HOTAIRM1 lncRNA is downregulated in clear cell renal cell carcinoma and inhibits the hypoxia pathway

Exosome-encapsulated lncRNA HOTAIRM1 contributes to PM2.5-aggravated COPD airway remodeling by enhancing myofibroblast differentiation

Emphysema, myofibroblast accumulation and airway remodeling can occur in the lungs due to exposure to atmospheric pollution, especially fine particulate matter (PM2.5), leading to chronic obstructive pulmonary disease (COPD). Specifically, bronchial epithelium-fibroblast communication participates in airway remodeling, which results in COPD. An increasing number of studies are now being conducted on the role of exosome-mediated cell-cell communication in disease pathogenesis. Here, we investigated whether exosomes generated from bronchial epithelial cells could deliver information to normal stromal fibroblasts and provoke cellular responses, resulting in airway obstruction in COPD. We studied the mechanism of exosome-mediated intercellular communication between human bronchial epithelial (HBE) cells and primary lung fibroblasts (pLFs). We found that PM2.5-induced HBE-derived exosomes promoted myofibroblast differentiation in pLFs. Then, the exosomal lncRNA expression profiles derived from PM2.5-treated HBE cells and nontreated HBE cells were investigated using an Agilent Human LncRNA Array. Combining coculture assays and direct exosome treatment, we found that HBE cell-derived exosomal HOTAIRM1 facilitated the myofibroblast differentiation of pLFs. Surprisingly, we discovered that exosomal HOTAIRM1 enhanced pLF proliferation to secrete excessive collagen secretion, leading to airway obstruction by stimulating the TGF-β/SMAD3 signaling pathway. Significantly, PM2.5 reduced FEV1/FVC and FEV1 and increased the level of serum exosomal HOTAIRM1 in healthy people; moreover, serum exosomal HOTAIRM1 was associated with PM2.5-related reductions in FEV1/FVC and FVC. These findings show that PM2.5 triggers alterations in exosome components and clarify that one of the paracrine mediators of myofibroblast differentiation is bronchial epithelial cell-derived HOTAIRM1, which has the potential to be an effective prevention and therapeutic target for PM2.5-induced COPD.

The single-cell evolution trajectory presented different hypoxia heterogeneity to reveal the carcinogenesis of genes in clear cell renal cell carcinoma: Based on multiple omics and real experimental verification

INTRODUCTION

Clear cell renal cell carcinoma (ccRCC) is the most prevalent and aggressive subtype of renal cell carcinoma, originating from renal tubular epithelial cells in the kidney. Hypoxia proves to be a feature commonly observed in solid tumors, leading to increased resistance to treatment and tumor progression.

METHODS

scRNA-seq data were procured from GSE159115 data set. We utilized UMAP and NMF algorithm for clustering and dimensionality reduction. The FindAllMarkers function was used to compare various groups and identify potential hypoxia marker genes. A series of in vitro experiments, including CFA, flow cytometry targeting cell cycle, CCK-8, and EDU, was applied to investigate how ANGPTL4 regulated the ccRCC progression. Two cell lines of ccRCC cells, 786-O and Caki, were used for si-ANGPTL4 transfection.

RESULTS

We annotated a total of a total of 6 cell clusters, namely ccRCC malignant cells, T cells, endothelial cells, myeloid cells, smooth muscle cells, and B cells. We observed higher levels of hypoxia-score in the ccRCC malignant cells, while lowest hypoxia-score in T and B cells. We detected multiple hypoxia-related subclusters of TME cells in ccRCC, among which S100A4 CD8+ T cells and nonhypoxia CD8+ T cells were found with a marked elevation of T cell inhibitory gene score. We identified that ANGPTL4+ endothelial cells might function as an integrative role in tumor angiogenesis. Multiple TME subclusters showed high potency in stratification of the prognosis of ccRCC patients. Moreover, by a series of in vitro experiment, we found ANGPTL4 regulated the ccRCC cell proliferation, probably through ERK/P38 pathway.

CONCLUSION

We discerned multiple hypoxia-related subclusters of TME cells in ccRCC, which displayed distinct functional features and great potency in predicting prognosis of ccRCC patients. We identified the role of ANGPTL4 in regulating ccRCC proliferation via ERK/p38 pathway.

Molecular subtyping and characterization of clear cell renal cell carcinoma by tumor differentiation trajectories

Previous bulk RNA sequencing or whole genome sequencing on clear cell renal cell carcinoma (ccRCC) subtyping mainly focused on ccRCC cell origin or the complex tumor microenvironment (TME). Based on the single-cell RNA sequencing (scRNA-seq) data of 11 primary ccRCC specimens, cancer stem-cell-like subsets could be differentiated into five trajectories, whereby we further classified ccRCC cells into three groups with diverse molecular features. These three ccRCC subgroups showed significantly different outcomes and potential targets to tyrosine kinase inhibitors (TKIs) or immune checkpoint inhibitors (ICIs). Tumor cells in three differentiation directions exhibited distinct interactions with other subsets in the ccRCC niches. The subtyping model was examined through immunohistochemistry staining in our ccRCC cohort and validated the same classification effect as the public patients. All these findings help gain a deeper understanding about the pathogenesis of ccRCC and provide useful clues for optimizing therapeutic schemes based on the molecular subtype analysis.

LncRNA HOTAIRM1 promotes dental follicle stem cell-mediated bone regeneration by regulating HIF-1α/KDM6/EZH2/H3K27me3 axis

Large bone defect reconstruction undergoes hypoxia and remains a major practical challenge. Bone tissue engineering with a more promising stem cell source facilitates the development of better therapeutic outcomes. Human dental follicle stem cells (hDFSCs) with superior multipotency, osteogenic capacity, and accessibility have been proven a promising cell source for bone regeneration. We previously identified a novel long noncoding RNA (lncRNA), HOTAIRM1, to be highly expressed in hDFSCs. Here we found that HOTAIRM1 overexpressed hDFSCs promoted bone regeneration in rat critical-size calvarial defect model. Mechanically, HOTAIRM1 was induced in hDFSCs under hypoxic conditions and activated HIF-1α. RNA-sequencing analysis indicated that HOTAIRM1 upregulated oxygen-sensing histone demethylases KDM6A/B and suppressed methyltransferase EZH2 via targeting HIF-1α. The osteogenic differentiation of hDFSCs was accompanied with demethylation of H3K27, and HOTAIRM1 overexpression decreased the distribution of H3K27me3 in osteogenic genes, including ALP, M-CSF, Wnt-3a, Wnt-5a, Wnt-7a, and β-catenin, thus promoted their transcription. Our study provided evidence that HOTAIRM1 upregulated KDM6A/B and inhibited EZH2 in a HIF-1α dependent manner to enhance the osteogenesis of hDFSCs. HOTAIRM1-mediated hDFSCs may serve as a promising therapeutic approach to promote bone regeneration in clinical practice.

Single-cell analyses reveal distinct expression patterns and roles of long non-coding RNAs during hESC differentiation into pancreatic progenitors

BACKGROUND

Deep understanding the differentiation process of human embryonic stem cells (hESCs) is essential for developing cell-based therapeutic strategy. Substantial efforts have been made to investigate protein-coding genes, yet it remains lacking comprehensive characterization of long non-coding RNAs (lncRNAs) during this process.

METHODS

hESCs were passaged every 5-6 days and had maintained stable karyotype even until the 50th generation. Pancreatic progenitor specification of in vitro differentiation from hESCs was performed and modified. The nuclei were stained with 4,6-Diamidino-2-phenylindole (DAPI). Droplet-based platform (10X Genomics) was applied to generate the single-cell RNA sequencing (scRNA-seq) data. The quality of the filtered read pairs was evaluated by using FastQC. Batch effects were removed using the size factor method. Dimension reduction and unsupervised clustering analyses were performed using Seurat R package. The Monocle 2 and MetaCell algorithms were used to order single cells on a pseudotime course and partition the scRNA-seq data into metacells, respectively. Co-expression network was constructed using WGCNA. Module- and hub-based methods were adopted to predict the functions of lncRNAs.

