Dataset Information

PPP1R14B is a diagnostic prognostic marker in patients with uterine corpus endometrial carcinoma.

ABSTRACT: Uterine corpus endometrial carcinoma (UCEC) is one of the most common malignancies of the female genital tract. A recently discovered protein-coding gene, PPP1R14B, can inhibit protein phosphatase 1 (PP1) as well as different PP1 holoenzymes, which are important proteins regulating cell growth, the cell cycle, and apoptosis. However, the association between PPP1R14B expression and UCEC remains undefined. The expression profiles of PPP1R14B in multiple cancers were analysed based on TCGA and GTE databases. Then, PPP1R14B expression in UCEC was investigated by gene differential analysis and single gene correlation analysis. In addition, we performed gene ontology term analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, gene set enrichment analysis, and Kaplan-Meier survival analysis to predict the potential function of PPP1R14B and its role in the prognosis of UCEC patients. Then, a tool for predicting the prognosis of UCEC, namely, a nomogram model, was constructed. PPP1R14B expression was higher in UCEC tumour tissues than in normal tissues. The results revealed that PPP1R14B expression was indeed closely associated with tumour development. The results of Kaplan-Meier plotter data indicated that patients with high PPP1R14b expression had poorer overall survival, disease-specific survival, and progression-free interval than those with low expression. A nomogram based on the results of multifactor Cox regression was generated. PPP1R14B is a key player in UCEC progression, is associated with a range of adverse outcomes, and can serve as a prognostic marker in the clinic.

SUBMITTER: He K

PROVIDER: S-EPMC10002989 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

PPP1R14B is a diagnostic prognostic marker in patients with uterine corpus endometrial carcinoma.

He Kang K Wang Taiwei T Huang Xuemiao X Yang Zhaoyun Z Wang Zeyu Z Zhang Shuang S Sui Xin X Jiang Junjie J Zhao Lijing L Zhao Lijing L

Journal of cellular and molecular medicine 20230223 6

Uterine corpus endometrial carcinoma (UCEC) is one of the most common malignancies of the female genital tract. A recently discovered protein-coding gene, PPP1R14B, can inhibit protein phosphatase 1 (PP1) as well as different PP1 holoenzymes, which are important proteins regulating cell growth, the cell cycle, and apoptosis. However, the association between PPP1R14B expression and UCEC remains undefined. The expression profiles of PPP1R14B in multiple cancers were analysed based on TCGA and GTE ...[more]

PMID: 36824011

Similar Datasets

Project description:BackgroundThe incidence and mortality of uterine corpus endometrial carcinoma (UCEC) are increasing yearly. There is currently no screening test for UCEC, and progress in its treatment is limited. It is important to identify new biomarkers for screening, diagnosing and predicting the outcomes of UCEC. A large number of previous studies have proven that KNL1 is crucial in the development of lung cancer, colorectal cancer and cervical cancer, but there is a lack of studies about the role of KNL1 in the development of UCEC.MethodsThe mRNA and protein expression data of KNL1 in The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and UALCAN databases and related clinical data were used to analyze the expression differences and clinical correlations of KNL1 in UCEC. A total of 108 clinical samples were collected, and the results of bioinformatics analysis were verified by immunohistochemistry. KNL1 and its related differentially expressed genes were used to draw a volcano map, construct a PPI protein interaction network, and perform gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA) and immune infiltration analysis to predict the function of KNL1 during UCEC progression. The prognostic data of TCGA and 108 clinical patients were used to analyze the correlation of KNL1 expression with the survival of patients, and KM survival curves were drawn. The UCEC cell lines Ishikawa and Hec-1-A were used to verify the function of KNL1.ResultsKNL1 is significantly overexpressed in UCEC and is associated with a poor prognosis. KNL1 overexpression is closely related to cell mitosis, the cell cycle and other functions and is correlated with the International Federation of Gynecology and Obstetrics (FIGO) stage, histological grade and other characteristics of UCEC patients. Knockdown of KNL1 expression in UCEC cell lines can inhibit their proliferation, invasion, metastasis and other phenotypes.ConclusionKNL1 is a prognostic and diagnostic biomarker associated with immune evasion in patients with UCEC.

