Novel targets and their functions in the prognosis of uterine corpus endometrial cancer patients

Aberrant mRNA expression is implicated in uterine corpus endometrial carcinoma (UCEC) oncogenesis and progression. However, effective prognostic biomarkers for UCEC remain limited. We aimed to construct a reliable multi-gene risk model using gene expression profiles. Utilizing TCGA data (543 UCEC samples, 35 controls), we identified 1517 differentially acting genes. Weighted gene co-expression complex analysis (WGCCA), hub gene screening, and risk regression analysis (RRA) were employed to determine prognosis-related genes and construct the risk model. Nomograms visualized risk scores and receiver operator characteristic (ROC) curves assessed model performance. Seven novel prognosis-related hub genes (ANGPT1, ASB2, GAL, GDF7, ONECUT2, SV2B, TRPC6) were identified. The model's concordance index (C index) by multivariate Cox regression analysis was 0.79. ROC curves yielded AUCs of 0.811 (3-year) and 0.79 (5-year), demonstrating the model's efficacy in predicting UCEC survival. Our study proposes a promising seven-biomarker risk model for predicting UCEC prognosis, offering potential clinical utility.

A paradigm shift in cancer research based on integrative multi-omics approaches: glutaminase serves as a pioneering cuproptosis-related gene in pan-cancer

BACKGROUND

Cuproptosis is a newly identified form of unprogrammed cell death. As a pivotal metabolic regulator, glutaminase (GLS) has recently been discovered to be linked to cuproptosis. Despite this discovery, the oncogenic functions and mechanisms of GLS in various cancers are still not fully understood.

METHODS

In this study, a comprehensive omics analysis was performed to investigate the differential expression levels, diagnostic and prognostic potential, correlation with tumor immune infiltration, genetic alterations, and drug sensitivity of GLS across multiple malignancies.

RESULTS

Our findings revealed unique expression patterns of GLS across various cancer types and molecular subtypes of carcinomas, underscoring its pivotal role primarily in energy and nutrition metabolism. Additionally, GLS showed remarkable diagnostic and prognostic performance in specific cancers, suggesting its potential as a promising biomarker for cancer detection and prognosis. Furthermore, we focused on uterine corpus endometrial carcinoma (UCEC) and developed a novel prognostic model associated with GLS, indicating a close correlation between GLS and UCEC. Moreover, our exploration into immune infiltration, genetic heterogeneity, tumor stemness, and drug sensitivity provided novel insights and directions for future research and laid the foundation for high-quality verification.

CONCLUSION

Collectively, our study is the first comprehensive investigation of the biological and clinical significance of GLS in pan-cancer. In our study, GLS was identified as a promising biomarker for UCEC, providing valuable evidence and a potential target for anti-tumor therapy. Overall, our findings shed light on the multifaceted functions of GLS in cancer and offer new avenues for further research.

Identification and validation of KIF23 as a hypoxia-regulated lactate metabolism-related oncogene in uterine corpus endometrial carcinoma

AIMS

The "Warburg effect" has been developed from the discovery that hypoxia-inducible factor 1α (HIF-1α) could promote the conversion of pyruvate to lactate. However, no studies have linked hypoxia and lactate metabolism to uterine corpus endometrial carcinoma (UCEC).

MAIN METHODS

Sequencing and clinical data of patients with UCEC were extracted from The Cancer Genome Atlas (TCGA) database. Hypoxia-related lactate metabolism genes (HRLGs) were screened using Spearman's correlation analysis. A prognostic signature based on HRLGs was developed using the least absolute shrinkage and selection operator (LASSO) algorithm. A comprehensive analysis was conducted on the molecular features, immune environment, mutation patterns, and response to drugs between different risk groups. In vitro and in vivo experiments were performed to verify the function of KIF23.

KEY FINDINGS

A five HRLG-based prognostic signature was identified. The prognostic outcome was unfavorable for the high-risk subgroup. Observation of increased pathway activities associated with cell proliferation and DNA damage repair was noted in the high-risk subgroup. Additionally, notable correlations were observed between risk score and immune microenvironment, mutational features, and drug responsiveness. Further, we confirmed KIF23 as a novel oncogene in UCEC, whose silencing decreased proliferation and promoted apoptosis of cancer cells. KIF23 knockdown reduced tumor growth in nude mice. We demonstrated that KIF23 was upregulated under hypoxic stress in a HIF-1α dependent manner. Moreover, KIF23 regulated lactate dehydrogenase A expression.

SIGNIFICANCE

The developed HRLG-related signature was associated with prognosis, immune microenvironment, and drug sensitivity in UCEC. We also revealed KIF23 as a hypoxia-regulated lactate metabolism-related oncogene.

MMP11 and MMP17 are potential biomarkers for uterine corpus endometrial carcinoma prognosis

BACKGROUND

Matrix metalloproteinases (MMP) are important proteases that degrade the extracellular matrix (ECM) and thus essentially mediate tumor vascularization, metastasis, and invasion. However, their potential roles in uterine corpus endometrial carcinoma (UCEC) are not fully understood.

PATIENTS AND METHODS

The expression, prognostic value, and correlation of UCEC patients with MMP were investigated using data from The Cancer Genome Atlas (TCGA) and other databases. Furthermore, differentially expressed genes (DEGs) were identified and their biological functions and correlations with infiltrating immune cells were analyzed.

