The mRNA related ceRNA-ceRNA landscape and significance across 20 major cancer types

Coding, or non-coding, that is the question

The advent of high-throughput sequencing uncovered that our genome is pervasively transcribed into RNAs that are seemingly not translated into proteins. It was also found that non-coding RNA transcripts outnumber canonical protein-coding genes. This mindboggling discovery prompted a surge in non-coding RNA research that started unraveling the functional relevance of these new genetic units, shaking the classic definition of "gene". While the non-coding RNA revolution was still taking place, polysome/ribosome profiling and mass spectrometry analyses revealed that peptides can be translated from non-canonical open reading frames. Therefore, it is becoming evident that the coding vs non-coding dichotomy is way blurrier than anticipated. In this review, we focus on several examples in which the binary classification of coding vs non-coding genes is outdated, since the same bifunctional gene expresses both coding and non-coding products. We discuss the implications of this intricate usage of transcripts in terms of molecular mechanisms of gene expression and biological outputs, which are often concordant, but can also surprisingly be discordant. Finally, we discuss the methodological caveats that are associated with the study of bifunctional genes, and we highlight the opportunities and challenges of therapeutic exploitation of this intricacy towards the development of anticancer therapies.

Identification of hub genes and potential therapeutic mechanisms related to HPV positive head and neck squamous carcinoma based on full transcriptomic detection and ceRNA network construction

Infection with human papillomavirus (HPV) is a major risk factor for head and neck squamous cell carcinoma (HNSCC). The objective of this study is to investigate the gene expression profiles and signaling pathways that are specific to HPV-positive HNSCC (HPV+ HNSCC). Moreover, a competing endogenous RNA (ceRNA) network analysis was utilized to identify the core gene of HPV+ HNSCC and potential targeted therapeutic drugs. Transcriptome sequencing analysis identified 3,253 coding RNAs and 3,903 non-coding RNAs (ncRNAs) that exhibited preferentially expressed in HPV+ HNSCC. Four key signaling pathways were selected through pathway enrichment analysis. By combining ceRNA network and protein-protein interaction (PPI) network topology analysis, RNA Polymerase II Associated Protein 2 (RPAP2), which also exhibited high expression in HPV+ HNSCC based on the TCGA database, was identified as the hub gene. Gene set enrichment analysis (GSEA) results revealed RPAP2's involvement in various signaling pathways, encompassing basal transcription factors, ubiquitin-mediated proteolysis, adherens junction, other glycan degradation, ATP-binding cassette (ABC) transporters, and oglycan biosynthesis. Five potential small molecule targeted drugs (enzastaurin, brequinar, talinolol, phenylbutazone, and afuresertib) were identified using the cMAP database, with enzastaurin showing the highest affinity for RPAP2. Cellular functional experiments confirmed the inhibitory effect of enzastaurin on cell viability of HPV+ HNSCC and RPAP2 expression levels. Additionally, enzastaurin treatment suppressed the expression levels of the top-ranked long non-coding RNA (lncRNA), circular RNA (circRNA), and microRNA (miRNA) in the ceRNA network. This study based on the ceRNA network provides valuable insights into the molecular mechanisms and potential therapeutic strategies for HPV+ HNSCC, and provide theoretical basis for the exploration of HPV+ HNSCC biomarkers and the development of targeted drugs.

RNA-RNA competitive interactions: a molecular civil war ruling cell physiology and diseases

The idea that proteins are the main determining factors in the functioning of cells and organisms, and their dysfunctions are the first cause of pathologies, has been predominant in biology and biomedicine until recently. This protein-centered view was too simplistic and failed to explain the physiological and pathological complexity of the cell. About 80% of the human genome is dynamically and pervasively transcribed, mostly as non-protein-coding RNAs (ncRNAs), which competitively interact with each other and with coding RNAs generating a complex RNA network regulating RNA processing, stability, and translation and, accordingly, fine-tuning the gene expression of the cells. Qualitative and quantitative dysregulations of RNA-RNA interaction networks are strongly involved in the onset and progression of many pathologies, including cancers and degenerative diseases. This review will summarize the RNA species involved in the competitive endogenous RNA network, their mechanisms of action, and involvement in pathological phenotypes. Moreover, it will give an overview of the most advanced experimental and computational methods to dissect and rebuild RNA networks.

Molecular mechanism of Ganji Fang in the treatment of hepatocellular carcinoma based on network pharmacology, molecular docking and experimental verification technology

Background: Hepatocellular carcinoma (HCC) is a malignant tumor harmful to human health. Ganji Fang (GJF) has good clinical efficacy in the treatment of HCC, but its mechanism is still unclear. Objective: The aim of this study was to investigate the mechanism of action of GJF in the treatment of HCC through network pharmacology, molecular docking and in vitro experiments. Methods: A series of network pharmacology methods were used to identify the potential targets and key pathways of GJF in the treatment of HCC. Then, molecular docking technology was used to explore the binding ability of key active ingredients and targets in GJF. Multiple external databases were used to validate the key targets. In in vitro experiments, we performed MTT assays, wound-healing assays, cell cycle assays, apoptosis assays and RT‒qPCR to verify the inhibitory effect of GJF on the Human hepatoma G2 (HepG2) cells. Result: A total of 162 bioactive components and 826 protein targets of GJF were screened, and 611 potential targets of HCC were identified. Finally, 63 possible targets of GJF acting on HCC were obtained. KEGG enrichment analyses showed that the top five pathways were the cell cycle, cellular senescence, p53 signaling pathway, PI3K/Akt signaling pathway, and progesterone-mediated oocyte maturation. Among them, we verified the PI3K/Akt signaling pathway. CCNE1, PKN1, CCND2, CDK4, EPHA2, FGFR3, CDK6, CDK2 and HSP90AAI were enriched in the PI3K/Akt pathway. The molecular docking results showed that the docking scores of eight active components of GJF with the two targets were all less than -5.0, indicating that they had certain binding activity. In vitro cell experiments showed that GJF could inhibit the proliferation and migration of HepG2 cells, block the cell cycle and induce apoptosis of HepG2 cells, which may be related to the PI3K/Akt signaling pathway. In summary, EPHA2 may be an important target of GJF in HCC, and pachymic acid may be an important critical active compound of GJF that exerts anticancer activity. Conclusion: In general, we demonstrated, for the first time, that the molecular mechanism of GJF in HCC may involve induction of G0/G1 phase cycle arrest through inhibition of the PI3K/Akt signaling pathway and promote apoptosis of hepatoma cell lines. This study provides a scientific basis for the subsequent clinical application of GJF and the in-depth study of its mechanism.

The new ceRNA crosstalk between mRNAs and miRNAs in intervertebral disc degeneration

Degeneration of the intervertebral disc has been linked to lower back pain. To date, pathophysiological mechanisms of intervertebral disc degeneration (IDD) remain unclear; it is meaningful to find effective diagnostic biomarkers and new therapeutic strategies for IDD. This study aimed to reveal the molecular mechanism of IDD pathogenesis from the multidimensional transcriptomics perspective. Here, we acquired IDD bulk omics datasets (GSE67567 and GSE167199) including mRNA, microRNA expression profiles, and single-cell RNA sequencing (GSE199866) from the public Gene Expression Omnibus (GEO) database. Through principal component analysis and Venn analysis, we found different expression patterns in the IDD transcription level and identified 156 common DEGs in both bulk datasets. GO and KEGG functional analyses showed these dysregulators were mostly enriched in the collagen-containing extracellular matrix, cartilage development, chondrocyte differentiation, and immune response pathways. We also constructed a potentially dysregulated competing endogenous RNA (ceRNA) network between mRNAs and miRNAs related to IDD based on microRNA target information and co-expression analysis of RNA profiles and identified 36 ceRNA axes including ZFP36/miR-155-5p/FOS, BTG2/hsa-miR-185-5p/SOCS3, and COL9A2/hsa-miR-664a-5p/IBA57. Finally, in integrating bulk and single-cell transcriptome data analyses, a total of three marker genes, COL2A1, PAX1, and ZFP36L2, were identified. In conclusion, the key genes and the new ceRNA crosstalk we identified in intervertebral disc degeneration may provide new targets for the treatment of IDD.

CEP55 3'-UTR promotes epithelial-mesenchymal transition and enhances tumorigenicity of bladder cancer cells by acting as a ceRNA regulating miR-497-5p

BACKGROUND

Centrosomal protein 55 (CEP55) is implicated in the tumorigenesis of bladder cancer (BC) but the detailed molecular mechanisms are unknown. We aim to develop a potential competing endogenous RNA (ceRNA) network related with CEP55 in BC.

METHODS

We first extracted the expression profiles of RNAs from The Cancer Genome Atlas (TCGA) database and used bioinformatic analysis to establish ceRNAs in BC. Real-time quantity PCR (RT-qPCR) and immunohistochemical analysis were performed to measure CEP55 expression in different bladder cell lines and different grades of cancer. Bioinformatics analysis and luciferase assays were conducted to predict potential binding sites among miR-497-5p, CEP55, parathyroid hormone like hormone (PTHLH) and high mobility group A2 (HMGA2). Tumor xenograft model was used to show the effect of CEP55 3'-UTR on cisplatin therapy. Bioinformatics analysis, luciferase assays, and 5' rapid amplification of cDNA ends (5'RACE) were to explore the function of CEP55 3'-untranslated region (3'-UTR) on targeting miR-497-5p. Western blot and immunofluorescence assays were to detect the epithelial-mesenchymal transition (EMT) induction of CEP55 3'-UTR.

