BHLHE22 Expression Is Associated with a Proinflammatory Immune Microenvironment and Confers a Favorable Prognosis in Endometrial Cancer.
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SUBMITTER: Darmawi
PROVIDER: S-EPMC9266305 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Endometrial cancer (EnC) is a malignant gynecological tumor commonly observed in developed countries, specifically among post?menopausal women. Although numerous patients with EnC receive promising prognoses, those with advanced or metastatic disease often have a poor prognosis and an impaired quality of life. Tripartite motif?containing 22 (TRIM22) has been confirmed to play many crucial roles in different biological processes, from inflammatory to tumorigenesis. However, the multifaceted roles of TRIM22 in EnC remain uncharacterized. Herein, comparing normal endometrial tissues with tumor tissues obtained from patients, it was concluded that TRIM22 expression was decreased in tumor tissues. However, the overexpression of TRIM22 served to inhibit the migratory, invasive, proliferative and cell cycle activity of EnC cells. Moreover, the knockdown of TRIM22 increased the migratory, invasive, and proliferative activity of the EnC cells. Furthermore, it was found that TRIM22 effectively suppressed EnC progression through the nucleotide binding oligomerization domain containing 2 (NOD2)/nuclear factor (NF)??B pathway. The data also demonstrated that TRIM22 functions as an inhibitor of EnC tumor xenograft growth in vivo. Overall, the findings of the present study define a novel regulatory role for TRIM22 in EnC progression. Moreover, TRIM22 may serve as an important prognostic predictor for EnC.
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Project description:The incidence of endometrial cancer is increasing each year, and treatment effects are poor for patients with advanced and specific subtypes. Exploring immune infiltration-related factors in endometrial cancer can aid in the prognosis of patients and provide new immunotherapy targets. We downloaded immune metagene and functional data of patients with different subtypes of endometrial cancer from The Cancer Genome Atlas database and selected the lymphocyte-specific kinase (LCK) metagene as a representative genetic marker of the immune microenvironment in endometrial cancer. The results showed that LCK metagene expression is related to the prognosis of patients with endometrioid endometrial adenocarcinoma subtypes and highly correlated with the PTEN and PIK3CA mutational status. A search for LCK-related modules returned seven independent genetic predictors of survival in patients with endometrial cancer. The TIMER algorithm showed that the expression of these seven genes was positively correlated with the infiltration levels of six types of immune cells. The diagnostic value of these markers was validated using real-time quantitative PCR and immunohistochemical methods. Our results identified CD74, HLA-DRB5, CD52, HLA-DPB1 and HLA-DRB1 as possible valuable genetic markers for the diagnosis and prognosis of endometrial cancer and provided a theoretical basis for immunotherapy targets for its clinical treatment.
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Project description:CKLF-like MARVEL transmembrane domain-containing 6 (CMTM6), a programmed death-ligand 1 (PD-L1) regulator, is widely expressed in various tumors and regulates the immune microenvironment. However, its prognostic value remains controversial, and the roles of CMTM6 in colorectal cancer (CRC) are still unknown. In this study, we aimed to elaborate the expression patterns of CMTM6 and PD-L1 in CRC and investigate their relationship with the infiltration of T cells and the prognosis of patients with CRC. Analysis of CMTM6 mRNA levels, gene ontology enrichment analysis and single-sample gene set enrichment analysis were performed in a The Cancer Genome Atlas colon cancer cohort. The expression of CMTM6 and PD-L1 and the infiltration of T cells in tumor tissues from our cohort containing 156 patients with CRC receiving adjuvant chemotherapy and 77 patients with CRC without chemotherapy were examined by immunohistochemistry assay. CMTM6 expression was upregulated in CRC compared with normal colon tissues, and CMTM6 levels were lower in advanced tumors than in early-stage tumors. High expression of CMTM6 correlated with lower pT stage and more CD4+/CD8+ tumor-infiltrating lymphocytes (TILs) and predicted a favorable prognosis in CRC. PD-L1 was expressed in CRC tissues at a low level, and PD-L1 positivity in tumor stroma (PD-L1(TS)), but not PD-L1 positivity in cancer cells (PD-L1(CC)), was associated with an increased density of CD4+ TILs and a favorable prognosis. The coexpression status of CMTM6 and PD-L1(TS) divided patients with CRC into three groups with low, moderate and high risks of progression and death, and patients with CMTM6High/PD-L1(TS)+ status had the longest survival. Moreover, the prognostic value of CMTM6/PD-L1 expression was more significant in patients with CRC treated with adjuvant chemotherapy than in those not treated with chemotherapy. CMTM6 has a critical impact on the immune microenvironment and can be used as an independent prognostic factor for CRC. The coexpression status of CMTM6 and PD-L1 can be used as a new classification to stratify the risk of progression and death for patients with CRC, especially for patients receiving adjuvant chemotherapy. These findings may provide insights into improving responses to immunotherapy-included comprehensive treatment for CRC in the future.
