Identification of long non-coding RNAs biomarkers associated with progression of endometrial carcinoma and patient outcomes

Evaluation of specific lncRNAs, miRNAs, and mRNAs in different groups of prostate cancer

Introduction

LncRNAs interact with miRNAs and mRNAs that can have a special expression pattern in a specific cell type. We investigated the specific lncRNAs, miRNAs, and mRNAs in different groups of prostate cancer (PC).

Methods

The mRNAs with significant expression differences were first analyzed using the GEO and TCGA databases. The lncRNAs and miRNAs were then identified in the miRWalk2, miRmap, OncomiR, miRGator 3.0, miRCancerDB, LncRNA2target, TANRIC, LncRNADisease, Lnc2Cancer v3.0, and LncBase. Seventy subjects, including sixty PC patients classified as local, locally advanced, biochemical relapse, metastatic, and benign groups, as well as ten normal individuals, were then included. Finally, real-time PCR determined the expression of the candidate biomarkers.

Results

The bioinformatics analysis detected candidate 6 miRNAs, 6 lncRNAs, and 6 mRNAs in different groups of PC patients. Unlike the significant decrease in candidate tumor suppressors, the expression levels of specific onco-lncRNA, onco-miRNA, and oncogenes exhibited a substantial increase in different groups of the patients compared to the normal group. The expression of lncRNAs, including LINC01128 (P=0.0182), LINC02246 (P<0.0001), and LINC02288 (P<0.0001), LINC00857 (P<0.0001), GNAS-AS1 (P<0.0001), and LINC02371 (P<0.0001), the expression of miRNAs, including miR-217 (P<0.0001), miR-375 (P<0.0001), miR-203a (P<0.0001), miR-876 (P=0.0046), miR-27b (P<0.0001), and miR-152 (P<0.0001), and the expression of oncogenes, including ST14 (P<0.0001), CD24 (P<0.0001), CDH1 (P<0.0001), DSC2 (P<0.0001), TGFB3 (P<0.0001), and MYL2 (P=0.0186) had significant changes at different groups of PC patients.

Conclusion

Our results identified promising biomarkers that play a role in specific groups of prostate cancer patients. Detecting specific biomarkers may be an effective strategy for different groups of PC patients.

CRISPR du-HITI an attractive approach to targeting Long Noncoding RNA HCP5 as inhibitory factor for proliferation of ovarian cancer cell

This research provides a glimmer of hope that the knockout of HCP5 leads to a therapy response to considerably prolong the life of patients with OC. RT-PCR evaluated the expression of lncRNA HCP5 in the ovarian cancer OVCAR-3 cell line. CRISPR knockout cell lines validated by western blot. Small genomic deletions at the targeted locus were induced. CCK-8 colony formation assays were used to analyze the effect of HCP5 knockout on the proliferation capacity of OVCAR-3 cells. Transwell migration and invasion assayed. Furthermore, the Sphere-formation assay isolated the most aggressive population of cancer stem cells. Bioinformatic analysis showed a significant correlation between lncRNA HCP5 up-regulation and OVCAR-3 cell proliferation. The ChIP technique assesses specific sites of interaction between transcription factors and DNA. Real-time PCR assays explored the relationship between HCP5, Hsa-miR-9-5p, CXCR4, CDH1, caspase-3, p53, bcl2 and survivin. PCR carried out amplification of the 448-bp band for sgRNA1 and sgRNA2 after the use of particular primers for HCP5. the number of breast cancer cells that moved to the bottom chamber reduced considerably after transfection with PX461-sgRNA1/2 vectors compared to the Blank control groups (P < 0.05). MTT assay designated growth curves that showed the rate of OVCAR-3 growth was significantly repressed (***P < 0.001) when compared with control OVCAR-3 cells after HCP5 knockdown. Also, the survival results of W.T cells in 24, 48 and 72 h showed 92%, 87% and 85%, respectively. This is while the cells of the CRISPR/Cas9 group in which LncRNA HCP5 was knocked out had 42% (*P < 0.05), 23%(**P < 0.01) and 14% (**P < 0.01) survival, respectively. The expression levels of caspase-3, Hsa-miR-9-5p, P53 genes in the HCP5 deletion of CRISPR/Cas9 group significantly increased than the W.T. control group; the deletion group showed a considerable reduction in HCP5 expression compared to the blank control group (3.6-fold, p < 0.01). Whereas BCL2, SURVIVIN, CXCR4, CDH1 genes expression markedly increased than in HCP5 knockout cells (5.8-fold, p < 0.05). These results indicate that CRISPR/Cas9-mediated HCP5 disruption on OVCAR-3 cell lines promotes anti-tumor biomarkers, suppressing ovarian cancer progression. Consistent with these results, HCP5 is one of the most critical lnc for the efficient proliferation and migration of OVCAR-3 cell lines.

