SNHG10 Promotes Cell Proliferation and Migration in Gastric Cancer by Targeting miR-495-3p/CTNNB1 Axis

The emerging landscape of small nucleolar RNA host gene 10 in cancer mechanistic insights and clinical relevance

Small nucleolar RNA host gene 10 (SNHG10) is a newly recognized long non-coding RNA (lncRNA) with significant implications in cancer biology. Abnormal expression of SNHG10 has been observed in various solid tumors and hematological malignancies. Research conducted in vivo and in vitro has revealed that SNHG10 plays a pivotal role in numerous biological processes, including cell proliferation, apoptosis, invasion and migration, drug resistance, energy metabolism, immune evasion, as well as tumor growth and metastasis. SNHG10 regulates tumor development through several mechanisms, such as competing with microRNA (miRNA) for binding sites, modulating various signaling pathways, influencing transcriptional activity, and affecting epigenetic regulation. The diverse biological functions and intricate mechanisms of SNHG10 highlight its considerable clinical relevance, positioning it as a potential pan-cancer biomarker and therapeutic target. This review aims to summarize the role of SNHG10 in tumorigenesis and cancer progression, clarify the molecular mechanisms at play, and explore its clinical significance in cancer diagnosis and prognosis prediction, along with its therapeutic potential.

Functional role of lncRNAs in gastrointestinal malignancies: the peculiar case of small nucleolar RNA host gene family

Long noncoding RNAs (lncRNAs) play crucial roles in normal physiology and are often de-regulated in disease states such as cancer. Recently, a class of lncRNAs referred to as the small nucleolar RNA host gene (SNHG) family have emerged as important players in tumourigenesis. Here, we discuss new findings describing the role of SNHGs in gastrointestinal tumours and summarize the three main functions by which these lncRNAs promote carcinogenesis, namely: competing with endogenous RNAs, modulating protein function, and regulating epigenetic marking. Furthermore, we discuss how SNHGs participate in different hallmarks of cancer, and how this class of lncRNAs may serve as potential biomarkers in cancer diagnosis and therapy.

The SNHG10-miR-495-3p-PTEN axis is involved in sevoflurane-mediated protective effects in cardiomyocytes against hypoxia/reoxygenation injury

Myocardial infarction (MI) has been considered a leading cause of death worldwide. Relieving ischemia-reperfusion myocardial damage is one of the major roles in treating MI. Sevoflurane postconditioning provides myocardial protection, and this study probes the mechanism of sevoflurane-mediated protective effects. A hypoxia/reoxygenation (H/R) model was constructed in cardiomyocytes, which were pretreated with 2.4% sevoflurane. Alterations in SNHG10, miR-495-3p, and PTEN levels were determined, and gain- or loss-of functional assays were conducted to confirm the role of the SNHG10/miR-495-3p axis, which is potentially regulated by sevoflurane. Cell viability, oxidative stress, and inflammatory reactions were all evaluated. The results indicated that sevoflurane post-conditioning attenuated H/R-induced cardiomyocyte damage and reduced the SHNH10 level. SNHG10 overexpression reversed sevoflurane-mediated protective effects on cardiomyocytes. Moreover, SNHG10 targeted miR-495-3p and restrained its expression, while miR-495-3p targeted PTEN, suppressed PTEN levels, and promoted HIF-1α expression. miR-495-3p overexpression decreased SNHG10-mediated myocardial injury and enhanced HIF-1α levels. However, no additional protection was found when sevoflurane was administered to H/R-exposed cardiomyocytes following treatment with the HIF-1α inhibitor LW6. Overall, sevoflurane protects cardiomyocytes from H/R by modulating the SNHG10-miR-495-3p-PTEN-HIF-1α axis.

The Functions and Mechanisms of Long Non-coding RNA SNHGs in Gastric Cancer

Gastric cancer (GC) is one of the most common malignancies worldwide. Despite significant advancements in surgical and adjuvant treatments, patient prognosis remains unsatisfactory. Long non-coding RNAs (lncRNAs) are a class of RNA molecules that lack protein-coding capacity but can engage in the malignant biological behaviors of tumors through various mechanisms. Among them, small nucleolar host genes (SNHGs) represent a subgroup of lncRNAs. Studies have revealed their involvement not only in gastric cancer cell proliferation, invasion, migration, epithelial- mesenchymal transition (EMT), and apoptosis but also in chemotherapy resistance and tumor stemness. This review comprehensively summarizes the biological functions, molecular mechanisms, and clinical significance of SNHGs in gastric cancer. It provides novel insights into potential biomarkers and therapeutic targets for the exploration of gastric cancer.

