Tumor Signature Analysis Implicates Hereditary Cancer Genes in Endometrial Cancer Development.
Ontology highlight
ABSTRACT:
SUBMITTER: Kondrashova O
PROVIDER: S-EPMC8067736 | biostudies-literature | 2021 Apr
REPOSITORIES: biostudies-literature
Publications
Tumor Signature Analysis Implicates Hereditary Cancer Genes in Endometrial Cancer Development.
Kondrashova Olga O Shamsani Jannah J O'Mara Tracy A TA Newell Felicity F McCart Reed Amy E AE Lakhani Sunil R SR Kirk Judy J Pearson John V JV Waddell Nicola N Spurdle Amanda B AB
Cancers 20210407 8
Risk of endometrial cancer (EC) is increased ~2-fold for women with a family history of cancer, partly due to inherited pathogenic variants in mismatch repair (MMR) genes. We explored the role of additional genes as explanation for familial EC presentation by investigating germline and EC tumor sequence data from The Cancer Genome Atlas (<i>n</i> = 539; 308 European ancestry), and germline data from 33 suspected familial European ancestry EC patients demonstrating immunohistochemistry-detected t ...[more]
Similar Datasets
Project description:Uterine corpus endometrial carcinoma locally infiltrates numerous immune cells and other tumor immune microenvironment components. These cells are involved in malignant tumor growth and proliferation and the process of resistance toward immunotherapies. Here, we aimed to develop a tumor immune microenvironment-related prognostic signature for high-risk grade III endometrial carcinoma based on The Cancer Genome Atlas. The signature was systematically correlated with immune infiltration characteristics of the tumor microenvironment. The seven-gene Riskscore signature was robust and performed well in training, testing, and Gene Expression Omnibus-independent cohorts. A nomogram comprising the gene signature accurately predicted patient prognosis, with our model performing better than other endometrial cancer-related signatures. Analysis of the IMvigor210 immunotherapy cohort revealed that subgroups with a low Riskscore had a better prognosis than subgroups with a high Riskscore. Subgroups with a low Riskscore exhibited immune cell infiltration and inflammatory profiles, whereas subgroups with a high Riskscore experienced progressive disease. The receiver operating characteristic curve indicated that risk score, neoantigen, and tumor mutation burden models together accurately predicted treatment response. Taken together, we developed a tumor microenvironment-based seven-gene prognostic stratification system to predict the prognosis of patients with high-risk endometrial cancer and guide more effective immunotherapy strategies.
| S-EPMC8426172 | biostudies-literature
Project description:Tumor mutation burden (TMB) is an essential biomarker to predict immunotherapy response. TMB measurement was mainly evaluated by whole-exome sequencing (WES), which was costly and difficult to be widely applied. In the present study, we aimed to establish and validate a miRNA signature to predict TMB level in endometrial cancer using The Cancer Genome Atlas (TCGA) database. MiRNA expression and somatic mutation profiles of uterine corpus endometrial carcinoma (UCEC) were downloaded from TCGA database. Total 518 patients with UCEC were randomly classified into training set (n=311) and validation set (n=207). Thirty-five differentially expressed miRNAs between high-TMB and low-TMB group were identified in training set. Least absolute shrinkage and selection operator (LASSO) method was performed to select out 26 miRNAs to establish the optimal signature. The accuracy of the miRNA signature for predicting TMB level was 0.833 for training set, 0.749 for validation set and 0.799 for total set. Moreover, the miRNA signature had significant correlation with immune checkpoints related genes (PD-1, PD-L1, CTLA-4) and mismatch repair related genes (BRCA1, BRCA2, MLH1, MSH6) expression. In conclusion, this miRNA signature could predict TMB level in endometrial cancer and might have some merits in providing guidance for immunotherapy in endometrial cancer.
| S-EPMC7670578 | biostudies-literature
Project description:Biomarkers are not only of significant importance for cancer diagnosis and selection of treatment plans but also recently increasingly used for the evaluation of malignancy development and tumor heterogeneity. Large-size tumors from clinical patients can be unique and valuable sources for the study of cancer progression, particularly to the extent of intratumoral heterogeneity. In the present study, we obtained a series of post-surgery puncture samples from a breast cancer patient with a 4 × 3.5 × 2 cm tumor in its original size. Immunohistochemistry for Ki-67, COX-2, and CA IX was performed and the expression levels within the breast cancer tumor mass were evaluated in the reconstructed 3D models. To further evaluate the intratumoral heterogeneity, we performed high throughput whole transcriptome sequencing of 12 samples from different spatial positions within the tumor tissue. Comparing the reconstructed 3D distribution of biomarkers with projected tumor growth models, asymmetric and heterogeneous expansion of tumor mass was found to be possibly influenced by factors such as blood supply, inflammation and/or hypoxia stimulations, as suggested from the correlation between the results of Ki-67 and CA IX or COX-2 staining. Furthermore, high-throughput RNA sequencing data provided additional information for profiling the intratumoral heterogeneity and expanded the understanding of cancer progression. Digital technology for medical imaging once properly integrated with molecular pathology examinations will become particularly helpful in dissecting out in-depth information for precision medicine. We prospect that this approach, facilitated by rapidly advancing artificial intelligence, could provide new insights for clinical decision-making in the future. Strategies for the continuous development from the present study for better performance and application were discussed.
