Identification and validation of a four-miRNA (miRNA-21-5p, miRNA-9-5p, miR-149-5p, and miRNA-30b-5p) prognosis signature in clear cell renal cell carcinoma

Identification of Disease-Associated MicroRNAs Via Locality-Constrained Linear Coding-Based Ensemble Learning

Clinical trials indicate that the dysregulation of microRNAs (miRNAs) is closely associated with the development of diseases. Therefore, predicting miRNA-disease associations is significant for studying the pathogenesis of diseases. Since traditional wet-lab methods are resource-intensive, cost-saving computational models can be an effective complementary tool in biological experiments. In this work, a locality-constrained linear coding is proposed to predict associations (ILLCEL). Among them, ILLCEL adopts miRNA sequence similarity, miRNA functional similarity, disease semantic similarity, and interaction profile similarity obtained by locality-constrained linear coding (LLC) as the priori information. Next, features and similarities extracted from multiperspectives are input to the ensemble learning framework to improve the comprehensiveness of the prediction. Significantly, the introduction of hypergraph-regular terms improves the accuracy of prediction by describing complex associations between samples. The results under fivefold cross validation indicate that ILLCEL achieves superior prediction performance. In case studies, known associations are accurately predicted and novel associations are verified in HMDD v3.2, miRCancer, and existing literature. It is concluded that ILLCEL can be served as a powerful tool for inferring potential associations.

MicroRNA-155-5p Targets JADE-1, Promoting Proliferation, Migration, and Invasion in Clear Cell Renal Cell Carcinoma Cells

Clear cell renal cell carcinoma (ccRCC) incidence has been rising in recent years, with strong association between differential microRNA (miRNA) expression and neoplastic progression. Specifically, overexpression of miR-155-5p has been associated with promoting aggressive cancer in ccRCC and other cancers. In this study, we further investigate the role of this miRNA and one of its protein targets, Jade-1, to better understand the mechanism behind aggressive forms of ccRCC. Jade-1, a tumor suppressor, is stabilized by Von-Hippel Lindau (VHL), which is frequently mutated in ccRCC. Experiments featuring downregulation of miR-155-5p in two ccRCC cell lines (786-O and Caki-1) attenuated their oncogenic potential and led to increased levels of Jade-1. Conversely, knockdown experiments with an anti-Jade-1 shRNA in 786-O and Caki-1 cells showed increased metastatic potential through elevated proliferation, migration, and invasion rates. In a mouse xenograft model, downregulation of miR-155 decreased the rate of tumor implantation and proliferation. Direct interaction between miR-155-5p and Jade-1 was confirmed through a 3'UTR luciferase reporter assay. These findings further elucidate the mechanism of action of miR-155-5p in driving an aggressive phenotype in ccRCC through its role in regulating Jade-1.

MiRNA-21-5p Accelerates EMT and Inhibits Apoptosis of Laryngeal Carcinoma via Inhibiting KLF6 Expression

The incidence of laryngeal carcinoma accounts for 1 to 5% of systemic malignancies and ranks second among head and neck malignancies. Screening more effective targets are meaningful for the treatment of laryngeal carcinoma. The purpose was to research the action of miR-21-5p in the occurrence of laryngeal carcinoma. Genecards combined with g:profiler was used for cluster analysis to predict gene-related miRNAs. Q-PCR assay was performed for measuring the level of miR-21-5p and Kruppel-like factor 6 (KLF6). miR-21-5p-mimic, miR-21-5p-inhibitor and sh-KLF6 were transfected using LipofectamineTM 2000. Both CCK-8 and EdU experiments were undertaken to detect cell proliferation ability. Western blot was used to detect apoptosis and epithelial-mesenchymal transition (EMT) related proteins. Wound healing assay and transwell assay were undertaken for migration and invasion, respectively. Three online software (ENCORI, miRWalk, and miRDB) were applied to screen the downstream of miR-21-5p. At the same time, a dual-luciferase reporter experiment was processed to verify the binding. Finally, a rescue experiment was applied to reveal the mediating role of miR-21-5p and KLF6. MiR-21-5p expressed highly in laryngeal carcinoma tissues and cell lines. Knockdown of miR-21-5p reduced the EMT, while enhancing apoptosis of laryngeal carcinoma cell lines. MiR-21-5p targeted KLF6 with negative relationships. The rescue assay results confirmed that sh-KLF6 rescued the action of miR-21-5p knockdown in developing laryngeal carcinoma cells. MiR-21-5p promotes the occurrence and development of laryngeal cancer by targeting KLF6. This finding may provide new insights into miRNA as a biomarker for diagnosing and treating laryngeal carcinoma in the future.

