Competing endogenous RNA network of endometrial carcinoma: A comprehensive analysis

Bioinformatics analysis proposes a possible role for long noncoding RNA MIR17HG in retinoblastoma

BACKGROUND

Retinoblastoma (RB) is the most common prevalent intraocular malignancy among infants and children, particularly in underdeveloped countries. With advancements in genomics and transcriptomics, noncoding RNAs have been increasingly utilized to investigate the molecular pathology of diverse diseases.

AIMS

This study aims to establish the competing endogenous RNAs network associated with RB, analyse the function of mRNAs and lncRNAs, and finds the relevant regulatory network.

METHODS AND RESULTS

This study establishes a network of competing endogenous RNAs by Spearman correlation analysis and prediction based on RB patients and healthy children. Enrichment analyzes based on Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes are conducted to analyze the potential biological functions of lncRNA and mRNA networks. Weighted gene co-expression network analysis (WGCNA) is employed to identify gene cluster modules exhibiting the strongest correlation with RB. The results indicate a significant correlation between the lncRNA MIR17HG (R = .73, p = .02) and the RB phenotype. ceRNA networks reveal downstream miRNAs (hsa-mir-425-5p and hsa-mir455-5p) and mRNAs (MDM2, IPO11, and ITGA1) associated with MIR17Hg. As an inhibitor of the p53 signaling pathway, MDM2 can suppress the development of RB.

CONCLUSION

In conclusion, lncRNAs play a role in RB, and the MIR17HG/hsa-mir-425-5p/MDM2 pathway may contribute to RB development by inhibiting the p53 signaling pathway.

C2orf48 promotes the progression of nasopharyngeal carcinoma by regulating high mobility group AT-hook 2

Recurrence and metastasis are the major factors affecting the survival of nasopharyngeal carcinoma (NPC), and the mechanism remains unclear. Long non-coding RNA chromosome 2 open reading frame 48 (C2orf48) has been shown to influence the prognosis of many cancers. However, C2orf48's function in NPC has not been clarified. In this investigation, C2orf48 expression in NPC was measured by quantitative real-time PCR (qRT-PCR) at the cellular and tissue levels, and the association between C2orf48 expression and the prognosis of patients with NPC was examined. Additionally, the effects of C2orf48 and high mobility group AT-hook 2 (HMGA2) upon NPC proliferation, migration, and invasion were examined employing the MTT assay, colony formation assay, and transwell assay, respectively. Furthermore, the association between C2orf48 and HMGA2 in NPC was investigated. Our research demonstrated that C2orf48 was overexpressed in NPC tissues and cell lines, and compared to patients with lower levels of C2orf48 expression, those with higher levels had poorer 5-year overall survival and progression-free survival. Functionally, C2orf48 overexpression accelerated NPC cells proliferation, migration, and invasion. Besides, the tandem mass tag (TMT) quantitative proteomic analysis indicated that HMGA2 may be a target of C2orf48. Moreover, upregulation of C2orf48 could increase HMGA2 expression, and HMGA2 silencing could counteract the proliferation, migration, and invasion changes induced by C2orf48 in NPC cells. These results reveal that overexpression of C2orf48 can promote NPC cells proliferation, migration, and invasion via regulating the expression of HMGA2 and C2orf48 may be a potentially important prognostic marker for NPC.

A new ferroptosis-related signature model including messenger RNAs and long non-coding RNAs predicts the prognosis of gastric cancer patients

BACKGROUND AND OBJECTIVES

Gastric cancer (GC) is among the most malignant tumor types, which causes heavy healthy and economic burden to the people and societies all around the world. Establishment of an effective set of prognostic marker will benefit a lot to the treatment of GC patients clinically. Ferroptosis is a newly identified regulated cell death modality, with tight relevance with GC development. However, its application in the prognosis of GC has not been studied in detail. Deregulated messenger RNA (mRNA) and long non-coding RNA (lncRNA) expression profile in tumor can serve as novel prognostic marker for predicting the survival and cancer relapse in patients.

METHODS

We downloaded ferroptosis-related gene expression microarray data, clinicopathologic information and a list of 259 ferroptosis-related genes from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Ferroptosis database, respectively. Then, correlation analysis, univariate and multivariate Cox regression analysis were used to construct a novel prognostic model for GC. Then, we validated the model in the GEO datasets. Finally, we evaluated the differences in immune microenvironment between high- and low-risk groups.

RESULTS

We utilized the ferroptosis-related mRNA and lncRNA profile to successfully construct a prognostic model (incorporating 2 mRNAs and 15 lncRNAs) in GC. Our model, integrating diverse clinical traits and critical factors of GC, showed desirable efficacy in the prognosis of GC patients. This model also manifested effectively in validation by using external patients' data.

CONCLUSIONS

Our study developed a novel ferroptosis-related signature to predict the prognosis of gastric cancer patients. The ferroptosis-related signature had a favorable predictive ability. This model may greatly boost the treatment of GC patients in clinical practice.

