A six-microRNA signature predicts survival of patients with uterine corpus endometrial carcinoma

Circulating miRNAs as a Tool for Early Diagnosis of Endometrial Cancer-Implications for the Fertility-Sparing Process: Clinical, Biological, and Legal Aspects

This review article explores the possibility of developing an integrated approach to the management of the different needs of endometrial cancer (EC) patients seeking to become pregnant. Life preservation of the woman, health preservation of the baby, a precocious and-as much as possible-minimally invasive characterization of the health and fertility parameters of the patient, together with the concerns regarding the obstetric, neonatal, and adult health risks of the children conceived via assisted reproductive techniques (ART) are all essential aspects of the problem to be taken into consideration, yet the possibility to harmonize such needs through a concerted and integrated approach is still very challenging. This review aims to illustrate the main features of EC and how it affects the normal physiology of pre-menopausal women. We also focus on the prospect of a miR-based, molecular evaluation of patient health status, including both EC early diagnosis and staging and, similarly, the receptivity of the woman, discussing the possible evaluation of both aspects using a single specific panel of circulating miRs in the patient, thus allowing a relatively fast, non-invasive testing with a significantly reduced margin of error. Finally, the ethical and legal/regulatory aspects of such innovative techniques require not only a risk-benefit analysis; respect for patient autonomy and equitable health care access allocation are fundamental issues as well.

MicroRNAs as Potential Biomarkers in Gynecological Cancers

MicroRNAs are non-coding transcripts that, thanks to the ability to regulate the mRNA of target genes, can affect the expression of genes encoding tumor suppressors and oncogenes. They can control many important cellular processes, including apoptosis, differentiation, growth, division, and metabolism. Therefore, miRNAs play an important role in the development of many cancers, including gynecological cancers. Ovarian cancer, endometrial cancer, cervical cancer, and vulvar cancer are the most common cancers in women and are a frequent cause of death. The heterogeneity of the pathogenesis of these gynecological diseases makes the diagnostic process a significant obstacle for modern medicine. To date, many studies have been carried out, in which particular attention has been paid to the molecular pathomechanism of these diseases, with particular emphasis on miRNAs. To date, the changed profile of many miRNAs, which influenced the promotion of proliferation, migration, invasion processes and the simultaneous inhibition of programmed cell death, has been proven many times. Detailed understanding of the molecular effects of miRNAs in the above-mentioned gynecological cancers will enable the development of potential predictive and prognostic biomarkers, as well as the optimization of the diagnostic process.

The interplay of sex steroid hormones and microRNAs in endometrial cancer: current understanding and future directions

Introduction

Endometrial cancer is a hormone-dependent malignancy, and sex steroid hormones play a crucial role in its pathogenesis. Recent studies have demonstrated that microRNAs (miRNAs) can regulate the expression of sex steroid hormone receptors and modulate hormone signaling pathways. Our aim is to provide an overview of the current understanding of the role of miRNAs in endometrial cancer regulated by sex steroid hormone pathways.

Methods

A thorough literature search was carried out in the PubMed database. The articles published from 2018 to the present were included. Keywords related to miRNAs, endometrial cancer, and sex steroid hormones were used in the search.

Results

Dysregulation of miRNAs has been linked to abnormal sex steroid hormone signaling and the development of endometrial cancer. Various miRNAs have been identified as modulators of estrogen and progesterone receptor expression, and the miRNA expression profile has been shown to be a predictor of response to hormone therapy. Additionally, specific miRNAs have been implicated in the regulation of genes involved in hormone-related signaling pathways, such as the PI3K/Akt/mTOR and MAPK/ERK pathways.

Conclusion

The regulation of sex steroid hormones by miRNAs is a promising area of research in endometrial cancer. Future studies should focus on elucidating the functional roles of specific miRNAs in sex steroid hormone signaling and identifying novel miRNA targets for hormone therapy in endometrial cancer management.

