Linc01094 Accelerates the Growth and Metastatic-Related Traits of Glioblastoma by Sponging miR-126-5p

Construction of prognostic markers for gastric cancer and comprehensive analysis of pyroptosis-related long non-coding RNAs

BACKGROUND

China's most frequent malignancy is gastric cancer (GC), which has a very poor survival rate, and the survival rate for patients with advanced GC is dismal. Pyroptosis has been connected to the genesis and development of cancer. The function of pyroptosis-related long non-coding RNAs (PRLs) in GC, on the other hand, remains uncertain.

AIM

To explore the construction and comprehensive analysis of the prognostic characteristics of long non-coding RNA (lncRNA) related to pyroptosis in GC patients.

METHODS

The TCGA database provided us with 352 stomach adenocarcinoma samples, and we obtained 28 pyroptotic genes from the Reactome database. We examined the correlation between lncRNAs and pyroptosis using the Pearson correlation coefficient. Prognosis-related PRLs were identified through univariate Cox analysis. A predictive signature was constructed using stepwise Cox regression analysis, and its reliability and independence were assessed. To facilitate clinical application, a nomogram was created based on this signature. we analyzed differences in immune cell infiltration, immune function, and checkpoints between the high-risk group (HRG) and low-risk group (LRG).

RESULTS

Five hundred and twenty-three PRLs were screened from all lncRNAs (absolute correlation coefficient > 0.4, P < 0.05). Nine PRLs were included in the risk prediction signature that was created through stepwise Cox regression analysis. We determined the risk score for GC patients and employed the median value as the dividing line between HRG and LRG. The ability of the risk signature to predict the overall survival (OS) of GC is demonstrated by the Kaplan-Meier analysis, risk curve, receiver operating characteristic curve, and decision curve analysis curve. The risk signature was shown to be an independent prognostic factor for OS in both univariate and multivariate Cox regression analyses. HRG showed a more efficient local immune response or modulation compared to LRG, as indicated by the predicted signal pathway analysis and examination of immune cell infiltration, function, and checkpoints (P < 0.05).

CONCLUSION

In general, we have created a brand-new prognostic signature using PRLs, which may provide ideas for immunotherapy in patients with GC.

TGF-β1-Induced LINC01094 promotes epithelial-mesenchymal transition in hepatocellular carcinoma through the miR-122-5p/TGFBR2-SAMD2-SMAD3 Axis

Hepatocellular carcinoma (HCC) is a common malignancy with a poor prognosis. It has been proven that long non-coding RNAs (lncRNAs) play an essential role in regulating HCC progression. However, the involvement of LINC01094 in regulating epithelial-mesenchymal transition (EMT) in HCC remains unclear. LINC01094 expression in HCC patients was retrieved from the Cancer Genome Atlas database. Overexpressing and downregulating LINC01094 were conducted to investigate its biological functions using Hep3B, SNU-387, and HuH-7 cells. Western blotting and morphological observation were performed to study the EMT in HCC cells. Transwell assay was adopted to determine the migration and invasion of HCC cells. The underlying mechanism of competitive endogenous RNAs (ceRNAs) was investigated using bioinformatics analysis, quantitative reverse-transcription polymerase chain reaction, and rescue experiments. Elevated LINC01094 expression was observed in HCC and associated with a poor prognosis. Knockdown of LINC01094 expression in SNU-387 and HuH-7 cells could inhibit migration, invasion, and EMT markers. Overexpression of LINC01094 indicated that LINC01094 promoted EMT via the TGF-β/SMAD signaling pathway. The bioinformatics analysis revealed that miR-122-5p was a target of LINC01094. The miRWalk database analysis showed that TGFBR2, SMAD2, and SMAD3 were downstream targets of miR-122-5p. Mechanically, LINC01094 acted as a ceRNA that facilitated HCC metastasis by sponging miR-122-5p to regulate the expression of TGFBR2, SMAD2, and SMAD3. Further, TGF-β1 could enhance the expression of LINC01094, forming a positive feedback loop. TGF-β1-induced LINC01094 expression promotes HCC cell migration and invasion by targeting the miR-122-5p/TGFBR2-SMAD2-SMAD3 axis. LINC01094 may be a potential prognostic biomarker and therapeutic target for HCC metastasis.