Ghrelin intronic lncRNAs, lnc-GHRL-3:2 and lnc-GHRL-3:3, as novel biomarkers in type 2 diabetes mellitus

BACKGROUND

We aim to identify circulating lncRNAs located in the region of the ghrelin (GHRL) gene that play a role in the development of T2DM.

METHODS

Bioinformatic tool was used to identify candidates GHRL-lncRNAs. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to compare the expression levels of selected lncRNAs on diabetic patients and non-diabetic controls.Receiver operating characteristic (ROC) curve analysis was performed to evaluate the discriminatory power of selected GHRL-lncRNAs.

RESULTS

The bioinformatic analysis predicted three antisense and eight sense-intronic GHRL- lncRNAs. Two differentially expressed GHRL-lncRNAs were detected in diabetic patients. The expression levels of lnc-GHRL-3:2, lnc-GHRL-3:3, and the GHRL mRNA were significantly (p ≤ .0001) lower in the diabetic patients. ROC analysis showed that the area under the curve (AUC) value was 0.93 for lnc-GHRL-3:2 and 0.90 for lnc-GHRL-3:3.

CONCLUSION

lnc-GHRL-3:2 and lnc-GHRL-3:3 are novel biomarkers and might play a regulatory role in T2DM pathogenesis.

COVID-19–associated lncRNAs as predictors of survival in uterine corpus endometrial carcinoma: A prognostic model

Background: Patients with uterine corpus endometrial carcinoma (UCEC) may be susceptible to the coronavirus disease-2019 (COVID-19). Long non–coding RNAs take on a critical significance in UCEC occurrence, development, and prognosis. Accordingly, this study aimed to develop a novel model related to COVID-19–related lncRNAs for optimizing the prognosis of endometrial carcinoma.

Methods: The samples of endometrial carcinoma patients and the relevant clinical data were acquired in the Carcinoma Genome Atlas (TCGA) database. COVID-19–related lncRNAs were analyzed and obtained by coexpression. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were performed to establish a COVID-19–related lncRNA risk model. Kaplan–Meier analysis, principal component analysis (PCA), and functional enrichment annotation were used to analyze the risk model. Finally, the potential immunotherapeutic signatures and drug sensitivity prediction targeting this model were also discussed.

Results: The risk model comprising 10 COVID-19–associated lncRNAs was identified as a predictive ability for overall survival (OS) in UCEC patients. PCA analysis confirmed a reliable clustering ability of the risk model. By regrouping the patients with this model, different clinic-pathological characteristics, immunotherapeutic response, and chemotherapeutics sensitivity were also observed in different groups.

Conclusion: This risk model was developed based on COVID-19–associated lncRNAs which would be conducive to the precise treatment of patients with UCEC.

Construction of Endometrial Carcinoma ceRNA Network and Screening of Key Genes Based on TCGA Database

Objective

Long noncoding RNA (lncRNA) has received more and more attention in human tumor research. This study is aimed at clarifying the regulatory network of lncRNAs-microRNAs- (miRNAs-) mRNAs and at determining the relevant targets in the development of endometrial cancers.

Methods

Download the miRNA, mRNA, and lncRNA expression profile data of endometrial cancer patients from TCGA; use the "DESeq2" package of R software to identify the differential expression of miRNAs, mRNAs, and lncRNAs; construct a network of ceRNA; and perform gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment assessment on mRNAs in the network of ceRNA; string and Cytoscape 3.7.2 perform PPI assessment on target genes and TOP 10 hub gene screening; Cytoscape 3.7.2 computer program was employed for constructing the lncRNA-miRNA-TOP10 hub mRNA network diagram to determine the signal axis; StarBase database to verify the Top10 hub mRNA expression; the "survival" package in R computer program was implemented to analyze the survival rate of all genes on the lncRNA-miRNA-Top10 hub mRNA network diagram; RT-qPCR to verify the expression level of genes on the signal axis.

Results

1119 differential mRNAs, 14 differential lncRNAs, and 65 differential miRNAs were screened in TCGA; we constructed a ceRNA regulatory network composed of 5 DELs, 7 DEMs, and 90 DEGs; String combined with Cytoscape to screen out Top10 hub genes, namely: LEFTY1, LIN28A, LHX3, ST8SIA3, CEP55, FBXO32, DCN, ANGPTL1, ADRA1A, and KCNMA1; the StarBase database verification results show that ADRA1A, ANGPTL1, FBXO32, KCNMA1, and DCN are downregulated in endometrial cancer tissues; LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 are upregulated in endometrial cancer; the constructed lncRNA-miRNA-hub Top10 mRNA network map identified CTD-2314B22, RP11-89 K21/hsa-miR-143, hsa-miR-424/LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 signal axis; survival analysis results show that CTD-2314B22, RP11-89 K21, hsa-miR-96, hsa-miR-211, LHX3, ST8SIA3, and DCN are all related to survival; RT-qPCR results indicate CTD-2314B22, RP11-89 K21, LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 are upregulated in endometrial cancer cells, and hsa-miR-143 and hsa-miR-424 are downregulated in endometrial cancer cells.