Development of a 4-miRNA prognostic signature for endometrial cancer

To develop an effective uterine corpus endometrial carcinoma (UCEC) risk assessment tool to monitor treatment outcomes. Limma package was used to analyze differentially expressed microRNAs (miRNAs) between UCEC tissues and normal tissues in the TCGA database. According to univariate Cox risk regression, least absolute shrinkage, and selection operator (LASSO) Cox analysis were performed to screen prognostic miRNAs and construct a risk scoring model. The prognostic performance of signature was evaluated by Kaplan-Meier and receiver operating characteristic. Multivariate Cox regression analysis was used to determine the independent prognostic factors of UCEC. Nomogram was constructed according to age, clinical stage, and risk score. A 4-miRNA signature based on miR-31-5p, miR-34a-5p, miR-26a-1-3p and miR-4772-3p was established. Risk scores of each patient were calculated by the 4-miRNA signature. After z-score, the patients were divided into high- and low-risk groups. The overall survival of high-risk patients was significantly shorter than that of low-risk patients, pointing to the high performance and independence of the 4-miRNA signature in predicting UCEC prognosis. The nomogram showed a high accuracy in predicting overall survival of UCEC patients. We developed a 4-miRNA signature that could effectively predict the prognosis of UCEC.

Recommendations for extracellular vesicle miRNA biomarker research in the endometrial cancer context

Endometrial cancer (EC) is the most common gynaecological malignancy in the developed world, and concerningly incidence is rising, particularly in younger people. Therefore, there is increased interest in novel diagnostic and prognostic biomarkers. Extracellular vesicles (EVs) are membrane-bound particles present in bodily fluids that have the potential to facilitate non-invasive, early diagnosis of EC and could aid with monitoring of recurrence and treatment response. EV cargo provides molecular insight into the tumor, with the lipid bilayer providing stability for RNA species usually prone to degradation. miRNAs have recently become a focus for EV biomarker research due to their ability to regulate cancer related pathways and influence cancer development and progression. This review evaluates the current literature on EV miRNA biomarkers with a focus on EC, and discusses the challenges facing this research. This review finally highlights areas of focus for EV miRNA biomarker research going forward, such as standardization of normalization approaches, sample storage and processing, extensive reporting of methodologies and moving away from single miRNA biomarkers.

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

Objective: To investigate the differential expression of microRNA (miRNA) in patients with endometrial cancer and its relationship with prognosis and survival. Method: We used The Cancer Genome Atlas (TCGA) database to analyze differentially expressed miRNAs in endometrial cancer tissues and adjacent normal tissues. In addition, we successfully screened out key microRNAs to build nomogram models for predicting prognosis and we performed survival analysis on the key miRNAs as well. Result: We identified 187 differentially expressed miRNAs, which includes 134 up-regulated miRNAs and 53 down-regulated miRNAs. Further univariate Cox regression analysis screened out 47 significantly differentially expressed miRNAs and selected 12 miRNAs from which the prognostic nomogram model for ECA patients by LASSO analysis was constructed. Survival analysis showed that high expression of hsa-mir-138-2, hsa-mir-548f-1, hsa-mir-934, hsa-mir-940, and hsa-mir-4758 as well as low-expression of hsa-mir-146a, hsa-mir-3170, hsa-mir-3614, hsa-mir-3616, and hsa-mir-4687 are associated with poor prognosis in EC patients. However, significant correlations between the expressions levels of has-mir-876 and hsa-mir-1269a and patients' prognosis are not found. Conclusion: Our study found that 12 significantly differentially expressed miRNAs might promote the proliferation, invasion, and metastasis of cancer cells by regulating the expression of upstream target genes, thereby affecting the prognosis of patients with endometrial cancer.

Identification of Key Prognostic-Related miRNA-mRNA Pairs in the Progression of Endometrial Carcinoma

OBJECTIVES

Endometrial carcinoma (EC) is one of the leading causes of death from gynecological cancer due to the high recurrence rate. However, the molecular mechanisms of EC progression are not well understood. This study aimed to identify critical genes and miRNAs associated with the progression and prognosis of EC and find the potential mRNA-miRNA regulatory relationship.