RESULTS

A total of 22 MMPs were found to be abnormally expressed in UCEC tumor tissues, and high expression of MMP11 and MMP17 were associated with a better UCEC prognosis. MMP11 and MMP17 were observed to be significantly enriched in tumor tissue ECM and were associated with pathways involving degradation, glycolytic metabolism, and PI3K-Akt signaling. Infiltration of natural killer (NK), mast, and NK CD56bright cells was enhanced in tumor tissues with high MMP11 and MMP17 expression.

CONCLUSION

MMP11 and MMP17 may affect UCEC prognosis by influencing immune cell infiltration and may be potential UCEC biomarkers.

Development of a necroptosis-related prognostic model for uterine corpus endometrial carcinoma

Necroptosis is a recently identified caspase-independent form of cell death which plays a significant role in the onset and progression of cancer. MicroRNAs (miRNAs) are vital for the development of uterine corpus endometrial carcinoma (UCEC) because they are an important regulatory component in necroptosis. This study developed a new necroptosis-related miRNAs profile to predict the prognosis of patients with UCEC. The TCGA-UCEC cohort's RNA sequencing data, consisting of 534 tumor samples and 33 normal samples, was downloaded. Ten differentially expressed miRNAs related to necroptosis were identified. A prediction model for necroptosis-related miRNAs was then created through COX regression and nomograms analysis. Clinical and pathological parameters were integrated to construct a nomogram and evaluate the model. Prognosis-related miRNAs were further used to predict target genes, and functional analysis was conducted to explore the potential mechanisms of these target genes. Subsequently, immune infiltration analysis was performed using transcriptome data to identify immune genes associated with prognosis, and the expression levels of target gene was validated using UCEC tissues. We identified 7 up-regulated miRNAs (hsa-miR-577, hsa-miR-7-5p, hsa-miR-210-3p, hsa-miR-210-5p, hsa-miR-200a-5p, hsa-miR-141-3p, hsa-miR-425-5p) and 3 down-regulated miRNAs (hsa-miR-7-2-3p, hsa-miR-383-5p, hsa-miR-29a-3p). The risk signature was based on univariate and multivariate COX analyses, constructed using 2 independent prognostic factors and miRNAs (hsa-miR-425-5p, hsa-miR-7-5p) associated with necroptosis. Nomograms demonstrated the prognostic value of risk level, age, FIGO stage, and histological type. Kaplan-Meier analysis revealed significant differences in overall survival (OS) outcomes associated with the expression of hsa-miR-425-5p (P < 0.001) and hsa-miR-7-5p (P = 0.015). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) investigations indicated that these miRNAs play crucial roles in tumor development, metastasis, and prognosis. Immune infiltration analysis showed decreased infiltration of CD8+ T cells, CD8+ T cells, NK cells, and M1 macrophages in normal tissues. Subsequently, a necroptosis-related immune gene significantly associated with prognosis (THRB) was identified, western blot and immunohistochemical staining confirmed the differential expression of THRB in normal endometrial tissues and tumor. Our findings demonstrate a close association between necroptosis and UCEC. The two necroptosis-related miRNAs used in this study may serve as valuable prognostic markers for UCEC patients, and are associated with immune cell infiltration. This suggests that necroptosis may be involved in the development of UCEC through its interaction with immune responses.

The Identification of Gamma-Glutamyl Hydrolase in Uterine Corpus Endometrial Carcinoma: a Predictive Model and Machine Learning

BACKGROUND

Poor neoplastic differentiation contributes to the rapid progression of uterine corpus endometrial carcinoma (UCEC). Thus, it is essential to identify candidate genes, clarifying the carcinogenesis and progression of UCEC.

METHODS

We screened genes that affect differentiation and prognosis in UCEC. Least absolute selection and shrinkage operator (LASSO) regression, univariate Cox, and multivariate Cox proportional risk regression analyses were performed to screen out γ-glutamyl hydrolase (GGH) as the candidate gene. The clinical value of GGH on prognosis was evaluated. The relationship between GGH and immune infiltration was assessed by CIBERSORT, EPIC, ssGSEA, unsupervised clustering and immunohistochemistry (IHC). Additionally, we investigated the effect of GGH knockdown in vitro.

RESULTS

Among the GGH, CDKN2A, and SIX1 genes, the impact of GGH was predominant on immune infiltration in UCEC. A nomogram containing GGH and other clinical features showed good predictive performance via curve analysis (DCA). In the functional analysis, GGH affected differentiation, tumour proliferation, and immune regulation. The immunosuppressive components were enriched in the GGH-high group, with poor immunotherapy efficacy. The study suggests that GGH may influence the progression of UCEC by regulating the glycolytic process.

CONCLUSIONS

GGH is closely associated with various immune cell infiltrations. Our study demonstrates the prognostic role of GGH in carcinogenesis in UCEC.

The construction, validation and promotion of the nomogram prognosis prediction model of UCEC, and the experimental verification of the expression and knockdown of the key gene GPX4

Background

Adequate prognostic prediction of Uterine Corpus Endometrial Carcinoma (UCEC) is crucial for informing clinical decision-making. However, there is a scarcity of research on the utilization of a nomogram prognostic evaluation model that incorporates pyroptosis-related genes (PRGs) in UCEC.

Methods

By analyzing data from UCEC patients in the TCGA database, four PRGs associated with prognosis were identified. Subsequently, a "risk score" was developed using these four PRGs and LASSO. Ordinary and web-based dynamic nomogram prognosis prediction models were constructed. The discrimination, calibration, clinical benefit, and promotional value of the selected GPX4 were validated. The expression level of GPX4 in UCEC cell lines was subsequently verified. The effects of GPX4 knock-down on the malignant biological behavior of UCEC cells were assessed.

