Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer

Ni, Leyi; Tang, Chengyun; Wang, Yuning; Wan, Jiaming; Charles, Morgan G; Zhang, Zilong; Li, Chen; Zeng, Ruijie; Jin, Yiyao; Song, Penghao; Wei, Ming; Li, Bocen; Zhang, Jin; Wu, Zhenghao

doi:10.3390/jpm12071154

Cited by 22 publications

(17 citation statements)

References 61 publications

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“…NF-κB, RelA (a subunit of NF-κB) and CEBPB are both key regulators in inflammation (Zahid et al, 2020;Zhao et al, 2020). MiRNAs can regulate various target genes in numerous biological processes and diseases, such as endometrial cancer (Ni et al, 2022). It has been reported that miR-181 family present a central role in vascular inflammation (Sun et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Gene profiling reveals the role of inflammation, abnormal uterine muscle contraction and vascularity in recurrent implantation failure

Dong

Zhou²,

Li³

et al. 2023

Front. Genet.

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Objective: Recurrent implantation failure (RIF) is now disturbing numerous infertile couples accepting assisted reproductive technology (ART). And the endometrial factors are crucial causes of recurrent implantation failure. However, its mechanism is still unclear. Thus, the aim of this study is to identify altered biologic processes in endometrium that may contribute to recurrent implantation failure.Methods: We recruited two microarray datasets (GSE103465, GSE111974) from Gene Expression Omnibus database (GEO), which contain endometrium from RIF and normal women during implantation period. Using the online tools GEO2R and Venny, we identified Differentially Expressed Genes (DEGs) of selected datasets, and obtained common DEGs. Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCatar pathway enrichment were conducted with Enrichr platform, “ssgsea” and “ggplot2” package of RStudio. PPI networks and hub gene related TF-gene interaction and TF-miRNA co-regulation networks were built via online tools STRING and NetworkAnalyst. Immune infiltration analysis was performed by CIBERSORT platform. Recurrent implantation failure subgroup identification was achieved through “ConsensusClusterPlus,” “tsne,” “ssgsea”, and “ggpubr” package in RStudio. Diagnostic characteristic ROC curves were constructed via “pROC” and “ggplot2” package of RStudio. Enrichr platform was utilized to find drugs targeting hub genes.Results: 26 common DEGs were confirmed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes/BioCarta analysis determined common DEGs were mainly enriched in inflammation associated pathways including TNF, NF-κB, IL-4, IL-10, IL-6, and TGF-β signaling pathways. Five hub genes (PTGS2, VCAM1, EDNRB, ACTA2, and LIF) and related TF-gene and TF-miRNA interactions were identified. Immune infiltration analysis indicated the importance of macrophage M2 in recurrent implantation failure patients. Importantly, subgroup identification analysis highlighted that recurrent implantation failure patients can be divided into two subgroups with different phenotypes. Moreover, the ROC curves and drugs may provide new diagnostic and therapeutic thought for recurrent implantation failure.

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Section: Discussionmentioning

confidence: 99%

Gene profiling reveals the role of inflammation, abnormal uterine muscle contraction and vascularity in recurrent implantation failure

Dong

Zhou²,

Li³

et al. 2023

Front. Genet.

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“…At present, some studies use gene set, RNA set model to predict the occurrence of disease and the prognosis of patients. Through integrating 12 differentially expressed miRNAs, it may affect the proliferation, invasion and metastasis of endometrial cancer, and then predict the prognosis of patients ( 37 ). Likewise, as an important component of the ferroptosis-mediated metabolic change gene set, IMPDH1 is found to be a risk factor in the risk score model for predicting OS of HCC patients ( 38 ).…”