A comprehensive insight into the role of small nucleolar RNAs (snoRNAs) and SNHGs in human cancers

Long non-coding RNAs (lncRNAs), which comprise most non-coding RNAs (ncRNAs), have recently become a focus of cancer research. How many functional ncRNAs exist is still a matter of debate. Although insufficient evidence supports that most lncRNAs function as transcriptional by-products, it is widely known that an increasing number of lncRNAs play essential roles in cells. Small nucleolar RNAs (snoRNAs), 60-300 nucleotides in length, have been better studied than long non-coding RNAs (lncRNAs) and are predominantly present in the nucleolus. Most snoRNAs are encoded in introns of protein- and non-protein-coding genes called small nucleolar RNA host genes (SNHGs). In this article, we explore the biology and characteristics of SNHGs and their role in developing human malignancies. In addition, we provide an update on the ability of these snoRNAs to serve as prognostic and diagnostic variables in various forms of cancer.

miR-495-3p as a promising tumor suppressor in human cancers

Noncoding RNAs are a type of cellular RNA not having the ability to translate into proteins. As an important type of ncRNA with a length of about 22 nucleotides (nt), microRNAs were revealed to contribute to regulating the various cellular functions via regulating the protein translation of target genes. Among them, available studies proposed that miR-495-3p is a pivotal player in cancer pathogenesis. These studies showed that the expression level of miR-495-3p decreased in various cancer cells, suggesting its tumor suppressor role in cancer pathogenesis. Long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) are the important regulators of miR-495-3p via sponging it, leading to increased expression levels of its target genes. Moreover, miR-495-3p was shown to have a promising potential to be a prognostic and diagnostic biomarker in cancer. MiR-495-3p also could affect the resistance of cancer cells to chemotherapy agents. Here, we discussed the molecular mechanisms of miR-495-3p in various cancer including breast cancer. In addition, we discussed the miR-495-3p potential as a prognostic and diagnostic biomarker as well as its activity in cancer chemotherapy. Finally, we discussed the current limitations regarding the use of microRNAs in clinics and the future prospects of microRNAs.

A comprehensive insight into the correlation between ncRNAs and the Wnt/β-catenin signalling pathway in gastric cancer pathogenesis

During the past decades, gastric cancer (GC) has emerged as one of the most frequent malignancies with a growing rate of prevalence around the world. Despite considerable advances in therapeutic methods, the prognosis and management of patients with gastric cancer (GC) continue to be poor. As one of the candidate molecular targets in the treatment of many types of cancer, the Wnt/β-catenin pathway includes a family of proteins that have important functions in adult tissue homeostasis and embryonic development. The aberrant regulation of Wnt/β-catenin signaling is strongly correlated with the initiation and development of numerous cancers, including GC. Therefore, Wnt/β-catenin signaling has been identified as one of the main targets for extending therapeutic approaches for GC patients. Non-coding RNAs (ncRNAs), including microRNAs and long ncRNAs, are important components of epigenetic mechanisms in gene regulation. They play vital roles in various molecular and cellular processes and regulate many signaling pathways, such as Wnt/β-catenin pathways. Insights into these regulatory molecules involved in GC development may lead to the identification of potential targets for overcoming the limitations of current therapeutic approaches. Consequently, this review aimed to provide a comprehensive overview of ncRNAs interactions involved in Wnt/β-catenin pathway function in GC with diagnostic and therapeutic perspectives. Video Abstract.

Identification of m6A/m5C/m1A-associated LncRNAs for prognostic assessment and immunotherapy in pancreatic cancer

Methylation of RNA plays an important role in cancer. Classical forms of such modifications include N6-methyladenine (m6A), 5-methylcytosine (m5C), and N1-methyladenine (m1A). Methylation-regulated long non-coding (lnc) RNAs are involved in various biological processes, such as tumor proliferation, apoptosis, immune escape, invasion, and metastasis. Therefore, we performed an analysis of transcriptomic and clinical data of pancreatic cancer samples in The Cancer Genome Atlas (TCGA). Using the co-expression method, we summarized 44 m6A/m5C/m1A-related genes and obtained 218 methylation-associated lncRNAs. Next, with COX regression, we screened 39 lncRNAs that are strongly associated with prognosis and found that their expression differed significantly between normal tissues and pancreatic cancer samples (P < 0.001). We then used the least absolute shrinkage and selection operator (LASSO) to construct a risk model comprising seven lncRNAs. In validation set, the nomogram generated by combining clinical characteristics accurately predicted the survival probability of pancreatic cancer patients at 1, 2, and 3 years after diagnosis (AUC = 0.652, 0.686, and 0.740, respectively). Tumor microenvironment analysis showed that the high-risk group had significantly more resting memory CD4 T cells, M0 macrophages, and activated dendritic cells and fewer naïve B cells, plasma cells, and CD8 T cells than the low-risk group (both P < 0.05). Most immune-checkpoint genes were significantly different between the high- and low-risk groups (P < 0.05). The Tumor Immune Dysfunction and Exclusion score showed that high-risk patients benefited more from treatment with immune checkpoint inhibitors (P < 0.001). Overall survival was also lower in high-risk patients with more tumor mutations than in low-risk patients with fewer mutations (P < 0.001). Finally, we explored the sensitivity of the high- and low-risk groups to seven candidate drugs. Our findings indicated that m6A/m5C/m1A-associated lncRNAs are potentially useful biomarkers for the early diagnosis and estimating the prognosis of, and ascertaining the responses to immunotherapy in, patients with pancreatic cancer.