Bioinformatic Analysis Divulged Novel Prognostic Circulating MicroRNAs and Their Potential Target Genes in Breast Cancer

Breast cancer (BC) is both an inherited and environmental-based disease which is the leading cause of death among women. Early detection of BC can prevent invasion and metastasis in patients. Currently, researchers endeavor to find non-invasive biological markers from body fluids. Circulating non-coding RNAs such as microRNAs (miRNAs) can potentially be valuable prognostic and detective biomarkers. To identify novel miRNA-based biomarkers, we utilized bioinformatic tools. To reach this goal, the miRNA expression profiles of GSE31309, GSE 44,281, GSE98181, and GSE118782 were analyzed through a limma package of R. Target gene prediction of differentially expressed miRNAs, called differentially expressed miRNAs (DEMs), between samples of healthy individuals and BC patients was implemented through Multimir package of R. Functional enrichment analysis of predicted target genes through Enrich R (online database) revealed that most of the genes are enriched in the mitochondrial outer membrane for cellular component, intrinsic apoptotic signaling regulations for biological processes, transcription co-receptor activity for molecular functions, and dopaminergic synapse pathway. Furthermore, our survival analysis results revealed that miR-29c and mir-361 have the potential to serve as prognostic biomarkers.

The Role of Long Noncoding RNA (lncRNAs) Biomarkers in Renal Cell Carcinoma

Renal cell carcinoma is one of the common cancers whose incidence and mortality are continuously growing worldwide. Initially, this type of tumour is usually asymptomatic. Due to the lack of reliable diagnostic markers, one-third of ccRCC patients already have distant metastases at the time of diagnosis. This underlines the importance of establishing biomarkers that would enable the prediction of the disease's course and the risk of metastasis. LncRNA, which modulates genes at the epigenetic, transcriptional, and post-transcriptional levels, appears promising. The actions of lncRNA involve sponging and sequestering target miRNAs, thus affecting numerous biological processes. Studies have confirmed the involvement of RNAs in various diseases, including RCC. In this review, we focused on MALAT1 (a marker of serious pathological changes and a factor in the promotion of tumorigenesis), RCAT1 (tumour promoter in RCC), DUXAP9 (a plausible marker of localized ccRCC), TCL6 (exerting tumour-suppressive effects in renal cancer), LINC00342 (acting as an oncogene), AGAP2 Antisense1 (plausible predictor of RCC progression), DLEU2 (factor promoting tumours growth via the regulation of epithelial-mesenchymal transition), NNT-AS1 (sponge of miR-22 contributing to tumour progression), LINC00460 (favouring ccRCC development and progression) and Lnc-LSG1 (a factor that may stimulate ccRCC metastasis).

Identification and validation of the molecular subtype and prognostic signature for clear cell renal cell carcinoma based on neutrophil extracellular traps

Background: Renal cell carcinoma (RCC) is one of the most common cancers, with an annual incidence of nearly 400,000 cases worldwide. Increasing evidence has also demonstrated the vital role of neutrophil extracellular traps (NETs) in cancer progression and metastatic dissemination. Methods: Consensus cluster analysis was performed to determine the number of ccRCC subtypes. The Kruskal-Wallis test or Student t-test was performed to evaluate the difference of infiltrating immune cell and gene expression in different groups. The Kaplan-Meier (KM) method was used to draw the survival curve. LASSO cox regression analysis was conducted to construct a NET-related prognostic signature. We also constructed a lncRNA-miRNA-mRNA regulatory axis by several miRNA and lncRNA target databases. Results: A total of 23 differentially expressed NET-related genes were obtained in ccRCC. Three clusters of ccRCC cases with significant difference in prognosis, immune infiltration, and chemotherapy and targeted therapy were identified. LASSO Cox regression analysis identified a NET-related prognostic signature including six genes (G0S2, DYSF, MMP9, SLC22A4, SELP, and KCNJ15), and this signature had a good performance in predicting the overall survival of ccRCC patients. The expression of prognostic signature genes was significantly correlated with the pTMN stage, immune infiltration, tumor mutational burdens, microsatellite instability, and drug sensitivity of ccRCC patients. MMP9 was identified as the hub gene. We also identified the lncRNA UBA6-AS1/miR-149-5p/MMP9 regulatory axis for the progression of ccRCC. Conclusion: Collectively, the current study identified three molecular clusters and a prognostic signature for ccRCC based on neutrophil extracellular traps. Integrative transcriptome analyses plus clinical sample validation may facilitate the biomarker discovery and clinical transformation.

Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion

MicroRNAs (miRNAs) are gene regulators involved in the pathogenesis of complex diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic targets. The prerequisite for designing effective miRNA therapies is accurate discovery of miRNA-disease associations (MDAs), which has attracted substantial research interests during the last 15 years, as reflected by more than 55 000 related entries available on PubMed. Abundant experimental data gathered from the wealth of literature could effectively support the development of computational models for predicting novel associations. In 2017, Chen et al. published the first-ever comprehensive review on MDA prediction, presenting various relevant databases, 20 representative computational models, and suggestions for building more powerful ones. In the current review, as the continuation of the previous study, we revisit miRNA biogenesis, detection techniques and functions; summarize recent experimental findings related to common miRNA-associated diseases; introduce recent updates of miRNA-relevant databases and novel database releases since 2017, present mainstream webservers and new webserver releases since 2017 and finally elaborate on how fusion of diverse data sources has contributed to accurate MDA prediction.