RESULTS

CEP55 expression as well as the expression levels of the oncogenic proteins PTHLH and HMGA2 were upregulated in BC cells while miR-497-5p was downregulated. Low miR-497-5p expression and high CEP55 and HMGA2 expression levels were associated with more advanced tumor clinical stage and pathological grade. Overexpression of the CEP55 3'-UTR promoted the proliferation, migration, and invasion of the EJ cell line in vitro and accelerated EJ-derived tumor growth in nude mice, while inhibition of the CEP55 3'-UTR suppressed all of these oncogenic processes. In addition, CEP55 3'-UTR upregulation reduced the cisplatin sensitivity of BC cell lines and xenograft tumors. Bioinformatics analysis, luciferase assays, and 5'RACE suggested that the CEP55 3'-UTR functions as a ceRNA targeting miR-497-5p, leading to miR-497-5p downregulation and disinhibition of PTHLH and HMGA2 expression. Further, CEP55 downregulated miR-497-5p transcription by promoting NF-[Formula: see text]B signaling. In turn, CEP55 3'-UTR ultimately promotes EMT and tumorigenesis by activating P38MAPK and ERK 1/2 pathways.

CONCLUSIONS

These results suggest that a ceRNA regulatory network involving CEP55 upregulates PTHLH and HMGA2 expression by suppressing endogenous miR-497-5p. We unveiled a novel mechanism of BC metastasis, and could become novel therapeutics targets in BC.

LncRNA-mediated ceRNA regulatory network provides new insight into chlorogenic acid synthesis in sweet potato

Sweet potato (Ipomoea batatas L.) is considered a highly nutritional and economical crop due to its high contents of bioactive substances, such as anthocyanin and chlorogenic acid (CGA), especially in leaves and stems. The roles of noncoding RNAs (ncRNA), including long noncoding RNA (lncRNA) and microRNA (miRNA), in CGA synthesis, are still unknown. In this study, the differentially expressed (DE) mRNAs, miRNAs, and lncRNAs in two leafy vegetable genotypes "FS7-6-14-7" (high CGA content) and "FS7-6" (low CGA content) were identified. The cis-regulation between lncRNA and mRNA was analyzed. Then, the CGA synthesis-related modules MEBlue and MEYellow were identified to detect trans-regulation mRNA-lncRNA pairs. The GO and KEGG annotations suggested that mRNA in these two modules was significantly enriched in the secondary metabolite synthesis biosynthesis category. A competing endogenous RNAs (ceRNA) network, including 8730 miRNA-mRNA and 444 miRNA-lncRNA pairs, was constructed by DEmiRNA target prediction. Then, a CGA synthesis-related ceRNA network was obtained with lncRNA and mRNA from MEBlue and MEYellow. Finally, one relational pair, MSTRG.47662.1/mes-miR398/itb04g00990, was selected for functional validation. Overexpression of lncRNA MSTRG.47662.1 and mRNA itb04g00990 increased CGA content in both tobacco and sweet potato callus, while overexpression of miRNA mes-miR398 decreased CGA content. Meanwhile, regression analysis of the expression patterns demonstrated that MSTRG.47662.1, acting as a ceRNA, promoted itb04g00990 expression by competitively binding mes-miR398 in CGA synthesis in sweet potato. Our results provide insights into how ncRNA-mediated ceRNA regulatory networks likely contribute to CGA synthesis in leafy sweet potato.

Inferring miRNA sponge modules across major neuropsychiatric disorders

The role of non-coding RNAs in neuropsychiatric disorders (NPDs) is an emerging field of study. The long non-coding RNAs (lncRNAs) are shown to sponge the microRNAs (miRNAs) from interacting with their target mRNAs. Investigating the sponge activity of lncRNAs in NPDs will provide further insights into biological mechanisms and help identify disease biomarkers. In this study, a large-scale inference of the lncRNA-related miRNA sponge network of pan-neuropsychiatric disorders, including autism spectrum disorder (ASD), schizophrenia (SCZ), and bipolar disorder (BD), was carried out using brain transcriptomic (RNA-Seq) data. The candidate miRNA sponge modules were identified based on the co-expression pattern of non-coding RNAs, sharing of miRNA binding sites, and sensitivity canonical correlation. miRNA sponge modules are associated with chemical synaptic transmission, nervous system development, metabolism, immune system response, ribosomes, and pathways in cancer. The identified modules showed similar and distinct gene expression patterns depending on the neuropsychiatric condition. The preservation of miRNA sponge modules was shown in the independent brain and blood-transcriptomic datasets of NPDs. We also identified miRNA sponging lncRNAs that may be potential diagnostic biomarkers for NPDs. Our study provides a comprehensive resource on miRNA sponging in NPDs.

LncRNA UCA1 accelerates osteosarcoma progression via miR-145 and Wnt/β-catenin pathway

Long non-coding (lnc) urothelial cancer associated 1 (UCA1) has been confirmed to participate in osteosarcoma (OS), but its specific mechanism is still under investigation. The study was designed to reveal the interaction between UCA1 and its downstream effector molecules, so as to determine whether there is any interaction of regulating physiological processes in tumor cells. Here, we studied the signaling cascade involving UCA1, miR-145, and HMGA1. The expression of UCA1 and miR-145 levels was interfered to assess their effects on physiological processes of tumor cells. The relationship between UCA1 and miR-145 as well as between HMGA1 and miR-145 was identified by the dual-luciferase reporter (DLR) assay, and the in vivo effect of UCA1 was estimated in nude mouse xenografts. As a result, a negative association was found between UCA1 and miR-145 in OS cells. Both UCA1 knockout and miR-145 over-expression inhibited malignant progression and induced apoptosis in MG-63 and U2OS cells. UCA1 knockout led to an increase in miR-145 and decreases in HMGA1, p-β-catenin and cyclin D1. In addition, UCA1 upregulation promoted tumor growth in vitro and changed miR-145 and HMGA1 levels in vivo. Moreover, the DLR assay and RNA immunoprecipitation (RIP) showed that UCA1 was likely to regulate HMGA1 levels by sponging miR-145. Overall, the inhibition of UCA1 increases miR-145 levels and decreases HMGA1 levels, thereby exerting an anti-tumor role in OS.

ceRNAR: An R package for identification and analysis of ceRNA-miRNA triplets

Competitive endogenous RNA (ceRNA) represents a novel mechanism of gene regulation that controls several biological and pathological processes. Recently, an increasing number of in silico methods have been developed to accelerate the identification of such regulatory events. However, there is still a need for a tool supporting the hypothesis that ceRNA regulatory events only occur at specific miRNA expression levels. To this end, we present an R package, ceRNAR, which allows identification and analysis of ceRNA-miRNA triplets via integration of miRNA and RNA expression data. The ceRNAR package integrates three main steps: (i) identification of ceRNA pairs based on a rank-based correlation between pairs that considers the impact of miRNA and a running sum correlation statistic, (ii) sample clustering based on gene-gene correlation by circular binary segmentation, and (iii) peak merging to identify the most relevant sample patterns. In addition, ceRNAR also provides downstream analyses of identified ceRNA-miRNA triplets, including network analysis, functional annotation, survival analysis, external validation, and integration of different tools. The performance of our proposed approach was validated through simulation studies of different scenarios. Compared with several published tools, ceRNAR was able to identify true ceRNA triplets with high sensitivity, low false-positive rates, and acceptable running time. In real data applications, the ceRNAs common to two lung cancer datasets were identified in both datasets. The bridging miRNA for one of these, the ceRNA for MAP4K3, was identified by ceRNAR as hsa-let-7c-5p. Since similar cancer subtypes do share some biological patterns, these results demonstrated that our proposed algorithm was able to identify potential ceRNA targets in real patients. In summary, ceRNAR offers a novel algorithm and a comprehensive pipeline to identify and analyze ceRNA regulation. The package is implemented in R and is available on GitHub (https://github.com/ywhsiao/ceRNAR).

LINC00662 enhances cell progression and stemness in breast cancer by MiR-144-3p/SOX2 axis

BACKGROUND

Breast cancer (BC) is one of the most prevalent malignancies among women globally. Emerging evidence indicates that long non-coding RNAs (lncRNAs) are associated with BC carcinogenesis. In the current study, we explored the mechanism by which LINC00662 regulates BC.

METHODS

Quantitative real-time PCR (qRT-PCR) assessed RNA expressions while western blot for protein levels. Kaplan Meier analysis evaluated overall survival (OS). Cytoplasmic/nuclear fractionation, RNA binding protein immunoprecipitation (RIP) and luciferase reporter assays probed into the underlying molecular mechanism of LINC00662 in BC. Xenograft model was established to explore the influence of LINC00662 on BC progression in vivo. R square graphs were utilized to represent RNA relationships.

RESULTS

LINC00662 is overtly overexpressed in BC tissues and cell lines. LINC00662 knockdown hampers cell proliferation, migration, invasion and stemness. LINC00662 expression is negatively correlated with OS of BC patients. LINC00662 up-regulates SOX2 expression by competitively binding to miR-144-3p, thereby modulating BC cell progression. Xenograft experiments verified that LINC00662 promotes BC tumor growth and cell stemness in vivo.

CONCLUSION

LINC00662 enhances cell proliferation, migration, invasion and stemness in BC by targeting miR-144-3p/SOX2 axis. The findings in the present study suggested that LINC00662 could be a potential therapeutic target for BC treatment.