DESIGN

The mRNA and miRNA data were downloaded from The Cancer Genome Atlas (TCGA) database. Next, differentially expressed genes (DEGs) were identified. Subsequently, prognosis-related genes and miRNAs were identified, followed by co-expression analysis of these mRNAs and miRNAs. Materials, Setting, and Methods: Samples in the mRNA microarray were divided into normal (n = 35), early stage (n = 385), and advanced stage (n = 153). Next, DEGs in normal versus early stage and early stage versus advanced stage were, respectively, identified, followed by Venn analysis to screen overlapping DEGs in 2 comparison groups. Based on the expression level of these DEGs, univariate Cox regression analysis and Kaplan-Meier method were performed to obtain prognosis-related genes. Moreover, genes-related miRNAs were predicted, and miRNA-mRNA co-expressed pairs were identified. Then, survival analysis of co-expressed miRNA was performed. Finally, co-expressed genes of key genes were identified, and then functional enrichment analysis was conducted.

RESULTS

After integrating analysis, 326 overlapping (309 upregulated and 17 downregulated) DEGs were obtained. Univariate Cox regression analysis showed that 44 mRNAs and 8 miRNAs were associated with the prognosis of EC. Combined with the co-expressed analysis, only one prognosis-related hsa-miR-326/ELFN2 axis was obtained. In addition, functional enrichment analysis showed that co-expressed genes of ELFN2 were mainly involved in the PI3K-Akt signaling pathway.

LIMITATIONS

These findings were obtained via bioinformatics analysis, and thus further experimental studies are urgently demanded to validate our results.

CONCLUSIONS

One key miRNA-mRNA regulatory pair (hsa-miR-326-ELFN2) was screened. This study provided a bioinformatics basis for the molecular mechanism of EC progression and might contribute to the identification of novel therapeutic targets.

Upregulation of microRNA miR-141-3p and its prospective targets in endometrial carcinoma: a comprehensive study

The clinicopathological value of microRNA-141-3p (miR-141-3p) and its prospective target genes in endometrial carcinoma (EC) remains unclear. The present study determined the expression level of miR-141-3p in EC via quantitative real-time PCR (RT-qPCR). RT-qPCR showed a markedly higher expression level of miR-141-3p in EC tissues than in non-EC endometrium tissues (P < 0.0001). The microarray and miRNA-seq data revealed upregulation of miR-141-3p. Integrated analysis based on 675 cases of EC and 63 controls gave a standardized mean difference of 1.737, confirmed the upregulation of miR-141-3p. The Kaplan-Meier survival curve showed that a higher expression of miR-141-3p positively corelated with a poorer prognosis. Combining the predicted targets and downregulated genes in EC, we obtained 271 target genes for miR-141-3p in EC. Two potential targets, PPP1R12A and PPP1R12B, were downregulated at both the mRNA and protein levels. This study indicates that the overexpression of miR-141-3p may play an important part in the carcinogenesis of EC. The overexpression of miR-141-3p may be a risk factor for the prognosis of patients with EC.

Immune and Metabolic Dysregulated Coding and Non-coding RNAs Reveal Survival Association in Uterine Corpus Endometrial Carcinoma

Uterine corpus endometrial carcinoma (UCEC) is one of the most common gynecologic malignancies, but only a few biomarkers have been proven to be effective in clinical practice. Previous studies have demonstrated the important roles of non-coding RNAs (ncRNAs) in diagnosis, prognosis, and therapy selection in UCEC and suggested the significance of integrating molecules at different levels for interpreting the underlying molecular mechanism. In this study, we collected transcriptome data, including long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs), of 570 samples, which were comprised of 537 UCEC samples and 33 normal samples. First, differentially expressed lncRNAs, miRNAs, and mRNAs, which distinguished invasive carcinoma samples from normal samples, were identified, and further analysis showed that cancer- and metabolism-related functions were enriched by these RNAs. Next, an integrated, dysregulated, and scale-free biological network consisting of differentially expressed lncRNAs, miRNAs, and mRNAs was constructed. Protein-coding and ncRNA genes in this network showed potential immune and metabolic functions. A further analysis revealed two clinic-related modules that showed a close correlation with metabolic and immune functions. RNAs in the two modules were functionally validated to be associated with UCEC. The findings of this study demonstrate an important clinical application for improving outcome prediction for UCEC.