RESULTS

A total of 77,382 cells during the differentiation process of hESCs toward pancreatic progenitors were sequenced. According to the single-cell map, the cells from different time points were authenticated to constitute a relatively homogeneous population, in which a total of 7382 lncRNAs could be detected. Through further analyzing the time course data, conserved and specific expression features of lncRNAs during hESC differentiation were revealed. Based upon pseudotime analysis, 52 pseudotime-associated lncRNAs that grouped into three distinct expression patterns were identified. We also implemented MetaCell algorithm and network-based methods to explore the functional mechanisms of these lncRNAs. Totally, 464 lncRNAs, including 49 pseudotime-associated lncRNAs were functionally annotated by either module-based or hub-based methods. Most importantly, we demonstrated that the lncRNA HOTAIRM1, which co-localized and co-expressed with several HOX genes, may play crucial role in the generation of pancreatic progenitors through regulation of exocytosis and retinoic acid receptor signaling pathway.

CONCLUSIONS

Our single-cell analyses provide valuable data resources for biological researchers and novel insights into hESC differentiation processes, which will guide future endeavors to further elucidate the roles of lncRNAs.

The expression and significance of long non-coding RNA ITGB2-AS1 in renal clear cell carcinoma

OBJECTIVES

To explore the expression and significance of long non-coding RNA ITGB2-AS1 in kidney renal clear cell carcinoma (KIRC).

METHODS

The expression of ITGB2-AS1 in KIRC tissues of 45 KIRC patients in the first affiliated hospital of Henan University, Henan, China, from September 2018 to December 2020, KIRC cells were detected and the relationship of ITGB2-AS1 and overall survival of KIRC patients were analyzed. The expression of ITGB2-AS1 in KIRC cells Caki-1 and ACHN was interfered, and the changes of cell proliferation, invasion, migration, and apoptosis were detected. Dual luciferase reporter gene assay and RNA pull-down assay were carried out to verify the relationship between ITGB2-AS1 and miR-338-3p or miR-338-3p and epidermal growth factor receptor (EGFR). The expression of miR-338-3p and EGFR were detected after the interference of ITGB2-AS1.

RESULTS

The expression of ITGB2-AS1 was expressed highly in KIRC tissues and cells (p<0.05). The overall survival of KIRC patients with high ITGB2-AS1 was poorer than those with low ITGB2-AS1. In Caki-1 cell, downregulation of ITGB2-AS1 suppressed the cell proliferation, invasion and migration, promoted the cell apoptosis (p<0.05). In ACHN cell, upregulation of ITGB2-AS1 promoted the cell proliferation, invasion and migration and inhibited the apoptosis (p<0.05). The ITGB2-AS1 targeted and regulated the expression of miR-338-3p/EGFR.

CONCLUSION

The ITGB2-AS1 is expressed highly in KIRC and affects the survival of patients by regulating cell proliferation, invasion, and apoptosis.

Tumor-derived exosomal HOTAIRM1 regulates SPON2 in CAFs to promote progression of lung adenocarcinoma

OBJECTIVE

SPON2 is one of the extracellular matrix proteins, which is closely related to the progression of a variety of tumors including non-small cell lung cancer (NSCLC), but its upstream regulation mechanism remains unclear. Our research aims to find the specific regulatory pathway of SPON2 by exploring the potential crosstalk between tumor cells and cancer-associated fibroblasts (CAFs) in tumor microenvironment (TME) of NSCLC.

METHODS

We analyzed T1 lung adenocarcinoma samples from TCGA and screened extracellular matrix proteins that indicate poor prognosis. Expression level of SPON2 was verified by qPCR in clinical samples. The exosomes of NSCLC cell supernatant were extracted and identified by nanoparticle tracking analysis (NTA) and transmission electron microscope, western blots. The exosomes and CAFs were co-cultured, and cell migration and Matrigel invasion assay were used to evaluate the effect of CAFs on the migration and invasion of NSCLC cells. The interaction between LncRNA and miRNA was verified by Targetscan prediction, luciferase reporter assay, and RNA binding protein immunoprecipitation (RIP).

RESULTS

We found that the expression of SPON2 was up-regulated in clinical T1a stage NSCLC patients. The expression of lnc HOTAIRM1 (HOTAIRM1) in exosomes secreted by NSCLC tissues increased. After exosomal HOTAIRM1 entered CAFs, HOTAIRM1 can adsorb miR-328-5p to up-regulate the expression of SPON2 in CAFs. Up-regulation of SPON2 in CAFs could promote the migration and invasion of NSCLC cells.

CONCLUSION

Tumor-derived exosomal HOTAIRM1 can transfer into CAFs and competitively adsorb miR-328-5p, and regulate the SPON2 expression of CAFs cells, ultimately promote the progression of NSCLC. The discovery of this regulatory pathway can provide a new potential therapeutic target for the diagnosis and treatment of NSCLC.

A hypoxia-related lncRNA model for prediction of head and neck squamous cell carcinoma prognosis

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is one of the most common and highly heterogeneous malignancies worldwide. Increasing studies have proven that hypoxia and related long non-coding RNA (lncRNA) are involved in the occurrence and prognosis of HNSCC. The goal of this work is to construct a risk assessment model using hypoxia-related lncRNAs (hrlncRNAs) for HNSCC prognosis prediction and personalized treatment.

METHODS

Transcriptome expression matrix, clinical follow-up data, and somatic mutation data of HNSCC patients were obtained from The Cancer Genome Atlas (TCGA). We used co-expression analysis to identify hrlncRNAs, then screened for differentially expressed lncRNAs (DEhrlncRNAs), and paired these DEhrlncRNAs. The risk model was established through univariate, least absolute shrinkage and selection operator (LASSO), and stepwise multivariate Cox regression. Finally, we assessed the model from multiple perspectives of tumor mutation burden (TMB), tumor immune infiltration, chemotherapeutic sensitivity, immune checkpoint inhibitor (ICI), and functional enrichment.

RESULTS

The risk assessment model included 14 hrlncRNA pairs. The risk score was observed to be a reliable prognostic factor. The high-risk patients had an unfavorable prognosis and significant differences from the low-risk group in TMB and tumor immune infiltration. In the high-risk patients, the common immune checkpoints were down-regulated, including CTLA4 and PDCD1, and the sensibility to paclitaxel and docetaxel was higher. The functional enrichment analysis suggested that the low-risk group was accompanied by activated immune function.

CONCLUSIONS

The risk assessment model of 14-hrlncRNA-pairs demonstrated a promising prognostic prediction for HNSCC patients and can guide personalized clinical treatment.

Targeting HOTAIRM1 Ameliorates Glioblastoma by Disrupting Mitochondrial Oxidative Phosphorylation and Serine Metabolism

Serine hydroxymethyltransferase 2 (SHMT2), which catalyzes the conversion of serine to glycine and one-carbon transfer reactions in mitochondria, is significantly upregulated in glioblastoma (GBM). However, the mechanism by which the stability of SHMT2 gene expression is maintained to drive GBM tumorigenesis has not been clarified. Herein, through microarray screening, we identified that HOXA Transcript Antisense RNA, Myeloid-Specific 1 (HOTAIRM1) modulates the SHMT2 level in various GBM cell lines. Serine catabolism and mitochondrial oxidative phosphorylation activities were decreased by HOTAIRM1 inhibition. Mechanistically, according to our mass spectrometry and eCLIP-seq results, HOTAIRM1 can bind to PTBP1 and IGF2BP2. Furthermore, HOTAIRM1 maintains the stability of SHMT2 by promoting the recognition of an m⁶A site and the interaction of PTBP1/IGF2BP2 with SHMT2 mRNA. The stability of HOTAIRM1 can also be enhanced and results in positive feedback regulation to support the progression of GBM. Thus, targeting HOTAIRM1 could be a promising metabolic therapy for GBM.