Comprehensive bioinformatic analyses of lncRNA-mediated ceRNA network for uterine corpus endometrial carcinoma

Background

Given that long non-coding RNAs (lncRNAs) involved in the tumor initiation or progression of the endometrium and that competing endogenous RNA (ceRNA) plays an important role in increasingly more biological processes, lncRNA-mediated ceRNA is likely to function in the pathogenesis of uterine corpus endometrial carcinoma (UCEC). Our present study aimed to explore the potential molecular mechanisms for the prognosis of UCEC through a lncRNA-mediated ceRNA network.

Methods

The transcriptome profiles and corresponding clinical profiles of UCEC dataset were retrieved from Clinical Proteomic Tumor Analysis Consortium (CPTAC) and The Cancer Genome Atlas (TCGA) databases respectively. Differentially expressed genes (DEGs) in UCEC samples were identified via "Edge R" package. Then, an integrated bioinformatics analysis including functional enrichment analysis, tumor infiltrating immune cell (TIIC) analysis, Kaplan-Meier curve, Cox regression analysis were conducted to analyze the prognostic biomarkers.

Results

In the CPTAC dataset of UCEC, a ceRNA network comprised of 36 miRNAs, 123 lncRNAs and 124 targeted mRNAs was established, and 8 of 123 prognostic-related Differentially Expressed long noncoding RNAs (DElncRNAs) were identified. While in the TCGA dataset, a ceRNA network comprised of 38 miRNAs, 83 lncRNAs and 110 targeted mRNAs was established, and 2 of 83 prognostic-related DElncRNAs were identified. After filtered by risk grouping and Cox regression analysis, 10 prognostic-related lncRNAs including LINC00443, LINC00483, C2orf48, TRBV11-2, MEG-8 were identified. In addition, 33 survival-related Differentially Expressed messenger RNA (DEmRNAs) in two ceRNA networks were further validated in the Human Protein Atlas Portal (HPA) database. Finally, six lncRNA/miRNA/mRNA axes were established to elucidate prognostic regulatory roles in UCEC.

Conclusions

Several prognostic lncRNAs are identified and prognostic model of lncRNA-mediated ceRNA network is constructed, which promotes the understanding of UCEC development mechanisms and potential therapeutic targets.

microRNA-491-5p regulates osteogenic differentiation of bone marrow stem cells in type 2 diabetes

OBJECTIVES

Osseointegration of oral implants has a low success rate in patients with type 2 diabetes. This is because of the inhibition of osteogenic differentiation in the jawbone marrow mesenchymal stem cells, in which the expression of microRNA(miR)-491-5p is significantly downregulated, as ascertained through gene chip screening. However, the underlying mechanisms are unclear. Here, we aimed to clarify the mechanisms involved in the influence of miR-491-5p on osteogenic differentiation.

SUBJECTS AND METHODS

Jawbone marrow mesenchymal stem cells were isolated from jawbones of patients with type 2 diabetes and subjected to bioinformatics and functional analyses. Osteogenesis experiments were conducted using the isolated cells and an in vivo model.

RESULTS

Knockdown and overexpression experiments revealed the positive effects of miR-491-5p expression on osteogenic differentiation in vivo and in vitro. Additionally, a dual-luciferase assay revealed that miR-491-5p targeted the SMAD/RUNX2 pathway by inhibiting the expression of epidermal growth factor receptor.

CONCLUSIONS

miR-491-5p is vital in osteogenic differentiation of jawbone mesenchymal stem cells; its downregulation in type 2 diabetes could be a major cause of decreased osteogenic differentiation. Regulation of miR-491-5p expression could improve osteogenic differentiation of jawbone mesenchymal stem cells in patients with type 2 diabetes.

Towards Personalized Medicine: Non-Coding RNAs and Endometrial Cancer

Endometrial cancer (EC) is the most frequent female cancer associated with excellent prognosis if diagnosed at an early stage. The risk factors on which clinical staging is based are constantly updated and genetic and epigenetic characteristics have recently been emerging as prognostic markers. The evidence shows that non-coding RNAs (ncRNAs) play a fundamental role in various biological processes associated with the pathogenesis of EC and many of them also have a prognosis prediction function, of remarkable importance in defining the therapeutic and surveillance path of EC patients. Personalized medicine focuses on the continuous updating of risk factors that are identifiable early during the EC staging to tailor treatments to patients. This review aims to show a summary of the current classification systems and to encourage the integration of various risk factors, introducing the prognostic role of non-coding RNAs, to avoid aggressive therapies where not necessary and to treat and strictly monitor subjects at greater risk of relapse.

