing high and low expression groups of GATA1. Whether the GATA1 could be an independent prognostic factor for UCEC, it was also validated. The therapeutic mechanism of capsaicin-related genes in UCEC was further investigated using enrichment analysis and immune methods as well as in combination with singlecell sequencing data. Finally, it was validated by cell experiments. Results: GATA1, a high-risk gene associated with prognosis, was obtained by screening. Kaplan-Meier analysis showed that the survival of the high expression group was lower than that of low expression group. ROC curves showed that the prediction effect of the model was good and stable (1-year area under curve (AUC): 0.601; 2-years AUC: 0.575; 3-years AUC: 0.610). Independent prognosis analysis showed that the GATA1 can serve as an independent prognostic factor for UCEC. Enrichment analysis showed that "neuroactive Ligand - receptor interaction and TYPE I DIABETES MELLITUS" had a significant enrichment effect. Single-cell sequencing showed that the GATA1 was significantly expressed in mast cells. Cell experiments showed that the capsaicin significantly reduced the UCEC cell activity and migration ability, as well as inhibited the expression of GATA1. Conclusion: This study suggests that the capsaicin has potential value and application prospect in the treatment of UCEC. It provides new genetic markers for the prognosis of UCEC patients. [ABSTRACT FROM AUTHOR]

Background: Uterine corpus endometrial carcinoma (UCEC), derived from the endometrium, is the most common type of endometrial malignasis. This gynecological malignancy is very common all over the world, especially in developed countries and shows a potentially rising trend correlated with the increase in obese women., Methods: Differentially Expressed Genes (DEGs) analysis was conducted on GSE7305 and GSE25628 datasets from the Gene Expression Omnibus (GEO). DEGs were identified using GEO2R (adjusted p-value <0.05, |logFC| > 1). Pathway analysis employed KEGG and Gene Ontology databases, while protein-protein interactions were analyzed using Cytoscape and Gephi. GEPIA was used for target gene validation., Results: We have identified 304 common DEGs and 78 hub genes using GEO and PPI analysis, respectively. The GO and KEGG pathways analysis revealed enrichment of DEGs in extracellular matrix structural constituent, extracellular space, cell adhesion, and ECM-receptor interaction. GEPIA analysis identified three genes, ENG, GNG4, and ECT2, whose expression significantly differed between normal and tumor samples., Conclusion: This analysis study identified the hub genes and associated pathways involved in the pathogenesis of UCEC. The identified hub genes exhibit remarkable potential as diagnostic biomarkers, providing a significant opportunity for early diagnosis and more effective therapeutic approaches for UCEC., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Dong Li,1,&ast; Juan Zhang,2,&ast; Lilong Wu,2 Xiaoming Yang,1 Zheng Chen,1 Jiangjing Yuan1 1Department of Obstetrics and Gynecology, International Peace Maternity and Child Health Hospital, Shanghai Key Laboratory of Embryo Original Diseases, Shanghai Municipal Key Clinical Speciality, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of China; 2Department of Obstetrics and Gynecology, Jinan Maternal and Child Health Care Hospital, Jinan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jiangjing Yuan Email drtracy80@163.comPurpose: Myelin and lymphocyte protein (MAL) plays an essential role in esophageal cancer, classic Hodgkin’s lymphoma and breast cancer. However, its role in uterine corpus endometrial carcinoma (UCEC) has not been explored. Therefore, the current study sought to explore the role of MAL in UCEC.Patients and Methods: Differentially expressed genes (DEGs) were identified by using Limma package in R based on TCGA-UCEC data. Kaplan–Meier plotter analysis was performed to explore the prognostic value of MAL. Function enrichment analyses were performed using GSVA. Further, roles of MAL in UCEC were validated using clinical cohort, which included 120 tumor and adjacent tissues. qRT-PCR and immunohistochemistry analyze the samples. Chi-square tests were performed to explore the associations between MAL expressions and clinicopathological features.Results: The findings showed that overexpression level of MAL in tumor was correlated with worse survival (p = 0.000424). MAL exhibited predictive power for survival time of UCEC patients (3 years: AUC = 0.635; 5 years: AUC = 0.635). Notably, high expression level of MAL was correlated with advanced stage of UCEC. MAL overexpression was significant in UCEC with microsatellite instability (MSI). Enrichment analysis showed that MAL was enriched mainly in MYC targets, epithelial mesenchymal transition and KRAS signaling. Furthermore, MAL was associated with infiltration of immune cells in the tumor micro-environment and immune checkpoint. Analysis showed a positive association between MAL and T cell (CD4+ memory resting). Correlation analysis showed that MAL was significantly positively correlated with several immune checkpoint, including CD274 (R = 0.3389, p = 0.0081), LAG3 (R = 0.2913, p = 0.0229), PDCD1LG2 (R = 0.5345, p < 0.0001). The prognosis value of MAL was confirmed through the experiment.Conclusion: The findings of the current study indicated that MAL is an effective prognostic biomarker and potential therapeutic target for UCEC patients. These results indicated that MAL functions as a diagnosis and therapeutic marker in UCEC treatment.Keywords: MAL, UCEC, prognosis, immune micro environment, biomarker