Conclusion

From the perspective of the lncRNA-miRNA-mRNA network, our study identified CTD-2314B22, RP11-89 K21/hsa-miR-143, hsa-miR-424/LEFTY1, LIN28A, LHX3, ST8SIA3, and CEP55 signal axis, which can present considerably potent biomarkers and therapeutic targets for treating endometrial cancer.

Joint changes in RNA, RNA polymerase II, and promoter activity through the cell cycle identify non-coding RNAs involved in proliferation

Proper regulation of the cell cycle is necessary for normal growth and development of all organisms. Conversely, altered cell cycle regulation often underlies proliferative diseases such as cancer. Long non-coding RNAs (lncRNAs) are recognized as important regulators of gene expression and are often found dysregulated in diseases, including cancers. However, identifying lncRNAs with cell cycle functions is challenging due to their often low and cell-type specific expression. We present a highly effective method that analyses changes in promoter activity, transcription, and RNA levels for identifying genes enriched for cell cycle functions. Specifically, by combining RNA sequencing with ChIP sequencing through the cell cycle of synchronized human keratinocytes, we identified 1009 genes with cell cycle-dependent expression and correlated changes in RNA polymerase II occupancy or promoter activity as measured by histone 3 lysine 4 trimethylation (H3K4me3). These genes were highly enriched for genes with known cell cycle functions and included 57 lncRNAs. We selected four of these lncRNAs-SNHG26, EMSLR, ZFAS1, and EPB41L4A-AS1-for further experimental validation and found that knockdown of each of the four lncRNAs affected cell cycle phase distributions and reduced proliferation in multiple cell lines. These results show that many genes with cell cycle functions have concomitant cell-cycle dependent changes in promoter activity, transcription, and RNA levels and support that our multi-omics method is well suited for identifying lncRNAs involved in the cell cycle.

Aberrant Expression of Long Non-coding RNAs in Exosomes in Follicle Fluid From PCOS Patients

Polycystic ovary syndrome (PCOS) is a common reproductive endocrine disease characterized by persistent anovulation and hyperandrogenism, affecting approximately 8–10% of women of childbearing age and occupying an important position in the etiology of infertility. There is increasing evidence that long non-coding RNAs (lncRNAs) are involved in the development of PCOS, but the potential regulatory mechanism is still unclear. This study performed high-throughput lncRNA sequencing of follicular fluid exosomes in non-PCOS infertility patients and PCOS infertility patients. The sequencing results led to the identification of 1,253 upregulated and 613 downregulated lncRNAs from a total of 1,866 detected candidates. There was no significant difference between the PCOS patients and non-PCOS patients in body mass index (BMI) or the fasting blood glucose (FBG) level. However, luteinizing hormone (LH), estradiol (E2), testosterone (T), serum prolactin (PRL), and anti-Mullerian hormone (AMH) levels were clearly upregulated in PCOS patients compared to those in non-PCOS patients. There was also an increase in LH/FSH (>2) in the PCOS patients. Functional analysis showed pathways related to endocytosis, the Hippo, the MAPK, and HTLV-1 infection. These results suggest that lncRNAs may play an important role in the pathogenesis of PCOS and may be potential targets for the diagnosis and treatment of PCOS.

The role of HOTAIR/miR-152-3p/LIN28B in regulating the progression of endometrial squamous carcinoma

INTRODUCTION

There is growing evidence that long non-coding RNAs (lncRNAs) are correlated with malignancy in the modulation of tumor progression. This study aims to investigate the effect of homeobox protein (HOX) transcript antisense RNA (HOTAIR) on the migration and invasion of ESC.

MATERIAL AND METHODS

Starbase was used to identify miRNAs with complementary base pairing with HOTAIR. RNA pull-down and qRT-PCR were employed to investigate the effect of HOTAIR on miR-152-3p. In vitro cell migration and invasion assays were performed to assess the effects of HOTAIR and miR-152-3p on ESC. Computational software, TargetScan, was then used to identify the potential target of miR-152-3p, and their relationship was verified by immunoblotting analysis, qRT-PCR and luciferase reporter assay.