Bioinformatic profiling identifies prognosis-related genes in the immune microenvironment of endometrial carcinoma

Endometrial carcinoma (EC) is a common malignancy of female genital system which exhibits a unique immune profile. It is a promising strategy to quantify immune patterns of EC for predicting prognosis and therapeutic efficiency. Here, we attempted to identify the possible immune microenvironment-related prognostic markers of EC. We obtained the RNA sequencing and corresponding clinical data of EC from TCGA database. Then, 3 immune scores based on the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm were computed. Correlation between above ESTIMATE scores and other immune-related scores, molecular subtypes, prognosis, and gene mutation status (including BRCA and TP53) were further analyzed. Afterwards, gene modules associated with the ESTIMATE scores were screened out through hierarchical clustering analysis and weighted gene co-expression network analysis (WGCNA). Differentially expressed analysis was performed and genes shared by the most relevant modules were found out. KEGG pathway enrichment analysis was conducted to explore the biological functions of those genes. Survival analysis was carried out to identify prognostic immune-related genes and GSE17025 database was further used to confirm the correlation between immune-related genes and the ImmuneScore. The immune-related scores based on ESTIMATE algorithm was closely related to the immune microenvironment of EC. 3 gene modules that had the closest correlations with 3 ESTIMATE scores were obtained. 109 immune-related genes were preliminarily found out and 29 pathways were significantly enriched, most of which were associated with immune response. Univariate survival analysis revealed that there were 14 genes positively associated with both OS and PFS. Among which, 11 genes showed marked correlations with ImmuneScore values in GSE17025 database. Our current study profiled the immune status and identified 14 novel immune-related prognostic biomarkers for EC. Our findings may help to investigate the complicated tumor microenvironment and develop novel individualized therapeutic targets for EC.

MicroRNA as Epigenetic Modifiers in Endometrial Cancer: A Systematic Review

Simple Summary

Endometrial cancer (EC) is the 2nd most common gynecologic cancer worldwide. MicroRNAs (miRNAs) are small noncoding RNAs that contribute to epigenetic regulation. The objective of this systematic review is to summarize our current knowledge on the role of miRNAs in the epigenetic deregulation of tumor-related genes in EC. It includes all miRNAs reported to be involved in EC including their roles in DNA methylation and RNA-associated silencing. This systematic review should be useful for development of novel strategies to improve diagnosis and risk assessment as well as for new treatments aimed at miRNAs, their target genes or DNA methylation.

Abstract

The objective of this systematic review is to summarize our current knowledge on the influence of miRNAs in the epigenetic deregulation of tumor-related genes in endometrial cancer (EC). We conducted a literature search on the role of miRNAs in the epigenetic regulation of EC applying the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The following terms were used: microRNA, miRNA, miR, endometrial cancer, endometrium, epigenetic, epimutation, hypermethylation, lynch, deacetylase, DICER, novel biomarker, histone, chromatin. The miRNAs were classified and are presented according to their function (tumor suppressor or onco-miRNA), their targets (when known), their expression levels in EC tissue vs the normal surrounding tissue, and the degree of DNA methylation in miRNA loci and CpG sites. Data were collected from 201 articles, including 190 original articles, published between November 1, 2008 and September 30, 2020 identifying 313 different miRNAs implicated in epigenetic regulation of EC. Overall, we identified a total of 148 miRNAs with decreased expression in EC, 140 miRNAs with increased expression in EC, and 22 miRNAs with discordant expression levels. The literature implicated different epigenetic phenomena including altered miRNA expression levels (miR-182, -230), changes in the methylation of miRNA loci (miR-34b, -129-2, -130a/b, -152, -200b, -625) and increased/decreased methylation of target genes (miR-30d,-191). This work provides an overview of all miRNAs reported to be involved in epigenetic regulation in EC including DNA methylation and RNA-associated silencing. These findings may contribute to novel strategies in diagnosis, risk assessment, and treatments aimed at miRNAs, their target genes or DNA methylation.