The Predictive Competing Endogenous RNA Regulatory Networks and Potential Prognostic and Immunological Roles of Cyclin A2 in Pan-Cancer Analysis

Although accumulating evidence has verified the relationship between CCNA2 and cancers, no pan-cancer analysis about the function and the upstream molecular mechanism of CCNA2 is available. For the first time, we analyzed potential oncogenic roles of CCNA2 in 33 cancer types via The Cancer Genome Atlas (TCGA) database. Overexpression of CCNA2 is widespread in almost all cancer types, and it is related to poor prognosis and advanced pathological stages in most cases. Moreover, we conducted upstream miRNAs and lncRNAs of CCNA2 to establish upstream regulatory networks in kidney renal clear cell carcinoma (LINC00997/miR-27b-3p/CCNA2), liver hepatocellular carcinoma (SNHG16, GUSBP11, FGD5-AS1, LINC00630, CD27-AS1, LINC00997/miR-22-3p/CCNA2, miR-29b-3p/CCNA2, miR-29c-3p/CCNA2, and miR-204-5p/CCNA2), and lung adenocarcinoma (miRNA-218-5p/CCNA2 and miR-204-5p/CCNA2) by expression analysis, survival analysis, and correlation analysis. The CCNA2 expression is positively correlated with Th2 cell infiltration and negatively correlated with CD4+ central memory and effector memory T-cell infiltration in different cancer types. Furthermore, CCNA2 is positively associated with expressions of immune checkpoints (CD274, CTLA4, HAVCR2, LAG3, PDCD1, and TIGIT) in most cancer types. Our first CCNA2 pan-cancer study contributes to understanding the prognostic and immunological roles and potential upstream molecular mechanisms of CCNA2 in different cancers.

Characterization and Validation of ceRNA-Mediated Pathway–Pathway Crosstalk Networks Across Eight Major Cardiovascular Diseases

Pathway analysis is considered as an important strategy to reveal the underlying mechanisms of diseases. Pathways that are involved in crosstalk can regulate each other and co-regulate downstream biological processes. Furthermore, some genes in the pathways can function with other genes via the relationship of the competing endogenous RNA (ceRNA) mechanism, which has also been demonstrated to play key roles in cellular biology. However, the comprehensive analysis of ceRNA-mediated pathway crosstalk is lacking. Here, we constructed the landscape of the ceRNA-mediated pathway–pathway crosstalk of eight major cardiovascular diseases (CVDs) based on sequencing data from ∼2,800 samples. Some common features shared by numerous CVDs were uncovered. A fraction of the pathway–pathway crosstalk was conserved in multiple CVDs and a core pathway–pathway crosstalk network was identified, suggesting the similarity of pathway–pathway crosstalk among CVDs. Experimental evidence also demonstrated that the pathway crosstalk was functioned in CVDs. We split all hub pathways of each pathway–pathway crosstalk network into three categories, namely, common hubs, differential hubs, and specific hubs, which could highlight the common or specific biological mechanisms. Importantly, after a comparison analysis of the hub pathways of networks, ∼480 hub pathway-induced common modules were identified to exert functions in CVDs broadly. Moreover, we performed a random walk algorithm on the hub pathway-induced sub-network and identified 23 potentially novel CVD-related pathways. In summary, our study revealed the potential molecular regulatory mechanisms of ceRNA crosstalk in pathway–pathway crosstalk levels and provided a novel routine to investigate the pathway–pathway crosstalk in cardiology. All CVD pathway–pathway crosstalks are provided in http://www.licpathway.net/cepathway/index.html.

Prognostic Implications and Immune Infiltration Characteristics of Chromosomal Instability-Related Dysregulated CeRNA in Lung Adenocarcinoma

An accumulating body of research indicates that long-noncoding RNAs (lncRNAs) regulate the target genes and act as competitive endogenous RNAs (ceRNAs) playing an indispensable role in lung adenocarcinoma (LUAD). LUAD is frequently accompanied by the feature of chromosomal instability (CIN); however, CIN-related ceRNAs have not been investigated yet. We systematically analyzed and integrated CIN-related dysregulated ceRNAs characteristics in LUAD samples for the first time. In TCGA LUAD cohort, CIN in tumor samples was significantly higher than that in those of adjacent, and patients with high CIN risk tended to have worse clinical outcomes. We constructed a double-weighted CIN-related dysregulated ceRNA network, in which edge weight and node weight represented the disorder extent of ceRNA and the correlation of RNA expression level and prognosis, respectively. After module mining and analysis, a potential prognostic biomarker composed of 12 RNAs (8 mRNAs and 4 lncRNAs) named CIN-related dysregulated ceRNAs (CRDC) was obtained. The CRDC risk score had a positive relation with clinical stage and CIN, and patients with high CRDC risk scores exhibited poor prognosis. Moreover, CRDC tended to be an independent risk factor with high robustness to overcome the effect of multicollinearity among other explanatory variables for disease-specific survival (DSS) in TCGA and two GEO cohorts. The result of functional analysis indicated that CRDC was involved in multiple cancer progresses, especially immune-related pathways. The patients with lower CRDC risk had higher B cell, T cell CD4+, T cell CD8+, neutrophil, macrophage, and myeloid dendritic cell infiltration than the patients with higher CRDC risk. Meanwhile, patients with lower CRDC risk could get more benefits from immunological therapy. The results suggested that the CRDC could be a potential prognostic biomarker and an immunotherapy predictor for lung adenocarcinoma.

The Involvement of Long Non-coding RNA and Messenger RNA Based Molecular Networks and Pathways in the Subacute Phase of Traumatic Brain Injury in Adult Mice

Traumatic brain injury (TBI) is a complex injury with a multi-faceted recovery process. Long non-coding RNAs (lncRNAs) are demonstrated to be involved in central nervous system (CNS) disorders. However, the roles of lncRNAs in long-term neurological deficits post-TBI are poorly understood. The present study depicted the microarray’s lncRNA and messenger RNA (mRNA) profiles at 14 days in TBI mice hippocampi. LncRNA and mRNA microarray was used to identify differentially expressed genes. Quantitative real-time polymerase chain reaction (qRT-PCR) was employed to validate the microarray results. Bioinformatics analysis [including Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, lncRNA-mRNA co-expression network, and lncRNA-miRNA-mRNA network] were applied to explore the underlying mechanism. A total of 264 differentially expressed lncRNAs and 232 expressed mRNAs were identified (fold change > 1.5 and P-value < 0.05). Altered genes were enriched in inflammation, immune response, blood–brain barrier, glutamatergic neurological effects, and neuroactive ligand-receptor, which may be associated with TBI-induced pathophysiologic changes in the long-term neurological deficits. The lncRNAs-mRNAs co-expression network was generated for 74 lncRNA-mRNA pairs, most of which are positive correlations. The lncRNA-miRNA-mRNA interaction network included 12 lncRNAs, 59 miRNAs, and 25 mRNAs. Numerous significantly altered lncRNAs and mRNAs in mice hippocampi were enriched in inflammation and immune response. Furthermore, these dysregulated lncRNAs and mRNAs may be promising therapeutic targets to overcome obstacles in long-term recovery following TBI.

Variation in the co-expression profile highlights a loss of miRNA-mRNA regulation in multiple cancer types

Recent research provides insight into the ability of miRNA to regulate various pathways in several cancer types. Despite their involvement in the regulation of the mRNA via targeting the 3′UTR, there are relatively few studies examining the changes in these regulatory mechanisms specific to single cancer types or shared between different cancer types.

We analyzed samples where both miRNA and mRNA expression had been measured and performed a thorough correlation analysis on 7494 experimentally validated human miRNA-mRNA target-gene pairs in both healthy and tumoral samples.

We show how more than 90% of these miRNA-mRNA interactions show a loss of regulation in the tumoral samples compared with their healthy counterparts.

As expected, we found shared miRNA-mRNA dysregulated pairs among different tumors of the same tissue. However, anatomically different cancers also share multiple dysregulated interactions, suggesting that some cancer-related mechanisms are not tumor-specific. 2865 unique miRNA-mRNA pairs were identified across 13 cancer types, ≈ 40% of these pairs showed a loss of correlation in the tumoral samples in at least 2 out of the 13 analyzed cancers. Specifically, miR-200 family, miR-155 and miR-1 were identified, based on the computational analysis described below, as the miRNAs that potentially lose the highest number of interactions across different samples (only literature-based interactions were used for this analysis).

Moreover, the miR-34a/ALDH2 and miR-9/MTHFD2 pairs show a switch in their correlation between healthy and tumor kidney samples suggesting a possible change in the regulation exerted by the miRNAs. Interestingly, the expression of these mRNAs is also associated with the overall survival. The disruption of miRNA regulation on its target, therefore, suggests the possible involvement of these pairs in cell malignant functions.

The analysis reported here shows how the regulation of miRNA-mRNA interactions strongly differs between healthy and tumoral cells, based on the strong correlation variation between miRNA and its target that we obtained by analyzing the expression data of healthy and tumor tissue in highly reliable miRNA-target pairs. Finally, a go term enrichment analysis shows that the critical pairs identified are involved in cellular adhesion, proliferation, and migration.

Constructing the ceRNA Regulatory Network and Combining Immune Cells to Evaluate Prognosis of Colon Cancer Patients

Objective: This study was conducted in order to construct a competitive endogenous RNA (ceRNA) network to screen RNA that plays an important role in colon cancer and to construct a model to predict the prognosis of patients.

Methods: The gene expression data of colon cancer were downloaded from the TCGA database. The difference was analyzed by the R software and the ceRNA network was constructed. The survival-related RNA was screened out by combining with clinical information, and the prognosis model was established by lasso regression. CIBERSORT was used to analyze the infiltration of immune cells in colon cancer, and the differential expression of immune cells related to survival was screened out by combining clinical information. The correlation between RNA and immune cells was analyzed by lasso regression. PCR was used to verify the expression of seven RNAs in colon cancer patients with different prognoses.

Results: Two hundred and fifteen lncRNAs, 357 miRNAs, and 2,955 mRNAs were differentially expressed in colon cancer. The constructed ceRNA network contains 18 lncRNAs, 42 miRNAs, and 168 mRNAs, of which 18 RNAs are significantly related to survival. Through lasso analysis, we selected seven optimal RNA construction models. The AUC value of the model was greater than 0.7, and there was a significant difference in the survival rate between the high- and low-risk groups. Two kinds of immune cells related to the prognosis of patients were screened out. The results showed that the expression of seven RNA markers in colon cancer patients with different prognoses was basically consistent with the model analysis.

Conclusion: We have established the regulatory network of ceRNA in colon cancer, screened out seven core RNAs and two kinds of immune cells, and constructed a comprehensive prognosis model of colon cancer patients.