RESULTS

Starbase predicted a potential miR-152-3p binding site in HOTAIR, which was validated by RNA pull-down assay. HOTAIR was negatively correlated with miR-152-3p in ESC. Moreover, HOTAIR promoted migration and invasion of ESC. The oncogenic activity of HOTAIR was partly through its negative regulation of miR-152-3p. LIN28B was identified to be a direct target of miR-152-3p. A negative correlation between LIN28B and miR-152-3p was observed in ESC. In addition, overexpression of miR-152-3p suppressed the progression of ESC by directly targeting and regulating LIN28B.

CONCLUSIONS

Our results reveal that HOTAIR may be a driver of ESC through inhibiting miR-152-3p, a tumor suppressor, suggesting that miR-152-3p may be a potential target for advanced ESC therapeutic treatment.

Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools

Endometrial cancer (EC) is the sixth most common cancer in women worldwide. Early diagnosis is critical in recurrent EC management. The present study aimed to identify biomarkers of EC early recurrence using a workflow that combined text and data mining databases (DisGeNET, Gene Expression Omnibus), a prioritization algorithm to select a set of putative candidates (ToppGene), protein-protein interaction network analyses (Search Tool for the Retrieval of Interacting Genes, cytoHubba), association analysis of selected genes with clinicopathological parameters, and survival analysis (Kaplan-Meier and Cox proportional hazard ratio analyses) using a The Cancer Genome Atlas cohort. A total of 10 genes were identified, among which the targeting protein for Xklp2 (TPX2) was the most promising independent prognostic biomarker in stage I EC. TPX2 expression (mRNA and protein) was higher (P<0.0001 and P<0.001, respectively) in ETS variant transcription factor 5-overexpressing Hec1a and Ishikawa cells, a previously reported cell model of aggressive stage I EC. In EC biopsies, TPX2 mRNA expression levels were higher (P<0.05) in high grade tumors (grade 3) compared with grade 1–2 tumors (P<0.05), in tumors with deep myometrial invasion (>50% compared with <50%; P<0.01), and in intermediate-high recurrence risk tumors compared with low-risk tumors (P<0.05). Further validation studies in larger and independent EC cohorts will contribute to confirm the prognostic value of TPX2.

Construction of a Competitive Endogenous RNA Network in Uterine Corpus Endometrial Carcinoma

BACKGROUND Long non-coding RNAs (lncRNAs) affect post-transcriptional regulation by interfering with microRNAs (miRNAs), and by acting as competitive endogenous RNAs (ceRNAs). The roles and mechanisms of lncRNAs as ceRNAs in the progression and prognosis of uterine corpus endometrial carcinoma are not well understood. MATERIAL AND METHODS We analyzed high-throughput transcriptome data downloaded from The Cancer Genome Atlas database for 548 patients with uterine corpus endometrial carcinoma, and the we constructed a ceRNA network. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses of differentially expressed messenger RNAs (DE-mRNAs) were performed using R software. Kaplan-Meier survival curves were generated for all RNAs in the ceRNA network. RESULTS We identified 2612 messenger RNAs (mRNAs), 1111 lncRNAs, and 187 miRNAs that were differentially expressed in uterine corpus endometrial carcinoma. We then identified mutual regulatory relationships between lncRNA-miRNA pairs and miRNA-mRNA pairs. A ceRNA regulatory network for uterine corpus endometrial carcinoma was successfully constructed, and consisted of 87 lncRNAs, 74 mRNAs, and 20 miRNAs. Nine lncRNAs, 3 miRNAs, and 22 mRNAs were associated with prognosis of uterine corpus endometrial carcinoma. We also analyzed the linear relationships between the expression of the 9 DE-lncRNAs and 22 DE-mRNAs with prognostic value. CONCLUSIONS Our study showed that the lncRNAs C2orf48 and LINC00261 might be key regulators of uterine corpus endometrial carcinoma and might serve as prognostic indicators. Our study contributes to the understanding of the molecular mechanisms of uterine corpus endometrial carcinoma, and it identifies lncRNAs that might serve as prognostic markers and therapeutic targets.

Novel Tumor Suppressor lncRNA Growth Arrest-Specific 5 (GAS5) In Human Cancer

Long noncoding RNAs (lncRNAs) play crucial regulatory roles in fundamental biological processes, and deregulations of lncRNAs have been linked to numerous human diseases, especially cancers. Of particular interest in this regard is lncRNA GAS5, which is mainly identified as a tumor suppressor in several cancers. GAS5 was significantly low expressed in multiple cancers and was associated with clinic-pathological characteristics and patient survival, indicating a novel potential diagnostic and prognostic biomarker, and a therapeutic target for cancer. Functionally, GAS5 is involved in cell proliferation, metastasis, invasion, apoptosis, epithelial-mesenchymal transition (EMT), and drug resistance, among others, via multiple molecular mechanisms, such as binding to DNA sequences, forming RNA-DNA triplex complex, triggering or suppressing the expression of genes, binding proteins to form chromatin-modifying complex, which activates or represses gene expression, and acting as miRNA sponge to suppress miRNA expression, leading to regulation of miRNA target genes. This review provides an overview of the current state of knowledge and role of GAS5 in clinical relevance, biological functions and molecular mechanisms underlying the dysregulation of expression and function of GAS5 in cancer. Finally, the potential prospective role as diagnostic and prognostic biomarker and therapeutic target in cancer is discussed.