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Project description:BackgroundInfiltrating immune and stromal cells are important components of the endometrial cancer (EC) microenvironment, which has a significant effect on the biological behavior of EC, suggesting that unique immune-related genes may be associated with the prognosis of EC. However, the association of immune-related genes with the prognosis of EC has not been elucidated. We attempted to identify immune-related genes with potentially prognostic value in EC using The Cancer Genome Atlas database and the relationship between immune microenvironment and EC.MethodsWe analyzed 578 EC samples from TCGA database and used weighted gene co-expression network analysis to screen out immune-related genes. We constructed a protein-protein interaction network and analyzed it using STRING and Cytoscape. Immune-related genes were analyzed through conjoint Cox regression and random forest algorithm analysis were to identify a multi-gene prediction model and stratify low-risk and high-risk groups of EC patients. Based on these data, we constructed a nomogram prediction model to improve prognosis assessment. Evaluation of Immunological, gene mutations and gene enrichment analysis were applied on these groups to quantify additional differences.ResultsUsing conjoint Cox regression and random forest algorithm, we found that TRBC2, TRAC, LPXN, and ARHGAP30 were associated with the prognosis of EC and constructed four gene risk models for overall survival and a consistent nomogram. The time-dependent receiver operating characteristic curve analysis revealed that the area under the curve for 1-, 3-, and 5-y overall survival was 0.687, 0.699, and 0.76, respectively. These results were validated using a validation cohort. Immune-related pathways were mostly enriched in the low-risk group, which had higher levels of immune infiltration and immune status.ConclusionOur study provides new insights for novel biomarkers and immunotherapy targets in EC.
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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.
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Project description:As the second common diagnosed cancer among gynecological tumors, endometrial cancer (EC) has heterogeneous pathogenesis and clinical manifestations. Therefore, prognosis prediction that considers gene expression value and clinical characteristics, is helpful to patients with EC. We downloaded RNA expression and clinical data from the TCGA database. We achieved 4 DEPRGs and constructed the PRG panel by univariate, lasso and multivariate Cox analysis. Based on the median value of the risk score, patients were divided into two groups. The Kaplan-Meier curve suggested that the patients with lower risk scores had better clinical outcomes of EC. AUC of ROC curves suggested the panel can be used as an independent predictor. Future analysis indicated the positive correlations between risk score and clinical characteristics. What's more, we performed GO and KEGG functional analysis and immune environment exploration to get an understanding of the potential molecular mechanism and immunotherapeutic target. To future validate the panel, we found that the relapse-free and overall survival probability of 4 prognostic DEPRGs between high-expression group and low-expression group were different through the Kaplan-Meier plotter in UCEC. In addition, GEPIA database and RT-PCR experiment indicated GPX4 and GSDMD were highly expressed in UCEC compared to normal endometrial tissue, and TIRAP and ELANE were downregulated. This study identified a PRG panel to predict the prognosis immune microenvironment in human EC. Then, Kaplan-Meier analysis and AUC below the ROC curves was used to validate the panel. In addition, Chi-square was used to show the clinical significance. GO, KEGG and GSEA were used to show the functional differences. Different immune-related databases were used to analyze the immune characteristics. The Kaplan-Meier plotter website was used to assess the effect of genes on survival. GEPIA and RT-PCR were used to analyze the expression level. In summary, we identified 4 prognosis-associated pyroptosis-related genes (ELANE, GPX4, GSDMD, and TIRAP). The panel can also predict prognosis prediction and immune microenvironment in human endometrial cancer.