Long noncoding RNA UNC5B-AS1 suppresses cell proliferation by sponging miR-24-3p in glioblastoma multiforme

BACKGROUND

Glioblastoma multiforme (GBM) is the most common primary CNS tumor, characterized by high mortality and heterogeneity. However, the related lncRNA signatures and their target microRNA (miRNA) for GBM are still mostly unknown. Therefore, it is critical that we discover lncRNA markers in GBM and their biological activities.

MATERIALS AND METHODS

GBM-related RNA-seq data were obtained from the Cancer Genome Atlas (TCGA) database. The "edger" R package was used for differently expressed lncRNAs (DELs) identification. Then, we forecasted prospective miRNAs that might bind to lncRNAs by Cytoscape software. Survival analysis of those miRNAs was examined by the starBase database, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the miRNAs' target genes was conducted by the Gene Set Enrichment Analysis (GSEA) database and R software. Moreover, the proliferative ability of unc-5 netrin receptor B antisense RNA 1 (UNC5B-AS1) cells was evaluated by Cell Counting Kit-8 (CCK-8) analysis. Mechanistically, the regulatory interaction between UNC5B-AS1 and miRNA in GBM biological processes was studied using CCK-8 analysis.

RESULTS

Our results indicated that overexpression of UNC5B-AS1 has been shown to suppress GBM cell growth. Mechanistically, miR-24-3p in GBM was able to alleviate the anti-oncogenic effects of UNC5B-AS1 on cell proliferation.

CONCLUSION

The discovery of the novel UNC5B-AS1-miR-24-3p network suggests possible lncRNA and miRNA roles in the development of GBM, which may have significant ramifications for the analysis of clinical prognosis and the development of GBM medications.

RNA-binding MSI proteins and their related cancers: A medicinal chemistry perspective

Musashi1 and Musashi2 are RNA-binding proteins originally found in drosophila, in which they play a crucial developmental role. These proteins are pivotal in the maintenance and differentiation of stem cells in other organisms. Research has confirmed that the Musashi proteins are highly involved in cell signal-transduction pathways such as Notch and TGF-β. These signaling pathways are related to the induction and development of cancers, such as breast cancer, leukemia, hepatoma and liver cancer. In this review we focus on how Musashi proteins interact with molecules in different signaling pathways in various cancers and how they affect the physiological functions of these pathways. We further illustrate the status quo of Musashi proteins-targeted therapies and predict the target RNA regions that Musashi proteins interact with, in the hope of exploring the prospect of the design of Musashi protein-targeted medicines.

Comparison of Oncogenes, Tumor Suppressors, and MicroRNAs Between Schizophrenia and Glioma: The Balance of Power

The risk of cancer in schizophrenia has been controversial. Confounders of the issue are cigarette smoking in schizophrenia, and antiproliferative effects of antipsychotic medications. The author has previously suggested comparison of a specific cancer like glioma to schizophrenia might help determine a more accurate relationship between cancer and schizophrenia. To accomplish this goal, the author performed three comparisons of data; the first a comparison of conventional tumor suppressors and oncogenes between schizophrenia and cancer including glioma. This comparison determined schizophrenia has both tumor-suppressive and tumor-promoting characteristics. A second, larger comparison between brain-expressed microRNAs in schizophrenia with their expression in glioma was then performed. This identified a core carcinogenic group of miRNAs in schizophrenia offset by a larger group of tumor-suppressive miRNAs. This proposed "balance of power" between oncogenes and tumor suppressors could cause neuroinflammation. This was assessed by a third comparison between schizophrenia, glioma and inflammation in asbestos-related lung cancer and mesothelioma (ALRCM). This revealed that schizophrenia shares more oncogenic similarity to ALRCM than glioma.

