Dataset Information

Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma.

ABSTRACT: 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.

SUBMITTER: Hou Y

PROVIDER: S-EPMC7186654 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma.

Hou Yufang Y Li Tiegang T Gan Wenqiang W Lv Silin S Zeng Zifan Z Yan Zheng Z Wang Weiqi W Yang Min M

Annals of translational medicine 20200301 6

<h4>Background</h4>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.<h4>Meth ...[more]

PMID: 32355783

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

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:BackgroundUCEC is the most common gynecological malignancy in many countries, and its mechanism of occurrence and development is related to tumor mutation burden (TMB) and immune cell infiltration. Therefore, it is necessary to systematically explore the TMB-related gene profile in immune cells to improve the prognosis of UCEC.MethodsWe integrated TMB-related genes with basic clinical information of UCEC patients based on TCGA dataset. Differentially expressed genes (DEGs) were selected through differential expression screening, PPI, and enrichment analysis. Additionally, we analyzed the components of immune cell infiltration of the DEGs to obtain the differential immunity-related genes. A single factor and multifactor Cox regression analyses were conducted to establish new prognostic indicators of OS and DFS based on TMB-related immune genes. To further study the correlation between survival and immune cell infiltration, a Cox model based on these immune infiltration compositions was built. Using the clinical variables, we established nomograms for OS and DFS.Results393 DEGs were significantly associated with clinical outcomes and the immune component in patients with UCEC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway and protein-protein interaction network (PPI) analyses revealed the role of these genes and information on related pathways. Then, two prognostic models were established based on the differential immune genes for OS (GFAP and MX2) and DFS (MX2, GFAP, IGHM, FGF20, and TRAV21). In DFS, the differential immune genes were related to CD4+?T cell, CD8+?T cell, macrophage, and neutrophil (all P?<?0.05). B cell and CD8+?T cell were independent prognostic factors from among the immune cell elements in UCEC. Finally, the risk scores of these models were combined with the clinical elements-based nomogram models, and the AUC values were all over 0.7.ConclusionsOur results identified several clinically significant differential immune genes and established relevant prognostic models, providing a basis for the molecular analysis of TMB and immune cells in UCEC, and identified potential prognostic and immune-related genes for UCEC. We added clinical related conditions for further analysis to confirm the identity of the genes and clinical elements-based models.

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.

Project description:Mammaglobin B, also referred to as secretoglobin family 2A member 1 (SCGB2A1), has been reported to be highly expressed in uterine corpus endometrial cancer (UCEC) compared with in the normal endometrium. However, the prognostic value of SCGB2A1 in UCEC remains unclear. The Oncomine, The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium databases were used to explore the differential expression of SCGB2A1. Furthermore, data of patients with UCEC were downloaded from TCGA, and logistic regression analysis, survival analysis, univariate and multivariate analyses, and nomogram construction were performed to identify its prognostic value in UCEC. Additionally, gene set enrichment analysis (GSEA) was utilized to estimate the mechanisms of SCGB2A1 in UCEC. Finally, immune infiltration of SCGB2A1 in UCEC was analyzed using the Tumor Immune Estimation Resource. Decreased mRNA and protein expression levels of SCGB2A1 were significantly associated with poor prognostic clinicopathological characteristics (all P<0.05). Additionally, low expression levels of SCGB2A1 were associated with decreased survival of patients with UCEC compared with high expression levels of SCGB2A1. Furthermore, the independent prognostic value of SCGB2A1 in UCEC was identified by univariate and multivariate analyses. A nomogram based on 6 variables, including SCGB2A1 expression, was developed for the estimation of the 1-, 3-, and 5-year survival probability in UCEC. Additionally, GSEA suggested that the vascular endothelial growth factor, PTEN, platelet-derived growth factor, DNA repair, KRAS signaling, and PI3K-AKT-mTOR signaling pathways were differentially enriched in the low SCGB2A1 expression phenotype. Finally, high infiltration levels of CD8+ T cells were associated with SCGB2A1 in UCEC and this was associated with prognosis. The present results indicated that SCGB2A1 may be a promising independent prognostic factor in UCEC. These signaling pathways may be crucial for the regulation of UCEC via SCGB2A1.

Project description:In the present study, the RNA sequencing (RNA-seq) data of uterine corpus endometrial carcinoma (UCEC) samples were collected and analyzed using bioinformatics tools to identify potential genes associated with the development of UCEC. UCEC RNA-seq data were downloaded from The Cancer Genome Atlas database. Differential analysis was performed using edgeR software. A false discovery rate <0.01 and |log2(fold change)|>1 were set as the cut-off criteria to screen for differentially expressed genes (DEGs). Differential gene co-expression analysis was performed using R/EBcoexpress package in R. DEGs in the gene co-expression network were subjected to Gene Ontology analysis using the Database for Annotation, Visualization and Integration Discovery. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was also performed on the DEGs using KOBAS 2.0 software. The ConnectivityMap database was used to identify novel drug candidates. A total of 3,742 DEGs were identified among the 552 UCEC samples and 35 normal controls, and comprised 2,580 upregulated and 1,162 downregulated genes. A gene co-expression network consisting of 129 DEGs and 368 edges was constructed. Genes were associated with the cell cycle and the tumor protein p53 signaling pathway. Three modules were identified, in which genes were associated with the mitotic cell cycle, nuclear division and the M phase of the mitotic cell cycle. Multiple key hub genes were identified, including cell division cycle 20, cyclin B2, non-SMC condensin I complex subunit H, BUB1 mitotic checkpoint serine/threonine kinase, cell division cycle associated 8, maternal embryonic leucine zipper kinase, MYB proto-oncogene like 2, TPX2, microtubule nucleation factor and non-SMC condensin I complex subunit G. In addition, the small molecule drug esculetin was implicated in the suppression of UCEC progression. Overall, the present study identified multiple key genes in UCEC and clinically relevant small molecule agents, thereby improving our understanding of UCEC and expanding perspectives on targeted therapy for this type of cancer.

Dataset Information

Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma.

Publications

Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma.

Similar Datasets

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