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 7-lncRNA signature predict prognosis of Uterine corpus endometrial carcinoma

Current research indicate that long noncoding RNAs (lncRNAs) are associated with the progression of various cancers and can be used as prognostic biomarkers. This study aims to construct a prognostic lncRNA signature for the risk assessment of Uterine corpus endometrial carcinoma (UCEC). The RNA-Seq expression profile and corresponding clinical data of UCEC patients obtained from The Cancer Genome Atlas database. First, some prognosis-related lncRNAs were obtained by univariate Cox analysis. The minimum absolute contraction and selection operator (LASSO) regression and the Cox proportional hazard regression method were used to further identify the lncRNA prognostic model. Finally, seven lncRNAs (AC110491.1, AL451137.1, AC005381.1, AC103563.2, AC007422.2, AC108025.2, and MIR7-3HG) were identified as potential prognostic factors. According to the model constructed by the above analysis, the risk score of each UCEC patient was calculated, and the patients were classified into high and low-risk groups. The low-risk group had significant survival benefits. Moreover, we constructed a nomogram that incorporated independent prognostic factors (age, tumor stage, tumor grade, and risk score). The c-index value for evaluating the predictive nomogram model was 0.801. The area under the curve was 0.797 (3-year survival). The calibration curve also showed that there was a satisfactory agreement between the predicted and observed values in the probability of 1-, 3-, and 5-year overall survival. On the basis of the coexpression relationship, we established a coexpression network of lncRNA-messenger RNA (mRNA) of the 7-lncRNA. The Kyoto Encyclopedia of Genes and Genomes analysis of the coexpressing mRNAs showed that the main pathways related to the 7-lncRNA signature were neuroactive ligand-receptor interaction, serotonergic synapse, and gastric cancer pathway. Therefore, our study revealed that the 7-lncRNA could be used to predict the prognosis of UCEC and for postoperative treatment and follow-up.

Knockdown of differentiation antagonizing non-protein coding RNA exerts anti-tumor effect by up-regulating miR-214 in endometrial carcinoma

Differentiation antagonizing non-protein coding RNA (DANCR) is a valuable long noncoding RNA (lncRNA) that involves in the progress of various cancers. However, the functions of DANCR in endometrial carcinoma (EC) have not been validated. In the present study, we aimed to evaluate the roles of DANCR in EC and explore the underlying mechanism. Expression patterns of DANCR in EC specimens and normal control specimens were determined using qRT-PCR. DANCR was knocked down in EC cell lines (AN3CA and HEC-1B) through transfection with small interfering RNA (siRNA) targeting DANCR (si-DANCR). Cell proliferation was examined using the cell counting kit-8 (CCK-8) assay. Cell apoptosis was measured by flow cytometry. Online software starBase was used to predict the target gene of DANCR. Luciferase reporter assay was carried out to confirm the association between DANCR and the predicted target microRNA (miRNA). DANCR expression was up-regulated in EC tissues as compared to the normal control tissues. Knockdown of DANCR in AN3CA and HEC-1B cells markedly suppressed cell proliferation and induced cell apoptosis. miR-214 was found to be a target miRNA of DANCR and its expression was significantly decreased in EC tissues. Suppression of miR-214 abolished the effects of si-DANCR on cell proliferation and apoptosis in AN3CA and HEC-1B cells. DANCR played an important role in promoting tumorigenesis of EC via sponging miR-214. DANCR might serve as a therapeutic target for the treatment of EC.

Association of HOTAIR gene polymorphisms and haplotypes with uterine leiomyoma susceptibility in southeast of Iran