Tumor-Suppressive and Oncogenic Roles of microRNA-149-5p in Human Cancers

Malignant tumors are always a critical threat to human health, with complex pathogenesis, numerous causative factors, and poor prognosis. The features of cancers, such as gene mutations, epigenetic alterations, and the activation and inhibition of signaling pathways in the organism, play important roles in tumorigenesis and prognosis. MicroRNA (miRNA) enables the control of various molecular mechanisms and plays a variety of roles in human cancers, such as radiation sensitivity and tumor immunity, through the regulation of target genes. MiR-149-5p participates in the process and is closely related to lipogenesis, the migration of vascular endothelial cells, and the expression of stem-cell-related proteins. In recent years, its role in cancer has dramatically increased. In this review, we summarize the regular physiological roles of miRNAs, specifically miR-149-5p, in the organism and discuss the tumor-suppressive or oncogenic roles of miR-149-5p in different human cancers with respect to signaling pathways involved in regulation. Possible clinical applications of miR-149-5p in future targeted therapies and prognosis improvement in oncology are suggested.

An Integrative Analysis Framework for Identifying the Prognostic Markers from Multidimensional RNA Data of Clear Cell Renal Cell Carcinoma

The altered regulatory status of long noncoding RNA (lncRNA), miRNA, and mRNA and their interactions play critical roles in tumor proliferation, metastasis, and progression, which ultimately influence cancer prognosis. However, there are limited studies of comprehensive identification of prognostic biomarkers from combined data sets of the three RNA types in the highly metastatic clear cell renal cell carcinoma (ccRCC). The current study employed an integrative analysis framework of functional genomics approaches and machine learning methods to the lncRNA, miRNA, and mRNA data and identified 16 RNAs (3 lncRNAs, 6 miRNAs, and 7 mRNAs) of prognostic value, with 9 of them novel. A 16 RNA-based score was established for prognosis prediction of ccRCC with significance (P < 0.0001). The area under the curve for the score model was 0.868 to 0.870 in the training cohort and 0.714 to 0.778 in the validation cohort. Construction of the lncRNA-miRNA-mRNA interaction network showed that the downstream mRNAs and upstream lncRNAs in the network initiated from the miRNA or lncRNA markers exhibit significant enrichment in functional classifications associated with cancer metastasis, proliferation, progression, or prognosis. The functional analysis provided clear support for the role of the RNA biomarkers in predicting cancer prognosis. This study provides promising biomarkers for predicting prognosis of ccRCC using multidimensional RNA data, and these findings are expected to facilitate potential clinical applications of the biomarkers.

Construction of five microRNAs prognostic markers and a prognostic model for clear cell renal cell carcinoma

Background

To determine the role of miRNA in the progression and outcome of renal clear cell carcinoma (ccRCC), establish a model for predicting outcome in patients with ccRCC and verify it using a Cox regression model. The miRNA target genes were predicted to understand their biological functions.

Methods

The microRNAs of 71 normal tissues and 545 tumor tissues were downloaded from TCGA (https://tcga-data.nci.nih.gov/tcga/). We also downloaded 537 clinical materials from this website. The miRNA difference analysis was carried out. A prognostic model was constructed using differential miRNA. The model was verified using Cox survival analysis, receiver operator characteristic (ROC), and independent predictive analysis.

Results

MiR-130b-3p, miR-365b-3p, miR-149-5p, miR-155-5p, and miR-144-5p can be used as independent prognostic indicators. We also analyzed the related functions of the target gene and found that target genes of miRNAs are involved in the signal pathways of some tumors, including cholesterol metabolism, HIF-1 signal pathway, focus adhesion, the Rap1 signal pathway, and hepatitis C.

Conclusions

The prognostic model constructed using five miRNAs is an independent and accurate factor. These miRNAs target genes are involved in regulating a variety of tumorigenesis and signal pathways. Therefore, we have reason to believe that the regulation of signal pathways by miRNA may play a critical role in the occurrence, development, and outcome of ccRCC, provide a new therapeutic target for ccRCC, and improve outcomes.

A Review on the Role of miR-149-5p in the Carcinogenesis

miR-149 is an miRNA with essential roles in carcinogenesis. This miRNA is encoded by the MIR149 gene on 2q37.3. The miR-149 hairpin produces miR-149-5p and miR-149-3p, which are the “guide” and the sister “passenger” strands, respectively. Deep sequencing experiments have shown higher prevalence of miR-149-5p compared with miR-149-3p. Notably, both oncogenic and tumor suppressive roles have been reported for miR-149-5p. In this review, we summarize the impact of miR-149-5p in the tumorigenesis and elaborate mechanisms of its involvement in this process in a variety of neoplastic conditions based on three lines of evidence, i.e., in vitro, in vivo and clinical settings.