Small Non-Coding-RNA in Gynecological Malignancies

Gynecologic malignancies, which include cancers of the cervix, ovary, uterus, vulva, vagina, and fallopian tube, are among the leading causes of female mortality worldwide, with the most prevalent being endometrial, ovarian, and cervical cancer. Gynecologic malignancies are complex, heterogeneous diseases, and despite extensive research efforts, the molecular mechanisms underlying their development and pathology remain largely unclear. Currently, mechanistic and therapeutic research in cancer is largely focused on protein targets that are encoded by about 1% of the human genome. Our current understanding of 99% of the genome, which includes noncoding RNA, is limited. The discovery of tens of thousands of noncoding RNAs (ncRNAs), possessing either structural or regulatory functions, has fundamentally altered our understanding of genetics, physiology, pathophysiology, and disease treatment as they relate to gynecologic malignancies. In recent years, it has become clear that ncRNAs are relatively stable, and can serve as biomarkers for cancer diagnosis and prognosis, as well as guide therapy choices. Here we discuss the role of small non-coding RNAs, i.e., microRNAs (miRs), P-Element induced wimpy testis interacting (PIWI) RNAs (piRNAs), and tRNA-derived small RNAs in gynecological malignancies, specifically focusing on ovarian, endometrial, and cervical cancer.

A Novel Prognostic Model of Endometrial Carcinoma Based on Clinical Variables and Oncogenomic Gene Signature

Due to the difficulty in predicting the prognosis of endometrial carcinoma (EC) patients by clinical variables alone, this study aims to build a new EC prognosis model integrating clinical and molecular information, so as to improve the accuracy of predicting the prognosis of EC. The clinical and gene expression data of 496 EC patients in the TCGA database were used to establish and validate this model. General Cox regression was applied to analyze clinical variables and RNAs. Elastic net-penalized Cox proportional hazard regression was employed to select the best EC prognosis-related RNAs, and ridge regression was used to construct the EC prognostic model. The predictive ability of the prognostic model was evaluated by the Kaplan-Meier curve and the area under the receiver operating characteristic curve (AUC-ROC). A clinical-RNA prognostic model integrating two clinical variables and 28 RNAs was established. The 5-year AUC of the clinical-RNA prognostic model was 0.932, which is higher than that of the clinical-alone (0.897) or RNA-alone prognostic model (0.836). This clinical-RNA prognostic model can better classify the prognosis risk of EC patients. In the training group (396 patients), the overall survival of EC patients was lower in the high-risk group than in the low-risk group [HR = 32.263, (95% CI, 7.707-135.058), P = 8e-14]. The same comparison result was also observed for the validation group. A novel EC prognosis model integrating clinical variables and RNAs was established, which can better predict the prognosis and help to improve the clinical management of EC patients.

Three plasma-based microRNAs as potent diagnostic biomarkers for endometrial cancer

BACKGROUND

MicroRNAs (miRNAs), with noticeable stability and unique expression pattern in plasma of patients with various diseases, are powerful non-invasive biomarkers for cancer detection including endometrial cancer (EC).

OBJECTIVE

The objective of this study was to identify promising miRNA biomarkers in plasma to assist the clinical screening of EC.

METHODS

A total of 93 EC and 79 normal control (NC) plasma samples were analyzed using Quantitative Real-time Polymerase Chain Reaction (qRT-PCR) in this four-stage experiment. The receiver operating characteristic curve (ROC) analysis was conducted to evaluate the diagnostic value. Additionally, the expression features of the identified miRNAs were further explored in tissues and plasma exosomes samples.

RESULTS

The expression of miR-142-3p, miR-146a-5p, and miR-151a-5p was significantly overexpressed in the plasma of EC patients compared with NCs. Areas under the ROC curve of the 3-miRNA signature were 0.729, 0.751, and 0.789 for the training, testing, and external validation phases, respectively. The diagnostic performance of the identified signature proved to be stable in the three public datasets and superior to the other miRNA biomarkers in EC diagnosis. Moreover, the expression of miR-151a-5p was significantly elevated in EC plasma exosomes.

CONCLUSIONS

A signature consisting of 3 plasma miRNAs was identified and showed potential for the non-invasive diagnosis of EC.

Six-gene-based prognostic model predicts overall survival in patients with uveal melanoma

BACKGROUND

Uveal melanoma (UM) is the most common primary intraocular tumor in adults, which has a high mortality rate and worse prognosis. Therefore, early potential molecular detection and prognostic evaluation seem more important for early diagnosis and treatment.