Uterine leiomyoma (UL) is the most common benign tumor of the uterus. HOX transcript antisense RNA (HOTAIR) as a lncRNAs is the product of HOXC gene that plays a major role in the invasion and development of different tumors. Several lines of evidence have been suggested the effects of HOTAIR polymorphisms on cancer risk. The aim of the present study was to analyze the effects of HOTAIR polymorphisms (rs12826786, rs920778, rs4759314 and rs1899663) on UL in southeast of Iran. A total of 152 women with UL and 182 age-matched healthy women were selected in the case-control study. The PCR-RFLP and ARMS-PCR methods were used for genotyping. HOTAIR rs920778 polymorphism was associated with a lower risk of UL in dominant [OR, 0.5 (95% CI, 0.3-0.9); P = 0.03], recessive [OR, 0.6 (95% CI, 0.4-0.9; P = 0.016] and allelic models [OR, 0.6(95% CI, 0.5-0.9); P = 0.004]. However, HOTAIR rs12826786 polymorphism was associated with a higher risk of UL in dominant [OR, 2.6 (95% CI, 1.6-4.1); P = 0.0001], recessive [OR, 1.9 (95% CI, 1-3.6); P = 0.04] and allelic models [OR, 1.8 (95% CI, 1.3-2.4); P = 0.0003]. There was no association between HOTAIR rs4759314 and rs1899663 polymorphisms and UL susceptibility. The frequency of CTGA haplotype was lower in UL women; however, the CCGA, TCGA, TTTA, and TTGA haplotypes were more frequent in UL women. Our results indicated that HOTAIR rs12826786 and rs920778 polymorphisms had a significant effect on UL susceptibility. The HOTAIR haplotypes could affect UL susceptibility.

Exploring lncRNA-Mediated Regulatory Networks in Endometrial Cancer Cells and the Tumor Microenvironment: Advances and Challenges

Recent studies have revealed both the promise and challenges of targeting long non-coding RNAs (lncRNAs) to diagnose and treat endometrial cancer (EC). LncRNAs are upregulated or downregulated in ECs compared to normal tissues and their dysregulation has been linked to tumor grade, FIGO stage, the depth of myometrial invasion, lymph node metastasis and patient survival. Tumor suppressive lncRNAs (GAS5, MEG3, FER1L4 and LINC00672) and oncogenic lncRNAs (CCAT2, BANCR, NEAT1, MALAT1, H19 and Linc-RoR) have been identified as upstream modulators or downstream effectors of major signaling pathways influencing EC metastasis, including the PTEN/PI3K/AKT/mTOR, RAS/RAF/MEK/ERK, WNT/β-catenin and p53 signaling pathways. TUG1 and TDRG1 stimulate the VEGF-A pathway. PCGEM1 is implicated in activating the JAK/STAT3 pathway. Here, we present an overview of the expression pattern, prognostic value, biological function of lncRNAs in EC cells and their roles within the tumor microenvironment, focusing on the influence of lncRNAs on established EC-relevant pathways. We also describe the emerging classification of EC subtypes based on their lncRNA signature and discuss the clinical implications of lncRNAs as valuable biomarkers for EC diagnosis and potential targets for EC treatment.

Identification of prognostic biomarkers of prostate cancer with long non-coding RNA-mediated competitive endogenous RNA network

Prostate cancer (PCa) is the second most frequently diagnosed male cancer, and no treatments exist for effective inhibition of metastatic spread of PCa. Long non-coding RNA (lncRNA) plays key roles in pathogenesis and development of various cancers through competing with endogenous RNAs (ceRNAs), but at present research on lncRNA functions in PCa is still very limited. Hence, this aspect was investigated using bioinformatics methods. Firstly, the functional lncRNA-mediated ceRNA network associated with PCa was constructed by the multi-step computational approach. Then the cytoscape software was used to analyze the node degree and betweenness centrality (BC) value of lncRNAs and mRNAs in the interaction. Finally, the lncRNAs were screened in the central region of the network by the node degree and BC value, and the functional enrichment of mRNAs was evaluated with the Gene Ontology (GO) database. In our results, LINC00476, MALAT1, SNHG11, LINC00649, and ILF3-AS1 are the lncRNAs which have the most nodes and higher BC values and considered as prognostic markers in PCa. GO analysis suggested that the function of screened lncRNAs was obviously focused on intracellular receptor signaling pathway, which indicated these lncRNAs might be potential biomarkers for diagnosis, evaluation and gene-targeted therapy of PCa.

Non-Coding RNAs in Glioma

Glioma is the most aggressive brain tumor of the central nervous system. The ability of glioma cells to migrate, rapidly diffuse and invade normal adjacent tissue, their sustained proliferation, and heterogeneity contribute to an overall survival of approximately 15 months for most patients with high grade glioma. Numerous studies indicate that non-coding RNA species have critical functions across biological processes that regulate glioma initiation and progression. Recently, new data emerged, which shows that the cross-regulation between long non-coding RNAs and small non-coding RNAs contribute to phenotypic diversity of glioblastoma subclasses. In this paper, we review data of long non-coding RNA expression, which was evaluated in human glioma tissue samples during a five-year period. Thus, this review summarizes the following: (I) the role of non-coding RNAs in glioblastoma pathogenesis, (II) the potential application of non-coding RNA species in glioma-grading, (III) crosstalk between lncRNAs and miRNAs (IV) future perspectives of non-coding RNAs as biomarkers for glioma.