MiR-149-5p: An Important miRNA Regulated by Competing Endogenous RNAs in Diverse Human Cancers

MicroRNAs (miRNAs) consist of a large family of small, non-coding RNAs with the ability to result in gene silencing post-transcriptionally. With recent advances in research technology over the past several years, the physiological and pathological potentials of miRNAs have been gradually uncovered. MiR-149-5p, a conserved miRNA, was found to regulate physiological processes, such as inflammatory response, adipogenesis and cell proliferation. Notably, increasing studies indicate miR-149-5p may act as an important regulator in solid tumors, especially cancers in reproductive system and digestive system. It has been acknowledged that miR-149-5p can function as an oncogene or tumor suppressor in different cancers, which is achieved by controlling a variety of genes expression and adjusting downstream signaling pathway. Moreover, the levels of miR-149-5p are influenced by several newly discovered long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs). However, there is blank about systematic function and mechanism of miR-149-5p in human cancers. In this review, we firstly summarize the present comprehension of miR-149-5p at the molecular level, its vital role in tumor initiation and progression, as well as its potential roles in monitoring diverse reproductive and digestive malignancies.

Aberration of lncRNA LINC00460 is a Promising Prognosis Factor and Associated with Progression of Clear Cell Renal Cell Carcinoma

Purpose

Long noncoding RNAs have been studied more and more as potential prognostic markers. However, the prognostic of LINC00460 in clear cell renal cell carcinoma (ccRCC) has not been explored. In this study, the potential role of LINC00460 was investigated in ccRCC.

Patients and Methods

One hundred thirteen pairs of ccRCC tissues and para-normal tissues were collected. The expressions of LINC00460 in these tissues and ccRCC cells were evaluated via qRT-PCR. The prognostic value of LINC00460 was accessed with the use of Kaplan–Meier analysis and Cox proportional hazards model analysis. The influence of LINC00460 on ccRCC cell proliferation, migration, and invasion was determined via cell counting kit-8 (CCK-8) and Transwell assays.

Results

The results revealed that LINC00460 was significantly enhanced in ccRCC tissues, as well as in ccRCC cell lines. The overexpression of LINC00460 was significantly associated with lymph node metastasis and TNM stage, and lead to poor overall survival. Knockdown of LINC00460 reduces the cell ability of proliferation, migration, and invasion. LINC00460 could sponge to miR-149-5p.

Conclusion

LINC00460 may be developed as a prognostic biomarker and molecular therapy target for ccRCC.

Network analysis of miRNA targeting m6A-related genes in patients with esophageal cancer

Background

We investigated the miRNA-m6A related gene network and identified a miRNA-based prognostic signature in patients with esophageal cancer using integrated genomic analysis.

Methods

We obtained expression data for m6A-related genes and miRNAs from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Survival analysis was conducted to identify potential prognostic biomarkers. LASSO Cox regression was performed to construct the overall survival (OS) associated prediction signature. We used the Kaplan-Meier (K-M) curve and receiver operating characteristic (ROC) curves to explore the signature's efficiency and accuracy. Interactions between the m6A-related genes and miRNAs were identified in starBase3.0 and used to construct the miRNA-m6A related gene network.

Results

We found that HNRNPC, YTHDF, ZC3H13, YTHDC2, and METTL14 were dysregulated in esophageal cancer tissues. Multivariate Cox regression analysis revealed that HNRNPC may be an independent risk factor for OS. Five hundred twenty-two potential upstream miRNAs were obtained from starBase3.0. Four miRNAs (miR-186, miR-320c, miR-320d, and miR-320b) were used to construct a prognostic signature, which could serve as a prognostic predictor independent from routine clinicopathological features. Finally, we constructed a key miRNA-m6A related gene network and used one m6A-related gene and four miRNAs associated with the prognosis. The results of our bioinformatics analysis were successfully validated in the human esophageal carcinoma cell lines KYSE30 and TE-1.

Conclusion

Our study identified a 4-miRNA prognostic signature and established a key miRNA-m6A related gene network. These tools may reliably assist with esophageal cancer patient prognosis.

A microRNA-clinical prognosis model to predict the overall survival for kidney renal clear cell carcinoma