Results

Four key PRGs and a "risk score" were identified, with the "risk score" calculated as (-0.4323) * GPX4 + (0.2385) * GSDME + (0.0525) * NLRP2 + (-0.3299) * NOD2. The nomogram prognosis prediction model, incorporating the "risk score," "age," and "FIGO stage," demonstrated moderate predictive performance (AUC >0.7), good calibration, and clinical significance for 1, 3, and 5-year survival. The web-based dynamic nomogram demonstrated significant promotional value (https://shibaolu.shinyapps.io/DynamicNomogramForUCEC/). UCEC cells exhibited abnormally elevated expression of GPX4, and the knockdown of GPX4 effectively suppressed malignant biological activities, including proliferation and migration, while inducing apoptosis. The findings from tumorigenic experiments conducted on nude mice further validated the results obtained from cellular experiments.

Conclusion

Following validation, the nomogram prognosis prediction model, which relies on four pivotal PRGs, demonstrated a high degree of accuracy in forecasting the precise probability of prognosis for patients with UCEC. Additionally, the web-based dynamic nomogram exhibited considerable potential for promotion. Notably, the key gene GPX4 exhibited characteristics of a potential oncogene in UCEC, as it facilitated malignant biological behavior and impeded apoptosis.

Deciphering DNA repair gene mutational landscape in uterine corpus endometrial carcinoma patients using next generation sequencing

Uterine Corpus Endometrial Carcinoma (UCEC) is a significant health concern with a complex genetic landscape impacting disease susceptibility and progression. This study aimed to unravel the spectrum of DNA repair gene mutations in Pakistani UCEC patients through Next Generation Sequencing (NGS) and explore their potential functional consequences via downstream analyses. NGS analysis of genomic DNA from 30 UCEC patients was conducted to identify clinically significant pathogenic mutations in DNA repair genes. This analysis revealed mutations in 4 key DNA repair genes: BRCA1, BRCA2, APC, and CDH1. Kaplan-Meier (KM) analysis was employed to assess the prognostic value of these mutations on patient overall survival (OS) in UCEC. To delve into the functional impact of these mutations, we performed RT-qPCR, immunohistochemistry (IHC), and western blot analyses on the mutated UCEC samples compared to their non-mutated counterparts. These results unveiled the up-regulation in the expression of the mutated genes, suggesting a potential association between the identified mutations and enhanced gene activity. Additionally, targeted bisulfite sequencing analysis was utilized to evaluate DNA methylation patterns in the promoters of the mutated genes. Strikingly, hypomethylation in the promoters of BRCA1, BRCA2, APC, and CDH1 was observed in the mutated UCEC samples relative to the non-mutated, indicating the involvement of epigenetic mechanisms in the altered gene expression. In conclusion, this study offers insights into the genetic landscape of DNA repair gene mutations in Pakistani UCEC patients. The presence of pathogenic mutations in BRCA1, BRCA2, APC, and CDH1, coupled with their down-regulation and hypermethylation, suggests a convergence of genetic and epigenetic factors contributing to genomic instability in UCEC cells. These findings enhance our understanding of UCEC susceptibility and provide potential avenues for targeted therapeutic interventions in Pakistani UCEC patients.

Exploring the role of PRDX4 in the development of uterine corpus endometrial carcinoma

Peroxicedoxin 4 (PRDX4), a member of the peroxicedoxins (PRDXs), has been reported in many cancer-related studies, but its role in uterine corpus endometrial carcinoma (UCEC) is not fully understood. In the present study, we found that PRDX4 was highly expressed in UCEC tissues and cell lines through the combination of bioinformatics analysis and experiments, and elevated PRDX4 levels were associated with poor prognosis. Knockdown of PRDX4 significantly blocked the proliferation and migration of the UCEC cell line Ishikawa and reduced degree of cell confluence. These findings highlight the oncogenic role of PRDX4 in UCEC. In addition, genes that interact with PRDX4 in UCEC were MT-ATP8, PBK, and PDIA6, and we speculated that these genes interacted with each other to promote disease progression in UCEC. Thus, PRDX4 is a potential diagnostic biomarker for UCEC, and targeting PRDX4 may be a potential therapeutic strategy for patients with UCEC.

TPD52 as a Potential Prognostic Biomarker and its Correlation with Immune Infiltrates in Uterine Corpus Endometrial Carcinoma: Bioinformatic Analysis and Experimental Verification

BACKGROUND

Aberrant expression of tumor protein D52 (TPD52) is associated with some tumors. The role of TPD52 in uterine corpus endometrial carcinoma (UCEC) remains uncertain.

OBJECTIVE

We aimed to investigate the involvement of TPD52 in the pathogenesis of UCEC.

METHODS

We employed bioinformatics analysis and experimental validation in our study.

RESULTS

Our findings indicated that elevated TPD52 expression in UCEC was significantly associated with various clinical factors, including clinical stage, race, weight, body mass index (BMI), histological type, histological grade, surgical approach, and age (p < 0.01). Furthermore, high TPD52 expression was a predictor of poorer overall survival (OS), progress-free survival (PFS), and disease-specific survival (DSS) (p = 0.011, p = 0.006, and p = 0.003, respectively). TPD52 exhibited a significant correlation with DSS (HR: 2.500; 95% CI: 1.153-5.419; p = 0.02). TPD52 was involved in GPCR ligand binding and formation of the cornified envelope in UCEC. Moreover, TPD52 expression was found to be associated with immune infiltration, immune checkpoints, tumor mutation burden (TMB)/ microsatellite instability (MSI), and mRNA stemness indices (mRNAsi). The somatic mutation rate of TPD52 in UCEC was 1.9%. A ceRNA network of AC011447.7/miR-1-3p/TPD52 was constructed. There was excessive TPD52 protein expression. The upregulation of TPD52 expression in UCEC cell lines was found to be statistically significant.