| S-EPMC11480302 | biostudies-literature
Project description:Protein ubiquitination is closely related to tumor occurrence and development. The specific role of ubiquitination in endometrial cancer remains largely unclear. Therefore, we constructed a novel endometrial cancer prognostic model based on ubiquitination-related genes. We extracted the expression matrices of ubiquitination-related genes from the Cancer Genome Atlas database, upon which we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses to obtain 22 ubiquitination-related genes for the construction of the prognostic model. Survival, regression, clinical correlation, and principal component analyses were performed to assess the performance of the model. Drug sensitivity analysis was performed based on these ubiquitination-related genes. Finally, a prognostic nomogram was constructed based on the prognostic model to quantify patient outcomes. Survival, regression, clinical correlation, and principal component analyses revealed that the performance of the prognostic model was satisfactory. Drug sensitivity analysis provided a potential direction for the treatment of endometrial cancer. The prognostic nomogram could be used to effectively estimate the survival rate of patients with endometrial cancer. In summary, we constructed a new endometrial cancer prognostic model and identified 5 differentially expressed, prognosis-associated, ubiquitination-related genes. These 5 genes are potential diagnostic and treatment targets for endometrial cancer. Supplementary Information The online version contains supplementary material available at 10.1186/s12957-022-02875-w.
| S-EPMC9824913 | biostudies-literature
Project description:Endometrial cancer (EC) is the fifth most common cancer in women from developed countries, accounting for 4.8% of new cases and 2.1% of deaths. The genetic basis for the familial risk of endometrial cancer has not been completely defined. Mostly, hereditary EC is part of two syndromes as Lynch syndrome (LS) and Hereditary Breast and Ovarian Cancer syndrome (HBOC). LS is the prototypical hereditary cancer syndrome in EC and accounts for 2-6% of all endometrial cancers. This disease is caused by autosomal dominant mutations in DNA mismatch repair (MMR) genes. Patients carrying a germline mutation in one of the MMR genes have a cumulative lifetime risk to develop EC of 20-70%. HBOC is an autosomal dominantly inherited disease, which mostly predisposes to breast and ovarian cancers, but it can be also associated with other malignancies. HBOC results from germline mutations in BRCA1/2 genes. The aim of this study was to determine the mutational status of a cohort of 40 EC patients, 19 belonging to families with LS and 21 to HBOC. Mutation analysis of MLH1, MSH2, BRCA1 and BRCA2 genes showed pathogenic variants in 17/40 (42.5%) patients. Out of 19 patients belonging to LS families, 8 (42.1%) showed a pathogenic variant. Out of 21 patients belonging to HBOC families, 9 (42.8%) showed a pathogenic variant. 1/21 (4.8%) patient report 1 variant of unknown significance (UV), c.599 C > T (p.T200I), in BRCA2. Moreover, in 1/21 (4.8%) patient we identified a novel missense variant in BRCA2, c.9541A > T (p.Met3181Leu). Mutational analysis was extended to family members, both healthy and cancer affected, of mutated patients; all the tested relatives affected with cancer displayed the pathogenic variant. Our data suggest that patients with hereditary EC have a high percentage of mutations in the LS and HBOC main susceptibility genes; therefore, the surveillance for EC, already indicated in LS patients, should also be recommended for patients with HBOC.
| S-EPMC7826304 | biostudies-literature
Project description:The occurrence and progression of tumors are linked to the process of pyroptosis. However, the precise involvement of pyroptosis-associated genes (PRGs) in endometrial cancer (EC) remains uncertain. 29 PRGs were identified as being either up-regulated or down-regulated in EC. PRGs subgroup analysis demonstrated distinct survival outcomes and diverse responses to chemotherapy and immune checkpoint blockade therapy. A higher expression of GPX4 and NOD2, coupled with lower levels of CASP6, PRKACA, and NLRP2, were found to be significantly associated with higher overall survival (OS) rates (p < 0.05). Conversely, lower expression of NOD2 was linked to lower progression-free survival (p = 0.021) and advanced tumor stage(p = 0.0024). NOD2, NLRP2, and TNM stages were identified as independent prognostic factors (p < 0.001). The LASSO prognostic model exhibited a notable decrease in OS among EC patients in the high-risk score group (ROC-AUC10-years: 0.799, p = 0.00644). Furthermore, NOD2 displayed a positive correlation with the infiltration of immune cells and the expression of immune checkpoints (p < 0.001). GPX4 and CASP6 are significantly associated with TMB and MSI (RTMB = 0.39; RMSI = 0.23). Additionally, a substantial upregulation of NOD2 was confirmed in both EC cells and tissue, indicating a positive relationship between advanced TNM stage (p < 0.0001) and infiltration of M1 phenotype macrophages. Nonetheless, its impact on patient OS did not reach statistical significance (p = 0.141). Our findings have contributed to the advancement of a prognostic model for EC patients. NOD2 receptor-mediated pyroptosis mechanism potentially regulates tumor immunity and promotes the transformation of macrophages from the M2 phenotype to the M1 phenotype, which significantly impacts the progression of EC.