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.

Background: Long non-coding RNAs (lncRNA) have been implicated in a hand of studies that supported an involvement and co-operation in Uterine Corpus Endometrial Carcinoma (UCEC). Enhancer RNAs (eRNA), a functional subtype of lncRNA, have a key role throughout the genome to guide protein production, thus potentially associated with diseases. Methods: In this study, we mainly applied the Cancer Genome Atlas (TCGA) dataset to systematically discover crucial eRNAs involving UCEC. For the key eRNAs in UCEC, we employed RT-qPCR to compare eRNA expression levels in tumor tissues and paired normal adjacent tissues from UCEC patients for validation. Furthermore, the relationships between the key eRNAs and immune activities were measured from several aspects, including the analysis for tumor microenvironment, immune infiltration cells, immune check point genes, tumor mutation burden, and microsatellite instability, as well as m6A related genes. Finally, the key eRNAs were verified by a comprehensive pan-cancer analysis. Results: IGFBP7 Antisense RNA 1 (IGFBP7-AS1) was identified as the key eRNA for its expression patterns of low levels in tumor tissues and favorable prognostic value in UCEC correlated with its target gene IGFBP7. In RT-qPCR analysis, IGFBP7-AS1 and IGFBP7 had down-regulated expression in tumor tissues, which was consistent with previous analysis. Moreover, IGFBP7-AS1 was found closely related with immune response in relevant immune analyses. Besides, IGFBP7-AS1 and its target gene IGFBP7 correlated with a multi-omics pan-cancer analysis. Conclusions: Finally, we suggested that IGFBP7-AS1 played a key role in impacting on clinical outcomes of UCEC patients for its possible influence on immune activity. [ABSTRACT FROM AUTHOR]

Endometrial carcinoma is one of the two cancers with rising mortality and morbidity in recent years. In the light of many controversies about its treatment, it is urgent to construct a new prognostic model and to find out new therapeutic directions. As a small drug molecule widely used in clinical treatment and experimental research in China, puerarin has recently been proven to have obvious anti-cancer effects in multiple cancer cells. In this study, bioinformatics analysis and experimental validation were used to explore the potential mechanism of puerarin for endometrial carcinoma and construct a prognostic model. A total of 22 drug-related differential genes were found by constructing a database of drug targets and disease genes. The protein–protein interaction network was constructed for GO and KEGG enrichment analysis to initially explore the potential mechanism of its therapeutic effects. To construct the prognostic model, validation was performed by risk regression analysis and LASSO analysis. Finally, two prognostic genes—PIM1 and BIRC5 were determined to establish high and low risk groups. Kaplan–Meier analysis displayed a higher survival rate in the low-risk group than in the high-risk group. ROC curves indicated the stable and good effect in prediction (one-year AUC is 0.626; two-year AUC is 0.620; three-year AUC is 0.623). The interrelationship between immunity and its disease was explored by immune infiltration analysis. Finally, the potential effect of puerarin on endometrial carcinoma cells was further verified by experiments. [ABSTRACT FROM AUTHOR]