Numerous studies have shown that microRNA (miRNA) serves as key regulatory factors in the origin and development of cancers. However, the biological mechanisms of miRNAs in kidney renal clear cell carcinoma (KIRC) are still unknown. It is necessary to construct an effective miRNA‐clinical model to predict the prognosis of KIRC. In this study, 94 differentially expressed miRNAs were found between para‐tumor and tumor tissues based on the Cancer Genome Atlas (TCGA) database. Seven miRNAs (hsa‐miR‐21‐5p, hsa‐miR‐3613‐5p, hsa‐miR‐144‐5p, hsa‐miR‐376a‐5p, hsa‐miR‐5588‐3p, hsa‐miR‐1269a, and hsa‐miR‐137‐3p) were selected as prognostic indicators. According to their cox coefficient, a risk score formula was constructed. Patients with risk scores were divided into high‐ and low‐risk groups based on the median score. Kaplan–Meier curves analysis showed that the low‐risk group had a better survival probability compared to the high‐risk group. The area under the ROC curve (AUC) value of the miRNA model was 0.744. In comparison with clinical features, the miRNA model risk score was considered as an independent prognosis factor in multivariate Cox regression analysis. In addition, we built a nomogram including age, metastasis, and miRNA prognostic model based on the results of multivariate Cox regression analysis. The decision curve analysis (DCA) revealed the clinical net benefit of the prognostic model. Gene set enrichment analysis (GSEA) results suggested that several important pathways may be the potential pathways for KIRC. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for the target genes of 7 miRNAs revealed that miRNAs may participate in KIRC progression via many specific pathways. Additionally, the levels of seven prognostic miRNAs showed a significant difference between KIRC tissues and adjacent non‐tumorous tissues. In conclusion, the miRNA‐clinical model provides an effective and accurate way to predict the prognosis of KIRC.

A Liquid-Liquid Phase Separation-Related Gene Signature as Prognostic Biomarker for Epithelial Ovarian Cancer

Objective

The aim of the present study was to construct and test a liquid-liquid phase separation (LLPS)-related gene signature as a prognostic tool for epithelial ovarian cancer (EOC).

Materials and Methods

The data set GSE26712 was used to screen the differentially expressed LLPS-related genes. Functional enrichment analysis was performed to reveal the potential biological functions. GSE17260 and GSE32062 were combined as the discovery to construct an LLPS-related gene signature through a three-step analysis (univariate Cox, least absolute shrinkage and selection operator, and multivariate Cox analyses). The EOC data set from The Cancer Genome Atlas as the test set was used to test the LLPS-related gene signature.

Results

The differentially expressed LLPS-related genes involved in several cancer-related pathways, such as MAPK signaling pathway, cell cycle, and DNA replication. Eleven genes were selected to construct the LLPS-related gene signature risk index as prognostic biomarker for EOC. The risk index could successfully divide patients with EOC into high- and low-risk groups. The patients in high-risk group had significantly shorter overall survival than those with in low-risk group. The LLPS-related gene signature was validated in the test set and may be an independent prognostic factor compared to routine clinical features.

Conclusion

We constructed and validated an LLPS-related gene signature as a prognosis tool in EOC through integrated analysis of multiple data sets.

miR-149-5p Regulates Goat Hair Follicle Stem Cell Proliferation and Apoptosis by Targeting the CMTM3/AR Axis During Superior-Quality Brush Hair Formation

The Yangtze River Delta white goat is a unique goat species that can produce superior quality brush hair. CKLF-like MARVEL transmembrane domain-containing 3 (CMTM3), which influences the transcriptional activity of androgen receptor (AR), was identified as a candidate gene related to superior-quality brush hair formation. CMTM3 is generally expressed at low levels, but miR-149-5p is highly expressed in the skin tissues of these goats. The mechanism by which CMTM3 regulates the proliferation and apoptosis of goat hair follicle stem cells has not been elucidated. Here, RT-qPCR, western blotting, 5-ethynyl-2′-deoxyuridine (EdU), cell cycle, apoptosis, and dual-luciferase assays were used to investigate the role and regulatory mechanism of CMTM3 and miR-149-5p. Functional studies showed that CMTM3 overexpression inhibited proliferation and induced apoptosis in cultured hair follicle stem cells, whereas silencing CMTM3 markedly facilitated cell proliferation and deterred apoptosis in cultured hair follicle stem cells. Then, using bioinformatic predictions and the aforementioned assays, including dual-luciferase assays, RT-qPCR, and western blotting, we confirmed that miR-149-5p targets CMTM3 and preliminarily investigated the interaction between CMTM3 and AR in goat hair follicle stem cells. Furthermore, miR-149-5p overexpression significantly accelerated the proliferation and attenuated the apoptosis of hair follicle stem cells. Conversely, miR-149-5p inhibition suppressed the proliferation and induced the apoptosis of hair follicle stem cells. These results reveal a miR-149-5p-related regulatory framework for the miR-149-5p/CMTM3/AR axis during superior quality brush hair formation, in which CMTM3 plays a negative role.

circ_001504 promotes the development of renal cell carcinoma by sponging microRNA-149 to increase NUCB2