CONCLUSION

TPD52 is upregulated in UCEC and may be a useful patent for prognostic biomarkers of UCEC, which may have important value for clinical treatment and supervision of UCEC patients.

Integrating ferroptosis-related genes (FRGs) and prognostic models to enhance UCEC outcome prediction and therapeutic insights

Ferroptosis is closely associated with uterine corpus endometrial carcinoma (UCEC) development. This project aimed to identify new potential biomarkers to predict the prognosis of UCEC. In this work, UCEC transcriptome data along with clinical information was retrieved from the TCGA database including a total of 382 FRGs. We performed univariate Cox regression analysis to evaluate ferroptosis-related genes (FRGs) for prognostic significance. The genes with prognostic significance were then analyzed using LASSO-Cox to construct a prognosis model. The model genes were further characterized through various proteomic analyses and expression detection in clinical samples. A multivariate Cox regression model was constructed containing four FRGs (CDKN1A, CDKN2A, CEBPG, NOS2). Among four FRGs, higher expressions of CDKN2A, CEBPG, and NOS2 were associated with poorer overall survival probability, while higher expression of CDKN1A was associated with better overall survival probability. The area under the receiver operating characteristic curve of the risk model was 0.617, 0.688, and 0.693 for 1 year, 3 years, and 5 years, respectively. Moreover, proteomic analysis showed that the protein expression of CDKN1A, CDKN2A, and CEBPG was higher in tumor tissues than that in normal tissues. Higher protein expression of CDKN1A and CDKN2A predicted poorer survival probability. Besides, CDKN1A protein had an interaction relationship with CDKN2A protein or NOS2 protein. In clinical samples, all four FRGs were upregulated in UCEC tissues, regardless of gene expression or protein expression. Our four FRGs risk model provides new insights for predicting the prognosis of UCEC patients.

Development and validation of a novel DNA damage repair-related long non-coding RNA signature in predicting prognosis, immunity, and drug sensitivity in uterine corpus endometrial carcinoma

Background

DNA damage response (DDR) confer resistance to chemoradiotherapy in cancer cells. However, the role of DDR-related lncRNAs (DRLs) in uterine corpus endometrial carcinoma (UCEC) is poorly understood. In this study, we aimed to identify a DRL-related prognostic signature that could guide the clinical treatment of UCEC.

Methods

We extracted transcriptome and clinical data of patients with UCEC from The Cancer Genome Atlas (TCGA) database and identified DRLs using Spearman correlation analysis. Univariate and multivariate Cox analyses were used to determine candidate prognostic DRLs. The samples were randomly divided into training and test cohorts in a 1:1 ratio. A DRL-related risk signature was constructed from the training cohort data using the least absolute shrinkage and selection operator (LASSO) algorithm, and validated using the test and entire cohorts. Subsequently, a prognostic nomogram was developed using a multivariate Cox regression analysis. The functional annotation, immune microenvironment, tumor mutation burden (TMB), immune checkpoint blockade (ICB) efficacy, and drug sensitivity were also comprehensively analyzed between different risk groups. Finally, the function of AC019069.1 was validated in vitro.

Results

A novel risk signature was developed based on nine DRLs. The risk score efficiently predicted the prognosis of patients with UCEC. Based on the median risk score, two subgroups were identified. The DDR-related pathways were upregulated in the high-risk group. Additionally, high-risk patients have low immune activity, poor response to ICB, and weak sensitivity to chemotherapeutic agents, possibly because of the proficient DDR system. Finally, we demonstrated AC019069.1 could promote cell proliferation, decrease apoptosis and maintain genome stability of UCEC cells.

Conclusions

The developed DRL-related signature can predict the prognosis, immune microenvironment, immunotherapy, and chemoradiotherapy responsiveness of UCEC. Our study also revealed the potential value of DDR-targeted therapy in treating high-risk patients with UCEC.

Glycosyltransferase-related prognostic and diagnostic biomarkers of uterine corpus endometrial carcinoma

Uterine corpus endometrial carcinoma (UCEC) has a strong ability of invasion and metastasis, high recurrence rate, and poor survival. Glycosyltransferases are one of the most important enzymes that coordinate the glycosylation process, and abnormal modification of proteins by glycosyltransferases is closely related to the occurrence and development of cancer. However, there were fewer reports on glycosyltransferase related biomarkers in UCEC. In this paper, based on the UCEC transcriptome data published on The Cancer Genome Atlas (TCGA), we predicted the relationship between the expression of glycosyltransferase-related genes (GTs) and the diagnosis and prognosis of UCEC using bioinformatics methods. And validation of model genes by clinical samples. We used 4 methods: generalized linear model (GLM), random forest (RF), support vector machine (SVM) and extreme gradient boosting (XGB) to screen biomarkers with diagnostic significance, and the binary logistic regression was used to establish a diagnostic model for the 2-GTs (AUC = 0.979). And the diagnostic model was validated using a GEO external database (AUC = 0.978). Moreover, a prognostic model for the 6-GTs was developed using univariate, Lasso, and multivariate Cox regression analyses, and the model was made more stable by internal validation using the bootstrap. In addition, risk score is closely related to immune microenvironment (TME), immune infiltration, mutation, immunotherapy and chemotherapy. Overall, this study provides novel biomarkers for the diagnosis and prognosis of UCEC, and the models established by these biomarkers can also provide a good reference for individualized and precision medicine in UCEC.