Backgrounds: Uterine corpus endometrial carcinoma (UCEC) is one of the greatest threats on the female reproductive system. The aim of this study is to explore the inflammation-related LncRNA (IRLs) signature predicting the clinical outcomes and response of UCEC patients to immunotherapy and chemotherapy. Methods: Consensus clustering analysis was employed to determine inflammation-related subtype. Cox regression methods were used to unearth potential prognostic IRLs and set up a risk model. The prognostic value of the prognostic model was calculated by the Kaplan-Meier method, receiver operating characteristic (ROC) curves, and univariate and multivariate analyses. Differential abundance of immune cell infiltration, expression levels of immunomodulators, the status of tumor mutation burden (TMB), the response to immune checkpoint inhibitors (ICIs), drug sensitivity, and functional enrichment in different risk groups were also explored. Finally, we used quantitative real-time PCR (qRT-PCR) to confirm the expression patterns of model IRLs in clinical specimens. Results: All UCEC cases were divided into two clusters (C1 = 454) and (C2 = 57) which had significant differences in prognosis and immune status. Five hub IRLs were selected to develop an IRL prognostic signature (IRLPS) which had value in forecasting the clinical outcome of UCEC patients. Biological processes related to tumor and immune response were screened. Function enrichment algorithm showed tumor signaling pathways (ERBB signaling, TGF-β signaling, and Wnt signaling) were remarkably activated in high-risk group scores. In addition, the high-risk group had a higher infiltration level of M2 macrophages and lower TMB value, suggesting patients with high risk were prone to a immunosuppressive status. Furthermore, we determined several potential molecular drugs for UCEC. Conclusion: We successfully identified a novel molecular subtype and inflammation-related prognostic model for UCEC. Our constructed risk signature can be employed to assess the survival of UCEC patients and offer a valuable reference for clinical treatment regimens. [ABSTRACT FROM AUTHOR]

BackgroundsUterine corpus endometrial carcinoma (UCEC) is one of the greatest threats on the female reproductive system. The aim of this study is to explore the inflammation-related LncRNA (IRLs) signature predicting the clinical outcomes and response of UCEC patients to immunotherapy and chemotherapy.MethodsConsensus clustering analysis was employed to determine inflammation-related subtype. Cox regression methods were used to unearth potential prognostic IRLs and set up a risk model. The prognostic value of the prognostic model was calculated by the Kaplan-Meier method, receiver operating characteristic (ROC) curves, and univariate and multivariate analyses. Differential abundance of immune cell infiltration, expression levels of immunomodulators, the status of tumor mutation burden (TMB), the response to immune checkpoint inhibitors (ICIs), drug sensitivity, and functional enrichment in different risk groups were also explored. Finally, we used quantitative real-time PCR (qRT-PCR) to confirm the expression patterns of model IRLs in clinical specimens.ResultsAll UCEC cases were divided into two clusters (C1 = 454) and (C2 = 57) which had significant differences in prognosis and immune status. Five hub IRLs were selected to develop an IRL prognostic signature (IRLPS) which had value in forecasting the clinical outcome of UCEC patients. Biological processes related to tumor and immune response were screened. Function enrichment algorithm showed tumor signaling pathways (ERBB signaling, TGF-β signaling, and Wnt signaling) were remarkably activated in high-risk group scores. In addition, the high-risk group had a higher infiltration level of M2 macrophages and lower TMB value, suggesting patients with high risk were prone to a immunosuppressive status. Furthermore, we determined several potential molecular drugs for UCEC.ConclusionWe successfully identified a novel molecular subtype and inflammation-related prognostic model for UCEC. Our constructed risk signature can be employed to assess the survival of UCEC patients and offer a valuable reference for clinical treatment regimens.

Yinghua Li, Jian Zhou The Third Departments of Gynecological Oncology, Hunan Cancer Hospital, Changsha, 410013, Hunan, People’s Republic of ChinaCorrespondence: Jian ZhouThree Departments of Gynecological Oncology, Hunan Cancer Hospital, No. 283 Tongzipo Road, Yuelu District, Changsha, 410013, Hunan, People’s Republic of ChinaTel +86-731-89762061Fax +86-731-89762063Email zhoujian@hnca.org.cnBackground: Uterine corpus endometrial carcinoma (UCEC) is a common malignancy worldwide developed in the female reproductive system, which can be life-threatening due to metastasis and poor prognosis. Deubiquitinating enzymes (DUBs) play key roles in ubiquitin–proteasome system. As a member of DUBs, the ubiquitin-specific protease 5 (USP5) has been found to be an oncogene in several cancers. This study aims to explore the function of USP5 in UCEC.Materials and Methods: Clinical significance of USP5 was assessed from The Cancer Genome Atlas (TCGA) UCEC dataset. Knockdown and overexpression were performed by transfecting the cells with siRNAs and pCDNA3.1 vectors, respectively. CCK8, colony formation, wound healing, transwell, PI, and PI/annexin V staining were conducted to check the effect of USP5 on cellular biology function. Western blot assay was used to detect protein expression.Results: USP5 was upregulated in UCEC patients. Its downregulation led to decreased migration and proliferation of UCEC cells, and meanwhile, cell cycle arrest and apoptosis were induced. By contrast, USP5 overexpression significantly promoted cell migration and cell mitosis. Further study revealed that USP5 could cause hyperactivation of mTOR/4EBP1 pathway and rapamycin treatment could totally reverse the effects of UPS5 overexpression.Conclusion: Our data demonstrated that USP5 functioned as an oncogene in UCEC, which provided new insights into the pathogenesis of UCEC and a promising molecular target for UCEC diagnosis and therapy.Keywords: USP5, UCEC, cell growth, mTOR/4EBP1