Knockdown circZNF131 Inhibits Cell Progression and Glycolysis in Gastric Cancer Through miR-186-5p/PFKFB2 Axis

Gastric cancer (GC) is a prevalent and heterogeneous malignancy in the digestive system. Increasing studies have suggested that circular RNAs are implicated in GC pathogenesis. This study aimed to explore the biological role and underlying mechanism of circRNA zinc finger protein 131 (circZNF131) in GC. The expression pattern of circZNF131, microRNA-186-5p (miR-186-5p), and 6-phosphofructo-2-kinase/fructose-2, 6-bisphosphatase 2 (PFKFB2) mRNA in GC tissues and cells was detected by quantitative real-time polymerase chain reaction. The stability of circZNF131 was verified using ribonuclease R assay. Functional experiments were performed by colony formation assay for cloning ability analysis, transwell assay and wounding healing assay for cell metastasis, and flow cytometry for cell apoptosis. Glycolysis metabolism was investigated by determining the levels of glucose uptake and lactate production. The protein detection of apoptosis- or glycolysis-associated markers, PFKFB2, and Ki-67 was implemented by western blot or immunohistochemistry. Dual-luciferase reporter assay was conducted to identify the interaction between miR-186-5p and circZNF131 or PFKFB2. The role of circZNF131 on tumor growth in nude mice was investigated via xenograft tumor assay. Expression analysis indicated that circZNF131 was upregulated in GC tissues and cells in a stable structure. Functional analyses showed that circZNF131 knockdown suppressed GC cell colony formation ability, migration, invasion and glycolysis metabolism, and induced cell apoptosis. Mechanically, miR-186-5p was a target of circZNF131, and miR-186-5p could bind to PFKFB2. Rescue experiments presented that miR-186-5p inhibition reversed the effects of circZNF131 knockdown on GC cell growth and glycolysis, and PFKFB2 overexpression abolished the impacts of miR-186-5p restoration on GC cell progression. Moreover, circZNF131 could positively modulate PFKFB2 expression via sponging miR-186-5p. In vivo, circZNF131 knockdown hindered GC tumor growth by regulating the miR-186-5p/PFKFB2 axis. circZNF131 could exert an oncogenic role in GC malignant development through the miR-186-5p/PFKFB2 axis, which might provide novel targets for GC treatment.

Pyroptosis-related lncRNA pairs to estimate the molecular features and prognostic outcomes of pancreatic ductal adenocarcinoma

Pyroptosis is a form of programmed cell death associated with inflammatory alterations. However, the intrinsic mechanisms and underlying correlation of pyroptosis-related lncRNAs (PRLs) in pancreatic ductal adenocarcinoma (PDAC) remain unclear. The objective of the current research was to identify pyroptosis-related lncRNAs and a prognostic model to predict the prognosis of patients. We extracted pyroptosis-related lncRNAs to construct a risk model and validated them at Fudan University Shanghai Cancer Center. Crosstalk between lncRNA SNHG10 and GSDMD was found to regulate pyroptosis levels. A new algorithm was used to establish a 0 or 1 PRL pair matrix and prognostic model. Six pyroptosis-related lncRNA pairs were identified and utilized to construct a risk model. The low-risk groups exhibited better prognoses than the high-risk groups. The area under the curve (AUC) indicated extremely high accuracy, reaching 0.810 at 1 year, 0.850 at 2 years, and 0.850 at 3 years in the training set. Patients with different risk scores exhibited distinct metabolic, inflammatory, and immune microenvironments as well as tumor mutation landscapes. Additionally, 9 commonly used chemotherapeutic drugs exhibited different sensitivities between the high- and low-risk groups. To conclude, we propose that pyroptosis exhibits a close correlation with PDAC. Our risk model based on PRL pairs may be beneficial for the accurate estimation of prognostic outcomes, the immune microenvironment, and drug sensitivity, bringing therapeutic hope for patients with PDAC.