Renal cell carcinoma (RCC) accounts for over 90% of primary renal tumors in adults. Although treatment approaches have steadily improved over the years, the prognosis outcome remains poor. With the aim of developing novel targets for RCC treatment, we explored the role of the circular RNA (circRNA) circ_001504 in the progression of RCC. We initially detected the expression of circ_001504 and microRNA (miRNA)-149 in RCC tissues and cells. RT-qPCR results showed that circ_001504 was highly expressed in RCC tissues, whereas miR-149 was poorly expressed. Interestingly, downregulation of circ_001504 suppressed malignant phenotypes in RCC cells, and upregulation of miR-149 exerted a similar effect. Bioinformatics analysis suggested potential binding sites between circ_001504 and miR-149, verified by a dual-luciferase reporter gene assay. Next, we identified nucleobindin 2 (NUCB2), a calcium-binding protein, as a target gene of miR-149. Furthermore, our data suggested that circ_001504 might serve as a competing endogenous RNA of miR-149, serving to elevate the expression of NUCB2. The silencing of circ_001504 resulted in decreased NUCB2 expression, which could be reversed by miR-149 inhibition. In addition, in vivo experiments demonstrated that circ_001504 depletion could suppress tumor growth in an established mouse RCC model. Collectively, reduced expression of circ_001504 lowered NUCB2 expression by sponging miR-149, thereby attenuating RCC progression, providing insight into circ_001504/miR-149/NUCB2 feedback loop into RCC treatment.

Identification of RNA Transcript Makers Associated With Prognosis of Kidney Renal Clear Cell Carcinoma by a Competing Endogenous RNA Network Analysis

Objective

This study aims to identify several RNA transcripts associated with the prognosis of kidney renal clear cell carcinoma (KIRC).

Methods

The differentially expressed mRNAs, lncRNAs, and miRNAs (DEmRNAs, DElncRNAs, and DEmiRNAs) between KIRC cases and controls were screened based on an RNA-seq dataset from The Cancer Genome Atlas (TCGA) database. Subsequently, miRcode, miRDB, and TargetScan database were used to predict interactions between lncRNAs, miRNAs and target mRNAs. Then, a ceRNA network was built using miRNAs-mRNAs and lncRNAs-miRNAs pairs. Functional analysis of mRNAs in ceRNA was performed. Finally, the survival analysis of RNA transcripts in ceRNA network and correlation analysis for key RNA regulators were carried out.

Results

There were 1527 DElncRNAs, 54 DEmiRNAs, and 2321 DEmRNAs. A ceRNA network was constructed among 81 lncRNAs, 9 miRNAs, and 197 mRNAs. Functional analysis showed that numerous mRNAs were significantly associated with regulation of cellular glucuronidation. In addition, 35 lncRNAs, 84 mRNAs and two miRNAs were significantly corelated to the survival of patients with KIRC (P < 0.05). Among them, miRNA-21 and miRNA-155 were negatively related to three lncRNAs (LINC00472, SLC25A5.AS1, and TCL6). Seven mRNA targets of miRNA-21 (FASLG, FGF1, TGFBI, ALX1, SLC30A10, ADCY2, and ABAT) and 12 mRNAs targets of miRNA-155 (STXBP5L, SCG2, SPI1, C12orf40, TYRP1, CTHRC1, TDO2, PTPRQ, TRPM8, ERMP1, CD36, and ST9SIA4) also acted as prognostic biomarkers for KIRC patients.

Conclusion

We screened numerous novel prognosis-related RNA markers for KIRC patients by a ceRNA network analysis, providing deeper understandings of prognostic values of RNA transcripts for KIRC.

miR-758-3p Inhibits Proliferation, Migration, and Invasion of Clear Cell Renal Cell Carcinoma and Predicts Favorable Prognosis

Background

Although miR-758-3p has been reported to be associated with multiple cancers, including hepatocellular carcinoma, bladder cancer, gastric cancer and papillary thyroid cancer, its role in clear cell renal cell carcinoma (ccRCC) remains unclear.

Methods

The expression levels of miR-758-3p in ccRCC tissues and cell lines were examined using qRT-PCR. Survival analysis was performed using Kaplan–Meier, while the prognostic significance of miR-758-3p was evaluated by Cox regression analysis. The effects of miR-758-3p on cell proliferation, migration and invasion were analyzed with CCK-8, crystal violet and transwell assays. Luciferase reporter assays were performed to determine the effect of miR-758-3p on MDM2. Western blot was applied to measure the expression of MDM2.

Results

The expression levels of miR-758-3p were down-regulated in human ccRCC tissues and cell lines. Moreover, the expression of miR-758-3p was closely associated with histological grade, TNM stage and vascular invasion. High expression of miR-758-3p was found to be capable of predicting favorable clinical prognosis in ccRCC patients. Additionally, whilst the proliferation, migration and invasion of ccRCC cells were inhibited upon overexpression of miR-758-3p, the effects were reversed upon miR-758-3p knockdown. Moreover, miR-758-3p was a modulator of MDM2 in ccRCC.

Conclusion

This study demonstrated that miR-758-3p is a potential prognostic biomarker for ccRCC patients. Data from this study showed that miR-758-3p exhibits different biological functions that inhibit the progression of ccRCC cells, hence it can be a potential therapeutic target candidate for treating ccRCC.