Abstract Background Traditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor. Results In this study, we devised supervised and unsupervised learning methods to determine mutational signatures from tumor RNA-seq data. As applications, we applied the methods to a training set of 587 TCGA uterine cancer RNA-seq samples, and examined in an independent testing set of 521 TCGA colorectal cancer RNA-seq samples. Both diseases are known associated with microsatellite instable high (MSI-H) and driver defects in DNA polymerase ɛ (POLɛ). From RNA-seq called variants, we found majority (> 95%) are likely germline variants, leading to C > T enriched germline variants (dbSNP) widely applicable in tumor and normal RNA-seq samples. We found significant associations between RNA-derived mutational burdens and MSI/POLɛ status, and insignificant relationship between RNA-seq total coverage and derived mutational burdens. Additionally we found that over 80% of variants could be explained by using the COSMIC mutational signature-5, -6 and -10, which are implicated in natural aging, MSI-H, and POLɛ, respectively. For classifying tumor type, within UCEC we achieved a recall of 0.56 and 0.78, and specificity of 0.66 and 0.99 for MSI and POLɛ respectively. By applying learnt RNA signatures from UCEC to COAD, we were able to improve our classification of both MSI and POLɛ. Conclusions Taken together, our work provides a novel method to detect RNA-seq derived mutational signatures with effective procedures to remove likely germline variants. It can leads to accurate classification of underlying driving mechanisms of DNA damage deficiency.

Background: Accumulating evidence suggests that anti-estrogens have been effective against multiple gynecological diseases, especially advanced uterine corpus endometrial carcinoma (UCEC), highlighting the contribution of the estrogen response pathway in UCEC progression. This study aims to identify a reliable prognostic signature for potentially aiding in the comprehensive management of UCEC.Methods: Firstly, univariate Cox and LASSO regression were performed to identify a satisfying UCEC prognostic model quantifying patients’ risk, constructed from estrogen-response-related genes and verified to be effective by Kaplan-Meier curves, ROC curves, univariate and multivariate Cox regression. Additionally, a nomogram was constructed integrating the prognostic model and other clinicopathological parameters. Next, UCEC patients from the TCGA dataset were divided into low- and high-risk groups according to the median risk score. To elucidate differences in biological characteristics between the two risk groups, pathway enrichment, immune landscape, genomic alterations, and therapeutic responses were evaluated to satisfy this objective. As for treatment, effective responses to anti-PD-1 therapy in the low-risk patients and sensitivity to six chemotherapy drugs in the high-risk patients were demonstrated.Results: The low-risk group with a relatively favorable prognosis was marked by increased immune cell infiltration, higher expression levels of HLA members and immune checkpoint biomarkers, higher tumor mutation burden, and lower copy number alterations. This UCEC prognostic signature, composed of 13 estrogen-response-related genes, has been identified and verified as effective.Conclusion: Our study provides molecular signatures for further functional and therapeutic investigations of estrogen-response-related genes in UCEC and represents a potential systemic approach to characterize key factors in UCEC pathogenesis and therapeutic responses.