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HOTAIRM1 regulates mitochondrial activity in GBM

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The target genes of HOTAIRM1 and the interacting RBPs were screened and identified

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SHMT2 mRNA has an m⁶A site that can be recognized by IGF2BP2

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HOTAIRM1 regulates the stability of SHMT2 by binding to PTBP1 and IGF2BP2

A ceRNA Network Composed of Survival-Related lncRNAs, miRNAs, and mRNAs in Clear Cell Renal Carcinoma

Clear cell renal carcinoma (ccRCC) is one of the most common renal carcinomas worldwide, which has worse prognosis compared with other subtypes of tumors. We propose a potential RNA regulatory mechanism associated with ccRCC progression. Accordingly, we screened out clinical factors and the expression of RNAs and miRNAs of ccRCC from the TCGA database. 9 lncRNAs (FGF12-AS2, WT1-AS, TRIM36-IT1, AC009093.1, LINC00443, TCL6, COL18A1-AS1, AC110619.1, HOTTIP), 2 miRNAs (mir-155 and mir-21), and 3 mRNAs (COL4A4, ERMP1, PRELID2) were selected from differential expression RNAs and built predictive survival models. The survival models performed very well in predicting prognosis and were found to be highly correlated with tumor stage. In addition, the survival-related lncRNA-miRNA-mRNA (ceRNA) network was constructed by 18 RNAs including 12 mRNAs, 2 miRNAs, and 4 lncRNAs. It is found that the “ECM-receptor interaction,” “Pathways in cancer,” and “Chemokine signaling pathway” as the main pathways in KEGG pathway analysis. Overall, we established predictive survival model and ceRNA network based on multivariate Cox regression analysis. It may open a new approach and potential biomarkers for clinical prognosis and treatment of ccRCC patients.

Construction of an individualized clinical prognostic index based on ubiquitination-associated lncRNA in clear cell renal cell carcinoma patients

BACKGROUND

ccRCC is considered as the main subtype of RCC, which accounted for sixth deadliest cancer worldwide. Recently, ubiquitination has been reported to be closely involved in the progression of tumore. The purpose of this study was to identify the ubiquitination-associated genes and co-expressed lncRNAs on the prognosis of clear cell renal cell carcinoma (ccRCC) patients.

METHODS AND PATIENTS

We downloaded 530 cases and the corresponding transcriptome profiling from The Cancer Genome Atlas (TCGA) database. We distinguished mRNA and lncRNA expression data from the transcriptome profiling and then extracted the expression of mRNAs that regulate protein ubiquitination. We obtained lncRNAs associated with protein ubiquitination regulation from the lncRNA data by gene co-expression analysis. Cox regression analysis of survival time, survival status, and lncRNA expression level was carried out, and a prognostic index (PI) was constructed.

RESULTS

The PI was established based on 8 prognostic lncRNAs that regulate protein ubiquitination and distinguish the high-risk group patients from all patients. Multivariate analysis indicated that this PI was an individualized clinical prognostic factor for patients with ccRCC. Regarding clinical characteristics, a ubiquitination-associated clinical-prognostic index (UCPI), containing 8 ubiquitination-related lncRNAs and age, was established and tested with AUC of 0.80.

CONCLUSION

We established a UCPI containing 8 lncRNAs related to protein ubiquitination. This UCPI may become an appropriate model to predict the prognosis in ccRCC patients and guide clinicians to adjust the follow-up regimen.

LncRNA MAGI2-AS3 inhibits tumor progression and angiogenesis by regulating ACY1 via interacting with transcription factor HEY1 in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) represents the most common type of RCC in adults, characterized by hyper-vascularization and metastatic relapse. Surgical resection is the main treatment due to poor response of ccRCC to radio-and chemotherapy. However, the high complexity of tumor vasculature in ccRCC has thwarted effects to develop new therapeutic strategies for ccRCC. In this study, we identify the anti-angiogenic activity of MAGI2-AS3 in ccRCC. 86 paired samples of tumor tissues and adjacent no-tumor tissues were collected from ccRCC patients. Dual-luciferase reporter assay, RIP, and ChIP assays were employed to confirm interactions between MAGI2-AS3, transcription factor HEY1, and the ACY1 gene. In other studies, we assayed human ccRCC cells RLC-310 for their viability, migration and invasion using CCK-8 detection and transwell chamber systems. Angiogenesis was evaluated in the Matrigel-based human umbilical vein endothelial cell (HUVEC)-RLC-310 coculture model and immunohistochemical staining for vascular endothelial growth factor (VEGF) and CD31 in tumor tissues collected from a xenograft ccRCC mouse model. MAGI2-AS3 and ACY1 expression was downregulated in ccRCC tissues, and low expression of MAGI2-AS3 was associated with poor patient survival. Overexpression of MAGI2-AS3 could reduce ccRCC cell viability and migration, inhibit vessel-like tube formation of HUVECs in vitro, and repress tumor growth and angiogenesis in vivo. MAGI2-AS3 bound with HEY1 and reduced the HEY1 enrichment at the ACY1 promoter region, thus increasing ACY1 gene transcription. HEY1 knockdown or ACY1 overexpression that resisted MAGI2-AS3 knockdown was found in the in vivo and in vitro settings. The present study demonstrates that MAGI2-AS3 exerts tumor-suppressive, anti-angiogenic activities in ccRCC by modulating the HEY1/ACY1 pathway, thus lending support for conducting further investigations of anti-angiogenesis therapy for ccRCC.

Long Noncoding RNA MMP2-AS1 Contributes to Progression of Renal Cell Carcinoma by Modulating miR-34c-5p/MMP2 Axis

Renal cell carcinoma (RCC) serves as a prevalent malignancy of urinary system and presents severe mortality and increasing incidence. Long noncoding RNAs (lncRNAs) have demonstrated critical roles in RCC development. Here, we were interested in the function of MMP2-AS1 during RCC progression. We observed that MP2-AS1 localized in both nucleus and cytoplasm of RCC cells using fluorescent in situ hybridization (FISH). The cell viability, proliferation, invasion, and migration of RCC cells were reduced by the depletion of MMP2-AS1. The MMP2-AS1 depletion-inhibited viability, proliferation, migration, and invasion of RCC cells were rescued by the overexpression of MMP2 in vitro. Consistently, the tumor growth of RCC cells was repressed by the depletion of MMP2-AS1 in the nude mice, while the overexpression of MMP2 could reverse this effect in vivo. Mechanically, we predicted the potential interaction of miR-34c-5p with both MMP2-AS1 and MMP2. The treatment of miR-34c-5p mimic reduced the luciferase activity of MMP2-AS1 and MMP2 3'UTR. The depletion of MMP2-AS1 enhanced miR-34c-5p expression and the expression of MMP2 was inhibited by miR-34c-5p in RCC cells. The protein levels of MMP2 were downregulated by MMP2-AS1 knockdown, while the inhibitor of miR-34c-5p rescued the expression of MMP2 in the cells. The treatment of miR-34c-5p mimic attenuated the cell viability, proliferation, invasion, and migration of RCC cells, in which MMP2 overexpression restored the phenotypes. MMP2-AS1 depletion-attenuated viability, proliferation, migration, and invasion of RCC cells were reversed by miR-34c-5p inhibitor. We concluded that MMP2-AS1 contributed to progression of renal cell carcinoma by modulating miR-34c-5p/MMP2 axis.