Identification of miRNA signatures for kidney renal clear cell carcinoma using the tensor-decomposition method

Cancer is a highly complex disease caused by multiple genetic factors. MicroRNA (miRNA) and mRNA expression profiles are useful for identifying prognostic biomarkers for cancer. Kidney renal clear cell carcinoma (KIRC), which accounts for more than 70% of all renal malignant tumour cases, was selected for our analysis. Traditional methods of identifying cancer prognostic markers may not be accurate. Tensor decomposition (TD) is a useful method uncovering the underlying low-dimensional structures in the tensor. The TD-based unsupervised feature extraction method was applied to analyse mRNA and miRNA expression profiles. Biological annotations of the prognostic miRNAs and mRNAs were examined utilizing the pathway and oncogenic signature databases DIANA-miRPath and MSigDB. TD identified the miRNA signatures and the associated genes. These genes were found to be involved in cancer-related pathways, and 23 genes were significantly correlated with the survival of KIRC patients. We demonstrated that the results are robust and not highly dependent upon the databases we selected. Compared with traditional supervised methods tested, TD achieves much better performance in selecting prognostic miRNAs and mRNAs. These results suggest that integrated analysis using the TD-based unsupervised feature extraction technique is an effective strategy for identifying prognostic signatures in cancer studies.

Clinical significance of miR-1180-3p in hepatocellular carcinoma: a study based on bioinformatics analysis and RT-qPCR validation

miRNAs play an indispensable role in human carcinogenesis. Dysregulated miR-1180-3p has been observed in several types of cancer, including hepatocellular carcinoma (HCC). This study intends to correlate the expression level of miR-1180-3p with clinical features and overall survival in HCC patients. The expression and clinical significance of miR-1180-3p, selected from GEO and TCGA databases, were verified using an RT-qPCR method. The target genes of miR-1180-3p were obtained using 3 miRNA target gene prediction databases, and their functions were analyzed using the online tool WebGestalt. miR-1180-3p expression was significantly upregulated in 88 HCC tissues compared with non-tumor liver tissues (0.004 ± 0.009 vs. 0.002 ± 0.002, t = − 2.099, P = 0.038). Additionally, we found that the expression levels of miR-1180-3p were significantly correlated with tumor number (χ² = 9.157, P = 0.006) and MVI (χ² = 11.354, P = 0.003). Based on Kaplan–Meier analysis, patients with high miR-1180 expression had a shorter overall survival than those with low miR-1180-3p expression (P = 0.002). Furthermore, multivariate Cox analyses indicated that miR-1180-3p expression was an independent prognostic factor for overall survival (HR = 13.36, 95% CI 1.16, 153.69, P = 0.038). In addition, a total of 733 target genes of miR-1180-3p were found from three prediction databases. The GO analyses demonstrated that the target genes were closely related to the proliferation and malignancy of tumors. The KEGG analysis showed that target genes were enriched in several key cancer-related signaling pathways, including the Pathways in cancer, the Ras signaling pathway, and the MAPK signaling pathway. In conclusion, we demonstrate that miR-1180-3p is upregulated in HCC and is associated with a poor prognosis. Thus, miR-1180-3p might be useful as a prognostic marker for HCC.

Identification of an Autophagy-Related Prognostic Signature for Clear Cell Renal Cell Carcinoma

Abnormal autophagy is closely related to the development of cancer. Many studies have demonstrated that autophagy plays an important role in biological function in clear cell renal cell carcinoma (ccRCC). This study aimed to construct a prognostic signature for ccRCC based on autophagy-related genes (ARGs) to predict the prognosis of ccRCC. Differentially expressed ARGs were obtained from ccRCC RNA-seq data in The Cancer Genome Atlas (TCGA) database. ARGs were enriched by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The prognostic ARGs used to construct the risk score models for overall survival (OS) and disease-free survival (DFS) were identified by Cox regression analyses. According to the median value of the risk score, patients were divided into a high-risk group and a low-risk group. The OS and DFS were analyzed by the Kaplan-Meier method. The predictive accuracy was determined by a receiver operating characteristic (ROC) curve analysis. Additionally, we performed stratification analyses based on different clinical variables and evaluated the correlation between the risk score and the clinical variables. The differentially expressed ARGs were mainly enriched in the platinum drug resistance pathway. The prognostic signatures based on 11 ARGs for OS and 5 ARGs for DFS were constructed and showed that the survive time was significantly shorter in the high-risk group than in the low-risk group (P < 0.001). The ROC curve for OS exhibited good predictive accuracy, with an area under the curve value of 0.738. In the stratification analyses, the OS time of the high-risk group was shorter than that of the low-risk group stratified by different clinical variables. In conclusion, an autophagy-related signature for OS we constructed can independently predict the prognosis of ccRCC patient, and provide a deep understanding of the potential biological mechanisms of autophagy in ccRCC.

Nomogram Based on microRNA Signature Contributes to Improve Survival Prediction of Clear Cell Renal Cell Carcinoma

Objective

Numerous microRNAs (miRNAs) have been identified in ccRCC and recommended to be used for predicting clear cell renal cell carcinoma (ccRCC) prognosis. However, it is not clear whether a miRNA-based nomogram results in improved survival prediction in patients with ccRCC.