Background: The field of gynaecological immunology has increasingly focused on recurrent spontaneous abortion (RSA). The complex mechanisms underlying the interaction between RSA and cancer are not well understood., Methods: Weighted gene coexpression network analysis (WGCNA), single-cell RNA sequencing (scRNA-seq), and machine learning algorithms were used for the analysis of RSA decidua samples to identify the hub genes. The expression and distribution of the hub genes were subsequently investigated via the pancancer database TCGA. A prognostic prediction was made to assess the impact of the hub genes on the cancer response, mutation burden, immune microenvironment, immune checkpoint, and chemotherapy. In vitro assays were performed to determine whether SLC8A1 influences HTR-8/SVneo cell proliferation, apoptosis and the concentration of calcium ions., Results: SLC8A1 was identified as a hub gene within RSA and was highly expressed in uterine corpus endometrial carcinoma (UCEC). The efficacy of SLC8A1 as a predictive marker was substantiated by calibration curves and the concordance index. The mutation rate of SLC8A1 was found to be 6 % on the basis of the waterfall plot. Immune analysis revealed notable differences in the fractions of T cells and macrophages between the high- and low-expression groups. Patients classified in the low-risk group exhibited enhanced responsiveness to osimertinib, dasatinib, and ibrutinib. The results of in vitro experiments revealed that SLC8A1 promotes proliferation and inhibits the apoptosis and concentration of calcium ions in HTR-8/SVneo cells., Conclusion: These findings suggest that SLC8A1 may serve as a promising prognostic biomarker and potential target for immunotherapy in the context of RSA and UCEC., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Background: Uterine Corpus Endometrial Carcinoma (UCEC) stands as one of the prevalent malignancies impacting women globally. Given its heterogeneous nature, personalized therapeutic approaches are increasingly significant for optimizing patient outcomes. This study investigated the prognostic potential of cellular senescence genes(CSGs) in UCEC, utilizing machine learning techniques integrated with large-scale genomic data., Methods: A comprehensive analysis was conducted using transcriptomic and clinical data from 579 endometrial cancer patients sourced from the Cancer Genome Atlas (TCGA). A subset of 503 CSGs was assessed through weighted gene co-expression network analysis (WGCNA) alongside machine learning algorithms, including Gaussian Mixture Model (GMM), support vector machine - recursive feature elimination (SVM-RFE), Random Forest, and eXtreme Gradient Boosting (XGBoost), to identify key differentially expressed cellular senescence genes. These genes underwent further analysis to construct a prognostic model., Results: Our analysis revealed two distinct molecular clusters of UCEC with significant differences in tumor microenvironment and survival outcomes. Utilizing cellular senescence genes, a prognostic model effectively stratified patients into high-risk and low-risk categories. Patients in the high-risk group exhibited compromised overall survival and presented distinct molecular and immune profiles indicative of tumor progression. Crucially, the prognostic model demonstrated robust predictive performance and underwent validation in an independent patient cohort., Conclusion: The study emphasized the significance of cellular senescence genes in UCEC progression and underscored the efficacy of machine learning in developing reliable prognostic models. Our findings suggested that targeting cellular senescence holds promise as a strategy in personalized UCEC treatment, thus warranting further clinical investigation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wei, Lin, Huang, Wei, Mao and Fan.)

The zinc finger DHHC-type containing 1 (ZDHHC1) gene is implicated in the pathogenesis and progression of various malignant tumors, but its precise involvement in uterine corpus endometrial carcinoma (UCEC) remains unknown. Thus, this study investigated ZDHHC1 expression in UCEC using publicly available TCGA and Xena databases and elucidated the functions and mechanisms of the ZDHHC1 gene in UCEC progression using bioinformatics and in vitro experiments. The correlation between ZDHHC1 expression and prognosis, clinical features, immune cells, and RNA modifications of UCEC was evaluated using nomograms, correlation, ROC, and survival analyses. The impacts of ZDHHC1 overexpression on UCEC progression and mechanisms were explored with bioinformatics and in vitro experiments. Our study revealed that ZDHHC1 expression was significantly downregulated in UCEC and correlated with poor prognosis, cancer diagnosis, clinical stage, age, weight, body mass index, histological subtypes, residual tumor, tumor grade, and tumor invasion. Notably, Cox regression analysis and constructed nomograms showed that downregulated ZDHHC1 expression was a prognostic factor associated with poor prognosis in patients with UCEC. Conversely, above-normal ZDHHC1 expression inhibited the cell growth, cell cycle transition, migration, and invasion of UCEC cells, which may be related to the cell cycle, DNA replication, PI3K-AKT, and other pathways that promote tumor progression. Altered ZDHHC1 expression in UCEC was significantly associated with RNA modifications and the changes in cancer immune cell populations, such as CD56 bright NK cells, eosinophils, Th2 cells, and cell markers. In conclusion, considerably reduced ZDHHC1 expression in UCEC is associated with cancer cell growth, metastasis, poor prognosis, immune infiltration, and RNA modifications, revealing the promising potential of ZDHHC1 as a prognostic marker for UCEC.