Construction of the novel immune risk scoring system related to CD8+ T cells in uterine corpus endometrial carcinoma

BACKGROUND

Uterine corpus endometrial carcinoma (UCEC) is a gynecological malignant tumor with high incidence and poor prognosis. Although immunotherapy has brought significant survival benefits to advanced UCEC patients, traditional evaluation indicators cannot accurately identify all potential beneficiaries of immunotherapy. Consequently, it is necessary to construct a new scoring system to predict patient prognosis and responsiveness of immunotherapy.

METHODS

CIBERSORT combined with weighted gene co-expression network analysis (WGCNA), non-negative matrix factorization (NMF), and random forest algorithms to screen the module associated with CD8⁺ T cells, and key genes related to prognosis were selected out by univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses to develop the novel immune risk score (NIRS). Kaplan-Meier (K-M) analysis was used to compare the difference of survival between high- and low- NIRS groups. We  also explored the correlations between NIRS, immune infiltration and immunotherapy, and three external validation sets were used to verify the predictive performance of NIRS. Furthermore, clinical subgroup analysis, mutation analysis, differential expression of immune checkpoints, and drug sensitivity analysis were performed to generate individualized treatments for patients with different risk scores. Finally, gene set variation analysis (GSVA) was conducted to explore the biological functions of NIRS, and qRT-PCR was applied to verify the differential expressions of three trait genes at cellular and tissue levels.

RESULTS

Among the modules clustered by WGCNA, the magenta module was most positively associated with CD8⁺ T cells. Three genes (CTSW, CD3D and CD48) were selected to construct NIRS after multiple screening procedures. NIRS was confirmed as an independent prognostic factor of UCEC, and patients with high NIRS had significantly worse prognosis compared to those with low NIRS. The high NIRS group showed lower levels of infiltrated immune cells, gene mutations, and expression of multiple immune checkpoints, indicating reduced sensitivity to immunotherapy. Three module genes were identified as protective factors positively correlated with the level of CD8⁺ T cells.

CONCLUSIONS

In this study, we constructed NIRS as a novel predictive signature of UCEC. NIRS not only differentiates patients with distinct prognoses and immune responsiveness, but also guides their therapeutic regimens.

LncRNA VPS9D1-AS1 Sponging miR-520a-5p Contributes to the Development of Uterine Corpus Endometrial Carcinoma by Enhancing BIRC5 Expression

The pattern of VPS9D1-AS1 expression and its effects on uterine corpus endometrial carcinoma (UCEC) remained unclear. VPS9D1-AS1, miR-520a-5p, and BIRC5 mRNA levels were quantified by qRT-PCR. Bax, Bcl-2, N-cadherin, E-cadherin, and BIRC5 protein levels were analyzed through western blotting. Cell migration, invasion, proliferation, as well as apoptosis of cells were checked after performing assay for wound-healing, Transwell, cell-counting kit-8 (CCK-8) assay, and western blotting. VPS9D1-AS1 effects on UCEC were observed in nude mice. Through bioinformatics tools, we analyzed the association present among miR-520a-5p, BIRC5, and VPS9D1-AS1 along with RNA immunoprecipitation, and Dual-Luciferase verification reporter analysis. Our findings suggested VPS9D1-AS1 gene expression was up-regulated in both tissues as well as cells of UCEC. VPS9D1-AS1 knockdown suppressed migration, invasion, epithelial-mesenchymal transition (EMT) along with proliferation of UCEC cells, caused in vitro cell apoptosis initiation, and in vivo reduction of tumor growth. Mechanistically, it was verified that VPS9D1-AS1 targeted BIRC5 and caused miR-520a-5p sponging. Inhibitor of miR-520-5p markedly reversed the anti-tumor effects of VPS9D1-AS1 knockdown or BIRC5 knockdown on UCEC progression. Our studies revealed that VPS9D1-AS1 contributed to the UCEC development and progression by binding to miR-520a-5p competitively and inducing BIRC5 expression, indicating that VPS9D1-AS1 might act as a therapeutic target to develop new therapies for UCEC patients.

The potential role of methyltransferase-like 5 in deficient mismatch repair of uterine corpus endometrial carcinoma

To explore the potential function of methyltransferase-like 5 (METTL5) in uterine corpus endometrial carcinoma (UCEC) and verify the relationship between deficient DNA mismatch repair (MMR) and METTL5. We used bioinformatics to predict the possible role of METTL5 and molecular biology methods to analyze METTL5 expression. We observed UCEC proliferation, development, and apoptosis using a METTL5 knockdown lentivirus and, coupled with METTL5 bioinformatics and Western blot analysis, detected microsatellite instability (MSI) and MMR. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. Finally, some METTL5-associated gene mutations in UCECs were detected. Results show that METTL5 expression in UCEC tumor tissue was increased, and UCEC patients with high METTL5 expression had worse prognostic outcomes. We also observed the highest METTL5 expression level in KLE cells. Furthermore, knocking down METTL5 weakened the proliferation, reduced tumor volume and biomarkers, and increased apoptosis. Moreover, METTL5 knockdown induced the MSH2, MSH6 and PMS2 expression in MMR. METTL5 was negatively correlated with gene silencing, mRNA binding, olfactory receptor activity, antigen processing and presentation, cytosolic DNA sensing, olfactory transduction, and RIG-1-like and Toll-like receptor signaling pathways. METTL5 may regulate MMR protein levels in UCECs, thus enhancing UCEC proliferation, development, and prognosis.