Low expression of lncRNA SBF2-AS1 regulates the miR-302b-3p/TGFBR2 axis, promoting metastasis in laryngeal cancer

The 5-year survival rate of laryngeal cancer continues to decline, and the laryngeal particularity of the anatomy adversely affects the patient's quality of life. Emerging evidence suggests that long noncoding RNAs (lncRNAs) are closely correlated to key steps in the malignant progression of cancer cells. In this study, we report the role of lncRNA SBF2-AS1/miR-302b-3p/TGFBR2 interactions in the metastasis of laryngeal squamous cell carcinoma (LSCC). We verified that SBF2-AS1 was significantly downregulated in LSCC tissues and cell lines using qRT-PCR analysis. Its low expression was correlated to lymph node metastasis and an advanced clinical stage. More importantly, LSCC patients with low expression of SBF2-AS1 tended to have a poor prognosis. Based on this, we performed gain-of-function and loss-of-function experiments in LSCC cell lines. The results confirmed that knocking down SBF2-AS1 can promote the metastasis of LSCC cells and enhance epithelial-mesenchymal transition phenotype, while the upregulation of SBF2-AS1 expression resulted in the opposite. Our in vivo model verified that SBF2-AS1 overexpression could inhibit LSCC cell metastasis. Subsequent mechanistic studies revealed that SBF2-AS1 acted as a competing endogenous RNA that upregulated the expression of TGFBR2 by endogenous sponging for miR-302b-3p in LSCC cell lines. Moreover, miR-302b-3p overexpression reversed the inhibitory effects on LSCC metastasis induced by upregulation of SBF2-AS1 expression, and inhibition of TGFBR2 expression reversed the effect of SBF2-AS1 on metastasis. Our study proposes SBF2-AS1 as a biomarker to predict the prognosis of LSCC patients and a novel potential therapeutic target.

Construction and comprehensive analysis of a competitive endogenous RNA network to reveal potential biomarkers for the malignant differentiation of glioma

BACKGROUND

Long noncoding RNAs (lncRNAs) can act as microRNA (miRNA) sponges to regulate protein-coding gene expression; therefore, lncRNAs are considered major components of the competitive endogenous RNA (ceRNA) network and have attracted growing attention. This study explored the regulatory mechanisms and functional roles of lncRNAs as ceRNAs in the malignant differentiation of low-grade glioma (LGG) to glioblastoma (GBM) and their potential impact on the prognosis of patients with GBM.

METHODS

LncRNA and messenger RNA (mRNA) data were extracted from the Cancer Genome Atlas (TCGA) database from 156 GBM samples and 529 LGG samples. Separately, the miRNA expression data were downloaded from the Gene Expression Omnibus database, with the GSE112009 dataset containing miRNA expression data from 10 GBM samples and 15 LGG samples. Weighted gene coexpression network analysis was performed to screen the glioma grade-related lncRNAs. Then, a ceRNA network was established. The database for annotation, visualization, and integrated discovery was adopted to conduct functional enrichment analysis based on 57 upregulated differentially expressed mRNAs in the ceRNA network. Finally, Kaplan-Meier curves were created for the survival analysis of 13 hub lncRNA by combining the clinical data of GBM patients in TCGA.

RESULTS

A ceRNA network including 16 lncRNAs, 18 miRNAs, and 78 mRNAs specific to the malignant differentiation of LGG to GBM was established. The 57 upregulated differentially expressed mRNAs in the ceRNA network were significantly enriched in 35 gene ontology terms and 5 pathways. The survival analysis showed that 2 lncRNAs (LINC00261 and HOXA10-AS) were prognostic biomarkers for patients with GBM in TCGA.

CONCLUSION

The proposed ceRNA network may help elucidate the regulatory mechanism by which lncRNAs function as ceRNAs and contribute to the malignant differentiation of LGG to GBM. Importantly, the candidate lncRNAs, miRNAs, and mRNAs involved in the ceRNA network can be further evaluated as potential therapeutic targets and prognostic biomarkers for GBM.

Comprehensive analysis of lncRNAs as biomarkers for diagnosis, prognosis, and treatment response in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common histological type of renal carcinoma and has a high recurrence rate and poor outcome. Accurate patient risk stratification based on genetic markers can help to identify the high-risk patient for early and further treatments and would promote patient survival. Long non-coding RNAs (lncRNAs) have attracted widespread attention as biomarkers for early diagnosis, treatment, and prognosis because of their high specificity and sensitivity. Here, we performed a systematic search in NCBI PubMed and found 44 lncRNAs as oncogenes, 18 lncRNAs as tumor suppressors, 199 lncRNAs as diagnostic biomarkers, 62 lncRNAs as prognostic biomarkers, and 3 lncRNAs as predictive biomarkers for ccRCC. We also comprehensively discuss the biological functions and molecular regulatory mechanisms of lncRNAs in ccRCC. Overall, the present study is a systemic analysis to assess the expression and clinical value of lncRNAs in ccRCC, and lncRNAs hold promise to be diagnostic, prognostic, and predictive biomarkers.

miRNA-218/FANCI is associated with metastasis and poor prognosis in lung adenocarcinoma: a bioinformatics analysis

Background

In this study, tumor microarray analysis was used to screen the key messenger RNAs (mRNAs) and microRNAs related to the progression of lung adenocarcinoma (LUAD), in order to provide a theoretical basis for early diagnosis, therapeutic targets, and prognosis evaluation of patients with LUAD.

Methods

The mRNA and miRNA expression datasets came from the Gene Expression Omnibus (GEO) project database. Differentially expressed genes (DEGs) and microRNAs (DEMs) between LUAD tissues and adjacent lung tissue were obtained using GEO2R. The Search Tool for the Retrieval of Interacting Genes website was also employed to construct and visualize the interactions of overlapped DEGs. The overall survival of DEMs was investigated using the Kaplan-Meier plotter. The TargetScan website (http://www.targetscan.org/) was used to verify the relationship between FA Complementation Group I (FANCI) and the expression of miRNA-218 (miR-218). The expression of FANCI was verified using the GEO and Human Protein Atlas databases, as well as Real Time Quantitative PCR using our own samples. Next, we analyzed the relationship between the expression of FANCI and the clinicopathological characteristics as well as the prognosis of patients with LUAD. We also explored whether the FANCI was related to immune cell infiltration in LUAD.

Results

FANCI was identified as a hub gene and associated with poor OS. We found that miR-218 negatively regulates FANCI mRNA expression. At the mRNA expression and protein level, FANCI was more highly expressed in LUAD tissues. The expression of FANCI in LUAD was related to tumor size (χ²=13.96, P<0.001), lymphatic metastasis (χ²=3.88, P<0.05), distant metastasis (χ²=45.39, P<0.001), and stage (χ²=11.03, P<0.05). In addition, the Cox regression model found that FANCI mRNA expression was an independent predictive factor of patient survival (P<0.05). FANCI expression was both weakly related to B cells and neutrophil infiltration in LUAD.

Conclusions

miR-218 may negatively regulate FANCI, and FANCI could promote metastasis via extracellular matrix (ECM) receptor interaction, leading to poor prognosis of LUAD. FANCI may be a key gene to the determine metastasis and poor prognosis in patients with LUAD. Changes in the immune microenvironment may be the mechanism through which FANCI leads to poor prognosis of LUAD.

The regulatory pattern of target gene expression by aberrant enhancer methylation in glioblastoma

Background

Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor with grim prognosis. Aberrant DNA methylation is an epigenetic mechanism that promotes GBM carcinogenesis, while the function of DNA methylation at enhancer regions in GBM remains poorly described.

Results

We integrated multi-omics data to identify differential methylation enhancer region (DMER)-genes and revealed global enhancer hypomethylation in GBM. In addition, a DMER-mediated target genes regulatory network and functional enrichment analysis of target genes that might be regulated by hypomethylation enhancer regions showed that aberrant enhancer regions could contribute to tumorigenesis and progression in GBM. Further, we identified 22 modules in which lncRNAs and mRNAs synergistically competed with each other. Finally, through the construction of drug-target association networks, our study identified potential small-molecule drugs for GBM treatment.

Conclusions

Our study provides novel insights for understanding the regulation of aberrant enhancer region methylation and developing methylation-based biomarkers for the diagnosis and treatment of GBM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04345-8.

Mathematical Modeling of ceRNA-Based Interactions

Competing endogenous RNA (ceRNA) molecules have emerged as key players in regulating gene expression, increasing the complexity of the range of possible dynamics within a cell. The actions of competing RNA typically are sponging behaviors, in a manner that fine-tunes gene expression, but there are particular network structures that may show destabilization due to ceRNA interactions. In this chapter, we discuss how these interactions can be modeled and probed from a mathematical, first-principles perspective.

Time to infer miRNA sponge modules

Inferring competing endogenous RNA (ceRNA) or microRNA (miRNA) sponge modules is a challenging and meaningful task for revealing ceRNA regulation mechanism at the module level. Modules in this context refer to groups of miRNA sponges which have mutual competitions and act as functional units for achieving biological processes. The recent development of computational methods based on heterogeneous data provides a novel way to discern the competitive effects of miRNA sponges on human complex diseases. This article aims to provide a comprehensive perspective of miRNA sponge module discovery methods. We first review the publicly available databases of cancer-related miRNA sponges, as the miRNA sponges involved in human cancers contribute to the discovery of cancer-associated modules. Then we review the existing computational methods for inferring miRNA sponge modules. Furthermore, we conduct an assessment on the performance of the module discovery methods with the pan-cancer dataset, and the comparison study indicates that it is useful to infer biologically meaningful miRNA sponge modules by directly mapping heterogeneous data to the competitive modules. Finally, we discuss the future directions and associated challenges in developing in silico methods to infer miRNA sponge modules. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Small Molecule-RNA Interactions Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

Development of a Prognostic Five-Gene Signature for Diffuse Lower-Grade Glioma Patients

Background: Diffuse lower-grade gliomas (LGGs) are infiltrative and heterogeneous neoplasms. Gene signature including multiple protein-coding genes (PCGs) is widely used as a tumor marker. This study aimed to construct a multi-PCG signature to predict survival for LGG patients.