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. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To determine the role of RNA-binding protein with serine-rich domain 1 (RNPS1) in uterine corpus endometrial carcinoma (UCEC), the role of RNPS1 knockdown in UCEC development in vitro and in vivo, and the relationship between RNPS1 and mismatch repair (MMR) in UCEC. METHODS: We predicted the potential function of RNPS1 using bioinformatics systems. The expression of RNPS1 in tissues and cell lines was analyzed by western blotting and immunohistochemistry. The expression of RNPS1 in MMR was assessed using bioinformatics and western blotting. The proliferation and apoptosis of UCEC cells were assessed under RNPS1 knockdown conditions, and RNPS1 regulation in MMR was detected by suppressing Notch signaling. Associations between RNPS1 and gene mutations in UCEC and prognosis were analyzed. RESULTS: The RNPS1 level was higher in UCEC tumors than in normal tissues and tumors or RL952 cells. Prognostic outcomes were worse when UCEC showed abundant RNPS1 expression. Lentiviral RNPS1 knockdown weakened tumor cell proliferation and suppressed biomarker expression, reduced the tumor volume, promoted apoptosis in vitro and in vivo, and inhibited UCEC development. Increased MutS homolog 2 (MSH2) and MutS homolog 6 (MSH6) levels in MMR after RNPS1 knockdown were reversed by inhibiting Notch signaling. Furthermore, RNPS1 was associated with mutations in NAA11, C2orf57, NUPR1, and other genes involved in UCEC prognosis. CONCLUSION: RNPS1 may regulate the expression levels of MSH2 and MSH6 in MMR, enhancing the proliferation, development, and prognosis of UCEC through a Notch signaling pathway in UCEC. Our study offers a new method and strategy for delaying UCEC development through modulating MMR.

Background: Traditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor. Results: In this study, we devised supervised and unsupervised learning methods to determine mutational signatures from tumor RNA-seq data. As applications, we applied the methods to a training set of 587 TCGA uterine cancer RNA-seq samples, and examined in an independent testing set of 521 TCGA colorectal cancer RNA-seq samples. Both diseases are known associated with microsatellite instable high (MSI-H) and driver defects in DNA polymerase ɛ (POLɛ). From RNA-seq called variants, we found majority (> 95%) are likely germline variants, leading to C > T enriched germline variants (dbSNP) widely applicable in tumor and normal RNA-seq samples. We found significant associations between RNA-derived mutational burdens and MSI/POLɛ status, and insignificant relationship between RNA-seq total coverage and derived mutational burdens. Additionally we found that over 80% of variants could be explained by using the COSMIC mutational signature-5, -6 and -10, which are implicated in natural aging, MSI-H, and POLɛ, respectively. For classifying tumor type, within UCEC we achieved a recall of 0.56 and 0.78, and specificity of 0.66 and 0.99 for MSI and POLɛ respectively. By applying learnt RNA signatures from UCEC to COAD, we were able to improve our classification of both MSI and POLɛ. Conclusions: Taken together, our work provides a novel method to detect RNA-seq derived mutational signatures with effective procedures to remove likely germline variants. It can leads to accurate classification of underlying driving mechanisms of DNA damage deficiency. [ABSTRACT FROM AUTHOR]

Cancer remains a significant global public health issue. There is growing proof that Ring Finger Protein 186 (RNF186) may play a function in pan-cancer, however, this has not yet been thoroughly determined. This study aims to analyze RNF186 with potential implications in progression and prognosis in human cancer. A comprehensive bioinformatics approaches combined with experimental verification were used across 33 types of cancers in this study to conduct a pan-cancer investigation of RNF186 from the perspectives of gene expression, prognosis, genomic alterations, immunological markers, gene set, and function. RNF186 is a valuable prognostic biomarker in several cancer types, especially breast invasive carcinoma (BRCA) and uterine corpus endometrial carcinoma (UCEC). The levels of RNF186 promoter methylation and genetic alterations may be responsible for some cancers' abnormal expression. Furthermore, RNF186 expression was determined to be associated with immune checkpoint genes. Analysis of RNF186-related genes revealed that proteasome and PI3K-AKT signaling pathway were primarily involved in the cellular function of RNF186. Additionally, our research first confirmed that RNF186 may function as an oncogene and contribute to cancer proliferation, migration and invasion in UCEC. In contrast, RNF186 may play an inhibitory role in BRCA progression. This function depends on the ligase activity of RNF186. This study suggests that RNF186 is a novel critical target for tumor progression in BRCA and UCEC. It reveals that RNF186 may be associated with tumor immunotherapy, which may provide an effective predictive evaluation of the prognosis of immunotherapy. [ABSTRACT FROM AUTHOR]