NcRNA-mediated upregulation of CAMK2N1 is associated with poor prognosis and tumor immune infiltration of gastric cancer

Gastric cancer (GC) is still notorious for its poor prognosis and aggressive characteristics. Though great developments have been made in diagnosis and therapy for GC, the prognosis of patient is still perishing. In this study, differentially expressed genes (DEGs) in GC were first screened using three Gene Expression Omnibus (GEO) datasets (GSE13911, GSE29998, and GSE26899). Second, The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) data were used to validate expression of these DEGs and perform survival analysis. We selected seven candidate genes (CAMK2N1, OLFML2B, AKR7A3, CYP4X1, FMO5, MT1H, and MT1X) to carry out the next analysis. To construct the ceRNA network, we screened the most potential upstream ncRNAs of the candidate genes. A series of bioinformatics analyses, including expression analysis, correlation analysis, and survival analysis, revealed that the SNHG10–hsa-miR-378a-3p might be the most potential regulatory axis in GC. Then, the expression of CAMK2N1, miR-378a-3p, and SNHG10 was verified in GC cell lines (GES-1, MGC-803, BGC-823, HGC-27, MKN-45, and AGS) by qRT-PCR and Western blotting. We found that SNHG10 and CAMK2N1 were highly expressed in gastric cancer lines, and the miR-378a-3p was lowly expressed in BGC-823, HGC-27, and MKN-45. Furthermore, CAMK2N1 levels were significantly negatively associated with tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression. In summary, our results suggest that the ncRNA-mediated high expression of CAMK2N1 is associated with poor prognosis and tumor immune infiltration of GC.

Identification of an autophagy-related 12-lncRNA signature and evaluation of NFYC-AS1 as a pro-cancer factor in lung adenocarcinoma

Objective: To develop an autophagy-related lncRNA-based risk signature and corresponding nomogram to predict overall survival (OS) for LUAD patients and investigate the possible meaning of screened factors.

Methods: Differentially expressed lncRNAs and autophagy genes were screened between normal and LUAD tumor samples from the TCGA LUAD dataset. Univariate and multivariate Cox regression analyses were performed to construct the lncRNA-based risk signature and nomogram incorporating clinical information. Then, the accuracy and sensitivity were confirmed by the AUC of ROC curves in both training and validation cohorts. qPCR, immunoblot, shRNA, and ectopic expression were used to verify the positive regulation of NFYC-AS1 on BIRC6. CCK-8, immunofluorescence, and flow cytometry were used to confirm the influence of NFYC-AS1 on cell proliferation, autophagy, and apoptosis via BIRC6.

Results: A 12-lncRNA risk signature and a nomogram combining related clinical information were constructed. Furthermore, the abnormal increase of NFYC-AS1 may promote LUAD progression through the autophagy-related gene BIRC6.

Conclusion: 12-lncRNA signature may function as a predictive marker for LUAD patients, and NFYC-AS1 along with BIRC6 may function as carcinogenic factors in a combinatorial manner.

LncRNA PCGEM1 promotes colorectal cancer cell proliferation and migration in positive feedback loop through PCGEM1/miR-433-3p/CTCF axis

BACKGROUND AND OBJECTIVES

Prostate cancer gene expression marker 1 (PCGEM1) has been identified as an oncogenic long non-coding RNA (lncRNA) in diverse cancers, but it has never been linked with colorectal cancer (CRC). Former studies have shown the mutual regulation between lncRNAs and transcription factors (TFs) in cancer. CCCTC binding factor (CTCF) has been reported to transcriptionally activate lncRNAs in cancers. We predicted the binding of CTCF on PCGEM1 promoter through UCSC (https://genome.ucsc.edu/), but their relation has not been studied. We aimed to investigate whether and how PCGEM1 functioned in CRC cells and the interaction between PCGEM1 and CTCF.

METHODS AND RESULTS

The impacts of PCGEM1 and CTCF inhibition on CRC cells were verified through loss-of-function experiments. Mechanism experiments were used to prove the binding between CTCF and PCGEM1 in CRC progression. PCGEM1 possessed a high expression level in CRC cells as well as tumors. CTCF transcriptionally activated PCGEM1 expression. Knockdown of PCGEM1 or CTCF impeded proliferation and migration and drove apoptosis of CRC cells. Moreover, PCGEM1 bound miR-433-3p to prevent miR-433-3p from targeting CTCF.

CONCLUSION

We first revealed PCGEM1/miR-433-3p/CTCF positive feedback loop as an oncogenic axis in CRC cells, which potentially provides new clues for the advancement of CRC treatment.