Methods: LGG data including PCG expression profiles and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Survival analysis, receiver operating characteristic (ROC) analysis, and random survival forest algorithm (RSFVH) were used to identify the prognostic PCG signature.

Results: From the training (n = 524) and test (n = 431) datasets, a five-PCG signature which can classify LGG patients into low- or high-risk group with a significantly different overall survival (log rank P < 0.001) was screened out and validated. In terms of prognosis predictive performance, the five-PCG signature is stronger than other clinical variables and IDH mutation status. Moreover, the five-PCG signature could further divide radiotherapy patients into two different risk groups. GO and KEGG analysis found that PCGs in the prognostic five-PCG signature were mainly enriched in cell cycle, apoptosis, DNA replication pathways.

Conclusions: The new five-PCG signature is a reliable prognostic marker for LGG patients and has a good prospect in clinical application.

Genome-wide data mining to construct a competing endogenous RNA network and reveal the pivotal therapeutic targets of Parkinson's disease

Parkinson's disease (PD) is one of the most common neurodegenerative movement disorders, for which there has been no effective treatments. To clarify the pathogenesis of PD, we constructed a competing endogenous RNA (ceRNA) network based on the genome-wide RNA sequencing data. It was found that 92 RNAs were differentially expressed, including 50 mRNAs, 25 miRNAs and 17 lncRNAs, based on which a ceRNA network was constructed and evaluated from 4 aspects of number of nodes, topological coefficients, closeness centrality and betweenness centrality. The functional annotation and enrichment analysis suggested that 6 functional modules, particularly the peripheral nervous system development and toxin metabolic process, dominated the development of PD. To validate the assumption, the gene set enrichment analysis (GSEA) was conducted basing on the genome-wide RNAs regardless whether they were differentially expressed or not. Consistently, the results revealed that dysregulation of MAG, HOXB3, MYRF and PLP1 led to metabolic disorders of sphingolipid and glutathione, which contributed to the pathogenesis of PD. Also, in-depth mining of previous literature confirmed a pivotal role of these dysregulated RNAs, which had been indicated to be potential diagnostic and therapeutic biomarkers of PD. Overall, we constructed a ceRNA network based on the dysregulated mRNAs, lncRNAs and miRNAs in PD, and the aberrant expression of MAG, HOXB3, MYRF and PLP1 caused metabolism disorder of sphingolipid and glutathione, and these genes are of great significance for the diagnosis and treatment of PD.

The Functional Characterization of Epigenetically Related lncRNAs Involved in Dysregulated CeRNA-CeRNA Networks Across Eight Cancer Types

Numerous studies have demonstrated that lncRNAs could compete with other RNAs to bind miRNAs, as competing endogenous RNAs (ceRNAs), to regulate each other. On the other hand, ceRNAs were found to be recurrently dysregulated in cancer status. However, limited studies considered the upstream epigenetic regulatory factors that disrupted the normal competing mechanism. In the present study, we constructed the lncRNA-associated dysregulated ceRNA networks across eight cancer types. lncRNAs in the individual dysregulated network and pan-cancer core dysregulated ceRNA subnetwork were found to play more important roles than mRNAs. Integrating lncRNA methylation profiles, we identified 49 epigenetically related (ER) lncRNAs involved in the dysregulated ceRNA networks, including 18 epigenetically activated (EA) lncRNAs, 18 epigenetically silenced (ES) lncRNAs, and 13 rewired ER lncRNAs across eight cancer types. Furthermore, we evaluated the epigenetic regulating patterns of these lncRNAs and screened nine pan-cancer ER lncRNAs (six EA and three ES lncRNAs). The nine lncRNAs were found to regulate the cancer hallmarks by competing with mRNAs. Moreover, we found that integrating the expression and methylation profiles of the nine lncRNAs could predict cancer incidence in eight cancer types robustly and the cancer outcome of several cancer types. These results provide an improved understanding of methylation regulation to ceRNA and offer novel potential molecular therapeutic targets for the diagnosis and prognosis across different cancer types.

Comprehensive analysis of lncRNA biomarkers in kidney renal clear cell carcinoma by lncRNA-mediated ceRNA network

Introduction

Kidney renal clear cell carcinoma (KIRC) has a high incidence globally, and its pathogenesis remains unclear. Long non-coding RNA (lncRNA), as a molecular sponge, participates in the regulation of competitive endogenous RNA (ceRNA). We aimed to construct a ceRNA network and screened out possible lncRNAs to predict KIRC prognosis.

Material and methods

All KIRC data were downloaded from the TCGA database and screened to find the possible target lncRNA; a ceRNA network was designed. Next, GO functional enrichment and KEGG pathway of differentially expressed mRNA related to lncRNA were performed. We used Kaplan-Meier curve analysis to predict the survival of these RNAs. We used Cox regression analysis to construct a model to predict KIRC prognosis.

Results

In the KIRC datasets, 1457 lncRNA, 54 miRNA and 2307 mRNA were screened out. The constructed ceRNA network contained 81 lncRNAs, nine miRNAs, and 17 mRNAs differentially expressed in KIRC. Survival analysis of all differentially expressed RNAs showed that 21 lncRNAs, four miRNAs, and two mRNAs were related to the overall survival rate. Cox regression analysis was performed again, and we found that eight lncRNAs were related to prognosis and used to construct predictive models. Three lnRNAs from independent samples were meaningful.

Conclusion

The construction of ceRNA network was involved in the process and transfer of KIRC, and three lncRNAs may be potential targets for predicting KIRC prognosis.

Clinicopathological-Associated Regulatory Network of Deregulated circRNAs in Hepatocellular Carcinoma

Simple Summary

Here, we present a novel strategy to identify key signatures of clinically-relevant co-expressed circRNA-mRNA networks in pertinent cancer-pathways that modulate the prognosis of HCC patients, by integrating clinicopathological features, circRNA and mRNA expression profiles. Five master circRNAs were identified and experimentally demonstrated to upregulate proliferate and promote transformation. Through further integration with miRNA-expression profiles, clinically-relevant competing-endogenous-RNA (ceRNA) networks of circRNA-miRNA-mRNAs were constructed. The most up-regulated nodal-circRNA, circGPC3 was experimentally demonstrated to up-regulate cell-cycle, migration and invasion. circGPC3 was found to act as a sponge of miR-378a-3p to regulate ASPM expression and modulate cell transformation. These 5 nodal circRNAs has potential to be good prognostic biomarkers with good prognostic performance. circGPC3 has great potential to be a promising non-invasive prognostic biomarker for early HCC. We have thus demonstrated the robustness of bioinformatically-predicted master circRNAs in clinically-relevant, circRNA-mRNA networks, underscoring the important roles that these identified deregulated key/master circRNAs play in HCC.

Abstract

Hepatocellular carcinoma (HCC) is one of the most common and lethal cancers worldwide. Here, we present a novel strategy to identify key circRNA signatures of clinically relevant co-expressed circRNA-mRNA networks in pertinent cancer-pathways that modulate prognosis of HCC patients, by integrating clinic-pathological features, circRNA and mRNA expression profiles. Through further integration with miRNA expression profiles, clinically relevant competing-endogenous-RNA (ceRNA) networks of circRNA-miRNA-mRNAs were constructed. At least five clinically relevant nodal-circRNAs, co-expressed with numerous genes, were identified from the circRNA-mRNA networks. These nodal circRNAs upregulated proliferation (except circRaly) and transformation in cells. The most upregulated nodal-circRNA, circGPC3, associated with higher-grade tumors and co-expressed with 33 genes, competes with 11 mRNAs for two shared miRNAs. circGPC3 was experimentally demonstrated to upregulate cell-cycle and migration/invasion in both transformed and non-transformed liver cell-lines. circGPC3 was further shown to act as a sponge of miR-378a-3p to regulate APSM (Abnormal spindle-like microcephaly associated) expression and modulate cell transformation. This study identifies 5 key nodal master circRNAs in a clinically relevant circRNA-centric network that are significantly associated with poorer prognosis of HCC patients and promotes tumorigenesis in cell-lines. The identification and characterization of these key circRNAs in clinically relevant circRNA-mRNA and ceRNA networks may facilitate the design of novel strategies targeting these important regulators for better HCC prognosis.

SPMLMI: predicting lncRNA-miRNA interactions in humans using a structural perturbation method

Long non-coding RNA (lncRNA)-microRNA (miRNA) interactions are quickly emerging as important mechanisms underlying the functions of non-coding RNAs. Accordingly, predicting lncRNA-miRNA interactions provides an important basis for understanding the mechanisms of action of ncRNAs. However, the accuracy of the established prediction methods is still limited. In this study, we used structural consistency to measure the predictability of interactive links based on a bilayer network by integrating information for known lncRNA-miRNA interactions, an lncRNA similarity network, and an miRNA similarity network. In particular, by using the structural perturbation method, we proposed a framework called SPMLMI to predict potential lncRNA-miRNA interactions based on the bilayer network. We found that the structural consistency of the bilayer network was higher than that of any single network, supporting the utility of bilayer network construction for the prediction of lncRNA-miRNA interactions. Applying SPMLMI to three real datasets, we obtained areas under the curves of 0.9512 ± 0.0034, 0.8767 ± 0.0033, and 0.8653 ± 0.0021 based on 5-fold cross-validation, suggesting good model performance. In addition, the generalizability of SPMLMI was better than that of the previously established methods. Case studies of two lncRNAs (i.e., SNHG14 and MALAT1) further demonstrated the feasibility and effectiveness of the method. Therefore, SPMLMI is a feasible approach to identify novel lncRNA-miRNA interactions underlying complex biological processes.