Background Sequencing studies across multiple cancers continue to reveal mutations and genes involved in the pathobiology of these cancers. Exome sequencing of oral cancers, a subset of Head and Neck Squamous cell Carcinomas (HNSCs) common among tobacco-chewing populations, revealed that ∼34% of the affected patients harbor mutations in the CASP8 gene. Uterine Corpus Endometrial Carcinoma (UCEC) is another cancer where ∼10% cases harbor CASP8 mutations. Caspase-8, the protease encoded by CASP8 gene, plays a dual role in programmed cell death, which in turn has an important role in tumor cell death and drug resistance. CASP8 is a protease required for the extrinsic pathway of apoptosis and is also a negative regulator of necroptosis. Using multiple tools such as differential gene expression, gene set enrichment, gene ontology, in silico immune cell estimates, and survival analyses to mine data in The Cancer Genome Atlas, we compared the molecular features and survival of these carcinomas with and without CASP8 mutations. Results Differential gene expression followed by gene set enrichment analysis showed that HNSCs with CASP8 mutations displayed a prominent signature of genes involved in immune response and inflammation. Analysis of abundance estimates of immune cells in these tumors further revealed that mutant-CASP8 HNSCs were rich in immune cell infiltrates. However, in contrast to Human Papilloma Virus-positive HNSCs that also exhibit high immune cell infiltration, which in turn is correlated with better overall survival, HNSC patients with mutant-CASP8 tumors did not display any survival advantage. Similar analyses of UCECs revealed that while UCECs with CASP8 mutations also displayed an immune signature, they had better overall survival, in contrast to the HNSC scenario. There was also a significant up-regulation of neutrophils (p-value = 0.0001638) as well as high levels of IL33 mRNA (p-value = 7.63747E−08) in mutant-CASP8 HNSCs, which were not observed in mutant-CASP8 UCECs. Conclusions These results suggested that carcinomas with mutant CASP8 have broadly similar immune signatures albeit with different effects on survival. We hypothesize that subtle tissue-dependent differences could influence survival by modifying the micro-environment of mutant-CASP8 carcinomas. High neutrophil numbers, a well-known negative prognosticator in HNSCs, and/or high IL33 levels may be some of the factors affecting survival of mutant-CASP8 cases.

Background: Most tumor tissues expressed spindle pole body component 25 ( SPC25 ), one of the four subunits of the NDC80 complex, at greater levels compared to surrounding normal tissues. According to earlier researches, this subunit strongly encouraged tumor cell proliferation and tumor growth, which resulted in worse prognoses in patients with hepatocellular, breast, lung, and prostate cancer. Precisely because SPC25 's role in uterine corpus endometrial carcinoma (UCEC) is understudied, we chose to concentrate on UCEC for gaining a more scientific and thorough understanding of SPC25 ., Methods: Along with examining SPC25 's differential expression, prognostic significance, and biological function in UCEC, our research sought to clarify the underlying mechanism by which SPC25 influences the course of UCEC and patient prognosis from the viewpoints of methylation and immune infiltration., Results: We observed differential expression of SPC25 gene in different clinicopathological features of UCEC and identified SPC25 as a hazard factor for poorer overall survival (OS), disease-specific survival (DSS), and progress free interval (PFI) in UCEC, particularly in its multiple clinical subtypes. In addition, we also discovered that SPC25 and its co-expressed genes mostly engaged in biological processes and signal transduction routes linked to cell cycle and cell division in UCEC. After investigating SPC25 's methylation status, we discovered that patients with UCEC had elevated SPC25 expression and a poor prognosis due to hypomethylation of CpG sites in the SPC25 gene sequence. Finally, we investigated SPC25 's potential role in immunotherapy and discovered that SPC25 might alter the major immune cell infiltration levels in the tumor microenvironment (TME) by regulating the expression of immunoregulatory molecules and chemokines, which would be beneficial for SPC25 to control the progression of UCEC., Conclusions: In conclusion, SPC25 was a useful predictive biomarker as well as a possible therapeutic target for UCEC., Competing Interests: The authors declare no conflict of interest., (© 2024 The Author(s). Published by IMR Press.)