Mutational signatures reveal ternary relationships between homologous recombination repair, APOBEC, and mismatch repair in gynecological cancers

Background

Revealing the impacts of endogenous and exogenous mutagenesis processes is essential for understanding the etiology of somatic genomic alterations and designing precise prognostication and treatment strategies for cancer. DNA repair deficiency is one of the main sources of endogenous mutagenesis and is increasingly recognized as a target for cancer therapeutics. The role and prevalence of mechanisms that underly different forms of DNA repair deficiencies and their interactions remain to be elucidated in gynecological malignancies.

Methods

We analyzed 1231 exomes and 268 whole-genomes from three major gynecological malignancies including uterine corpus endometrial carcinoma (UCEC) as well as ovarian and cervical cancers. We also analyzed data from 134 related cell lines. We extracted and compared de novo and refitted mutational signature profiles using complementary and confirmatory approaches and performed interaction analysis to detect co-occurring and mutually exclusive signatures.

Results

We found an inverse relationship between homologous recombination deficiency (HRd) and mismatch repair deficiency (MMRd). Moreover, APOBEC co-occurred with HRd but was mutually exclusive with MMRd. UCEC tumors were dominated by MMRd, yet a subset of them manifested the HRd and APOBEC signatures. Conversely, ovarian tumors were dominated by HRd, while a subset represented MMRd and APOBEC. In contrast to both, cervical tumors were dominated by APOBEC with a small subsets showing the POLE, HRd, and MMRd signatures. Although the type, prevalence, and heterogeneity of mutational signatures varied across the tumor types, the patterns of co-occurrence and exclusivity were consistently observed in all. Notably, mutational signatures in gynecological tumor cell lines reflected those detected in primary tumors.

Conclusions

Taken together, these analyses indicate that application of mutation signature analysis not only advances our understanding of mutational processes and their interactions, but also it has the potential to stratify patients that could benefit from treatments available for tumors harboring distinct mutational signatures and to improve clinical decision-making for gynecological malignancies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03259-0.

Identification of Key Prognostic-Related miRNA-mRNA Pairs in the Progression of Endometrial Carcinoma

OBJECTIVES

Endometrial carcinoma (EC) is one of the leading causes of death from gynecological cancer due to the high recurrence rate. However, the molecular mechanisms of EC progression are not well understood. This study aimed to identify critical genes and miRNAs associated with the progression and prognosis of EC and find the potential mRNA-miRNA regulatory relationship.

DESIGN

The mRNA and miRNA data were downloaded from The Cancer Genome Atlas (TCGA) database. Next, differentially expressed genes (DEGs) were identified. Subsequently, prognosis-related genes and miRNAs were identified, followed by co-expression analysis of these mRNAs and miRNAs. Materials, Setting, and Methods: Samples in the mRNA microarray were divided into normal (n = 35), early stage (n = 385), and advanced stage (n = 153). Next, DEGs in normal versus early stage and early stage versus advanced stage were, respectively, identified, followed by Venn analysis to screen overlapping DEGs in 2 comparison groups. Based on the expression level of these DEGs, univariate Cox regression analysis and Kaplan-Meier method were performed to obtain prognosis-related genes. Moreover, genes-related miRNAs were predicted, and miRNA-mRNA co-expressed pairs were identified. Then, survival analysis of co-expressed miRNA was performed. Finally, co-expressed genes of key genes were identified, and then functional enrichment analysis was conducted.

RESULTS

After integrating analysis, 326 overlapping (309 upregulated and 17 downregulated) DEGs were obtained. Univariate Cox regression analysis showed that 44 mRNAs and 8 miRNAs were associated with the prognosis of EC. Combined with the co-expressed analysis, only one prognosis-related hsa-miR-326/ELFN2 axis was obtained. In addition, functional enrichment analysis showed that co-expressed genes of ELFN2 were mainly involved in the PI3K-Akt signaling pathway.

LIMITATIONS

These findings were obtained via bioinformatics analysis, and thus further experimental studies are urgently demanded to validate our results.

CONCLUSIONS

One key miRNA-mRNA regulatory pair (hsa-miR-326-ELFN2) was screened. This study provided a bioinformatics basis for the molecular mechanism of EC progression and might contribute to the identification of novel therapeutic targets.

LHX1 as a potential biomarker regulates EMT induction and cellular behaviors in uterine corpus endometrial carcinoma

OBJECTIVES

To investigate the expression of LHX1 and its role as a biomarker in the diagnosis and prognosis of Uterine Corpus Endometrial Carcinoma (UCEC).

METHODS

The Cancer Genome Atlas (TCGA) database was used to detect the expression level of LHX1 in UCEC cells and tissues, and to find out the effect of LHX1 on prognosis. Co-expressed genes were then identified by Spearman correlation analysis, and the protein-protein interaction network was constructed using Cytoscape software. The R "clusterProfiler" package was used to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. A series of in vitro experiments were performed to evaluate LHX1 expression and detect UCEC cell proliferation, invasion, and migration. Western blotting was used to determine the effect of LHX1 on expression levels of Epithelial-Mesenchymal Transition (EMT)-related proteins.