METHODS

Gene expression data were obtained from The Cancer Genome Atlas-Uveal melanomas database. Survival genes were identified by univariate analysis and were regarded to be associated with the overall survival of UM patients. Then, pathway enrichment analysis of these survival genes was performed. Robust likelihood-based survival model and multivariate survival analysis were conducted to identify more reliable genes and the prognostic signature for UM survival prediction. Two internal datasets and another two UM datasets from Gene Expression Omnibus (GEO) were used for the validation of prognostic signature.

RESULTS

Firstly, 2,010 survival genes were screened by univariate survival analysis. GO and KEGG analysis revealed that these genes were mainly involved in pathways such as mRNA processing, RNA splicing, spliceosome and ubiquitin mediated proteolysis. Secondly, a six-gene signature was identified by Robust likelihood-based survival model approach. The gene expression of the six genes can successfully divide UM samples into high- and low-risk groups and have strong survival prediction ability. What's more, the expression of six genes was compared in 80 healthy adipose tissue samples obtained from GTEx (Genotype-Tissue Expression) database and further validated in internal datasets and GEO datasets, which also can predict UM patient survival.

CONCLUSIONS

The six genes (SH2D3A, TMEM201, LZTS1, CREG1, NIPA1 and HIST1H4E) model might play a vital role in prognosis of UM, which should be helpful for further insight into the treatment of uveal melanoma.

Establishment of the Prognosis Predicting Signature for Endometrial Cancer Patient

BACKGROUND Novel biomarkers provide clinicians more critical information on tumor genetic features and patients' prognosis. Here, we aimed to establish prognosis-predicting signatures for endometrial carcinoma (EC) patients based on the miRNA information. MATERIAL AND METHODS The Cancer Genome Atlas (TCGA) website was available for dataset extraction. Prognosis-associated miRNAs were generated by univariate Cox regression test. Online websites were used to predict the targeted genes of these enrolled miRNAs. The miRNA-mRNA network was described by Cytoscape software, while the relevant signaling pathways of these targeted genes were enriched by Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. RESULTS The miRNA-based overall survival (OS) and recurrence-free survival (RFS) predicting signatures were constructed by LASSO Cox regression analyses, respectively, by which, the endometrial carcinoma patients were separated into high- and low-risk groups in both the discovery and validation sets. Univariate Cox regression analyses suggested that these high-risk patients had elevated death and recurrence risk compared to low-risk patients. In addition, multivariate Cox regression analysis confirmed that our signatures were independent prognosticate factors with or without clinicopathological features for endometrial carcinoma patients. Moreover, the miRNA-mRNA network was displayed by Cytoscape software, and the pathway enrichment analyses found that the targeted genes of these enrolled miRNAs were enriched in tumor progression and drug resistance-related pathways. CONCLUSIONS The OS and RFS predicting classifiers serve as independent prognosis-associated determiners for EC patients.

The Role and Therapeutic Potential of miRNAs in Colorectal Liver Metastasis

Colorectal cancer (CRC) is the fourth leading cause of cancer-related deaths worldwide. Liver metastasis is the major cause of CRC patient mortality, occurring in 60% patients with no effective therapies. Although studies have indicated the role of miRNAs in CRC, an in-depth miRNA expression analysis is essential to identify clinically relevant miRNAs and understand their potential in targeting liver metastasis. Here we analyzed miRNA expressions in 405 patient tumors from publicly available colorectal cancer genome sequencing project database. Our analyses showed miR-132, miR-378f, miR-605 and miR-1976 to be the most significantly downregulated miRNAs in primary and CRC liver metastatic tissues, and CRC cell lines. Observations in CRC cell lines indicated that ectopic expressions of miR-378f, -605 and -1976 suppress CRC cell proliferation, anchorage independent growth, metastatic potential, and enhance apoptosis. Consistently, CRC patients with higher miR-378f and miR-1976 levels exhibited better survival. Together, our data suggests an anti-tumorigenic role of these miRNAs in CRC and warrant future in vivo evaluation of the molecules for developing biomarkers or novel therapeutic strategies.