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Project description:The identification of predictive biomarkers and novel targets to optimize immunotherapy strategies for epithelial ovarian cancer (EOC) is urgently needed. CD38 is a multifunctional glycoprotein that acts as an ectoenzyme and immune receptor. However, the underlying immunological mechanisms and prognostic value of CD38 in EOC remain unclear. CD38 gene expression in EOC was evaluated by using Gene Expression Profiling Interactive Analysis (GEPIA) and TISIDB database. The prognostic value was calculated using GEPIA and Kaplan-Meier plotter. Gene set enrichment analysis was conducted to study the roles of CD38 in the EOC microenvironment. Furthermore, the relationship between CD38 expression level and immune cell infiltration was analyzed by the Tumor Immune Estimation Resource and TISIDB. The GEPIA and TISIDB databases showed that CD38 expression in EOC was higher than that in normal tissue and was highest in the immunoreactive subtype among the four molecular types. A total of 424 cases from GEPIA revealed that high levels of CD38 were associated with longer disease-free survival [hazard ratio (HR) = 0.66, P = 0.00089] and increased overall survival rate (HR = 0.67, P = 0.0016). Kaplan-Meier plotter also confirmed the prognostic value of CD38 in EOC. Data from The Cancer Genome Atlas database demonstrated that gene signatures in many categories, such as immune response and adaptive immune response, were enriched in EOC samples with high CD38 expression. In addition, CD38 was positively correlated with immune cell infiltration, especially infiltration of activated CD8+ T cells, CD4+ T cells, and B cells. CD38 is positively correlated with prognosis and immune cell infiltration in the EOC microenvironment and contributes to the regulation of antitumor immunity. CD38 could be used as a prognostic biomarker and potential immunotherapy target.
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Project description:We aimed to investigate the role of ROR?t (Retinoic acid-related orphan receptor gamma) in the tumor microenvironment of differentiated thyroid carcinoma. We retrospectively analyzed 56 patients (48 papillary and 8 follicular thyroid carcinomas). Immunohistochemical expression of ROR?t was compared to other immune markers previously investigated by our group, clinical and pathological information. All patients presented cytoplasmic expression of ROR?t in thyroid tumor cells. Seven (12.5%) patients presented no nuclear expression of ROR?t. Positivity was few (up to 10%) in 14 patients; 10 to 50% in 5 patients (8.9%); and more than 50% in 30 patients (53.6%). Nuclear ROR?t positivity was associated with absence of distant metastasis at diagnosis (p?=?0.013) and the need of less cumulative doses of radioactive iodine (p?=?0.039). Patients whose tumors were positive for nuclear ROR?t presented higher 10-years relapse-free survival rate than those patients who were negative for ROR?t (p?=?0.023). We classified the patients according to the clustering of immunological immunohistochemical markers. We were able to distinguish a subset (A) of 38 patients who presented high expression of nuclear ROR?t and tended to be scarce in proinflammatory immune markers. Other 16 patients integrated a second subset (B) whose tumor microenvironment accumulated proinflammatory markers and presented low expression of nuclear nuclear ROR?t. Distant metastasis at diagnosis were more frequent among patients from cluster B than from cluster A (p?=?0.008). Our results reinforce that the expression of ROR?t together with other immune markers might help predict the prognosis of patients with thyroid cancer and help individualize clinical management.
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