LncRNA GIHCG promoted the proliferation and migration of renal cell carcinoma through regulating miR-499a-5p/XIAP axis

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LncRNA GIHCG facilitated the proliferation and migration while suppressed apoptosis of RCC cells.

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LncRNA GIHCG directly sponged miR-499a-5p and down-regulated its expression.

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MiR-499a-5p negatively regulated XIAP expression.

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LncRNA GIHCG knockdown inhibited the growth and metastasis of RCC in nude mice.

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LncRNA GIHCG contributed to the development of RCC through miR-499a-5p/XIAP axis.

Background

Our previous study demonstrated that lncRNA GIHCG is upregulated in renal cell carcinoma (RCC) and that knockdown of lncRNA GIHCG suppresses the proliferation and migration of RCC cells. However, the mechanism of lncRNA GIHCG in RCC needs further exploration.

Methods

The proliferation, cell cycle, migration, and apoptosis of RCC cells were tested using CCK-8, flow cytometry, wound healing and Annexin-V/-FITC/PI flow cytometry assays, respectively. Dual-luciferase reporter and RNA pull-down or RNA immunoprecipitation assays (RIPs) were performed to analyze the interactions among lncRNA GIHCG, miR-499a-5p and XIAP. A tumour xenograft study was conducted to verify the function of lncRNA GIHCG in RCC development in vivo.

Results

Knockdown of lncRNA GIHCG inhibited cell proliferation and migration and induced G0/G1 arrest while promoting apoptosis. Overexpression of lncRNA GIHCG led to the opposite results. LncRNA GIHCG sponged miR-499a-5p and downregulated its expression in RCC cells. MiR-499a-5p overexpression suppressed RCC cell growth. MiR-499a-5p targeted XIAP and inhibited its expression. LncRNA GIHCG knockdown reduced the growth of tumour xenografts in vivo and the expression of XIAP while increasing miR-499a-5p levels.

Conclusion

LncRNA GIHCG accelerated the development of RCC by targeting miR-499a-5p and increasing XIAP levels.

Prediction of lncRNA-Disease Associations via Closest Node Weight Graphs of the Spatial Neighborhood Based on the Edge Attention Graph Convolutional Network

Accumulated evidence of biological clinical trials has shown that long non-coding RNAs (lncRNAs) are closely related to the occurrence and development of various complex human diseases. Research works on lncRNA–disease relations will benefit to further understand the pathogenesis of human complex diseases at the molecular level, but only a small proportion of lncRNA–disease associations has been confirmed. Considering the high cost of biological experiments, exploring potential lncRNA–disease associations with computational approaches has become very urgent. In this study, a model based on closest node weight graph of the spatial neighborhood (CNWGSN) and edge attention graph convolutional network (EAGCN), LDA-EAGCN, was developed to uncover potential lncRNA–disease associations by integrating disease semantic similarity, lncRNA functional similarity, and known lncRNA–disease associations. Inspired by the great success of the EAGCN method on the chemical molecule property recognition problem, the prediction of lncRNA–disease associations could be regarded as a component recognition problem of lncRNA–disease characteristic graphs. The CNWGSN features of lncRNA–disease associations combined with known lncRNA–disease associations were introduced to train EAGCN, and correlation scores of input data were predicted with EAGCN for judging whether the input lncRNAs would be associated with the input diseases. LDA-EAGCN achieved a reliable AUC value of 0.9853 in the ten-fold cross-over experiments, which was the highest among five state-of-the-art models. Furthermore, case studies of renal cancer, laryngeal carcinoma, and liver cancer were implemented, and most of the top-ranking lncRNA–disease associations have been proven by recently published experimental literature works. It can be seen that LDA-EAGCN is an effective model for predicting potential lncRNA–disease associations. Its source code and experimental data are available at https://github.com/HGDKMF/LDA-EAGCN.

Linc1548 promotes the transition of epiblast stem cells into neural progenitors by engaging OCT6 and SOX2

The transition of embryonic stem cells from the epiblast stem cells (EpiSCs) to neural progenitor cells (NPCs), name as the neural induction process, is crucial for cell fate determination of neural differentiation. However, the mechanism of this transition is unclear. Here, we identified a long non-coding RNA (linc1548) as a critical regulator of neural differentiation of mouse embryonic stem cells (mESCs). Knockout of linc1548 did not affect the conversion of mESCs to EpiSCs, but delayed the transition from EpiSCs to NPCs. Moreover, linc1548 interacts with the transcription factors OCT6 and SOX2 forming an RNA-protein complex to regulate the transition from EpiSCs to NPCs. Finally, we showed that Zfp521 is an important target gene of this RNA-protein complex regulating neural differentiation. Our findings prove how the intrinsic transcription complex mediated by a lncRNA linc1548 and can better understand the intrinsic mechanism of neural fate determination.

Identification and Validation of HOTAIRM1 as a Novel Biomarker for Oral Squamous Cell Carcinoma

ORAL squamous cell carcinoma (OSCC) is a malignant tumor with the highest incidence among tumors involving the oral cavity maxillofacial region, and is notorious for its high recurrence and metastasis potential. Long non-coding RNAs (lncRNAs), which regulate the genesis and evolution of cancers, are potential prognostic biomarkers. This study identified HOTAIRM1 as a novel significantly upregulated lncRNA in OSCC, which is strongly associated with unfavorable prognosis of OSCC. Systematic bioinformatics analyses demonstrated that HOTAIRM1 was closely related to tumor stage, overall survival, genome instability, the tumor cell stemness, the tumor microenvironment, and immunocyte infiltration. Using biological function prediction methods, including Weighted gene co-expression network analysis (WGCNA), Gene set enrichment analysis (GSEA), and Gene set variation analysis (GSVA), HOTAIRM1 plays a pivotal role in OSCC cell proliferation, and is mainly involved in the regulation of the cell cycle. In vitro, cell loss-functional experiments confirmed that HOTAIRM1 knockdown significantly inhibited the proliferation of OSCC cells, and arrested the cell cycle in G1 phase. At the molecular level, PCNA and CyclinD1 were obviously reduced after HOTAIRM1 knockdown. The expression of p53 and p21 was upregulated while CDK4 and CDK6 expression was decreased by HOTAIRM1 knockdown. In vivo, knocking down HOTAIRM1 significantly inhibited tumor growth, including the tumor size, weight, volume, angiogenesis, and hardness, monitored by ultrasonic imaging and magnetic resonance imaging In summary, our study reports that HOTAIRM1 is closely associated with tumorigenesis of OSCC and promotes cell proliferation by regulating cell cycle. HOTAIRM1 could be a potential prognostic biomarker and a therapeutic target for OSCC.

gGATLDA: lncRNA-disease association prediction based on graph-level graph attention network

Background

Long non-coding RNAs (lncRNAs) are related to human diseases by regulating gene expression. Identifying lncRNA-disease associations (LDAs) will contribute to diagnose, treatment, and prognosis of diseases. However, the identification of LDAs by the biological experiments is time-consuming, costly and inefficient. Therefore, the development of efficient and high-accuracy computational methods for predicting LDAs is of great significance.

Results

In this paper, we propose a novel computational method (gGATLDA) to predict LDAs based on graph-level graph attention network. Firstly, we extract the enclosing subgraphs of each lncRNA-disease pair. Secondly, we construct the feature vectors by integrating lncRNA similarity and disease similarity as node attributes in subgraphs. Finally, we train a graph neural network (GNN) model by feeding the subgraphs and feature vectors to it, and use the trained GNN model to predict lncRNA-disease potential association scores. The experimental results show that our method can achieve higher area under the receiver operation characteristic curve (AUC), area under the precision recall curve (AUPR), accuracy and F1-Score than the state-of-the-art methods in five fold cross-validation. Case studies show that our method can effectively identify lncRNAs associated with breast cancer, gastric cancer, prostate cancer, and renal cancer.