Identification of Two Exosomal miRNAs in Circulating Blood of Cancer Patients by Using Integrative Transcriptome and Network Analysis

Exosomes carry molecules of great biological and clinical interest, such as miRNAs. The contents of exosomes vary between healthy controls and cancer patients. Therefore, miRNAs and other molecules transported in exosomes are considered a potential source of diagnostic and prognostic biomarkers in cancer. Many miRNAs have been detected in recent years. Consequently, a substantial amount of miRNA-related data comparing patients and healthy individuals is available, which contributes to a better understanding of the initiation, development, malignancy, and metastasis of cancer using non-invasive sampling procedures. However, a re-analysis of available ncRNA data is rare. This study used available data about miRNAs in exosomes comparing healthy individuals and cancer patients to identify possible global changes related to the presence of cancer. A robust transcriptomic analysis identified two common miRNAs (miR-495-3p and miR-543) deregulated in five cancer datasets. They had already been implicated in different cancers but not reported in exosomes circulating in blood. The study also examined their target genes and the implications of these genes for functional processes.

EnANNDeep: An Ensemble-based lncRNA-protein Interaction Prediction Framework with Adaptive k-Nearest Neighbor Classifier and Deep Models

lncRNA-protein interactions (LPIs) prediction can deepen the understanding of many important biological processes. Artificial intelligence methods have reported many possible LPIs. However, most computational techniques were evaluated mainly on one dataset, which may produce prediction bias. More importantly, they were validated only under cross validation on lncRNA-protein pairs, and did not consider the performance under cross validations on lncRNAs and proteins, thus fail to search related proteins/lncRNAs for a new lncRNA/protein. Under an ensemble learning framework (EnANNDeep) composed of adaptive k-nearest neighbor classifier and Deep models, this study focuses on systematically finding underlying linkages between lncRNAs and proteins. First, five LPI-related datasets are arranged. Second, multiple source features are integrated to depict an lncRNA-protein pair. Third, adaptive k-nearest neighbor classifier, deep neural network, and deep forest are designed to score unknown lncRNA-protein pairs, respectively. Finally, interaction probabilities from the three predictors are integrated based on a soft voting technique. In comparing to five classical LPI identification models (SFPEL, PMDKN, CatBoost, PLIPCOM, and LPI-SKF) under fivefold cross validations on lncRNAs, proteins, and LPIs, EnANNDeep computes the best average AUCs of 0.8660, 0.8775, and 0.9166, respectively, and the best average AUPRs of 0.8545, 0.8595, and 0.9054, respectively, indicating its superior LPI prediction ability. Case study analyses indicate that SNHG10 may have dense linkage with Q15717. In the ensemble framework, adaptive k-nearest neighbor classifier can separately pick the most appropriate k for each query lncRNA-protein pair. More importantly, deep models including deep neural network and deep forest can effectively learn the representative features of lncRNAs and proteins.

Bioinformatic Analyses of the Ferroptosis-Related lncRNAs Signature for Ovarian Cancer

Both ferroptosis and lncRNAs are significant for ovarian cancer (OC). Whereas, the study of ferroptosis-related lncRNAs (FRLs) still few in ovarian cancer. We first constructed an FRL-signature for patients with OC in the study. A total of 548 FRLs were identified for univariate Cox regression analysis, and 21 FRLs with significant prognosis were identified. The prognostic characteristics of nine FRLs was constructed and validated, showing opposite prognosis in two subgroups based on risk scores. The multivariate Cox regression analysis and nomogram further verified the prognostic value of the risk model. By calculating ferroptosis score through ssGSEA, we found that patients with higher risk scores exhibited higher ferroptosis scores, and high ferroptosis score was a risk factor. There were 40 microenvironment cells with significant differences in the two groups, and the difference of Stromal score between the two groups was statistically significant. Six immune checkpoint genes were expressed at different levels in the two groups. In addition, five m6A regulators (FMR1, HNRNPC, METTL16, METTL3, and METTL5) were higher expressed in the low-risk group. GSEA revealed that the risk model was associated with tumor-related pathways and immune-associated pathway. We compared the sensitivity of chemotherapy drugs between the two risk groups. We also explored the co-expression, ceRNA relation, cis and trans interaction of ferroptosis-related genes and lncRNAs, providing a new idea for the regulatory mechanisms of FRLs. Moreover, the nine FRLs were selected for detecting their expression levels in OC cells and tissues.