Integrative Analysis of Differently Expressed Genes Reveals a 17-Gene Prognosis Signature for Endometrial Carcinoma

Endometrial carcinoma (EC) is the fifth widely occurring malignant neoplasm among women all over the world. However, there is still lacking efficacy indicators for EC's prognosis. Here, we analyzed two databases including an RNA-sequencing-based TCGA dataset and a microarray-based GSE106191. After normalizing the raw data, we identified 114 common genes with upregulation and 308 common genes with downregulation in both the TCGA and GSE106191 databases. Bioinformatics analysis showed that the differently expressed genes in EC were related to the IL17 signaling pathway, PI3K-Akt signaling pathway, and cGMP-PKG signaling pathway. Furthermore, we performed the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and generated a signature featuring 17 prognosis-related genes (MAL2, ANKRD22, METTL7B, IL32, ERFE, OAS1, TRPC1, SRPX, RAPGEF4, PSD3, SIMC1, TRPC6, WFS1, PGR, PAMR1, KCNK6, and FAM189A2) and found that it could predict OS in EC patients. The further analysis showed that OAS1, MAL2, ANKRD22, METTL7B, and IL32 were significantly upregulated in EC samples after comparison with normal samples. However, TRPC1, SRPX, RAPGEF4, PSD3, SIMC1, TRPC6, WFS1, PGR, PAMR1, KCNK6, and FAM189A2 were significantly downregulated in EC samples in comparison with normal samples. And correlation analysis showed that our results showed that the expressions of 17 prognosis-related hub genes were significantly correlated based on Pearson correlation. We here offer a newly genetic biomarker for the prediction of EC patients' prognosis.

lncRNA MIR210HG promotes the progression of endometrial cancer by sponging miR-337-3p/137 via the HMGA2-TGF-β/Wnt pathway

Epithelial-mesenchymal transition (EMT) promotes tumorigenesis and metastasis and increases tumor tolerance to treatment intervention. Abnormal activation of transforming growth factor β (TGF-β) and Wnt pathway induces EMT. Long non-coding RNAs (lncRNAs) significantly influence EMT regulation. Herein, we show that MIR210HG is overexpressed in endometrial cancer tissues, which is associated with poor prognosis. MIR210HG silencing significantly inhibited proliferation, migration, invasion, and EMT phenotype formation in vitro as well as tumorigenesis in vivo. Mechanistically, bioinformatics analyses, RNA binding protein immunoprecipitation (RIP) assays, and luciferase assays showed that MIR210HG acts as a molecular sponge of miR-337-3p and miR-137 to regulate the expression of HMGA2. Additionally, MIR210HG overexpression significantly enriched the Wnt/β-catenin and TGF-β/Smad3 signaling pathway genes, while MIR210HG or HMGA2 knockdown suppressed the Wnt/β-catenin and TGF-β/Smad3 signaling pathway. Our findings on the MIR210HG-miR-337-3p/137-HMGA2 axis illustrate its potential as a target for endometrial cancer therapeutic development.

Non-Coding RNAs as Prognostic Markers for Endometrial Cancer

Endometrial cancer (EC) has been classified over the years, for prognostic and therapeutic purposes. In recent years, classification systems have been emerging not only based on EC clinical and pathological characteristics but also on its genetic and epigenetic features. Noncoding RNAs (ncRNAs) are emerging as promising markers in several cancer types, including EC, for which their prognostic value is currently under investigation and will likely integrate the present prognostic tools based on protein coding genes. This review aims to underline the importance of the genetic and epigenetic events in the EC tumorigenesis, by expounding upon the prognostic role of ncRNAs.

Using mRNAsi to identify prognostic-related genes in endometrial carcinoma based on WGCNA

AIMS

Cancer Stem Cells (CSCs) refers to heterogeneous tumor cells retaining the abilities of self-renewal and differentiation. This study used mRNAsi, which is an index to describe the similarity between tumor cells and CSCs, to define genes involved in endometrial carcinoma.

MATERIALS AND METHODS

The mRNA expression profiles of 552 tumor samples and 23 non-tumor samples were calculated for differentially expressed genes. WGCNA was utilized to construct gene co-expression networks and classify screened genes into different modules. Univariate and multivariate Cox regression models were performed to identify and construct the prognostic model. Time-dependent receiver operating characteristic (ROC), Kaplan-Meier curve, multivariate Cox regression analysis, and nomogram were used to assess the prognostic capacity of the six-gene signature. The screened genes were further validated by GEO (GSE17025) and qRT-PCR in EC tissues.

KEY FINDINGS

2573 upregulated and 1890 downregulated genes were identified. A total of 35 genes in the turquoise module were identified as key genes. With multivariate analysis, six genes (DEPDC1, FAM83D, NCAPH, SPC25, TPX2, and TTK) up-regulated in endometrial carcinoma were identified, and their higher expression was associated with a higher stage/age/grade. Moreover, ROC and Kaplan-Meier plots indicated these genes had a high prognostic value for EC. A nomogram was constructed for clinical use. In addition, we explored the pathogenesis involving six genes. The results showed that these genes may become pathogenic as their copy numbers changes and methylation level reduces. Finally, GSEA revealed these genes had a close association with cell cycle, etc. SIGNIFICANCE: These findings may provide new insights into the treatment of diseases.

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.