Exploring miRNA Sponge Networks of Breast Cancer by Combining miRNA-disease-lncRNA and miRNA-target Networks

Background:

Recently, ample researches show that microRNAs (miRNAs) not only interact with coding genes but interact with a pool of different RNAs. Those RNAs are called miRNA sponges, including long non-coding RNAs (lncRNAs), circular RNA, pseudogenes and various messenger RNAs. Understanding regulatory networks of miRNA sponges can better help researchers to study the mechanisms of breast cancers.

Objective:

We develop a new method to explore miRNA sponge networks of breast cancer by combining miRNAdisease-lncRNA and miRNA-target networks (MSNMDL).

Method:

Firstly, MSNMDL infers miRNA-lncRNA functional similarity networks from miRNAdisease- lncRNA networks. Secondly, MSNMDL forms lncRNA-target networks by using lncRNA to replace the role of matched miRNA in miRNA-target networks according to the lncRNA-miRNA pair of miRNA-lncRNA functional similarity networks. And MSNMDL only retains the genes of breast cancer in lncRNA-target networks to construct candidate miRNA sponge networks. Thirdly, MSNMDL merges these candidate miRNA sponge networks with other miRNA sponge interactions and then selects top-hub lncRNA and its interactions to construct miRNA sponge networks.

Results:

MSNMDL is superior to other methods in terms of biological significance and its identified modules might act as module signatures for prognostication of breast cancer.

Conclusion:

MiRNA sponge networks identified by MSNMDL are biologically significant and are closely associated with breast cancer, which makes MSNMDL a promising way for researchers to study the pathogenesis of breast cancer.

LOXL1‑AS1 promotes thymoma and thymic carcinoma progression by regulating miR‑525‑5p‑HSPA9

Due to the lack of specific symptoms in early thymic epithelial tumours (TETs), patients are mostly in the advanced stage at the time of presentation. The aim of the present study was to explore the mechanism by which the long noncoding RNA (lncRNA) LOXL1-AS1 affects thymoma and thymic carcinoma progression by targeting the miR-525-5p-HSPA9 axis. Bioinformatics was used to analyse the process of LOXL1-AS1 targeting miR-525-5p-HSPA9 and its expression characteristics in TET. The relationships between LOXL1-AS1, miR-525-5p, HSPA9 and prognosis were analysed. The dual luciferase reporter assay was applied to verify targeting. The gene was knocked down or overexpressed by plasmid transfection. Cell counting kit 8 (CCK-8) assay, flow cytometry and Transwell assay were used to detect cell viability, apoptosis and invasion ability, respectively. Proteins and RNAs were examined by western blot analysis and qPCR, respectively. A tumour-burdened assay was used to perform in vivo verification. LOXL1-AS1 and HSPA9 were overexpressed in thymoma and thymic carcinoma; high levels of LOXL1-AS1 and HSPA9 were associated with poor prognosis, and there was a significant positive correlation between their levels. Downregulation of miR-525-5p expression was also associated with poor prognosis of patients. Clinical trials also demonstrated the same trends. miR-525-5p inhibited the expression of HSPA9 protein by targeting the 3′-untranslated region (UTR) of HSPA9 mRNA. LOXL1-AS1 promoted the expression of HSPA9 as a sponge targeting miR-525-5p. Animal experiment results also showed that knockdown of miR-525-5p promoted cancer by promoting the expression of HSPA9. In conclusion, LOXL1-AS1 and HSPA9 are highly expressed in thymoma and thymic carcinoma; miR-525-5p is expressed at low levels in thymoma and thymic carcinoma; and downregulation of miR-525-5p is associated with poor prognosis. In summary, this study demonstrates that LOXL1-AS1 acts as a sponge that targets miR-525-5p to promote HSPA9 expression, thereby promoting the growth and invasion and inhibiting apoptosis of thymoma and thymic carcinoma cells.

SNHG15 facilitated malignant behaviors of oral squamous cell carcinoma through targeting miR-188-5p/DAAM1

BACKGROUND

Long non-coding RNA (lncRNA) small nucleolar RNA host gene 15 (SNHG15) has been discovered and demonstrated to have significant function in multiple cancers. Nevertheless, how it participates in the progression of oral squamous cell carcinoma (OSCC) and its potential regulatory system are still unclear.

METHODS

RT-qPCR detected the expression of SNHG15, miR-188-5p, and DAAM1. RNA pull down, RT-qPCR, and bioinformatics were used for finding and selecting downstream targets of SNHG15.

RESULTS

SNHG15 presented a high expression in OSCC cells. Moreover, inhibition of SNHG15 exhibited repressive influence on proliferative, migrated, and invasive abilities but induce apoptosis of OSCC cells. Through the search of bioinformatics and RNA pull down assays, we confirmed that miR-188-5p was one target of SNHG15 in OSCC cells. Additionally, miR-188-5p could hamper the growth of OSCC cells. Moreover, it was manifested that DAAM1 was down-regulated by miR-188-5p. DAAM1 was up-regulated in OSCC cells. Furthermore, it exerted oncogenic function in the course of OSCC. Eventually, overexpression of DAAM1 offsets the effects of down-regulation of SNHG15 on the development of OSCC.

CONCLUSION

To summarize, our study certified that SNHG15 contributed to the process of OSCC via sponging miR-188-5p to elevate DAAM1 expression. SNHG15 might offer novel sight to improve the results of treatment for OSCC.

Prognostic Value of an Autophagy-Related Five-Gene Signature for Lower-Grade Glioma Patients

Background: Molecular characteristics can be good indicators of tumor prognosis and have been introduced into the classification of gliomas. The prognosis of patients with newly classified lower-grade gliomas (LGGs, including grade 2 and grade 3 gliomas) is highly heterogeneous, and new molecular markers are urgently needed.

Methods: Autophagy related genes (ATGs) were obtained from Human Autophagy Database (HADb). From the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), gene expression profiles including ATG expression information and patient clinical data were downloaded. Cox regression analysis, receiver operating characteristic (ROC) analysis, Kaplan–Meier analysis, random survival forest algorithm (RSFVH) and stratification analysis were performed.

Results: Through univariate Cox regression analysis, we found a total of 127 ATGs associated with the prognosis of LGG patients from TCGA dataset and a total of 131 survival-related ATGs from CGGA dataset. Using TCGA dataset as the training group (n = 524), we constructed a five-ATG signature (including BAG1, BID, MAP1LC3C, NRG3, PTK6), which could divide LGG patients into two risk groups with significantly different overall survival (Log Rank P < 0.001). Then we confirmed in the independent CGGA dataset that the five-ATG signature had the ability to predict prognosis (n = 431, Log Rank P < 0.001). We further discovered that the predictive ability of the five-ATG signature was better than the existing clinical indicators and IDH mutation status. In addition, the five-ATG signature could further classify patients after receiving radiotherapy or chemotherapy into groups with different prognosis.

Conclusions: We identified a five-ATG signature that could be a reliable prognostic marker and might be therapeutic targets for autophagy therapy for LGG patients.

Integrated analysis of competing endogenous RNA in esophageal carcinoma

Background

The Competing endogenous RNA (CeRNA) network plays important roles in the development and progression of multiple human cancers. Increasing attention has been paid to CeRNA in esophageal carcinoma (ESCA).

Methods

We explored The Cancer Genome Atlas (TCGA) database and then analyzed the RNAs of 142 samples to obtain long non-coding RNAs (lncRNAs), micro RNAs (miRNAs), and messenger RNAs (mRNAs) with different expression trends alongside the progress of ESCA. A series test of cluster (STC) analysis was carried out to identify a set of unique model expression tendencies. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to validate the function of key genes that were obtained from the STC analysis.

Results

Through our analysis, 272 lncRNAs, 87 miRNAs, and 692 mRNAs showed upward expression or downward expression trends, and these molecules were tightly involved in cell cycle, pathways in cancer, metabolic processes, and protein phosphorylation, among others. Ultimately, we constructed a CeRNA network containing a total of 71 lncRNAs, 56 miRNAs, and 125 mRNAs. The overall survival (OS) was analyzed using univariate Cox regression analysis to clarify the relationship between these key molecules from the CeRNA network and the prognosis of ESCA patients. Through survival analysis, we finally screened out two lncRNAs (DLEU2, RP11-890B15.3), three miRNAs (miR-26b-3p, miR-92a-3p, miR-324-5p), and one mRNA (SIK2) as crucial prognostic factors for ESCA.

Conclusions

The novel CeRNA network that we constructed will provide new novel prognostic biomarkers and therapeutic targets for patients with ESCA.

Identification and Analysis of Three Hub Prognostic Genes Related to Osteosarcoma Metastasis

Osteosarcoma (OS) often occurs in children and often undergoes metastasis, resulting in lower survival rates. Information on the complexity and pathogenic mechanism of OS is limited, and thus, the development of treatments involving alternative molecular and genetic targets is hampered. We categorized transcriptome data into metastasis and nonmetastasis groups, and 400 differential RNAs (230 messenger RNAs (mRNAs) and 170 long noncoding RNAs (lncRNAs)) were obtained by the edgeR package. Prognostic genes were identified by performing univariate Cox regression analysis and the Kaplan-Meier (KM) survival analysis. We then examined the correlation between the expression level of prognostic lncRNAs and mRNAs. Furthermore, microRNAs (miRNAs) corresponding to the coexpression of lncRNA-mRNA was predicted, which was used to construct a competitive endogenous RNA (ceRNA) regulatory network. Finally, multivariate Cox proportional risk regression analysis was used to identify hub prognostic genes. Three hub prognostic genes (ABCG8, LOXL4, and PDE1B) were identified as potential prognostic biomarkers and therapeutic targets for OS. Furthermore, transcriptions factors (TFs) (DBP, ESX1, FOS, FOXI1, MEF2C, NFE2, and OTX2) and lncRNAs (RP11-357H14.16, RP11-284N8.3, and RP11-629G13.1) that were able to affect the expression levels of genes before and after transcription were found to regulate the prognostic hub genes. In addition, we identified drugs related to the prognostic hub genes, which may have potential clinical applications. Immunohistochemistry (IHC) and quantitative real-time polymerase chain reaction (qRT-PCR) confirmed that the expression levels of ABCG8, LOXL4, and PDE1B coincided with the results of bioinformatics analysis. Moreover, the relationship between the hub prognostic gene expression and patient prognosis was also validated. Our study elucidated the roles of three novel prognostic biomarkers in the pathogenesis of OS as well as presenting a potential clinical treatment for OS.