Knockdown of small nucleolar RNA host gene 10 (SNHG10) alleviates the injury of human neuroblastoma cells via the miR-1277-5p/insulin substrate receptor 2 axis

Parkinson's disease is a common neurodegenerative disease with a complex physio-pathology. So far, there is no effective medical strategies to prevent the progression of Parkinson's disease. Understanding the mechanisms underlying the progression of Parkinson's disease could provide insights into the formulation of novel preventative or treatment strategies. Small nucleolar RNA host gene 10 (SNHG10) is a lncRNA which has been implicated in the development of many cancers. However, its potential role in Parkinson's disease remains unknown. In this study, we found that SNHG10 was upregulated while miR-1277-5p was downregulated in the Parkinson's disease cell model of 1-Methyl-4-phenyl-pyridine ion (MPP+) induced SH-SY5Y cells. We further revealed that SNHG10 sponged miR-1277-5p to negatively regulate its expression, and miR-1277-5p could bind to the 3'UTR of insulin substrate receptor 2 (IRS2) mRNA to suppress its expression. These data suggest that SNHG10 regulates IRS2 through interacting with miR-1277-5p in the cell model of Parkinson's disease. Through a series of molecular experiments and functional assays, we demonstrated that downregulating SNHG10 in the cell model of Parkinson's disease attenuated the cell injury by reducing the expression of IRS2. Meanwhile, inhibiting miR-1277-5p or overexpressing IRS2 could partially reverse the effect of SNHG10 knockdown. In summary, our data indicate that knockdown of SNHG10 mitigates MPP+ induced damage in SH-SY5Y cells via the miR-1277-5p/IRS2 axis.

Development and Validation of Lactate Metabolism-Related lncRNA Signature as a Prognostic Model for Lung Adenocarcinoma

BACKGROUND

Lung cancer has been a prominent research focus in recent years due to its role in cancer-related fatalities globally, with lung adenocarcinoma (LUAD) being the most prevalent histological form. Nonetheless, no signature of lactate metabolism-related long non-coding RNAs (LMR-lncRNAs) has been developed for patients with LUAD. Accordingly, we aimed to develop a unique LMR-lncRNA signature to determine the prognosis of patients with LUAD.

METHOD

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to derive the lncRNA expression patterns. Identification of LMR-lncRNAs was accomplished by analyzing the co-expression patterns between lncRNAs and LMR genes. Subsequently, the association between lncRNA levels and survival outcomes was determined to develop an effective signature. In the TCGA cohort, Cox regression was enlisted to build an innovative signature consisting of three LMR-lncRNAs, which was validated in the GEO validation cohort. GSEA and immune infiltration analysis were conducted to investigate the functional annotation of the signature and the function of each type of immune cell.

RESULTS

Fourteen differentially expressed LMR-lncRNAs were strongly correlated with the prognosis of patients with LUAD and collectively formed a new LMR-lncRNA signature. The patients could be categorized into two cohorts based on their LMR-lncRNA signatures: a low-risk and high-risk group. The overall survival of patients with LUAD in the high-risk group was considerably lower than those in the low-risk group. Using Cox regression, this signature was shown to have substantial potential as an independent prognostic factor, which was further confirmed in the GEO cohort. Moreover, the signature could anticipate survival across different groups based on stage, age, and gender, among other variables. This signature also correlated with immune cell infiltration (including B cells, neutrophils, CD4⁺ T cells, CD8⁺ T cells, etc.) as well as the immune checkpoint blockade target CTLA-4.

CONCLUSION

We developed and verified a new LMR-lncRNA signature useful for anticipating the survival of patients with LUAD. This signature could give potentially critical insight for immunotherapy interventions in patients with LUAD.

N6-Methyladenosine-Related Long Non-coding RNA Signature Associated With Prognosis and Immunotherapeutic Efficacy of Clear-Cell Renal Cell Carcinoma

Increasing evidence suggests that N6-methyladenosine (m6A) and long non-coding RNAs (lncRNAs) play important roles in cancer progression and immunotherapeutic efficacy in clear-cell renal cell carcinoma (ccRCC). In this study, we conducted a comprehensive ccRCC RNA-seq analysis using The Cancer Genome Atlas data to establish an m6A-related lncRNA prognostic signature (m6A-RLPS) for ccRCC. Forty-four prognostic m6A-related lncRNAs (m6A-RLs) were screened using Pearson correlation analysis (|R| > 0.7, p < 0.001) and univariable Cox regression analysis (p < 0.01). Using consensus clustering, the patients were divided into two clusters with different overall survival (OS) rates and immune status according to the differential expression of the lncRNAs. Gene set enrichment analysis corroborated that the clusters were enriched in immune-related activities. Twelve prognostic m6A-RLs were selected and used to construct the m6A-RLPS through least absolute shrinkage and selection operator Cox regression. We validated the differential expression of the 12 lncRNAs between tumor and non-cancerous samples, and the expression levels of four m6A-RLs were further validated using Gene Expression Omnibus data and Lnc2Cancer 3.0 database. The m6A-RLPS was verified to be an independent and robust predictor of ccRCC prognosis using univariable and multivariable Cox regression analyses. A nomogram based on age, tumor grade, clinical stage, and m6A-RLPS was generated and showed high accuracy and reliability at predicting the OS of patients with ccRCC. The prognostic signature was found to be strongly correlated to tumor-infiltrating immune cells and immune checkpoint expression. In conclusion, we established a novel m6A-RLPS with a favorable prognostic value for patients with ccRCC. The 12 m6A-RLs included in the signature may provide new insights into the tumorigenesis and allow the prediction of the treatment response of ccRCC.

SNHG10 Is a Prognostic Biomarker Correlated With Immune Infiltrates in Prostate Cancer

SNHG10 is a long non-coding RNA (lncRNA) found to be overexpressed in multiple human cancers including prostate cancer (PC). However, the underlying mechanisms of SNHG10 driving the progression of PC remains unclear. In this study, we investigated the role of SNHG10 in PC and found that SNHG10 expression was significantly increased in datasets extracted from The Cancer Genome Atlas. Increased expression of SNHG10 was related to advanced clinical parameters. Receiver operating curve analysis revealed the significant diagnostic ability of SNHG10 (AUC = 0.805). In addition, immune infiltration analysis, and GSEA showed that SNHG10 expression was correlated with oxidative phosphorylation and immune infiltrated cells. Finally, we determined that SNHG10 regulated cell proliferation, migration, and invasion of PC in vitro. In conclusion, our data demonstrated that SNHG10 was correlated with progression and immune infiltration, and could serve as a prognostic biomarker for PC.

Integrated analysis on the N6-methyladenosine-related long noncoding RNAs prognostic signature, immune checkpoints, and immune cell infiltration in clear cell renal cell carcinoma

Background

Patients with advanced clear cell renal cell carcinoma (ccRCC) have a poor prognosis and lack effective prognostic biomarkers. N6‐methyladenosine‐related lncRNAs (m6A‐related long noncoding RNAs [lncRNAs]) have been confirmed to be associated with the development of multiple tumors, but its role in ccRCC is not clear.

Methods

Gene expression data and clinical information of ccRCC patients were extracted from The Cancer Genome Atlas Database. The prognostic m6A‐related lncRNAs were obtained by Pearson's correlation analysis and univariate Cox regression analysis. Afterward, the cluster classification and its correlation with prognosis, clinical characteristics, and immunity were analyzed. LASSO regression was used to establish the prognostic risk model. The predictive performance of the prognostic model was evaluated and validated by survival analysis and receiver operating characteristic curve analysis, et al. The expression of immune checkpoints and immune cell infiltration in patients with different risks were systematically analyzed.

Results

A total of 27 prognostic m6A‐related lncRNAs were identified. These m6A‐related lncRNAs were differentially expressed between tumor and normal tissues. Among them, 24 high‐risk m6A‐related lncRNAs were overexpressed in Cluster 2 and correlated with poor prognosis, low stromal score, high expression of immune checkpoints, and immunosuppressive cells infiltration. Based upon, a prognostic risk model composed of seven m6A‐related lncRNAs was constructed. After a series of analyses, it was proved that this model had good sensitivity and specificity, and could predict the prognosis of patients with different clinical stratification. The expression of PD‐1, PD‐L1, CTLA‐4, LAG‐3, TIM‐3, and TIGIT were significantly increased in the high‐risk patients, and there was a correlation between the risk score and immune cell infiltration.

Conclusions

The seven m6A‐related lncRNAs prognostic risk signature showed reliable prognostic predictive power for ccRCC and was associated with the expression of immune checkpoints and immune cell infiltration. This seven m6A‐related lncRNAs signature will be helpful in managing ccRCC and guiding individualized immunotherapy.

SUMOylation of IGF2BP2 promotes vasculogenic mimicry of glioma via regulating OIP5-AS1/miR-495-3p axis

Rationale: Glioma is the most common primary malignant tumor of human central nervous system, and its rich vascular characteristics make anti-angiogenic therapy become a therapeutic hotspot. However, the existence of glioma VM makes the anti-angiogenic therapy ineffective. SUMOylation is a post-translational modification that affects cell tumorigenicity by regulating the expression and activity of substrate proteins.