Conclusion

The experimental results indicate that our method is a useful approach for predicting potential LDAs.

An immune-related lncRNA risk coefficient model to predict the outcomes in clear cell renal cell carcinoma

Objective: Using model algorithms, we constructed an immune-related long non-coding RNAs (lncRNAs) risk coefficient model to predict outcomes for patients with clear cell renal cell carcinoma (ccRCC) to understand the infiltration of tumor immune cells and the sensitivity to immune-targeted drugs.

Methods: Open genes data were downloaded from The Cancer Genome Atlas and The Immunology Database and Analysis Portal, and immune-related lncRNAs were obtained through Pearson correlation analysis. R language software was used to obtain differentially expressed immune-related lncRNAs and immune-related lncRNA pairs. The model was constructed using least absolute shrinkage and selector operation regression analysis, and receiver operator characteristic curves were drawn. The Akaike information criterion was used to distinguish the high-risk from the low-risk group. We also conducted correlation analysis for the high- and low-risk subgroups.

Results: We identified 27 immune-related lncRNAs pairs, 16 of which were included in the model construction. After merging clinical data, the areas under the curve of 1 -year, 3-year, and 5-year survival times of ccRCC patients were 0.867, 0.832, and 0.838, respectively. Subgroup analyses were conducted according to the cut-off value. We found that the high-risk group was associated with poor outcomes. The risk score and tumor stage were independent predictors of the outcome of ccRCC. The risk model predicted specific immune cell infiltration, immune checkpoint gene expression levels, and high-risk groups more sensitive to sunitinib targeted therapy.

Conclusion: We obtained prognostic-related novel ccRCC markers and risk model that predicts the outcome of patients with ccRCC and helps identify those who can benefit from sunitinib.

Identification of autophagy-related long non-coding RNA prognostic and immune signature for clear cell renal cell carcinoma

Background

Studies over the past decade have shown that long non-coding RNAs (lncRNAs) play an essential role in the tumorigenesis and progression of kidney renal clear cell carcinoma (KIRC). Meanwhile, autophagy has been demonstrated to regulate KIRC pathogenesis and targeting therapy resistance. However, the prognostic value of autophagy-related lncRNAs in KIRC patients has not been reported before.

Methods

In this study, we obtained transcriptome data of 611 KIRC cases from the TCGA database and 258 autophagy-related mRNAs from the HADb database to identify autophagy-related lncRNAs by co-expression network. A prognostic model was then established basing on these autophagy-related lncRNAs, dividing patients into high-risk and low-risk groups. Survival analysis, clinical variables dependent receiver operating characteristic (ROC) analyses, univariate/multivariate Cox analyses, and clinical correlation analysis were performed based on risk signature with R language. Gene set enrichment analysis (GSEA) was then performed to investigate the potential mechanism of the risk signature promoting KIRC progression with GSEA software. CIBERSORT algorithm was performed to assess the impact of these lncRNAs on the infiltration of immune cells.

Results

A total of 17 lncRNAs were screened out and all these lncRNAs were found significantly related to KIRC patients’ overall survival in subsequent survival analyses. Besides, the overall survival time in the high-risk group was much poorer than in the low-risk group. The ROC analysis revealed that the prognostic value of risk signature was better than age, gender, grade, and N stage. Univariate/multivariate analyses suggested that the risk signature was an independent predictive factor for KIRC patients. Immune and autophagy related pathways were dramatically enriched in high-risk and low-risk groups, respectively, and lncRNAs related immune cells were identified by CIBERSORT.

Conclusions

In summary, our identified 17 autophagy-related lncRNAs had prognostic value for KIRC patients which may function in immunomodulation.

Circulating microRNAs from the Molecular Mechanisms to Clinical Biomarkers: A Focus on the Clear Cell Renal Cell Carcinoma

microRNAs (miRNAs) are emerging as relevant molecules in cancer development and progression. MiRNAs add a post-transcriptional level of control to the regulation of gene expression. The deregulation of miRNA expression results in changing the molecular circuitry in which miRNAs are involved, leading to alterations of cell fate determination. In this review, we describe the miRNAs that are emerging as innovative molecular biomarkers from liquid biopsies, not only for diagnosis, but also for post-surgery management in cancer. We focus our attention on renal cell carcinoma, in particular highlighting the crucial role of circulating miRNAs in clear cell renal cell carcinoma (ccRCC) management. In addition, the functional deregulation of miRNA expression in ccRCC is also discussed, to underline the contribution of miRNAs to ccRCC development and progression, which may be relevant for the identification and design of innovative clinical strategies against this tumor.

ACSNI: An unsupervised machine-learning tool for prediction of tissue-specific pathway components using gene expression profiles

Determining the tissue- and disease-specific circuit of biological pathways remains a fundamental goal of molecular biology. Many components of these biological pathways still remain unknown, hindering the full and accurate characterization of biological processes of interest. Here we describe ACSNI, an algorithm that combines prior knowledge of biological processes with a deep neural network to effectively decompose gene expression profiles (GEPs) into multi-variable pathway activities and identify unknown pathway components. Experiments on public GEP data show that ACSNI predicts cogent components of mTOR, ATF2, and HOTAIRM1 signaling that recapitulate regulatory information from genetic perturbation and transcription factor binding datasets. Our framework provides a fast and easy-to-use method to identify components of signaling pathways as a tool for molecular mechanism discovery and to prioritize genes for designing future targeted experiments (https://github.com/caanene1/ACSNI).

Development and Validation of an Immune-Related Long Non-coding RNA Prognostic Model in Glioma

Background: Long non-coding RNAs (lncRNAs) play an important role in the immune processes of glioma. Immune related lncRNAs (IRlncRs) may be a critical prognosis in patients with glioma. The current study aimed to construct a glioma immune-related prognosis model by IRlncRs.

Methods: Transcriptome RNA-sequencing data of glioma were obtained from The Cancer Genome Atlas (TCGA) and an immune‑related risk score (IRRS) model was constructed by Lasso and multivariate Cox regression analysis. Receiver Operating Characteristic (ROC) curves were used to assess the sensitivity and specificity of the prognosis on IRRS. A predictive nomogram and a time-dependent ROC curve was performed in training and validation cohort. We explored the relationships between survival‑related IRlncRs (sIRlncRs) and clinicopathologic parameters. Functional annotation of the sIRlncRs was investigated by gene set enrichment analysis (GSEA) and principal component analysis (PCA). The relationships between IRRS model and immune cell infiltration and co-expression network analysis among the sIRlncRs were performed for molecular mechanism study.

Results: A total of 10 sIRlncRs were enrolled to build IRRS model. The IRRS was identified as an independent prognostic factor and correlated with the overall survival (AUC =0.880). The nomogram was constructed successfully with IRRS, age and grade as variables. Immune cell infiltration analysis indicated that B cells, neutrophil, dendritic and macrophage cells were positively correlated with IRRS. PCA and GSEA illustrated that the lncRNA signature enrolled the IRRS model was closely related to immune status. Additionally, co-expression network showed that there was a strong correlation between 10 sIRlncRs at the transcriptional level.

Conclusion: We successfully constructed a remarkable clinical model of sIRlncRs with potential prognostic value for glioma patients, which provides an insight into immunological research and treatment strategies of glioma.

A Risk Signature with Autophagy-Related Long Noncoding RNAs for Predicting the Prognosis of Clear Cell Renal Cell Carcinoma: Based on the TCGA Database and Bioinformatics

BACKGROUND

Disorders of autophagic processes have been reported to affect the survival outcome of clear cell renal cell carcinoma (ccRCC) patients. The purpose of our study was to identify and validate the candidate prognostic long noncoding RNA signature of autophagy.