The role of the miR1976/CD105/integrin αvβ6 axis in vaginitis induced by Escherichia coli infection in mice

Vaginitis is very common among women, especially women of childbearing age, and is associated with significantly increased risk of preterm birth and pelvic inflammatory diseases. An imbalance in the vaginal flora, the primary cause of vaginitis, promotes the initiation and progression of vaginal infections. However, the responsible mechanisms are still poorly understood. Using a murine vaginitis model of Escherichia coli infection, we demonstrated that decreased expression of microRNA1976 and increased expression of CD105 and integrin αvβ6 were closely associated with the progression of vaginal infection. Importantly, we demonstrated for the first time that the microRNA1976/CD105/integrin αvβ6 axis regulates E. coli-mediated vaginal infection in mice, as evidenced by the finding that E. coli-induced vaginal infection was reversed by microRNA1976 overexpression and exacerbated by CD105 overexpression. The regulation of CD105 and integrin αvβ6 by microRNA1976 was further confirmed in a murine model of vaginitis with adenoviral vector treatment. Taken together, our data suggested that microRNA1976 negatively regulates E. coli-induced vaginal infection in mice at least in part by suppressing CD105 and integrin αvβ6 expression. These findings may provide new insight into the mechanisms of E. coli-induced vaginitis, identify a novel diagnostic biomarker and a potential therapeutic target for flora imbalance-associated vaginitis.

Identification and Function Analysis of a Five-Long Noncoding RNA Prognostic Signature for Endometrial Cancer Patients

This study aimed to construct a long noncoding RNA (lncRNA)-based prognostic signature to improve the survival prediction for endometrial cancer (EC) patients and guide individualized treatments. mRNA and miRNA sequencing and clinical data of 526 patients with EC (randomized to training or validation set, n = 263) were collected from The Cancer Genome Atlas database. Differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs), and differentially expressed miRNAs (DEMs) were identified between 263 EC samples and 33 normal controls. Univariate and multivariate Cox regression analyses identified five DELs (LINC00475, LINC01352, MIR503HG, KCNMB2-AS1, and LINC01143) that were overall survival related. The Kaplan-Meier curve showed that the risk score model established by these five DELs can significantly distinguish the survival ratio of patients at high risk from those at low risk. The receiver operating characteristic curve indicated that this risk score exhibited good survival prediction performance, with the area under the curve of 0.978. In addition, this risk score was independent of other clinical factors. Stratification analysis based on two independent prognostic clinical factors (histologic grade and recurrence status) demonstrated that the high-risk score was still a poor prognostic factor for patients with histologic grade 3, recurrence or nonrecurrence status. In nomogram model, the risk score was one of the main contributions to survival rates, and its Harrell's concordance index was higher than the other two independent clinical factors, although all lower than the combined. Furthermore, mechanism analyses showed that these lncRNAs functioned by coexpressing with DEGs (i.e., LINC00475-PTGDR, LINC01352/MIR503HG-BACH2, KCNMB2-AS1-PCSK9, LINC01143-NUF2/PTTG1) or as a competing endogenous RNA of DEMs to regulate DEGs (LINC00475-miR-4728-PTGDR, MIR503HG-miR-3170-BACH2). In conclusion, our novel risk score system may be a promising prognostic biomarker to guide personalized treatment for EC patients and it can add prognostic value for current clinical system.

A novel seven‑miRNA prognostic model to predict overall survival in head and neck squamous cell carcinoma patients

Head and neck squamous cell carcinoma (HNSCC) is highly prevalent worldwide, and the outcome of HNSCC is still difficult to predict due to the lack of appropriate prognostic markers. In the present study, a prognostic model based on a miRNA panel was established to better predict the survival of HNSCC patients. miRNA expression data and clinical information regarding HNSCC patients were acquired from The Cancer Genome Atlas (TCGA) database. Accompanying clinical data was obtained from the University of California, Santa Cruz (UCSC) Xena browser. Using this data, 140 differentially expressed miRNAs (DEMs) were identified between HNSCC tissue samples (n=525) and adjacent normal tissue samples (n=44). The present prognostic model included seven miRNAs (i.e. hsa‑miR‑499a, hsa‑miR‑548k, hsa‑miR‑3619, hsa‑miR‑99a, hsa‑miR‑137, hsa‑miR‑3170, and hsa‑miR‑654), which were identified using least absolute shrinkage and selection operator (LASSO) and Cox regression analyses. The independence of the predictive power of this model was validated by further analyses using clinical information. The outstanding performance of the seven‑miRNA prognostic model was confirmed by time‑dependent receiver operating characteristic curve (ROC) analysis. These results indicated that combining the miRNA panel with pathological characteristics may provide a more accurate prognosis for HNSCC. Functional identification of the target genes of the focal miRNAs using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were also performed. The present study demonstrated that the novel miRNA panel reported here may be useful in making different prognoses and may improve the clinical management of patients with HNSCC.