RESULTS

LHX1 was upregulated in UCEC tissues and correlated with poor overall survival and disease-specific survival outcomes. Functional enrichment analysis suggested that genes co-expressed with LHX1 were enriched in cell adhesion. The expression of LHX1 was positively correlated with the expression levels of genes related to EMT induction and invasion. LHX1 can enhance the proliferation, migration, and invasion activities of UCEC cells in vitro, and alter the expression levels of EMT-related proteins.

CONCLUSION

LHX1 expression was highly upregulated in UCEC cells and tissues, which was correlated with the prognosis of patients with UCEC. LHX1 may regulate UCEC progression at least in part by modulating EMT induction.

Identifying immune subtypes of uterine corpus endometrial carcinoma and a four-paired-lncRNA signature with immune-related lncRNAs

Uterine corpus endometrial carcinoma (UCEC) is the third most frequent gynecological malignancies in the female reproductive system. Long non-coding RNAs (lncRNAs) are closely involved in tumor progression. This study aimed to develop an immune subtyping system and a prognostic model based on lncRNAs for UCEC. Paired lncRNAs and non-negative matrix factorization were applied to identify immune subtypes. Enrichment analysis was conducted to assess functional pathways, immune-related genes, and cells. Univariate and multivariate Cox regression analysis were performed to analyze the relation between lncRNAs and overall survival (OS). A prognostic model was constructed and optimized by least absolute shrinkage and selection operator (LASSO) and Akaike information criterion (AIC). Two immune subtypes (C1 and C2) and four paired-prognostic lncRNAs closely associated with overall survival were identified. Some immune features, sensitivity of chemotherapy and immunotherapy, and the relation with immune escape showed variations between two subtypes. A nomogram established based on prognostic model and clinical features was effective in OS prediction. The immune subtyping system based on lncRNAs and the four-paired-lncRNA signature was predictive of UCEC prognosis and can facilitate personalized therapies such as immunotherapy or RNA-based therapy for UCEC patients.

ZBTB7A, a potential biomarker for prognosis and immune infiltrates, inhibits progression of endometrial cancer based on bioinformatics analysis and experiments

Backgroud

ZBTB protein is an important member of the C2H2 zinc finger protein family. As a transcription factor, it is widely involved in the transcriptional regulation of genes, cell proliferation, differentiation, and apoptosis. The ZBTB7A has been largely linked to different kinds of tumors due to its diverse function. However, the value for ZBTB7A in uterine corpus endometrial carcinoma (UCEC) is unclear.

Methods

In our work, we assessed the importance of ZBTB7A in UCEC. Firstly, Using Oncomine and Tumor Immunoassay Resource (TIMER) databases to evaluate the expression of ZBTB7A. Secondly, we explored the co-expression network of ZBTB7A through the cBioPortal online tool, Metascape, and LinkedOmics. TIMER was also used to explore the relationship between ZBTB7A and tumor immune invasion, and to detect the correlation between the ZBTB7A and the marker genes related to immune infiltration. Finally, CCK8, migration, ChIP assays were introduced to partly validate ZBTB7A function in endometrial cancer cells.

Results

We found the ZBTB7A expression in TIMER was associated with various cancers, especially UCEC. The decreased expression of ZBTB7A was markedly related to the stage and prognosis of UCEC. Furthermore, ZBTB7A was also related to the expression of various immune markers such as Neutrophils, Dendritic cell, T cell (general), Th1, Th2, and Treg. Finally, we verified that ZBTB7A repressed E2F4 transcription and inhibited cells proliferation and migration. These results indicate that ZBTB7A may play a vital role in regulating immune cell infiltration in UCEC, and is a valuable prognostic marker.

Conclusions

In summary, we demonstrate that ZBTB7A is notably downregulated in UCEC, plays a vital role in regulating immune cell infiltration, possesses diagnostic and prognostic values and attenuates E2F4 transcription and cell proliferation, migration in vitro.

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

Background

Uterine corpus endometrial carcinoma (UCEC) is a frequent gynecological malignancy with a poor prognosis particularly at an advanced stage. Herein, this study aims to construct prognostic markers of UCEC based on immune-related genes to predict the prognosis of UCEC.

Methods

We analyzed expression data of 575 UCEC patients from The Cancer Genome Atlas database and immune genes from the ImmPort database, which were used for generation and validation of the signature. We constructed a transcription factor regulatory network based on Cistrome databases, and also performed functional enrichment and pathway analyses for the differentially expressed immune genes. Moreover, the prognostic value of 410 immune genes was determined using the Cox regression analysis. We then constructed and verified a prognostic signature. Finally, we performed immune infiltration analysis using TIMER-generating immune cell content.

Results

The immune cell microenvironment as well as the PI3K-Akt, and MARK signaling pathways were involved in UCEC development. The established prognostic signature revealed a ten-gene prognostic signature, comprising of PDIA3, LTA, PSMC4, TNF, SBDS, HDGF, HTR3E, NR3C1, PGR, and CBLC. This signature showed a strong prognostic ability in both the training and testing sets and thus can be used as an independent tool to predict the prognosis of UCEC. In addition, levels of B cells and neutrophils were significantly correlated with the patient’s risk score, while the expression of ten genes was associated with immune cell infiltrates.

Conclusions

In summary, the ten-gene prognostic signature may guide the selection of the immunotherapy for UCEC.