| S-EPMC11393226 | biostudies-literature
Project description:Cervical cancer and endometrial cancer remain serious threats to women's health. Even though some patients can be treated with surgery plus chemoradiotherapy as a conventional option, the overall efficacy is deemed unsatisfactory. As such, the development for new treatment approaches is truly necessary. In recent years, immunotherapy has been widely used in clinical practice and it is an area of great interest that researchers are keeping attention on. However, a thorough immune-related genes (IRGs) study for cervical cancer and endometrial cancer is still lacking. We therefore aim to make a comprehensive evaluation of IRGs through bioinformatics and large databases, and also investigate the relationship between the two types of cancer. We reviewed the transcriptome RNAs of IRGs and clinical data based on the TCGA database. Survival-associated IRGs in cervical/endometrial cancer were identified using univariable and multivariable Cox proportional-hazard regression analysis for developing an IRG signature model to evaluate the risk of patients. In the end, this model was validated based on the enrichment analyses through GO, KEGG, and GSEA pathways, Kaplan-Meier survival curve, ROC curves, and immune cell infiltration. Our results showed that out of 25/23 survival-associated IRGs for cervical/endometrial cancer, 13/12 warranted further examination by multivariate Cox proportional-hazard regression analysis and were selected to develop an IRGs signature model. As a result, enrichment analyses for high-risk groups indicated main enriched pathways were associated with tumor development and progression, and statistical differences were found between high-risk and low-risk groups as shown by Kaplan-Meier survival curve. This model could be used as an independent measure for risk assessment and was considered relevant to immune cell infiltration, but it had nothing to do with clinicopathological characteristics. In summary, based on comprehensive analysis, we obtained the IRGs signature model in cervical cancer (LTA, TFRC, TYK2, DLL4, CSK, JUND, NFATC4, SBDS, FLT1, IL17RD, IL3RA, SDC1, PLAU) and endometrial cancer (LTA, PSMC4, KAL1, TNF, SBDS, HDGF, LTB, HTR3E, NR2F1, NR3C1, PGR, CBLC), which can effectively evaluate the prognosis and risk of patients and provide justification in immunology for further researches.
| S-EPMC7385326 | biostudies-literature
Project description:BackgroundThe epithelial-mesenchymal transition (EMT) plays an indispensable role in the development and progression of Endometrial cancer (EC). Nevertheless, little evidence is reported to uncover the functionality and application of EMT-related molecules in the prognosis of EC. This study aims to develop novel molecular markers for prognosis prediction in patients with EC.MethodsRNA sequencing profiles of EC patients obtained from The Cancer Genome Atlas (TCGA) database were used to screen differential expression genes (DEGs) between tumors and normal tissues. The Cox regression model with the LASSO method was utilized to identify survival-related DEGs and to establish a prognostic signature whose performance was evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC) and calibration curve. Eventually, functional enrichment analysis and cellular experiments were performed to reveal the roles of prognosis-related genes in EC progression.ResultsA total of 540 EMT-related DEGs in EC were screened, and subsequently a four-gene risk signature comprising SIRT2, SIX1, CDKN2A and PGR was established to predict overall survival of EC. This risk signature could serve as a meaningfully independent indicator for EC prognosis via multivariate Cox regression (HR = 2.002, 95%CI = 1.433-2.798; P < 0.001). The nomogram integrating the risk signature and clinical characteristics exhibited robust validity and performance at predicting EC overall survival indicated by ROC and calibration curve. Functional enrichment analysis revealed that the EMT-related genes risk signature was associated with extracellular matrix organization, mesenchymal development and cellular component morphogenesis, suggesting its possible relevance to epithelial-mesenchymal transition and cancer progression. Functionally, we demonstrated that the silencing of SIX1, SIRT2 and CDKN2A expression could accelerate the migratory and invasive capacities of tumor cells, whereas the downregulation of PGR dramatically inhibited cancer cells migration and invasion.ConclusionsAltogether, a novel four-EMT-related genes signature was a potential biomarker for EC prognosis. These findings might help to ameliorate the individualized prognostication and therapeutic treatment of EC patients.