LncRNA LINC01094 Promotes Cells Proliferation and Metastasis through the PTEN/AKT Pathway by Targeting AZGP1 in Gastric Cancer

Long noncoding RNAs (lncRNAs) were recently reported to play an essential role in multiple cancer types. Herein, through next-generation sequencing, we screened metastasis-driving molecules by using tissues from early-stage gastric cancer (GC) patients with lymph node metastasis, and we identified a lncRNA LINC01094, which was associated with the metastasis of GC. According to the clinical data from the TCGA, GSE15459, and GSE62254 cohorts, the high expression of LINC01094 was associated with an unfavorable prognosis. Moreover, 106 clinical GC and paired normal samples were collected, and the qRT-PCR results showed that the high expression of LINC01094 was associated with high T and N stages and a poor prognosis. We found that LINC01094 promotes the proliferation and metastasis of GC in vitro and in vivo. AZGP1 was found as the protein-binding partner of LINC01094 by using RNA pulldown and RNA-binding protein immunoprecipitation (RIP) assays. LINC01094 antagonizes the function of AZGP1, downregulates the expression of PTEN, and further upregulates the AKT pathway. Collectively, our results suggested that LINC01094 might predict the prognosis of GC patients and become the therapy target for GC.

An immune infiltration-related long non-coding RNAs signature predicts prognosis for hepatocellular carcinoma

Background: With a high incidence and dismal survival rate, hepatocellular carcinoma (HCC) tops the list of the world's most frequent malignant tumors. Immunotherapy is a new approach to cancer treatment, and its effect on prolonging overall survival (OS) varies from patient to patient. For a more effective prognosis and treatment of HCC, we are committed to identifying immune infiltration-related long non-coding RNAs (IIRLs) with prognostic value in hepatocellular carcinoma. Methods: In our study, we calculated immune scores of 369 hepatocellular carcinoma samples from the Cancer Genome Atlas (TCGA) database by using an estimation algorithm, and obtained long non-coding RNAs (lncRNAs) associated with immune infiltration by using Weighted Gene Co-expression Network analysis (WGCNA). For training cohort, univariate Cox, least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analysis were used to determine prognostic IIRLs, we established a prognostic IIRLs signature. By testing cohort and entire cohort, we confirmed that the signature is practical. The prognosis of people with different clinicopathological stages and risk scores were predicted by the nomogram we constructed. In addition, Immune cell infiltration analysis and prediction of therapeutic drugs were performed. Results: 93 IIRLs were obtained by WGCNA. Furthermore, the prognostic value of these IIRLs were evaluated by using univariate Cox, Lasso and multivariate Cox analysis. Four IIRLs were used to create a signature with a prognosis. Time-related receiver operating characteristic (ROC) curve revealed that this model had an acceptable prognostic value for HCC patients. By using univariate and multivariate Cox regression analysis, this risk score has been shown to be an independent prognostic factor for HCC. The nomogram we made showed good predictions. Except for that, the treatment with immune checkpoint inhibitors (ICI) was likely to be more effective for low-risk patients. Conclusion: Based on four IIRLs, a prognostic signature was created in this research showed good accuracy in predicting OS. This study also provided valuable references for Immunotherapy of hepatocellular carcinoma.

LINC01094/SPI1/CCL7 Axis Promotes Macrophage Accumulation in Lung Adenocarcinoma and Tumor Cell Dissemination

Objective

Infiltration of tumor-associated macrophages is closely linked to the malignant development of human cancers. This research studies the function of C-C motif chemokine ligand 7 (CCL7) in the macrophage accumulation in lung adenocarcinoma (LUAD) and the underpinning mechanism.

Methods

The expression profile of CCL7 in LUAD and its correlations with patient's prognosis and macrophage infiltration were predicted via bioinformatics systems. Artificial up- or downregulation of CCL7 was induced in LUAD cells to explore its function in the mobility, EMT of cancer cells, and migration of M2 macrophages. Cancer cells were implanted in NOD/SCID mice to induce xenograft tumors. The CCL7-related transcription factors or factors were predicted by bioinformatic tools, and the molecular interactions were confirmed by immunoprecipitation or luciferase assays.