Project description:Background:Uterine corpus endometrial carcinoma (UCEC) is a clinically heterogeneous disease, and this heterogeneity is associated with tumor development, clinical characteristics, and prognostic outcomes. Mutant-allele tumor heterogeneity (MATH) is a novel, non-biased, quantitative measure to assess intra-tumor heterogeneity based on next-generation sequencing data. We aimed to explore the use of MATH as a measure for tumor heterogeneity and its prognostic role in UCEC patients. Methods:We calculated MATH scores from the available data of 560 UCEC patients from The Cancer Genome Atlas (TCGA) and investigated their correlations with clinical characteristics, genetic alterations, and overall survival. Predictive accuracy was quantified using the area under the receiver operating characteristic curve (AUC) and the index of concordance (C-index). Results:In total, 242 MATH scores were obtained from the UCEC cohort. MATH scores were significantly related to age, race, cancer type, clinical stage, histological grade, molecular type, targeted molecular therapy, and hormonal therapy. Furthermore, the genomic pattern on the basis of MATH scores showed that mutation rates of TP53 (tumor protein p53) and ARID1A (AT-rich interaction domain 1A) were independently associated with MATH scores. Correlation analysis revealed a significantly positive association of MATH scores with the fraction of somatic copy number alteration (SCNA). Importantly, a high MATH score was significantly associated with shorter overall survival [hazard ratio (HR), 2.342; 95% confidence interval (CI), 1.110-4.942]. Multivariate Cox regression combined with stratified analysis revealed that the MATH score is an independent prognostic factor in UCEC patients under 60 years old, and predictive quantification showed the MATH score had an AUC of 0.756 and a C-index of 0.845. Conclusions:Our results suggest that MATH, a practical and useful way to measure intra-tumor heterogeneity, may serve as a significant biomarker for the prognosis of patients with UCEC, enabling more accurate prediction of clinical outcomes.

Project description: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.

Project description: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.

Project description:BackgroundLeukemia inhibitory factor (LIF) exhibits significant tumor-promoting function, while its cognate receptor (LIFR) is considered to act as either a tumor promoter or suppressor. Dysregulation of LIF and LIFR is associated with the initiation, progression and metastasis of multiple cancer entities. Although increasing numbers of studies are revealing an indispensable critical role of LIFR in tumorigenesis for various different cancers, no systematic analysis of LIFR has appeared thus far.MethodsHere, we comprehensively analyzed the expression profile and prognostic value of LIFR, and correlations between LIFR and the infiltration of immune cells and clinicopathological parameters across different tumor types using several bioinformatic tools. The expression profile of LIFR in various tumor types and clinical stages was investigated using the TIMER2 and GEPIA2 databases. Genetic alternations of LIFR were extracted from cBioPortal. The prognostic value of LIFR was assessed using GEPIA2 and Sanger box databases, and correlations between LIFR expression and immune infiltration were analyzed using the CIBERSORT method and TIMER2 database. The correlations between LIFR expression and immune and stromal scores were assessed using ESTIMATE. We also analyzed correlations between LIFR and immunoregulators. Finally, we detected an effect of LIFR on Uterine Corpus Endometrial Carcinoma (UCEC) and evaluated the expression level of LIFR in clinical UCEC samples.ResultsAberrant expression of LIFR in cancers and its prognosis ability, especially in UCEC was documented. Significantly lower levels of LIFR expression level correlated with better prognosis in multiple tumor types. LIFR expression was positively correlated with the abundance of cancer-associated fibroblasts (CAFs) and endothelial cells in the tumor microenvironment. Additionally, LIFR expression was strongly associated with the presence of immune modulators and checkpoint genes. Overexpression of LIFR suppressed the migration and invasion of UCEC cells in vitro.ConclusionOur pan-cancer detection data provided a novel understanding of the roles of LIFR in oncogenesis.

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

Dataset Information

PPP1R14B is a diagnostic prognostic marker in patients with uterine corpus endometrial carcinoma.

Publications

PPP1R14B is a diagnostic prognostic marker in patients with uterine corpus endometrial carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets