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BTG1 inhibits malignancy as a novel prognosis signature in endometrial carcinoma.

ABSTRACT: Background:Endometrial carcinoma (EC) is one of the three major malignant tumors of the female reproductive system. In recent years, the incidence and mortality rate of EC have increased. B-cell translocation gene 1 (BTG1) is an anti-proliferation gene that regulates the occurrence and development of a variety of tumors, but there is no research regarding this gene in EC. Methods:Based on The Cancer Genome Atlas (TCGA) database, we used a variety of bioinformatics tools and databases to explore the expression and prognosis of BTG1. We verified expression and prognosis of BTG1 in EC using qRT-PCR and analyzed the relevant clinicopathological parameters. We functionally enriched BTG1 and related genes in EC patients through the bioinformatics website and analyzed miRNA targets of BTG1 and interacting protein networks. Cell proliferation, wound healing, transwell invasion, and cell apoptosis assays were used to detect the effects of BTG1 on the malignant biological behavior of endometrial carcinoma cells (ECCs). The effect of BTG1 on the epithelial-to-mesenchymal transition (EMT) process was detected using western blot. Results:We analyzed the expression and prognosis of BTG1 based on TCGA and found that low expression of BTG1 was associated with poor EC prognosis. The qRT-PCR suggested that BTG1 had low expression in EC. BTG1 expression was significantly correlated with overall survival (OS) shortening. Clinicopathological analysis suggested that expression of BTG1 was related to invasion depth and the International Federation of Gynecology and Obstetrics (FIGO) stage. EC pathological tissue type, fertility history, lymphatic metastasis, menopause, estrogen receptor (ER), progesterone receptor (PR), and age of diagnosis were not related. Functional enrichment analysis showed that BTG1 plays an important role in regulating embryonic development, tumorigenesis, apoptosis, and cell cycle. Biological behavior experiments suggest that BTG1 inhibits proliferation, migration, and invasion of ECCs, and promotes apoptosis of ECCs. Western blot indicated that BTG1 inhibited the EMT process of ECCs. Conclusions:BTG1, as a tumor suppressor gene, plays an important role in the occurrence and development of EC. We believe that BTG1 can be used as a potential prognostic biomarker for EC.

SUBMITTER: Li Y

PROVIDER: S-EPMC7542768 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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BTG1 inhibits malignancy as a novel prognosis signature in endometrial carcinoma.

Li Yibing Y Huo Jianing J He Junjian J Zhang Yunzheng Y Ma Xiaoxin X Ma Xiaoxin X

Cancer cell international 20201007

<h4>Background</h4>Endometrial carcinoma (EC) is one of the three major malignant tumors of the female reproductive system. In recent years, the incidence and mortality rate of EC have increased. B-cell translocation gene 1 (BTG1) is an anti-proliferation gene that regulates the occurrence and development of a variety of tumors, but there is no research regarding this gene in EC.<h4>Methods</h4>Based on The Cancer Genome Atlas (TCGA) database, we used a variety of bioinformatics tools and databa ...[more]

PMID: 33041670

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Project description:Background TP53 mutations are associated with poor outcome for patients with endometrial carcinoma (EC). However, to date, there have been no studies focused on the construction of TP53 mutational status-associated signature in EC. In this study, we aim to conduct a TP53 mutation-associated prognostic gene signature for EC. Methods Hence, we explored the mutational landscape of TP53 in patients with EC based on the simple nucleotide variation data downloaded from The Cancer Genome Atlas (TCGA) database. Differential expression analysis and least absolute shrinkage and selection operator (LASSO)–Cox analysis was used to establish TP53 mutation-associated prognostic gene signature. The overall survival rate between the high-risk and low-risk groups was compared by the Kaplan–Meier (K-M) method. Results We found that the TP53 mutation was associated with poor outcome, older age, lower BMI, and higher grade and stage of EC in patients. A TP53 mutational status-associated signature was established based on transcriptome profiling data. Moreover, the patients in TCGA database were categorized into high- and low-risk groups. Kaplan–Meier (K-M) analysis indicated that the patients in the high-risk group have poor survival outcome. Furthermore, receiver operating characteristic (ROC) curves confirmed the robust prognostic prediction efficiency of the TP53 mutational status-associated signature. Finally, the prognostic ability was successfully verified in the other two datasets from cBioPortal database as well as in 60 clinical specimens. Univariate (hazard ratio (HR) = 1.041, 95%CI = 1.031–1.051, p < 0.001) and multivariate (hazard ratio (HR) = 1.029, 95%CI = 1.018–1.040, p < 0.001) Cox regression analyses indicated that the TP53 mutational status-associated signature could be used as an independent prognostic factor for EC patients. Conclusion In summary, our research constructed a powerful TP53 mutational status-associated signature that could be a potential novel prognostic biomarker and therapeutic target for EC.