Results

CCL7 was highly expressed in LUAD and linked to increased TAM infiltration. Knockdown of CCL7 suppressed the chemotaxis and M2 skewing of macrophages, and it blocked the EMT and mobility of LUAD cells. CCL7 downregulation also suppressed macrophage infiltration in xenograft tumors in mice. Spi-1 proto-oncogene (SPI1) was confirmed as an upstream factor activating CCL7 transcription, and LINC01094 was found to bind to SPI1 to promote its nuclear translocation. Upregulation of SPI1 restored the chemotactic migration and M2 polarization of macrophages in LUAD cells.

Conclusion

This paper reveals that LINC01094 binds to SPI1 to promote its nuclear translocation, which further activates CCL7 transcription by binding to its promoter, leading to M2 macrophage accumulation and dissemination of tumor cells.

Identification of a Hypoxia-Angiogenesis lncRNA Signature Participating in Immunosuppression in Gastric Cancer

Hypoxia and angiogenesis are the leading causes of tumor progression, and their strong correlation has been discovered in many cancers. However, their collective function’s prognostic and biological roles were not reported in gastric cancer. Hence, we aimed to investigate the effects of hypoxia and angiogenesis on gastric cancer via sequencing data. This study used weighted gene coexpression network analysis and random forest regression to build a hypoxia-angiogenesis-related model (HARM) via the TCGA-STAD lncRNA data. It estimated the HARM’s correlation with clinical features and its accuracy for survival prediction. Sequential functional analyses were conducted to investigate its biological role, and we next sought the immune landscape status and immunological function variation by ESTIMATE score calculation and GSVA, respectively. Seven different algorithms were conducted to assess the immunocyte infiltration, and TIDE score and immune checkpoint levels were compared between the high- and low-HARM groups. As a result, we found that HARM predicted patient survival with high accuracy and was correlated with higher stages of gastric cancer. Various cancer-associated pathways and macrophage-related regulations were upregulated in the high-HRAM group. The high-HARM group harbored higher immune levels, and M2 macrophages and cancer-associated fibroblasts were particularly highly unfiltered. Furthermore, globally upregulated immune checkpoints and higher TIDE scores were observed in the high-HARM group. Finally, we filtered eight drugs with lower IC50 in the high-HARM group as potential drugs for the HARM-targeted therapy. We believe this study opens up novel perspectives into the interaction between hypoxia-angiogenesis and immunosuppression and will provide novel insights for gastric cancer immunotherapy.

lncRNA MIR4435-2HG Accelerates the Development of Bladder Cancer through Enhancing IQGAP3 and CDCA5 Expression

Background. Bladder cancer (BCa) is one of the most prevalent cancers occurring in the urinary system. Long noncoding RNAs (lncRNAs), in recent years, have emerged as crucial regulators in various biological processes of tumors. Aim. To identify the role of MIR4435-2 host gene (MIR4435-2HG) and uncover its molecular mechanism in BCa. Methods. Firstly, quantitative real-time PCR (RT-qPCR) analysis was used to examine MIR4435-2HG expression in BCa cells. Cell Counting Kit-8 (CCK-8), 5-ethynyl-2 $\prime$ -deoxyuridine (EdU), wound healing, and transwell assays were implemented to identify the role of MIR4435-2HG in BCa. RNA-binding protein immunoprecipitation (RIP), RNA pull down, and luciferase reporter assays were applied to explore the potential mechanism of MIR4435-2HG in BCa. Results. MIR4435-2HG was highly expressed in BCa. Moreover, MIR4435-2HG silencing abrogated BCa cell proliferation, migration, and invasion. In terms of underlying mechanism, MIR44352HG acted as a microRNA-2467-3p (miR-2467-3p) sponge to control the expression of IQ motif containing GTPase activating protein 3 (IQGAP3) and cell division cycle associated 5 (CDCA5), resulting in activation of the rat sarcoma virus (Ras)/rapidly accelerated fibrosarcoma (Raf)/mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) and PI3K/AKT/mTOR signaling pathways. Conclusion. MIR4435-2HG involves in the progression of BCa, which might provide novel insights for BCa treatment.

Construction of a Prognostic Signature of 10 Autophagy-Related lncRNAs in Gastric Cancer

Background

Autophagy plays a double-edged sword role in cancers. LncRNAs could regulate cancer initiation and development at various levels. However, the role of autophagy-related lncRNAs (ARlncs) in gastric cancer (GC) remains indistinct.