Long noncoding RNA SNHG14 promotes hepatocellular carcinoma progression by regulating miR-876-5p/SSR2 axis

Background

Aberrant expressions of long noncoding RNAs (lncRNAs) have been demonstrated to be related to the progress of HCC. The mechanisms that SNHG14 has participated in the development of HCC are obscure.

Methods

Quantitative real-time PCR (qRT-PCR) was used to measure the lncRNA, microRNA and mRNA expression level. Cell migration, invasion and proliferation ability were evaluated by transwell and CCK8 assays. The ceRNA regulatory mechanism of SNHG14 was evaluated by RNA immunoprecipitation (RIP) and dual luciferase reporter assay. Tumorigenesis mouse model was used to explore the roles of miR-876-5p in vivo. The protein levels of SSR2 were measured by western blot assay.

Results

In this study, we demonstrated that SNHG14 was highly expressed in HCC tissues, meanwhile, the elevated expression of SNHG14 predicted poor prognosis in patients with HCC. SNHG14 promoted proliferation and metastasis of HCC cells. We further revealed that SNHG14 functioned as a competing endogenous RNA (ceRNA) for miR-876-5p and that SSR2 was a downstream target of miR-876-5p in HCC. Transwell, CCK8 and animal experiments exhibited miR-876-5p inhibited HCC progression in vitro and in vivo. By conducting rescue experiments, we found the overexpression of SSR2 or knocking down the level of miR-876-5p could reverse the suppressive roles of SNHG14 depletion in HCC.

Conclusion

SNHG14 promotes HCC progress by acting as a sponge of miR-876-5p to regulate the expression of SSR2 in HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01838-5.

SPONGEdb: a pan-cancer resource for competing endogenous RNA interactions

microRNAs (miRNAs) are post-transcriptional regulators involved in many biological processes and human diseases, including cancer. The majority of transcripts compete over a limited pool of miRNAs, giving rise to a complex network of competing endogenous RNA (ceRNA) interactions. Currently, gene-regulatory networks focus mostly on transcription factor-mediated regulation, and dedicated efforts for charting ceRNA regulatory networks are scarce. Recently, it became possible to infer ceRNA interactions genome-wide from matched gene and miRNA expression data. Here, we inferred ceRNA regulatory networks for 22 cancer types and a pan-cancer ceRNA network based on data from The Cancer Genome Atlas. To make these networks accessible to the biomedical community, we present SPONGEdb, a database offering a user-friendly web interface to browse and visualize ceRNA interactions and an application programming interface accessible by accompanying R and Python packages. SPONGEdb allows researchers to identify potent ceRNA regulators via network centrality measures and to assess their potential as cancer biomarkers through survival, cancer hallmark and gene set enrichment analysis. In summary, SPONGEdb is a feature-rich web resource supporting the community in studying ceRNA regulation within and across cancer types.

Systematic analysis of enhancer regulatory circuit perturbation driven by copy number variations in malignant glioma

Background: Enhancers are emerging regulatory regions controlling gene expression in diverse cancer types. However, the functions of enhancer regulatory circuit perturbations driven by copy number variations (CNVs) in malignant glioma are unclear. Therefore, we aimed to investigate the comprehensive enhancer regulatory perturbation and identify potential biomarkers in glioma.

Results: We performed a meta-analysis of the enhancer centered regulatory circuit perturbations in 683 gliomas by integrating CNVs, gene expression, and transcription factors (TFs) binding. We found widespread CNVs of enhancers during glioma progression, and CNVs were associated with the perturbations of enhancer activities. In particular, the degree of perturbations for amplified enhancers was much greater accompanied by the glioma malignant progression. In addition, CNVs and enhancers cooperatively regulated the expressions of cancer-related genes. Genome-wide TF binding profiles revealed that enhancers were pervasively regulated by TFs. A network-based analysis of TF-enhancer-gene regulatory circuits revealed a core TF-gene module (58 interactions including seven genes and 14 TFs) that was associated survival of patients with glioma (p < 0.001). Finally, we validated this prognosis-associated TF-gene regulatory module in an independent cohort. In summary, our analyses provided new molecular insights for enhancer-centered transcriptional perturbation in glioma therapy.

Conclusion: Integrative analysis revealed enhancer regulatory perturbations in glioma and also identified a network module that was associated with patient survival, thereby providing novel insights into enhancer-centered cancer therapy.

cg04448376, cg24387542, cg08548498, and cg14621323 as a Novel Signature to Predict Prognosis in Kidney Renal Papillary Cell Carcinoma

INTRODUCTION

DNA methylation plays a vital role in prognosis prediction of cancers. In this study, we aimed to identify novel DNA methylation site biomarkers and create an efficient methylated site model for predicting survival in kidney renal papillary cell carcinoma (KIRP).

METHODS

DNA methylation and gene expression profile data were downloaded from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Differential methylated genes (DMGs) and differential expression genes (DEGs) were identified and then searched for the hub genes. Cox proportional hazards regression was applied to identify DNA methylated site biomarkers from the hub genes. Kaplan-Meier survival and ROC analyses were used to validate the effective prognostic ability of the methylation gene site biomarker. The biomarker sites were validated in the GEO cohorts. The GO and KEGG annotation was done to explore the biological function of DNA methylated site signature.

RESULTS

Nine DMGs with opposite expression patterns containing 47 methylated sites were identified. Finally, four methylated sites were identified using the hazard regression model (cg04448376, cg24387542, cg08548498, and cg14621323) located in UTY, LGALS9B, SLPI, and PFN3, respectively. These sites classified patients into high- and low-risk groups in the training cohort. The 5-year survival rates for patients with low-risk and high-risk scores were 97.5% and 75.9% (P < 0.001). The prognostic accuracy and signature methylation sites were validated in the test (TCGA, n = 87) and GEO cohorts (n = 14). Multivariate regression analysis showed that the signature was an independent prediction prognostic factor for KIRP. Based on this analysis, we developed methylated site signature nomogram that predicts an individual's risk of survival. Functional analysis suggested that these signature genes are involved in the biological processes of protein binding.

CONCLUSIONS

Our study demonstrated that the methylated gene site signature might be a powerful prognostic tool for evaluating survival rate and guiding tailored therapy for KIRP patients.

Competing Endogenous RNA Networks as Biomarkers in Neurodegenerative Diseases

Protein aggregation is classically considered the main cause of neuronal death in neurodegenerative diseases (NDDs). However, increasing evidence suggests that alteration of RNA metabolism is a key factor in the etiopathogenesis of these complex disorders. Non-coding RNAs are the major contributor to the human transcriptome and are particularly abundant in the central nervous system, where they have been proposed to be involved in the onset and development of NDDs. Interestingly, some ncRNAs (such as lncRNAs, circRNAs and pseudogenes) share a common functionality in their ability to regulate gene expression by modulating miRNAs in a phenomenon known as the competing endogenous RNA mechanism. Moreover, ncRNAs are found in body fluids where their presence and concentration could serve as potential non-invasive biomarkers of NDDs. In this review, we summarize the ceRNA networks described in Alzheimer's disease, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis and spinocerebellar ataxia type 7, and discuss their potential as biomarkers of these NDDs. Although numerous studies have been carried out, further research is needed to validate these complex interactions between RNAs and the alterations in RNA editing that could provide specific ceRNET profiles for neurodegenerative disorders, paving the way to a better understanding of these diseases.

Construction and analysis of competing endogenous RNA network of MCF-7 breast cancer cells based on the inhibitory effect of 6-thioguanine on cell proliferation

Previous research has proven that 6-thioguanine (6-TG) inhibits the growth of MCF-7 breast cancer cells. Accumulating evidence indicates that long non-coding (lnc)RNAs are involved in the development of various cancer types as competitive endogenous (ce)RNA molecules. The present study was conducted to investigate the regulatory mechanism underlying the function of lncRNAs as ceRNA molecules in MCF-7 cells and to identify more effective prognostic biomarkers for breast cancer treatment. The expression profiles of lncRNAs in untreated MCF-7 cells and 6-TG-treated MCF-7 cells were compared by RNA-seq. The regulatory associations among lncRNAs, micro (mi)RNAs and mRNAs were analyzed and verified by the TargetScan, miRDB and miRTarBas databases. The ceRNA networks were constructed by Cytoscape. The expression levels of two lncRNAs and two miRNAs in the ceRNA network were measured by reverse transcription-quantitative PCR. The OncoLnc and Kaplan-Meier plotter network databases were utilized to determine the effects of lncRNA and miRNA expression on the survival of patients with breast cancer. A ceRNA network was constructed for MCF-7 breast cancer cells treated with 6-TG, and this network may provide valuable information for further research elucidating the molecular mechanism underlying the effects of 6-TG on breast cancer. Moreover, LINC00324, MIR22HG, miR-370-3p and miR-424-5p were identified as potential prognostic and therapeutic biomarkers for breast cancer.

An aberrant DNA methylation signature for predicting hepatocellular carcinoma

Background

By the time they are clinically diagnosed, patients with hepatocellular carcinoma (HCC) are often at the advanced stage. DNA methylation has become a useful predictor of prognosis for cancer patients. Research on DNA methylation as a biomarker for assessing the risk of occurrence in HCC patients is limited. The purpose of this study was to develop an efficient methylation site model for predicting survival in patients with HCC.