miRNA-mRNA Associated With Survival in Endometrial Cancer

Although various factors may contribute to its initiation and progression, the etiology and prognostic factors of endometrial carcinoma (EC) remains not fully understood. We sought to understand the role of changes in transcriptome during the progress of EC by exploring public datasets. The aberrant expression characteristics of EC based on RNA-Seq and miRNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed. Kaplan-Meier analysis was performed to assess the relationship between differently expressed genes (DEGs) and patient survival. As a result, 320 out of 4,613 differently expressed mRNAs (DE mRNAs) and 68 out of 531 differently expressed miRNAs (DE miRNAs) with a significantly poorer survival were determined. We predicted eight paired DE miRNAs and DE mRNAs through TargetScan. Patients with three out of the eight paired low rate of miRNA/mRNA (miR-497/EMX1, miR-23c/DMBX1, and miR-670/KCNS1) expression had a significantly poorer survival. Furthermore, the simultaneous presence of these selected low miRNA/mRNA pairs occurred in most patients and resulted in a significantly poorer survival rate. Luciferase reporter assay identified that EMX1 was a direct target of miR-497. Both low expression of miR-497 and overexpression of EMX1 were significantly associated with more advanced clinicopathologic characteristics (stage, tumor status, grade, and histology) besides survival (all P values < 0.05). Multivariate analysis also demonstrated that miR-497 remained an independent prognostic variable for overall survival. In summary, we identified that a series of DE mRNAs and miRNAs, including eight paired DE miRNAs and mRNAs, were associated with survival in EC. Clinical evaluation of downregulated miR-497 and paired upregulated EMX1 confirmed the value of our prediction analysis. The simultaneous presence of low rate of these selected low miRNA/mRNA pairs (miR-497/EMX1, miR-23c/DMBX1, and miR-670/KCNS1) might have a better prediction value. Therefore, further studies are required to validate these findings.

The Use of microRNAs in the Management of Endometrial Cancer: A Meta-Analysis

Introduction: Endometrial cancer (EC) is the most important gynecological cancer in terms of incidence. microRNAs (miRs), which are post-transcriptional regulators implicated in a variety of cellular functions including carcinogenesis, are particularly attractive candidates as biomarkers. Indeed, several studies have shown that the miR expression pattern appears to be associated with prognostic factors in EC. Our objective is to review the current knowledge of the role of miRs in carcinogenesis and tumor progression and their association with the prognosis of endometrial cancer. Materials and Method: We performed a literature search for miR expression in EC using MEDLINE, PubMed (the Internet portal of the National Library of Medicine) and The Cochrane Library, Cochrane databases “Cochrane Reviews” and “Clinical Trials” using the following keywords: microRNA, endometrial cancer, prognosis, diagnosis, lymph node, survival, plasma, FFPE (formalin-fixed, paraffin-embedded). The miRs were classified and presented according to their expression levels in cancer tissue in relation to different prognostic factors. Results: Data were collected from 74 original articles and 8 literature reviews which described the expression levels of 261 miRs in ECs, including 133 onco-miRs, 110 miR onco-suppressors, and 18 miRs with discordant functions. The review identified 30 articles studying the expression pattern of miR in neoplastic endometrial tissue compared to benign and/or hyperplastic tissues, 12 articles detailing the expression profile of miRs as a function of lymph node status, and 14 articles that detailed the expression pattern of miRs in endometrial tumor tissue according to overall survival or in the absence of recurrence. Conclusions: The findings presented here suggest that miR analysis merits a role as a prognostic factor in the management of patients with endometrial cancer.