Methods

GC gene expression profile and clinical data were acquired from the Cancer Genome Atlas (TCGA). The prognostic signature composed of ARlncs was established via cox regression analysis. Kaplan–Meier (K-M) survival curve was adopted to show overall survival (OS). Independence and reliability of risk signature were visualized by cox regression analysis and ROC curve. A nomogram was constructed and the reliability was analyzed by ROC curve. Immune infiltrating cells and check points were also analyzed.

Results

A prognostic signature was constructed which stratified GC patients into high- and low-risk groups according to risk score calculated via the 10 ARlncs including LINC01094, AC068790.7, AC090772.1, AC005165.1, PVT1, LINC00106, AC026368.1, AC090912.3, AC013652.1, UICLM. Patients in high-risk group showed a poor prognosis (p<0.001). Cox regression analysis showed signature was an independent prognostic factor (p<0.001). Areas under curves (AUC) of ROC for risk signature for predicting OS outweighed age, gender, grade, T, M and N, which suggested the reliability of the signature. A nomogram was constructed with risk signature, T, M, N and age and its AUC of ROC for 1-, 3-, and 5-year was 0.700, 0.730, 0.757 respectively, which showed good reliability. Macrophage M2, T cell CD8+ and T cell CD4+ memory resting had greatest difference between the two risk groups according to CIBERSORE-ABS algorithm (p<0.001). CD274 (PD-L1), PDCD1 (PD-1) and PDCD1LG2 (PD-L2) were expressed higher in the high-risk group (p<0.05), which implied that immunotherapy may be a good choice for these patients.

Conclusion

The risk signature based on 10 ARlncs can serve as an efficacious prognostic predictor and guide the immunotherapies and precise treatment for GC patients.

A Necroptosis-Related lncRNA-Based Signature to Predict Prognosis and Probe Molecular Characteristics of Stomach Adenocarcinoma

Background: As a caspase-independent type of cell death, necroptosis plays a significant role in the initiation, and progression of gastric cancer (GC). Numerous studies have confirmed that long non-coding RNAs (lncRNAs) are closely related to the prognosis of patients with GC. However, the relationship between necroptosis and lncRNAs in GC remains unclear.

Methods: The molecular profiling data (RNA-sequencing and somatic mutation data) and clinical information of patients with stomach adenocarcinoma (STAD) were retrieved from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was conducted to identify the necroptosis-related lncRNAs (NRLs). Subsequently, univariate Cox regression and LASSO-Cox regression were conducted to establish a 12-NRLs signature in the training set and validate it in the testing set. Finally, the prognostic power of the 12-NRLs signature was appraised via survival analysis, nomogram, Cox regression, clinicopathological characteristics correlation analysis, and the receiver operating characteristic (ROC) curve. Furthermore, correlations between the signature risk score (RS) and immune cell infiltration, immune checkpoint molecules, somatic gene mutations, and anticancer drug sensitivity were analyzed.

Results: In the present study, a 12-NRLs signature comprising REPIN1-AS1, UBL7-AS1, LINC00460, LINC02773, CHROMR, LINC01094, FLNB-AS1, ITFG1-AS1, LASTR, PINK1-AS, LINC01638, and PVT1 was developed to improve the prognosis prediction of STAD patients. Unsupervised methods, including principal component analysis and t-distributed stochastic neighbor embedding, confirmed the capability of the present signature to separate samples with RS. Kaplan-Meier and ROC curves revealed that the signature had an acceptable predictive potency in the TCGA training and testing sets. Cox regression and stratified survival analysis indicated that the 12-NRLs signature were risk factors independent of various clinical parameters. Additionally, immune cell infiltration, immune checkpoint molecules, somatic gene mutations, and half-inhibitory concentration differed significantly among different risk subtypes, which implied that the signature could assess the clinical efficacy of chemotherapy and immunotherapy.

Conclusion: This 12-NRLs risk signature may help assess the prognosis and molecular features of patients with STAD and improve treatment modalities, thus can be further applied clinically.