Project description: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.

Project description:Endometrial cancer (UCEC) is a complex malignant tumor characterized by both genetic level and clinical trial. Patients with UCEC exhibit the similar clinical features, however, they have distinct outcomes due to molecular heterogeneity. The aim of this study was to access the prognostic value of long non-coding RNAs (lncRNAs) in UCEC patients and to identify potential lncRNA signature for predicting patients' survival and improving patient-tailored treatment.We performed a comprehensive genome-wide analysis of lncRNA expression profiles and clinical data in a large cohort of 301 UCEC patients. UCEC patients were randomly divided into the discovery cohort (n?=?150) and validation cohort (n?=?151). A novel lncRNA-focus expression signature was identified in the discovery cohort, and independently accessed in the validation cohort. Additionally, the lncRNA signature was evaluated by multivariable Cox regression and stratification analysis as well as functional enrichment analysis.We detected a novel lncRNA-focus expression signature (LFES) consisting of 11 lncRNAs that were associated with survival based on risk scoring strategy in UCEC. The risk score based on the LFES was able to separate patients of discovery cohort into high-risk and low-risk groups with significantly different overall survival and progression-free survival, and has been successfully confirmed in the validation cohort. Furthermore, the LFES is an independent prognostic predictor of survival and demonstrates superior prognostic performance compared with the clinical covariates for predicting 5-year survival (AUC?=?0.887). Functional analysis has linked the expression of prognostic lncRNAs to well-known tumor suppressor or ontogenetic pathways in endometrial carcinogenesis.Our study revealed a novel 11-lncRNA signature to predict survival of UCEC patient. This lncRNA signature may be a valuable and alternative marker for risk evaluation to aid patient-tailored treatment and improve the outcome of patients with UCEC.

Project description:The aim of this study was to build a prognostic model for endometrial cancer (EC) patients based on RNA-binding proteins (RBPs). RNA sequencing and clinical data for uterine corpus EC (UCEC) were obtained from The Cancer Genome Atlas (TCGA). Univariate and multivariate Cox regression analysis were used to obtain the following risk formula: score = sum (corresponding coefficient × expression of each gene). A nomogram was developed to accurately predict patient survival based on risk score, age, stage, and grade. Immunohistochemistry (IHC) was used to verify the expression of RBPs in EC. The mRNA expression of RBPs was measured by qRT-PCR. The effects of RBPs on the malignant biologic behavior of EC were detected using CCK-8, colony formation, and transwell invasion assays. A novel prognostic signature was constructed, comprising three RBPs (CD3EAP, SBDS, and TDRKH). The risk score was: Risk score = (0.860 × CD3EAP expression) + (0.622 × 6SBDS expression) + (0.427 × 4TDRKH expression). The area under the receiver operating characteristic curves (AUCs) of risk score for 1-, 3-, and 5-year overall survival (OS) was 0.75, 0.68, and 0.65, respectively. The AUCs of the nomogram for 1-, 3-, and 5-year OS were 0.811, 0.793, and 0.814, respectively. In our independent cohort, the IHC results revealed that CD3EAP (P < 0.001) and TDRKH (P < 0.001) were upregulated and SBDS (P < 0.001) was downregulated in EC. Immunostaining showed the expression levels of CD3EAP, SBDS and TDRKH for each patient and these were multiplied by their respective coefficients of 0.860, 0.622 and 0.427 to obtain the risk scores. The AUCs of risk score for 1-, 3-, and 5-year OS were 0.888, 0.793, and 0.780 respectively. The AUCs of the nomogram for 1-, 3-, and 5-year OS were 0.790, 0.826, and 0.906, respectively. Cell functional experiments also confirmed the influence of the key RBPs on the malignant biologic behavior of EC. In summary, a characteristic model based on our three RBPs accurately predicted the prognosis of EC. Our in-depth analysis of these RBPs may inform the development of novel strategies for the diagnosis and treatment of EC.

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BTG1 inhibits malignancy as a novel prognosis signature in endometrial carcinoma.

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BTG1 inhibits malignancy as a novel prognosis signature in endometrial carcinoma.

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