Methods

miRNA profiles from tumors and normal tissues were downloaded from The Cancer Genome Atlas (TCGA) database and analyzed using the "limma" package. The association between differentially expressed miRNAs and patient prognosis was identified using univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. Next, all patients were randomly divided into development and validation cohorts at a ratio of 1 : 1. A nomogram was established based on independent prognostic factors in the development cohort. The prognostic performance of the nomogram was validated in both cohorts using the concordance index (C-index) and calibration plots.

Results

Multivariate Cox analysis identified the 13-miRNA signature, as well as AJCC stage and age, as independent prognostic factors after adjusting for other clinical covariates. The nomogram was built based on the independent variables. In the development cohort, the C-index for the constructed nomogram to predict overall survival (OS) was 0.792, which was higher than the C-index (0.731) of the AJCC staging system and C-index (0.778) of the miRNA signature. The nomogram demonstrated good discriminative ability in the validation cohort in predicting OS, with a C-index of 0.762. The calibration plots indicated an excellent agreement between the nomogram predicted survival probability and the actual observed outcomes. Furthermore, decision curve analysis (DCA) indicated that the nomogram was superior to the AJCC staging system in increasing the net clinical benefit.

Conclusions

The novel proposed nomogram based on a miRNA signature is a more reliable and robust tool for predicting the OS of patients with ccRCC compared to AJCC staging system, thus, improving clinical decision-making.

A seven-miRNA expression-based prognostic signature and its corresponding potential competing endogenous RNA network in early pancreatic cancer

The present study aimed to establish a microRNA (miRNA/miR) signature to predict the prognosis of patients with pancreatic cancer (PC) at the early stage and to investigate the involvement of competing endogenous RNAs (ceRNAs) in PC. Using mature miRNA expression profiles from The Cancer Genome Atlas, differentially expressed miRNAs in tissues derived from patients exhibiting early PC and tissues from healthy individuals were compared. The least absolute shrinkage and selection operator regression method was used to construct a miRNA-based signature for predicting prognosis. The miRNet tool, gene set enrichment analysis (GSEA) and the LncRNADisease database were utilized to explore the mechanistic involvement of ceRNAs. A total of seven downregulated miRNAs in PC (miR-424-5p, miR-139-5p, miR-5586-5p, miR-126-3p, miR-3613-5p, miR-454-3p and miR-1271-5p) were selected to generate a signature. Based on this seven-miRNA signature, it was possible to stratify patients with PC into low- and high-risk groups. The overall survival of the low-risk group was significantly longer than that of the high-risk group (P<0.001). The seven-miRNA signature was able to predict the 2-year-survival rate of patients with early PC with an area under the curve of 0.750. Furthermore, as opposed to routine clinicopathological features, this seven-miRNA signature was an independent prognostic factor according to multivariate Cox regression analysis. GSEA indicated that the extracellular matrix receptor interaction pathway and the transforming growth factor-β signaling pathway were enriched in the high-risk group. A ceRNA network of the seven-miR signature was constructed. In conclusion, the present study provided a seven-miRNA signature, according to which patients with early PC may be divided into high- and low-risk groups. The ceRNA network of the prognostic signature was preliminarily explored.

miR-1-3p suppresses the epithelial-mesenchymal transition property in renal cell cancer by downregulating Fibronectin 1

Purpose

Renal cell cancer (RCC) is one of the primary causes of malignancy deaths all over the world. The most important cause of RCC-related mortality is metastasis. Epithelial-mesenchymal transition (EMT) plays an important role in metastasis of malignant tumors including RCC. miR-1-3p is confirmed to be decreased in many types of cancer. Nevertheless, the function of miR-1-3p in RCC metastasis and EMT process was still unclear.

Materials and methods

In this study, information from clinical investigation, in vitro study, and in vivo study discovered miR-1-3p expression character and its status in RCC. The character of miR-1-3p in invasive and metastatic properties in vitro and in vivo was also inspected in RCC cells and xenograft tumor model, and expression levels of EMT markers were evaluated in RCC cells and tissues.

Results

miR-1-3p was proved to be decreased in RCC cell lines and tissues compared with normal renal cells and tissues. miR-1-3p expression level in RCC tissues was closely related with capsulation, lymph node metastasis, and vascular invasion. miR-1-3p was found to be able to block the EMT process in A498 and CAKI-1 RCC cells and tumors. Luciferase reporter assay and expression level rescue assays were employed to reveal that miR-1-3p inhibited the invasion and migration property of RCC cells by directly targeting Fibronectin 1. Upregulation of Fibronectin 1 partially reversed the suppressive effect of miR-1-3p on EMT process.

Conclusion

In brief, this study has verified that miR-1-3p blocked the EMT process of RCC cells by reducing Fibronectin 1 expression. miR-1-3p/Fibronectin 1 axis may be considered as a new target for drug development of RCC.