Multiomics profile and prognostic gene signature of m6A regulators in uterine corpus endometrial carcinoma

Uterine corpus endometrial carcinoma (UCEC) is the most common type of gynecologic malignancy worldwide. Despite advances in the treatments of UCEC, its incidence and mortality rates are still increasing. N6-methyladenosine (m6A) is the most common form of RNA modification and has attracted increasing interest in cancer pathogenesis and progression. Thus, we aimed to identify the landscape of m6A regulators and build a prognostic gene signature in UCEC. In this study, we first analyzed copy number variations (CNVs), single nucleotide variations (SNVs) and gene expression profiles as well as matched clinical information of UCEC patients from The Cancer Genome Atlas (TCGA) database. Next, we determined that CNVs in m6A regulatory genes had a significant negative impact on patient survival. The mRNA expression levels of a total of 16 m6A regulators were significantly correlated with different CNV patterns. Using univariate Cox regression analysis, IGF2BP1, KIAA1429, IGF2BP3, YTHDF3, and IGF2BP2 were found to be closely associated with UCEC patient survival outcomes. Based on the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression models, we built a 3-gene (IGF2BP3, KIAA1429 and IGF2BP1) signature of m6A regulators with prognostic value in UCEC that could effectively predict patient prognosis (log-rank test p-value < 0.0001). In addition, risk scores were significantly different between patients stratified by tumor stage, SNV, and CNV. Multivariate Cox regression analysis suggested that risk score might be an independent prognostic indicator for the overall survival of patients with UCEC (p-value < 0.05). Gene enrichment analysis indicated that high IGF2BP1 gene expression is associated with cytoplasmic stress granules. KIAA1429 gene expression is associated with cellular nucleic acid metabolism. The expression of the IGF2BP3 gene is associated with RNA binding processes. In conclusion, we determined that genetic alterations in m6A regulatory genes could be effective and reliable biomarkers for UCEC prognosis prediction.

A Five-microRNA Signature as Risk Stratification System in Uterine Corpus Endometrial Carcinoma

BACKGROUND

MicroRNAs (miRs) have been shown to play important roles in various cancers and may be a reliable prognostic marker. However, its prognostic value in endometrial carcinoma (UCEC) needs to be further explored.

OBJECTIVES

The aim of this study was to create a miR-based signature to effectively predict the prognosis for patients with uterine corpus endometrial carcinoma (UCEC).

METHODS

Using UCEC data set in TCGA, we identified differentially expressed miRs between UCEC and healthy endometrial tissues. The LASSO method was used to construct a miR-based signature prognosis index for predicting prognosis in the training cohort. The miR-based signature prognosis index was validated in an independent test cohort. MiRNet tool was applied to perform functional enrichment analysis of this miR-based signature.

RESULTS

A total of 208 miRs were differentially expressed between UCEC and healthy endometrial tissues. Five miRs (miR-652, miR-3170, miR-195, miR-34a, and miR-934) were identified to generate a prognosis index (PI). The five-miR signature is a promising biomarker for predicting the 5-year-survival rate of UCEC with AUC = 0.730. The PI remained an independent prognostic factor adjusted by routine clinicopathologic factors. Using the PI, we could successfully identify the high-risk individuals, furthermore, it still worked in an independent test cohort. The five miRs involved in various pathways associated with cancer.

CONCLUSION

We proposed and validated a five-miR signature that could serve as an independent prognostic predictor of UCECs.

Alteration of tumor associated neutrophils by PIK3CA expression in endometrial carcinoma from TCGA data

Uterine corpus endometrial carcinoma (UCEC) is one of the most common cancer in female worldwide. PIK3CA has been proven to be a strong prognostic biomarker in UCEC. Nevertheless, current studies have not investigated what effects PIK3CA had on tumor associated neutrophils (TANss). Kaplan-Meier methods were used to compute the survival time of TCGA UCEC patients. GO and KEGG enrichment analysis unveiled relevant pathways PIK3CA affected using DEGs between PIK3CA high expression group and PIK3CA low expression group in TCGA UCEC, as well as GSEA. immune infiltration status was calculated using TIMER. We found that PIK3CA influenced a number of pathways including immune related pathways. The fraction of TANs was certainly altered by PIK3CA expression in UCEC. Our findings suggest that PIK3CA expression may play an important role in tumor immune microenvironment and could alter fraction of TANs in UCEC.

A six-microRNA signature predicts survival of patients with uterine corpus endometrial carcinoma

Uterine corpus endometrial carcinoma (UCEC) is one of the most common female gynecological malignant tumors that threaten women health seriously. MicroRNAs (miRNAs) has been proved to play critical roles in tumor pathogenesis and malignant progression. In this study, we aimed to explore a novel signature of microRNA expression for predicting the overall survival (OS) of patients with UCEC. The genome-wide miRNA expression profiles and relevant clinical characteristics of 348 patients with UCEC were downloaded from the Cancer Genome Atlas (TCGA) data portal and analyzed comprehensively. A total of 144 miRNAs were confirmed to be expressed differentially in tumor tissues. Among them, 6 miRNAs (hsa-mir-15a.MIMAT0000068, hsa-mir-142.MIMAT0000433, hsa-mir-142.MIMAT0000434, hsa-mir-3170.MIMAT0015045, hsa-mir-1976.MIMAT0009451, and hsa-mir-146a.MIMAT0000449) were validated to be significantly correlated with the OS of patients with UCEC. The risk indictor established by the 6-microRNA signature was proved be an independent prognostic factor (Hazard ratio = 0.391; 95% CI: 0.195-0.783; P = 0.008). In conclusion, we identified miRNAs that were correlated with the occurrence and progression of UCEC and established a 6-microRNA expression signature as a predictor for the OS of patients with UCEC.