METHODS

Transcriptome profiles were obtained from The Cancer Genome Atlas. The autophagy gene list was obtained from the Human Autophagy Database. Based on coexpression analysis, we obtained a list of autophagy-related lncRNAs (ARlncRNAs). GO enrichment analysis and KEGG pathway analysis were conducted to explore the functional annotation of these ARlncRNAs. Univariate and multivariate Cox regression analyses were conducted to elucidate the correlation between overall survival and the expression level of each ARlncRNAs. We then established a prognostic signature that was a linear combination of the regression coefficients from the multivariate Cox regression model (β) multiplied by the expression levels of the respective ARlncRNAs in the training cohort. The predictive performance was tested in the validation cohort. Additionally, the independence of the risk signature was assessed, and the relationship between the risk signature and conventional clinicopathological features was explored.

RESULTS

Seven autophagy-related lncRNAs with prognostic value (SNHG3, SNHG17, MELTF-AS1, HOTAIRM1, EPB41L4A-DT, AP003352.1, and AC145423.2) were identified and integrated into a risk signature, dividing patients into low-risk and high-risk groups. The risk signature was independent of conventional clinical characteristics as a prognostic indicator of ccRCC (HR, 1.074, 95% confidence interval: 1.036-1.113, p < 0.001) and was valuable in the prediction of ccRCC progression.

CONCLUSION

Our risk signature has potential prognostic value in ccRCC, and these ARlncRNAs may play a significant role in ccRCC tumor biology.

LncRNA HIF1A-AS2 accelerates malignant phenotypes of renal carcinoma by modulating miR-30a-5p/SOX4 axis as a ceRNA

OBJECTIVE

Several reports have proposed that lncRNAs, as potential biomarkers, participate in the progression and growth of malignant tumors. HIF1A-AS2 is a novel lncRNA and potential biomarker, involved in the genesis and development of carcinomas. However, the molecular mechanism of HIF1A-AS2 in renal carcinoma is unclear.

METHODS

The relative expression levels of HIF1A-AS2 and miR-30a-5p were detected using RT-qPCR in renal carcinoma tissues and cell lines. Using loss-of-function and overexpression, the biological effects of HIF1A-AS2 and miR-30a-5p in kidney carcinoma progression were characterized. Dual luciferase reporter gene analysis and Western blot were used to detect the potential mechanism of HIF1A-AS2 in renal carcinomas.

RESULTS

HIF1A-AS2 was upregulated in kidney carcinoma tissues when compared with para-carcinoma tissues (P < 0.05). In addition, tumor size, tumor node mestastasis stage and differentiation were identified as being closely associated with HIF1A-AS2 expression (P < 0.05). Knockdown or overexpression of HIF1A-AS2 either restrained or promoted the malignant phenotype and WNT/β-catenin signaling in renal carcinoma cells (P < 0.05). MiR-30a-5p was downregulated in renal cancers and partially reversed HIF1A-AS2 functions in malignant renal tumor cells. HIF1A-AS2 acted as a microRNA sponge that actively regulated the relative expression of SOX4 in sponging miR-30a-5p and subsequently increased the malignant phenotypes of renal carcinomas. HIF1A-AS2 showed a carcinogenic effect and miR-30a-5p acted as an antagonist of the anti-oncogene effects in the pathogenesis of renal carcinomas.

CONCLUSIONS

The HIF1A-AS2-miR-30a-5p-SOX4 axis was associated with the malignant progression and development of renal carcinoma. The relative expression of HIF1A-AS2 was negatively correlated with the expression of miR-30a-5p, and was closely correlated with SOX4 mRNA levels in renal cancers.

Downregulation of lncRNA ZNF582-AS1 due to DNA hypermethylation promotes clear cell renal cell carcinoma growth and metastasis by regulating the N(6)-methyladenosine modification of MT-RNR1

Background

Emerging evidence confirms that lncRNAs (long non-coding RNAs) are potential biomarkers that play vital roles in tumors. ZNF582-AS1 is a novel lncRNA that serves as a potential prognostic marker of cancers. However, the specific clinical significance and molecular mechanism of ZNF582-AS1 in ccRCC (clear cell renal cell carcinoma) are unclear.

Methods

Expression level and clinical significance of ZNF582-AS1 were determined by TCGA-KIRC data and qRT-PCR results of 62 ccRCCs. DNA methylation status of ZNF582-AS1 promoter was examined by MSP, MassARRAY methylation and demethylation analysis. Gain-of-function experiments were conducted to investigate the biological roles of ZNF582-AS1 in the phenotype of ccRCC. The subcellular localization of ZNF582-AS1 was detected by RNA FISH. iTRAQ, RNA pull-down and RIP-qRT-PCR were used to identify the downstream targets of ZNF582-AS1. rRNA MeRIP-seq and MeRIP-qRT-PCR were utilized to examine the N(6)-methyladenosine modification status. Western blot and immunohistochemistry assays were used to determine the protein expression level.

Results

ZNF582-AS1 was downregulated in ccRCC, and decreased ZNF582-AS1 expression was significantly correlated with advanced tumor stage, higher pathological stage, distant metastasis and poor prognosis. Decreased ZNF582-AS1 expression was caused by DNA methylation at the CpG islands within its promoter. ZNF582-AS1 overexpression inhibited cell proliferative, migratory and invasive ability, and increased cell apoptotic rate in vitro and in vivo. Mechanistically, we found that ZNF582-AS1 overexpression suppressed the N(6)-methyladenosine modification of MT-RNR1 by reducing rRNA adenine N(6)-methyltransferase A8K0B9 protein level, resulting in the decrease of MT-RNR1 expression, followed by the inhibition of MT-CO2 protein expression. Furthermore, MT-RNR1 overexpression reversed the decreased MT-CO2 expression and phenotype inhibition of ccRCC induced by increased ZNF582-AS1 expression.

Conclusions

This study demonstrates for the first time that ZNF582-AS1 functions as a tumor suppressor gene in ccRCC and ZNF582-AS1 may serve as a potential biomarker and therapeutic target of ccRCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01889-8.

Identification and validation of the clinical roles of the VHL-related LncRNAs in clear cell renal cell carcinoma

Accumulating evidence suggests that lncRNAs (long non-coding RNAs) function as oncogenes or tumor suppressor genes in ccRCC (clear cell renal cell carcinoma). Although VHL (Von Hippel-Lindau) gene inactivation is by far the most common carcinogenic driving event in ccRCC, the roles of VHL-related lncRNAs in ccRCC remain unknown. In this study, using RNA-seq and clinical data in TCGA-KIRC (the Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma), we identified VHL-related lncRNAs through WGCNA (Weighted Gene Co-expression Network Analysis), correlation analysis and catRAPID algorithm, and explored their clinical characteristics in ccRCC. Results showed that 10 lncRNAs (AC112220.2, AL391121.1, USP46-AS1, AL450326.1, MID1IP1-AS1, SUCLG2-AS1, RAP2C-AS1, FGD5-AS1, AC018647.2 and AC015922.2) were identified as VHL-related lncRNAs, and they were down-regulated in ccRCC tissues. Survival analysis results indicated that high expression groups of AC112220.2, AL391121.1, USP46-AS1, AL450326.1, SUCLG2-AS1, RAP2C-AS1, FGD5-AS1, AC018647.2 and AC015922.2 had significantly longer OS (Overall Survival) than their respective low expression groups. Meanwhile high AC112220.2, USP46-AS1, AL450326.1, SUCLG2-AS1, FGD5-AS1, AC018647.2 and AC015922.2 expression groups had remarkably longer DFS (Disease Free Survival) than their respective low expression groups. Besides, FGD5-AS1 and AL391121.1 expression were decreased in VHL mutant tissues compared with VHL non-mutant tissues. Moreover, high expression group of FGD5-AS1 had significantly longer OS and DFS than their respective low expression groups in VHL mutant ccRCC. In addition, we found that DNA hypermethylation may also play an important role in decreased FGD5-AS1 expression. Furthermore, we validated the expression of FGD5-AS1 in VHL mutant and non-mutant ccRCC tissues and cell lines. In conclusion, our results demonstrated that lncRNA FGD5-AS1 was significantly associated with VHL and can serve as a novel biomarker of ccRCC.