Methods

DNA methylation and gene expression profile data were extracted from The Cancer Genome Atlas (TCGA) database. Markers of DNA-methylated site in two subsets (the training subset and the test subset) were identified using a random survival forest algorithm and Cox proportional hazards regression. Then, Gene Ontology annotations were applied to investigate the functions of DNA methylation signatures.

Results

A total of 37 hub genes containing 713 methylated sites were identified among the differentially methylated genes (DMGs) and differentially expressed genes (DEGs). Finally, seven methylation sites (cg12824782, cg24871714, cg18683774, cg22796509, cg19450025, cg10474350, and cg06511917) were identified. In the training group and the test group, the area under the curve predicting the survival of patients with HCC was 0.750 and 0.742, respectively. The seven methylation sites signature could be used to divide the patients in the training group into high- and low-risk subgroups [overall survival (OS): 2.81 vs. 2.11 years; log-rank test, P<0.05]. Then, the prediction ability of the model was validated in the test dataset through risk stratification (OS: 2.04 vs. 2.88 years; log-rank test, P<0.05). Functional analysis demonstrated that these signature genes were related to the activity of DNA-binding transcription activator, RNA polymerase II distal enhancer sequence-specific DNA binding, and enhancer sequence-specific DNA binding.

Conclusions

The results of this study showed that the signature is useful for predicting the survival of HCC patients and thus, can facilitate treatment-related decision-making.

Screening of Methylation Gene Sites as Prognostic Signature in Lung Adenocarcinoma

PURPOSE

Most lung adenocarcinoma (LUAD) patients are diagnosed at the advanced stage and have poor prognosis. DNA methylation plays an important role in the prognosis prediction of cancers. The objective of this study was to identify new DNA methylation sites as biomarkers for LUAD prognosis.

MATERIALS AND METHODS

We downloaded DNA methylation data from The Cancer Genome Atlas data portal. Cox proportional hazard regression model and random survival forest algorithm were applied to identify the DNA-methylation sites. Methylation of sites were validated in the Gene Expression Omnibus cohorts. Function annotation were done to explore the biological function of DNA methylated sites signature.

RESULTS

Six DNA methylation sites were identified as prognosis signature. The signature yielded acceptable discrimination between the high-risk group and low-risk group. The discrimination effect of this DNA methylation signature for the OS was obvious, with a median OS of 21.89 months vs. 17.74 months for high-risk vs. low-risk groups. This prognostic prediction model was validated by the test group and GEO dataset. The predictive survival value was higher for the prognostic prediction model than that for the tumor node metastasis stage. Adjuvant hemotherapy could not affect the prediction of the signature. Functional analysis indicated that these signature genes were involved in protein binding and cytoplasm.

CONCLUSION

We identified the prognostic signature for LUAD by combining six DNA methylation sites. This could service as potential robust and specificity signature in the prognosis prediction of LUAD.

LncRNA SNHG3 promotes autophagy-induced neuronal cell apoptosis by acting as a ceRNA for miR-485 to up-regulate ATG7 expression

Long non-coding RNAs (lncRNAs) are bound up with various human diseases. However, their roles in brain ischemia-reperfusion (I/R) injury remain largely unknown. This study aimed to reveal the potential mechanism of LncRNA SNHG3 on autophagy-induced neuronal cell apoptosis in the brain I/R injury. LncRNA SNHG3 and miR-485 or autophagy markers LC3II/I and Beclin-1 expressions were detected by qRT-PCR or Western blot and the apoptosis of N2a cells was analyzed by flow cytometry. Besides, the interactions between LncRNA SNHG3 and miR-485, miR-485 and ATG7 were validated by RNA pull-down and dual-luciferase reporter system assays. After the Oxygen and Glucose Deprivation (OGD) treatment of N2a cells transfected with pcDNA-SNHG3, pcDNA-SNHG3 + miR-485 mimic for 6 h, 1 mM autophagy inhibitor 3-MA was added and reoxygenated for 24 h, the effect of LncRNA SNHG3 on the autophagy-induced neuronal cell apoptosis was measured by Western blot and flow cytometry. LncRNA SNHG3 was highly expressed in the mouse model of transient middle cerebral artery occlusion and cell model of Oxygen and Glucose Deprivation/Reperfusion, while miR-485 was lowly expressed. Furthermore, miR-485 negatively regulated the luciferase activities of LncRNA SNHG3 and ATG7. After the OGD treatment of N2a cells transfected with pcDNA-SNHG3, pcDNA-SNHG3 + miR-485 mimic for 6 h, 1 mM 3-MA was added and reoxygenated for 24 h, the overexpression of LncRNA SNHG3 raised the ratio of LC3-II/LC3-I and Beclin-1 expression and boosted the apoptosis of N2a cells, while these effects were reversed after the transfection of miR-485 mimic. In general, our data expounded that the interference with LncRNA SNHG3 improved brain I/R injury by up-regulating miR-485 and down-regulating ATG7 to restrain autophagy and neuronal cell apoptosis.

Genome-wide analysis of long non-coding RNAs responsive to multiple nutrient stresses in Arabidopsis thaliana

Nutrient stress is the most important environmental stress that limits plant growth and development. Although recent evidence highlights the vital functions of long non-coding RNAs (lncRNA) in response to single nutrient stress in some model plants, a comprehensive investigation of the effect of lncRNAs in response to nutrient stress has not been performed in Arabidopsis thaliana. Here, we presented the identification and characterization of lncRNAs under seven nutrient stress conditions. The expression pattern analysis revealed that aberrant expression of lncRNAs is a stress-specific manner under nutrient stress conditions and that lncRNAs are more sensitive to nutrient stress than protein-coding genes (PCGs). Moreover, competing endogenous RNA (ceRNA) network and lncRNA-mRNA co-expression network (CEN) were constructed to explore the potential function of these lncRNAs under nutrient stress conditions. We further combined different expressed lncRNAs with ceRNA network and CEN to select key lncRNAs in response to nutrient stress. Together, our study provides important information for further insights into the role of lncRNAs in response to stress in plants.

Biomarker Discovery for the Carcinogenic Heterogeneity Between Colon and Rectal Cancers Based on lncRNA-Associated ceRNA Network Analysis

Background

Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. Emerging evidence has revealed that risk factors and metastatic patterns differ greatly between colon and rectal cancers. However, the molecular mechanism underlying their pathogenic differences remains unclear. Therefore, we here aimed to identify non-coding RNA biomarkers based on lncRNA-associated ceRNA network (LceNET) to elucidate the carcinogenic heterogeneity between colon and rectal cancers.

Methods

A global LceNET in human was constructed by employing experimental evidence-based miRNA-mRNA and miRNA-lncRNA interactions. Then, four context-specific ceRNA networks related to cancer initiation and metastasis were extracted by mapping differentially expressed lncRNAs, miRNAs and mRNAs to the global LceNET. Notably, a novel network-based bioinformatics model was proposed and applied to identify lncRNA/miRNA biomarkers and critical ceRNA triplets for understanding the carcinogenic heterogeneity between colon and rectal cancers. Moreover, the identified biomarkers were further validated by their diagnostic/prognostic performance, expression pattern and correlation analysis.

Results

Based on network modeling, lncRNA KCNQ1OT1 (AUC>0.85) and SNHG1 (AUC>0.94) were unveiled as common diagnostic biomarkers for the initiation and metastasis of colon and rectal cancers. qRT-PCR analysis uncovered that these lncRNAs had significantly higher expression level in CRC cell lines with high metastatic potential. In particular, KCNQ1OT1 and SNHG1 function in colon and rectal cancers via different ceRNA mechanisms. For example, KCNQ1OT1/miR-484/ANKRD36 axis was involved in the initiation of colon cancer, while KCNQ1OT1/miR-181a-5p/PCGF2 axis was implicated in the metastasis of rectal cancer; the SNHG1/miR-484/ORC6 axis played a role in colon cancer, while SNHG1/miR-423-5p/EZH2 and SNHG1/let-7b-5p/ATP6V1F axes participated in the initiation and metastasis of rectal cancer, respectively. In these ceRNA triplets, miR-484, miR-181a-5p, miR-423-5p and let-7b-5p were identified as miRNA biomarkers with excellent distinguishing ability between normal and tumor tissues, and ANKRD36, PCGF2, EZH2 and ATP6V1F were closely related to the prognosis of corresponding cancer.

Conclusion

The landscape of lncRNA-associated ceRNA network not only facilitates the exploration of non-coding RNA biomarkers, but also provides deep insights into the oncogenetic heterogeneity between colon and rectal cancers, thereby contributing to the optimization of diagnostic and therapeutic strategies of CRC.

MMP1 3'UTR facilitates the proliferation and migration of human oral squamous cell carcinoma by sponging miR-188-5p to up-regulate SOX4 and CDK4

Growing evidence indicates that the non-coding 3'-untranslated region (3'UTR) of genes acts as competing endogenous RNAs (ceRNAs) to exert their roles in a number of diseases, including cancer. In the present study, MMP1 messenger RNA was identified to be significantly up-regulated in oral squamous cell carcinoma (OSCC) tissues, and both MMP1 and its 3'UTR promoted tumor growth and cell motility. Further mechanism investigations indicated that MMP1 3'UTR was able to antagonize miR-188-5p; in addition, overexpression of MMP1 3'UTR up-regulated the expression level of SOX4 and CDK4, target genes of miR-188-5p, which have also been identified as oncogenic driver genes in OSCC. Therefore, a ceRNA regulatory network among MMP1, SOX4, and CDK4 mediated via competing for binding to miR-188-5p was proved. Taken together, the present study demonstrates for the first time that MMP1 mRNA participates in the development of OSCC via ceRNA regulatory mechanism and genes involved in the ceRNA network may provide a novel avenue for target therapy.