Methods: The binding and modification of IGF2BP2 and SUMO1 were identified using Ni²⁺-NTA agarose bead pull-down assays, CO-IP and western blot; and in vitro SUMOylation assays combined with immunoprecipitation and immunofluorescence staining were performed to explore the detail affects and regulations of the SUMOylation on IGF2BP2. RT-PCR and western blot were used to detect the expression levels of IGF2BP2, OIP5-AS1, and miR-495-3p in glioma tissues and cell lines. CCK-8 assays, cell transwell assays, and three-dimensional cell culture methods were used for evaluating the function of IGF2BP2, OIP5-AS1, miR-495-3p, HIF1A and MMP14 in biological behaviors of glioma cells. Meantime, RIP and luciferase reporter assays were used for inquiring into the interactions among IGF2BP2, OIP5-AS1, miR-495-3p, HIF1A and MMP14. Eventually, the tumor xenografts in nude mice further as certained the effects of IGF2BP2 SUMOylation on glioma cells.

Results: This study proved that IGF2BP2 mainly binds to SUMO1 and was SUMOylated at the lysine residues K497, K505 and K509 sites, which can be reduced by SENP1. SUMOylation increased IGF2BP2 protein expression and blocked its degradation through ubiquitin-proteasome pathway, thereby increasing its stability. The expressions of IGF2BP2 and OIP5-AS1 were up-regulated and the expression of miR-495-3p was down-regulated in both glioma tissues and cells. IGF2BP2 enhances the stability of OIP5-AS1, thereby increasing the binding of OIP5-AS1 to miR-495-3p, weakening the binding of miR-495-3p to the 3'UTR of HIF1A and MMP14 mRNA, and ultimately promoting the formation of VM in glioma.

Conclusions: This study first revealed that SUMOylation of IGF2BP2 regulated OIP5-AS1/miR-495-3p axis to promote VM formation in glioma cells and xenografts growth in nude mice, providing a new idea for molecular targeted therapy of glioma.

Long non-coding RNA SNHG14 aggravates LPS-induced acute kidney injury through regulating miR-495-3p/HIPK1

Acute kidney injury (AKI) is a complex syndrome with an abrupt decrease of kidney function, which is associated with high morbidity and mortality. Sepsis is the common cause of AKI. Mounting evidence has demonstrated that long non-coding RNAs (lncRNAs) play critical roles in the development and progression of sepsis-induced AKI. In this study, we aimed to illustrate the function and mechanism of lncRNA SNHG14 in lipopolysaccharide (LPS)-induced AKI. We found that SNHG14 was highly expressed in the plasma of sepsis patients with AKI. SNHG14 inhibited cell proliferation and autophagy and promoted cell apoptosis and inflammatory cytokine production in LPS-stimulated HK-2 cells. Functionally, SNHG14 acted as a competing endogenous RNA (ceRNA) to negatively regulate miR-495-3p expression in HK-2 cells. Furthermore, we identified that HIPK1 is a direct target of miR-495-3p in HK-2 cells. We also revealed that the SNHG14/miR-495-3p/HIPK1 interaction network regulated HK-2 cell proliferation, apoptosis, autophagy, and inflammatory cytokine production upon LPS stimulation. In addition, we demonstrated that the SNHG14/miR-495-3p/HIPK1 interaction network regulated the production of inflammatory cytokines (TNF-α, IL-6, and IL-1β) via modulating NF-κB/p65 signaling in LPS-challenged HK-2 cells. In conclusion, our findings suggested a novel therapeutic axis of SNHG14/miR-495-3p/HIPK1 to treat sepsis-induced AKI.

ETS1-activated SNHG10 exerts oncogenic functions in glioma via targeting miR-532-3p/FBXL19 axis

Background

In past few years, long non-coding RNAs (lncRNAs) have been reported to play regulatory roles during cancer progression. LncRNA SNHG10 has been explored in several sorts of cancers. However, its detailed role and mechanism are still not well understood in glioma.

Methods

Expression levels of genes were evaluated by RT-qPCR. EdU, TUNEL, sphere formation, wound healing and transwell assays appraised the effect of SNHG10 on glioma cellular processes. The interaction between molecules was examined by ChIP, RIP, RNA pull down and luciferase reporter assays.

Results

High level of SNHG10 was detected in glioma cells. Functional assay confirmed that SNHG10 promoted the proliferation, migration, invasion and stemness of glioma cells. Moreover, miR-532-3p was validated to bind with SNHG10 and expressed at a low level in glioma cells. Importantly, miR-532-3p exerted inhibitory functions in glioma. Furthermore, it was found that FBXL19 targeted by miR-532-3p facilitated cell growth and stemness in glioma, and that SNHG10 worked in glioma by increasing FBXL19 expression through sequestering miR-532-3p. More importantly, ETS1 promoted the transcription of SNHG10 and it mediated contribution to the malignant behaviors of glioma cells by SNHG10/miR-532-3p/FBXL19 signaling.

Conclusion

SNHG10 was transcriptionally activated by ETS1 and played an oncogenic role in glioma by sponging miR-532-3p and up-regulating FBXL19.