An Effective Hypoxia-Related Long Non-Coding RNAs Assessment Model for Prognosis of Clear Cell Renal Carcinoma

Hypoxia is a significant clinical feature and regulates various tumor processes in clear cell renal carcinoma (ccRCC). Increasing evidence has demonstrated that long non-coding RNAs (lncRNAs) are closely associated with the survival outcomes of ccRCC patients and regulates hypoxia-induced tumor processes. Thus, this study aimed to develop a hypoxia-related lncRNA (HRL) prognostic model for predicting the survival outcomes in ccRCC. LncRNAs in ccRCC samples were extracted from The Cancer Genome Atlas database. Hypoxia-related genes were downloaded from the Molecular Signatures Database. A co-expression analysis between differentially expressed lncRNAs and hypoxia-related genes in ccRCC samples was performed to identify HRLs. Univariate and multivariate Cox regression analyses were performed to select nine optimal lncRNAs for developing the HRL model. The prognostic model showed good performance in predicting prognosis among patients with ccRCC, and the validation sets reached consistent results. The model was also found to be related to the clinicopathologic parameters of tumor grade and tumor stage and to tumor immune infiltration. In conclusion, our findings indicate that the hypoxia-lncRNA assessment model may be useful for prognostication in ccRCC cases. Furthermore, the nine HRLs included in the model might be useful targets for investigating the tumorigenesis of ccRCC and designing individualized treatment strategies.

Downregulation of the lncRNA ASB16-AS1 Decreases LARP1 Expression and Promotes Clear Cell Renal Cell Carcinoma Progression via miR-185-5p/miR-214-3p

Clear cell renal cell carcinoma (ccRCC) comprises approximately 75% of renal cell carcinomas, which is one of the most common and lethal urologic cancers, with poor quality of life for patients and is a huge economic burden to health care systems. It is imperative we find novel prognostic and therapeutic targets for ccRCC clinical intervention. In this study, we found that the expression of the long noncoding RNA (lncRNA) ASB16-AS1 was downregulated in ccRCC tissues compared with non-diseased tissues and was also associated with advanced tumor stage and larger tumors. By constructing cell and mouse models, it was found that downregulated lncRNA ASB16-AS1 enhanced cell proliferation, migration, invasion, and promoted tumor growth and metastasis. Furthermore, by performing bioinformatics analysis, biotinylated RNA pull-downs, AGO2-RIP, and luciferase reporter assays, our findings showed that downregulated ASB16-AS1 decreased La-related protein 1 (LARP1) expression by inhibiting miR-185-5p and miR-214-3p. Furthermore, it was found that overexpression of LARP1 reversed the promotive effects of downregulated ASB16-AS1 on ccRCC cellular progression. Our results revealed that downregulated ASB16-AS1 promotes ccRCC progression via a miR-185-5p-miR-214-3p-LARP1 pathway. We suggest that this pathway could be used to monitor prognosis and presents therapeutic targets for ccRCC clinical management.

HOTAIRM1 promotes osteogenic differentiation and alleviates osteoclast differentiation by inactivating the NF-κB pathway

Osteoporosis (OP), one of the most prevalent chronic progressive bone diseases, is caused by deficiency in bone formation by osteoblasts or excessive bone resorption by osteoclasts and subsequently increases the risk of bone fractures. Emerging evidence has indicated that long noncoding RNAs (lncRNAs) play key roles in many biological processes and various disorders. However, the role and mechanism of HOX antisense intergenic RNA myeloid 1 (HOTAIRM1), a myeloid-specific lncRNA, in osteoclast differentiation, osteogenic differentiation, and OP remain unclear. In this study, we found that HOTAIRM1 was upregulated during ossification of ligamentum flavum and osteogenic differentiation, while it was downregulated in osteoclast differentiation and in the bone and serum of human and mouse with OP. Further investigation revealed that silencing Hotairm1 decreased the expression of the osteogenic markers and attenuated osteogenesis. Moreover, forced Hotairm1 expression inhibited the expressions of the osteoclastogenesis markers and alleviated receptor activator of nuclear factor kappa B (NF-κB) ligand (RANKL)-induced osteoclast differentiation. Mechanically, Hotairm1 repressed the phosphorylation of p65 and inhibitor of κBα (IκBα) and attenuated RANKL-mediated enhancement of phos-p65 and IκBα, suggesting that Hotairm1 inhibits RANKL-induced osteoclastogenesis through the NF-κB pathway. In conclusion, our data identified a crucial role of HOTAIRM1 in OP, providing a proof of this molecule as a potential diagnostic marker and a possible therapeutic target against OP.

HOTAIR and androgen receptor synergistically increase GLI2 transcription to promote tumor angiogenesis and cancer stemness in renal cell carcinoma

Tumor angiogenesis is a major characteristic of renal cell carcinoma (RCC). Herein, we report a novel mechanism of how lncRNA and androgen receptor (AR) drive the Hedgehog pathway to promote tumor angiogenesis in RCC. We found that the high expression of lncRNA HOTAIR in RCC is associated with poor prognosis. Moreover, HOTAIR and AR form a feedback loop to promote the expression of each other. Interestingly, we also found that in RCC, HOTAIR is associated with the Hedgehog pathway, especially GLI2, via bioinformatics analysis. Furthermore, HOTAIR promotes GLI2 expression in the presence of AR. Mechanistically, HOTAIR interacts with AR and they cooperatively bind to GLI2 promoter and increase its transcription activity. We further confirmed how HOTAIR-AR axis regulates GLI2 expression by analyzing its function in RCC cells and found that HOTAIR and AR synergistically enhanced the expression of GLI2 downstream genes, such as VEGFA, PDGFA, and cancer stem cell transcription factors, and promoted tumor angiogenesis and cancer stemness in RCC cells both in vitro and in tumor xenografts. Overall, these findings suggest that HOTAIR and GLI2 could be novel therapeutic targets against RCC.

PTGER3 and MMP-2 play potential roles in diabetic nephropathy via competing endogenous RNA mechanisms

BACKGROUND

Diabetic nephropathy (DN) is a primary complication of diabetes mellitus (DM). The pathology of DN is still vague, and diagnostic accuracy is not enough. This study was performed to identify miRNAs and genes that have possibilities of being used as therapeutic targets for DN in type 2 DM.

METHODS

Human miRNA data GSE51674 and gene data GSE111154 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and miRNAs (DEmiRNAs) in the kidney between control and DN patients were screened out. The competing endogenous RNA (ceRNA) network was constructed, and key lncRNA-miRNA-mRNA pairs were selected accordingly. Potential drugs targeting DEGs were screened out and validated using PCR analysis.

RESULTS

Totally, 83 DEmiRNAs and 293 DEGs were identified in GSE51674 and GSE111154, respectively. Thirteen of the top 20 DEmiRNAs (10 up and 10 down) targeted to 47 DEGs. In the ceRNA network, RP11-363E7.4/TTN-AS1/HOTAIRM1-hsa-miR-106b-5p-PTGER3 and LINC00960-hsa-miR-1237-3p-MMP-2 interaction pairs were identified as the key ceRNA network. Interestingly, PTGER3 and hsa-miR-1237-3p were downregulated, and MMP-2 and hsa-miR-106b-5p were upregulated in the kidney of patients with DN compared with normal controls, respectively. PTGER3 and MMP-2 were targeted by drugs including iloprost, treprostinil, or captopril, and the deregulation of the two genes was confirmed in the plasma samples from patients with DN as compared with controls.