Identification of a six-gene signature with prognostic value for patients with endometrial carcinoma

Uterine corpus endometrial carcinoma (UCEC) is frequently diagnosed among women worldwide. However, there are different prognostic outcomes because of heterogeneity. Thus, the aim of the current study was to identify a gene signature that can predict the prognosis of patients with UCEC. UCEC gene expression profiles were first downloaded from the The Cancer Genome Atlas (TCGA) database. After data processing and forward screening, 11 390 key genes were selected. The UCEC samples were randomly divided into training and testing sets. In total, 996 genes with prognostic value were then examined by univariate Cox survival analysis with a P-value <0.01 in the training set. Next, using robust likelihood-based survival modeling, we developed a six-gene signature (CTSW, PCSK4, LRRC8D, TNFRSF18, IHH, and CDKN2A) with a prognostic function in UCEC. A prognostic risk score system was developed by multivariate Cox proportional hazard regression based on this six-gene signature. According to the Kaplan-Meier curve, patients in the high-risk group had significantly poorer overall survival (OS) outcomes than those in the low-risk group (log-rank test P-value <0.0001). This signature was further validated in the testing dataset and the entire TCGA dataset. In conclusion, we conducted an integrated study to develop a six-gene signature for the prognostic prediction of patients with UCEC. Our findings may provide novel biomarkers for prognosis and have significant implications in the understanding of therapeutic targets for UCEC.

Long non-coding RNA: its evolutionary relics and biological implications in mammals: a review

The central dogma of gene expression propounds that DNA is transcribed to mRNA and finally gets translated into protein. Only 2–3% of the genomic DNA is transcribed to protein-coding mRNA. Interestingly, only a further minuscule part of genomic DNA encodes for long non-coding RNAs (lncRNAs) which are characteristically more than 200 nucleotides long and can be transcribed from both protein-coding (e.g. H19 and TUG1) as well as non-coding DNA by RNA polymerase II. The lncRNAs do not have open reading frames (with some exceptions), 3`-untranslated regions (3’-UTRs) and necessarily these RNAs lack any translation-termination regions, however, these can be spliced, capped and polyadenylated as mRNA molecules. The flexibility of lncRNAs confers them specific 3D-conformations that eventually enable the lncRNAs to interact with proteins, DNA or other RNA molecules via base pairing or by forming networks. The lncRNAs play a major role in gene regulation, cell differentiation, cancer cell invasion and metastasis and chromatin remodeling. Deregulation of lncRNA is also responsible for numerous diseases in mammals. Various studies have revealed their significance as biomarkers for prognosis and diagnosis of cancer. The aim of this review is to overview the salient features, evolution, biogenesis and biological importance of these molecules in the mammalian system.

Exploration of DNA methylation markers for diagnosis and prognosis of patients with endometrial cancer

The accurate diagnosis of endometrial cancer (EC) holds great promise for improving its treatment choice and prognosis prediction. This work aimed to identify diagnostic biomarkers for differentiating EC tumors from tumors in other tissues, as well as prognostic signatures for predicting survival in EC patients. We identified 48 tissue-specific markers using a cohort of genome-wide methylation data from three common gynecological tumors and their corresponding normal tissues. A diagnostic classifier was constructed based on these 48 CpG markers that could predict cancerous versus normal tissue with an overall correct rate of 98.3% in the entire repository. Fifteen CpG markers associated with the overall survival (OS) and development of EC were also identified based on the methylation patterns of the EC samples. A prognostic model that aggregated these prognostic CpG markers was established and shown to have a higher discriminative ability to distinguish EC patients with an elevated risk of mortality than the FIGO staging system and several other clinical prognostic variables. This study presents the utility of DNA methylation in identifying biomarkers for the diagnosis and prognosis of EC and will help improve our understanding of the underlying mechanisms involved in the development of EC.

Establishment of a nine-gene prognostic model for predicting overall survival of patients with endometrial carcinoma

Endometrial carcinoma (EC) is the most common malignant tumor of the female genital tract in developed countries. The prognosis of early stage EC is favorable, but a subset faces high risk of cancer progression or recurrence. EC has a poor prognosis upon progression to advanced or metastatic stages. Therefore, our goal is to build a robust prognostic model for predicting overall survival (OS) in EC patients. In this study, 1571 genes were identified as being associated with OS based on genomewide expression profiles using a training dataset. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that these genes were involved in various cancer-related signaling pathways. Nine signature genes were further selected using stepwise selection, and their potential role in the development of EC was demonstrated by performing differential expression analysis between EC and normal uterine tissues. A prognostic model that aggregated these nine signature genes was ultimately established and effectively divided EC patients into two risk groups. OS for patients in the high-risk group was significantly poorer compared with that of the low-risk group. This nine-gene model was subsequently validated and evaluated using the TCGA dataset and shown to have a high discriminating power to distinguish EC patients with an elevated risk of mortality based on the FIGO staging system and other prognostic factors. This study provides a novel prognostic model for the identification of EC patients with elevated risk of mortality and will help to improve our understanding of the underlying mechanisms involved in prognostic EC factors.