| S-EPMC10506329 | biostudies-literature
Project description:BackgroundsEpithelial-mesenchymal transition (EMT) is a sequential process where tumor cells develop from the epithelial state to the mesenchymal state. EMT contributes to various tumor functions including initiation, propagating potential, and resistance to therapy, thus affecting the survival time of patients. The aim of this research is to set up an EMT-related prognostic signature for endometrial cancer (EC).MethodsEMT-related gene (ERG) expression and clinical data were acquired from The Cancer Genome Atlas (TCGA). The entire set was randomly divided into two sets, one for contributing the risk model (risk score) and the other for validating. Univariate and multivariate Cox proportional hazards regression analyses were applied to the training set to select the prognostic ERGs. The expression of 10 ERGs was confirmed by qRT-PCR in clinical samples. Then, we developed a nomogram predicting 1-/3-/5-year survival possibility combining the risk score and clinical factors. The entire set was stratified into the high- and low-risk groups, which was used to analyze the immune infiltrating, tumorigenesis pathways, and response to drugs.ResultsA total of 220 genes were screened out from 1,316 ERGs for their differential expression in tumor versus normal. Next, 10 genes were found to be associated with overall survival (OS) in EC, and the expression was validated by qRT-PCR using clinical samples, so we constructed a 10-ERG-based risk score to distinguish high-/low-risk patients and a nomogram to predict survival rate. The calibration plots proved the predictive value of our model. Gene Set Enrichment Analysis (GSEA) discovered that in the low-risk group, immune-related pathways were enriched; in the high-risk group, tumorigenesis pathways were enriched. The low-risk group showed more immune activities, higher tumor mutational burden (TMB), and higher CTAL4/PD1 expression, which was in line with a better response to immune checkpoint inhibitors. Nevertheless, response to chemotherapeutic drugs turned out better in the high-risk group. The high-risk group had higher N 6-methyladenosine (m6A) RNA expression, microsatellite instability level, and stemness indices.ConclusionWe constructed the ERG-related signature model to predict the prognosis of EC patients. What is more, it might offer a reference for predicting individualized response to immune checkpoint inhibitors and chemotherapeutic drugs.
| S-EPMC8795518 | biostudies-literature
Project description:BackgroundUterus corpus endometrial cancer (UCEC) is the main malignant tumor in gynecology, with a high degree of heterogeneity, especially in terms of prognosis and immunotherapy efficacy. DNA methylation is one of the most important epigenetic modifications. Studying DNA methylation can help predict the prognosis of cancer patients and provide help for clinical treatment. Our research aims to discover whether abnormal DNA methylation can predict the prognosis of UCEC and reflect the patient's tumor immune microenvironment.Patients and methodsThe clinical data, DNA methylation data, gene expression data and somatic mutation data of UCEC patients were all downloaded from the TCGA database. The MethylMix algorithm was used to integrate DNA methylation data and mRNA expression data. Univariate Cox regression analysis, Multivariate Cox regression analysis, and Lasso Cox regression analysis were used to determine prognostic DNA methylation-driven genes and to construct an independent prognostic index (MDS). ROC curve analysis and Kaplan-Meier survival curve analysis were used to evaluate the predictive ability of MDS. GSEA analysis was used to explore possible mechanisms that contribute to the heterogeneity of the prognosis of UCEC patients.Results3 differential methylation-driven genes (DMDGs) (PARVG, SYNE4 and CDO1) were considered as predictors of poor prognosis in UCEC. An independent prognostic index was finally established based on 3 DMDGs. From the results of ROC curve analysis and survival curve analysis, MDS showed excellent prognostic ability in TCGA-UCEC. A new nomogram based on MDS and other prognostic clinical indicators has also been successfully established. The C-index of the nomogram for OS prediction was 0.764 (95% CI = 0.702-0.826). GSEA analysis suggests that there were differences in immune-related pathways among patients with different prognosis. The abundance of M2 macrophages and M0 macrophages were significantly enhanced in the high-risk group while T cells CD8, Eosinophils and Neutrophils were markedly elevated in the low-risk group. Meanwhile, patients in the low-risk group had higher levels of immunosuppressant expression, higher tumor mutational burden and immunophenoscore (IPS) scores. Joint survival analysis revealed that 7 methylation-driven genes could be independent prognostic factors for overall survival for UCEC.ConclusionWe have successfully established a risk model based on 3 DMDGs, which could accurately predict the prognosis of patients with UCEC and reflect the tumor immune microenvironment.
| S-EPMC8272318 | biostudies-literature