Background. Sequencing studies across multiple cancers continue to reveal mutations and genes involved in the pathobiology of these cancers. Exome sequencing of oral cancers, a subset of Head and Neck Squamous cell Carcinomas (HNSCs) common among tobacco-chewing populations, revealed that 34% of the affected patients harbor mutations in the CASP8 gene. Uterine Corpus Endometrial Carcinoma (UCEC) is another cancer where 10% cases harbor CASP8 mutations. Caspase-8, the protease encoded by CASP8 gene, plays a dual role in programmed cell death, which in turn has an important role in tumor cell death and drug resistance. CASP8 is a protease required for the extrinsic pathway of apoptosis and is also a negative regulator of necroptosis. Using multiple tools such as differential gene expression, gene set enrichment, gene ontology, in silico immune cell estimates, and survival analyses to mine data in The Cancer Genome Atlas, we compared the molecular features and survival of these carcinomas with and without CASP8 mutations. Results. Differential gene expression followed by gene set enrichment analysis showed that HNSCs with CASP8 mutations displayed a prominent signature of genes involved in immune response and inflammation. Analysis of abundance estimates of immune cells in these tumors further revealed that mutant-CASP8 HNSCs were rich in immune cell infiltrates. However, in contrast to Human Papilloma Virus-positive HNSCs that also exhibit high immune cell infiltration, which in turn is correlated with better overall survival, HNSC patients with mutant-CASP8 tumors did not display any survival advantage. Similar analyses of UCECs revealed that while UCECs with CASP8 mutations also displayed an immune signature, they had better overall survival, in contrast to the HNSC scenario. There was also a significant up-regulation of neutrophils (p-value = 0.0001638) as well as high levels of IL33 mRNA (p-value = 7.63747E-08) in mutant- CASP8 HNSCs, which were not observed in mutant-CASP8 UCECs. Conclusions. These results suggested that carcinomas with mutant CASP8 have broadly similar immune signatures albeit with different effects on survival. We hypothesize that subtle tissue-dependent differences could influence survival by modifying the micro- environment of mutant-CASP8 carcinomas. High neutrophil numbers, a well-known negative prognosticator in HNSCs, and/or high IL33 levels may be some of the factors affecting survival of mutant-CASP8 cases. [ABSTRACT FROM AUTHOR]

The rising incidence and mortality rate of Uterine Corpus Endometrial Carcinoma (UCEC) pose significant health concerns. CC and CXC chemokines have been linked to tumorigenesis and cancer progression. Recognizing the growing significance of CC and CXC chemokines' diagnostic and prognostic significance in diverse cancer types, our objective was to comprehensively analyze the diagnostic and prognostic values of hub genes from the CC and CXC chemokines in UCEC, utilizing both in silico and clinical samples and cell lines-based approaches. In silico analyses include STRING, Cytoscape, Cytohubba, The Cancer Genome Atlas (TCGA) datasets analysis via the UALCAN, GEPIA, OncoDB, and MuTarget, SurvivalGenie, MEXPRESS, cBioPoratal, TIMER, ENCORI, and DrugBank. Meanwhile, clinical samples and cell lines based analyses include Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), targeted bisulfite sequencing (bisulfite-seq) analysis, and immunohistochemistry (IHC). Through present study, we identified CCL25 (CC motif chemokine ligand 25), CXCL10 (C-X-C motif chemokine ligand 10), CXCL12 (C-X-C motif chemokine ligand 12), and CXCL16 (C-X-C motif chemokine ligand 16) as crucial hub genes among the CC and CXC chemokines. Analyzing the expression data from TCGA, we observed a significant up-regulation of CCL25, CXCL10, and CXCL16 in UCEC samples compared to controls. In contrast, we noted a significant down-regulation of CXCL12 expression in UCEC samples. On clinical UCEC samples and cell lines analysis, the significant higher expression of CCL25, CXCL10, and CXCL16 and significant lower expression of CXCL12 were also denoted in UCEC samples than the controls via RT-qPCR and IHC analyses. Moreover, in silico analysis also confirmed the abnormal promoter methylation levels of the hub genes in TCGA UCEC samples, which was later validated by the clinical samples using targeted based bisulfite-seq analysis. In addition, various additional aspects of the CCL25, CXCL10, CXCL12, and CXCL16 have also been uncovered in UCEC during the present study. Our findings offer novel insights that contribute to the clinical utility of CCL25, CXCL10, CXCL12, and CXCL16 chemokines as potential diagnostic and prognostic biomarkers in UCEC., Competing Interests: None., (AJCR Copyright © 2023.)