lncRNA DLEU1 contributes to tumorigenesis and development of endometrial carcinoma by targeting mTOR

lncRNA DLEU1 as a non-coding gene, involves in the occurrence and development of multiple tumors. However, there is no related report in endometrial carcinoma. In order to focus on the role and mechanism of lncRNA DLEU1 in endometrial carcinoma, we used qRT-PCR to detect the expression of lncRNA DLEU1 and found that lncRNA DLEU1 was highly expressed in endometrial carcinoma compared to normal endometrium. Moreover, compared to Ishikawa and KLE, lncRNA DLEU1 was higher in HEC-1B. In addition, up-regulation of lncRNA DLEU1 promoted cell viability, migration, invasion, and reduced the proportion of apoptosis. Otherwise, down-regulation of lncRNA DLEU1 produced opposite results. Xenograft nude mice model assay showed that lncRNA DLEU1 can promote tumorigenesis in vivo. RiP confirmed that lncRNA DLEU1 could bind to mTOR. The rescue experiments revealed that silence of mTOR after up-regulation of lncRNA DLEU1 resulted in decrease of cell viability, migration, and invasion and increase of apoptosis. The expression changes of PI3K, AKT1, p70S6K, rpS6, GSK3β, STAT3, and Bcl-xl were consistent with lncRNA DLEU1 and mTOR in Western blot. Thus, we suggest that lncRNA DLEU1 combines with mTOR and then increases the expression of PI3K/AKT/mTOR pathway to promote endometrial carcinoma tumorigenesis and progression. The present discovery has probability to provide a biomarker and lay the foundation for targeted therapy of endometrial carcinoma.

Non-Coding RNAs and Endometrial Cancer

Non-coding RNAs (ncRNAs) are involved in the regulation of cell metabolism and neoplastic transformation. Recent studies have tried to clarify the significance of these information carriers in the genesis and progression of various cancers and their use as biomarkers for the disease; possible targets for the inhibition of growth and invasion by the neoplastic cells have been suggested. The significance of ncRNAs in lung cancer, bladder cancer, kidney cancer, and melanoma has been amply investigated with important results. Recently, the role of long non-coding RNAs (lncRNAs) has also been included in cancer studies. Studies on the relation between endometrial cancer (EC) and ncRNAs, such as small ncRNAs or micro RNAs (miRNAs), transfer RNAs (tRNAs), ribosomal RNAs (rRNAs), antisense RNAs (asRNAs), small nuclear RNAs (snRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), competing endogenous RNAs (ceRNAs), lncRNAs, and long intergenic ncRNAs (lincRNAs) have been published. The recent literature produced in the last three years was extracted from PubMed by two independent readers, which was then selected for the possible relation between ncRNAs, oncogenesis in general, and EC in particular.

Prognostic Values of Long Noncoding RNA GAS5 in Various Carcinomas: An Updated Systematic Review and Meta-Analysis

The growth arrest-specific transcript 5 (GAS5) is a long noncoding RNA with low expression in multiple cancers. This meta-analysis aims to explore the association between GAS5 expression levels and cancer patients' prognosis. We collected all the relevant literatures about GAS5 expression levels associated with overall survival (OS), lymph node metastasis (LNM) and high tumor stage (II/III/IV) (HTS) from the PubMed and Web of Science. The hazard ratio (HR) and the corresponding 95% confidence interval (CI) were calculated to evaluate the link strength between GAS5 and cancer prognosis. A total of 934 patients from 14 studies were included to the present meta-analysis, according to the inclusion and exclusion criteria. The results demonstrated that low expression of GAS5 could predict poor OS in cancer patients (HR = 1.955, 95% CI: 1.551-2.465, P < 0.001). Meanwhile we also analyzed the following cancers independently: hepatocellular carcinoma (HR = 1.893, 95% CI: 1.103-3.249, P = 0.021) and urothelial carcinoma (HR = 1.653, 95% CI: 1.185-2.306, P = 0.003). Compared to the high GAS5 expression group, additionally, patients with low GAS5 expression in tumor tissues were more prone to lymph node metastasis (OR = 0.234, 95%CI: 0.153-0.358, P < 0.001) and high tumor stage (OR = 0.185, 95% CI:0.102-0.333, P < 0.001). In conclusion, this meta-analysis showed that GAS5 might be served as a novel biomarker for predicting prognosis in various types of cancers.