Section: Discussionmentioning

confidence: 99%

IMPDH1, a prognostic biomarker and immunotherapy target that correlates with tumor immune microenvironment in pan-cancer and hepatocellular carcinoma

et al. 2022

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BackgroundsIMPDH1, a rate-limiting enzyme in de novos synthesis of guanine nucleotides, plays an essential role in the growth and progression of certain tumors. However, there is still a lack of study on IMPDH1 evaluating its role in the tumor immune microenvironment, the potential mechanisms, and its potential as a promising tumor therapeutic target.MethodsThe Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Genotype-Tissue Expression (GTEx), TIMER2.0, KM-Plotter, University of Alabama at Birmingham Cancer data analysis Portal (UALCAN), cbioportal, The Human Protein Atlas (HPA), and Gene Expression Profiling Interactive Analysis 2 (GEPIA2) were used to perform the systematic analysis of IMPDH1, including mRNA expression, protein expression, prognostic value, Enrichment analysis, DNA methylation, immune cell infiltration in pan-cancer, Then, we conducted qRT-PCR and immunohistochemistry to analyze the expression level of IMPDH1 in cancer tissues and non-cancer tissues of patients with primary hepatocellular carcinoma (HCC), and performed the same verification at cellular level.ResultsWe discovered that IMPDH1 was highly expressed in a variety of tumors and was associated with poor prognosis. IMPDH1 not only had the potential as a tumor prognostic marker and therapeutic target, but also was closely related to immune cells, immune checkpoints and immune-related genes and pathways in the tumor immune microenvironment (TIME). Meanwhile, IMPDH1 expression influenced the efficacy and prognosis of tumor patients treated with immune checkpoint inhibitors.ConclusionsIMPDH1 may be as a potential combined target of immunotherapy.

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“…Currently, several studies have reported prognostic prediction models for UCEC. Ni et al constructed a prognostic model composed of 12 miRNAs for UCEC, which can accurately predict the survival of UCEC [ 58 ]. Using redox-related genes, Geng et al developed a clinical outcome prognostic model [ 59 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of m7G Methylation-Related miRNA Signature Associated with Survival and Immune Microenvironment Regulation in Uterine Corpus Endometrial Carcinoma

Chen

Sun

Hou

et al. 2022

BioMed Research International

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Background. N7-methylguanosine (m7G) has been implicated in the development of cancer. The role of m7G-related miRNAs in the survival prediction of UCEC patients has not been investigated. Current research was the first to construct an m7G-related miRNA model to accurately predict the survival of patients with uterine corpus endometrial carcinoma (UCEC) and to explore immune cell infiltration and immune activity in the tumor microenvironment. Methods. RNA-seq data and clinical information of UCEC patients were derived from The Cancer Genome Atlas (TCGA) database. Using the TargetScan online database, we predicted miRNAs linked to the m7G-related genes and identified miRNAs which were significantly associated with the survival in UCEC patients and constructed a risk scoring model. The TCGA-UCEC cases were scored according to the risk model, and the high- and low-risk groups were divided by the median risk value. Gene enrichment analysis and immune cell infiltration and immune function analysis were performed using “clusterProfiler” and “GSVA” packages in R. Results. The survival prediction model consisted of 9 miRNAs, namely, hsa-miR-1301, hsa-miR-940, hsa-miR-592, hsa-miR-3170, hsa-miR-876, hsa-miR-215, hsa-miR-934, hsa-miR-3920, and hsa-miR-216b. Survival of UCEC patients in the high-risk group was worse than that in the low-risk group ( p < 0.001 ). The receiver operating characteristic (ROC) curve showed that the model had good predictive performance, and the area under the curve was 0.800, 0.690, and 0.705 for 1-, 3-, and 5-year survival predictions, respectively. There were differences in the degree of immune cell infiltration and immune activity between the low-risk and high-risk groups. The expression levels of the identified differentially expressed genes correlated with the susceptibility to multiple anticancer drugs. Conclusions. The survival prediction model constructed based on 9 m7G-related miRNAs had good predictive performance.

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Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer

Cited by 22 publications

References 61 publications

Gene profiling reveals the role of inflammation, abnormal uterine muscle contraction and vascularity in recurrent implantation failure

Gene profiling reveals the role of inflammation, abnormal uterine muscle contraction and vascularity in recurrent implantation failure

IMPDH1, a prognostic biomarker and immunotherapy target that correlates with tumor immune microenvironment in pan-cancer and hepatocellular carcinoma

Identification of m7G Methylation-Related miRNA Signature Associated with Survival and Immune Microenvironment Regulation in Uterine Corpus Endometrial Carcinoma

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