CONCLUSIONS

We speculated that the RP11-363E7.4/TTN-AS1/HOTAIRM1-hsa-miR-106b-5p-PTGER3 and LINC00960-hsa-miR-1237-3p-MMP-2 networks were associated with diabetic renal injury.

Dysregulation of Long Non-coding RNAs and mRNAs in Plasma of Clear Cell Renal Cell Carcinoma Patients Using Microarray and Bioinformatic Analysis

Objective: The roles of long non-coding RNAs (lncRNAs) in the diagnosis of clear cell renal cell carcinoma (ccRCC) are still not well-defined. We aimed to identify differentially expressed lncRNAs and mRNAs in plasma of ccRCC patients and health controls systematically.

Methods: Expression profile of plasma lncRNAs and mRNAs in ccRCC patients and healthy controls was analyzed based on microarray assay. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway-based approaches were used to investigate biological function and signaling pathways mediated by the differentially expressed mRNAs. SOCS2-AS1 was selected for validation using Real-Time PCR. The differentially expressed lncRNAs and mRNAs were further compared with E-MTAB-1830 datasets using Venn and the NetworkAnalyst website. The GEPIA and ULCAN websites were utilized for the evaluation of the expression level of differentially expressed mRNA and their association with overall survival (OS).

Results: A total of 3,664 differentially expressed lncRNAs were identified in the plasma of ccRCC patients, including 1,511 up-regulated and 2,153 down-regulated lncRNAs (fold change ≥2 and P < 0.05), respectively. There were 2,268 differentially expressed mRNAs, including 932 up-regulated mRNAs and 1,336 down-regulated mRNAs, respectively (fold change ≥2 and P < 0.05). Pathway analysis based on deregulated mRNAs was mainly involved in melanogenesis and Hippo signaling pathway (P < 0.05). In line with the lncRNA microarray findings, the SOCS2-AS1 was down-regulated in ccRCC plasma and tissues, as well as in cell lines. Compared with the E-MTAB-1830 gene expression profiles, we identified 18 lncRNAs and 87 mRNAs differently expressed in both plasma and neoplastic tissues of ccRCC. The expression of 10 mRNAs (EPB41L4B, CCND1, GGT1, CGNL1, CYSLTR1, PLAUR, UGT3A1, PROM2, MUC12, and PCK1) was correlated with the overall survival (OS) rate in ccRCC patients based on the GEPIA and ULCAN websites.

Conclusions: We firstly reported differentially expressed lncRNAs in ccRCC patients and healthy controls systemically. Several differentially expressed lncRNAs and mRNAs were identified, which might serve as diagnostic or prognostic markers. The biological function of these lncRNAs and mRNAs should be further validated. Our study may contribute to the future treatment of ccRCC and provide novel insights into cancer biology.

Long noncoding RNA HOTAIRM1 in human cancers

Long noncoding RNAs (lncRNAs) are a group of RNAs over 200 nucleotides in length involved in diverse processes in tumor cells including proliferation, invasion and apoptosis. Given these facts, it is hardly accidental that variations in the expression of some lncRNAs have been found to be closely related to carcinogenesis and tumor growth and metastasis. HOTAIRM1, first discovered as an important factor for granulocytic differentiation in NB4 promyelocytic leukemia, has been shown to be a salient cancer-related lncRNA abnormally expressed in a variety of tumors. In this review, we summarize current evidence on the critical role of HOTAIRM1 in human malignancy, its potential mechanism of action and future use in the development of effective therapeutics.

Long-Noncoding RNA (lncRNA) in the Regulation of Hypoxia-Inducible Factor (HIF) in Cancer

Hypoxia is dangerous for oxygen-dependent cells, therefore, physiological adaption to cellular hypoxic conditions is essential. The transcription factor hypoxia-inducible factor (HIF) is the main regulator of hypoxic metabolic adaption reducing oxygen consumption and is regulated by gradual von Hippel-Lindau (VHL)-dependent proteasomal degradation. Beyond physiology, hypoxia is frequently encountered within solid tumors and first drugs are in clinical trials to tackle this pathway in cancer. Besides hypoxia, cancer cells may promote HIF expression under normoxic conditions by altering various upstream regulators, cumulating in HIF upregulation and enhanced glycolysis and angiogenesis, altogether promoting tumor proliferation and progression. Therefore, understanding the underlying molecular mechanisms is crucial to discover potential future therapeutic targets to evolve cancer therapy. Long non-coding RNAs (lncRNA) are a class of non-protein coding RNA molecules with a length of over 200 nucleotides. They participate in cancer development and progression and might act as either oncogenic or tumor suppressive factors. Additionally, a growing body of evidence supports the role of lncRNAs in the hypoxic and normoxic regulation of HIF and its subunits HIF-1α and HIF-2α in cancer. This review provides a comprehensive update and overview of lncRNAs as regulators of HIFs expression and activation and discusses and highlights potential involved pathways.

Bioinformatics profiling integrating a three immune-related long non-coding RNA signature as a prognostic model for clear cell renal cell carcinoma

Background

Renal cell carcinoma (RCC) is one of the most common aggressive malignant tumors in urogenital system, and the clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinoma. Immune related long non-coding RNAs (IRlncRs) plentiful in immune cells and immune microenvironment (IME) are potential in evaluating prognosis and assessing the effects of immunotherapy. A completed and meaningful IRlncRs analysis based on abundant ccRCC gene samples from The Cancer Genome Atlas (TCGA) will provide insight in this field.

Methods

Based on the TCGA dataset, we integrated the expression profiles of IRlncRs and overall survival (OS) in the 611 ccRCC patients. The immune score of each sample was calculated based on the expression level of immune-related genes and used to identify the most meaningful IRlncRs. Survival-related IRlncRs (sIRlncRs) was estimated by calculating the algorithm of difference and COX regression analysis in ccRCC patients. Based on the median immune-related risk score (IRRS) developed from the screened sIRlncRs, the high-risk and low-risk components were distinguished. Functional annotation was detected by gene set enrichment analysis (GSEA) and principal component analysis (PCA), and the immune composition and purity of the tumor was evaluated by microenvironment cell population records. The expression levels of three sIRlncRs were verified in various tissues and cell lines.

Results

A total of 39 IRlncRs were collected by Pearson correlation analyses among immune score and the lncRNA expression. A total of 7 sIRlncRs were significantly associated with the clinical outcomes of ccRCC patients. Three sIRlncRs (ATP1A1-AS1, IL10RB-DT and MELTF-AS1) with the most significant prognostic values were enrolled to build the IRRS model in which the OS of in the high-risk group was shorter than that in the low-risk group. The IRRS was identified as an independent prognosis factor and correlated with the OS. The high-risk group and low-risk group illustrated different distributions in PCA and different immune status in GSEA. Besides, we found the more significant expression in certain ccRCC cell lines and tumor tissues of ccRCC patients compared with the HK-2 and adjacent tissues respectively. Additionally, the expression levels of lncR-MELTF-AS1 and IL10RB-DT were remarkably enhanced along the more advanced T-stages, but the lncR-ATP1A1-AS1 showed the inverse gradient.

Conclusion

Our results demonstrate some sIRlncRs with remark clinical relevance show the latent monitoring and prognosis values for ccRCC patients and may provide new insight in immunological researches and treatment strategies of ccRCC patients.