Upregulated long intergenic non-protein coding RNA 1094 (LINC01094) is linked to poor prognosis and alteration of cell function in colorectal cancer

Colorectal cancer (CRC) showed high cancer-related mortality in recent years partly due to the absence of an effective prognostic predictor. This research intended to evaluate the prognostic value and potential role of long intergenic non-protein coding RNA 1094 (LINC01094) in CRC. In this work, we evaluated the LINC01094 level in 122 CRC patients’ tissues and in human CRC cell lines. We explored the ability of LINC01094 in overall survival and progression-free survival estimate. The effect of LINC01094 dysregulation on the CRC cells was investigated. LINC01094 is highly expressed in CRC tissues and cells than normal ones. This high expression was correlated with absent vascular invasion, positive lymph node metastasis, and advanced TNM stage. With the result of Kaplan-Meier analysis and multivariate Cox’s proportional hazard analysis, LINC01094 was an effective biomarker for CRC overall survival. Downregulation of LINC01094 impeded the malignant biological behavior (proliferation, invasion, and migration) of CRC cells, while overexpression of LINC01094 boosted that maybe by sponging miR-1266-5p. LINC01094 might function as an oncogene in CRC and allowed the discovery of a new biomarker for prognosis and therapy of CRC.

Ferroptosis‑related long non‑coding RNAs and the roles of LASTR in stomach adenocarcinoma

Ferroptosis is a form of programmed cell death that participates in diverse physiological processes. Increasing evidence suggests that long noncoding RNAs (lncRNAs) regulate ferroptosis in tumors, including stomach adenocarcinoma (STAD). In the present study, RNA-sequencing data from The Cancer Genome Atlas database and ferroptosis-related markers from the FerrDb data resource were analyzed to select differentially expressed lncRNAs. Univariate and multivariate Cox regression analyses were performed on these differentially expressed lncRNAs to screen 12 lncRNAs linked with overall survival (OS) and 13 associated with progression-free survival (PFS). Subsequently, two signatures for predicting OS and PFS were established based on these lncRNAs. Kaplan-Meier analyses indicated that the high-risk group of patients with STAD had relatively poor prognosis. The areas under the receiver operating characteristic curves of the two signatures indicated their excellent efficacy in predicting STAD prognosis. In addition, the effect of the lncRNA LASTR on proliferation and migration in gastric cancer was confirmed and the relationship between LASTR and ferroptosis was initially explored through experiments. These results provide potential novel targets for tumor treatment and promote personalized medicine.

Bioinformatics analysis of long non-coding RNA-associated competing endogenous RNA network in schizophrenia

Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein-protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.

Identification of an Immune-Related LncRNA Signature in Gastric Cancer to Predict Survival and Response to Immune Checkpoint Inhibitors

Immune microenvironment in gastric cancer is closely associated with patient’s prognosis. Long non-coding RNAs (lncRNAs) are emerging as key regulators of immune responses. In this study, we aimed to construct a prognostic model based on immune-related lncRNAs (IRLs) to predict the overall survival and response to immune checkpoint inhibitors (ICIs) of gastric cancer (GC) patients. The IRL signature was constructed through a bioinformatics method, and its predictive capability was validated. A stratification analysis indicates that the IRL signature can distinguish different risk patients. A nomogram based on the IRL and other clinical variables efficiently predicted the overall survival of GC patients. The landscape of tumor microenvironment and mutation status partially explain this signature’s predictive capability. We found the level of cancer-associated fibroblasts, endothelial cells, M2 macrophages, and stroma cells was high in the high-risk group, while the number of CD8⁺ T cells and T follicular helper cells was high in the low-risk group. Immunophenoscore (IPS) is validated for ICI response, and the IRL signature low-risk group received higher IPS, representing a more immunogenic phenotype that was more inclined to respond to ICIs. In addition, we found RNF144A-AS1 was highly expressed in GC patients and promoted the proliferation, migration, and invasive capacity of GC cells. We concluded that the IRL signature represents a novel useful model for evaluating GC survival outcomes and could be implemented to optimize the selection of patients to receive ICI treatment.

LINC01094 promotes the invasion of ovarian cancer cells and regulates the Wnt/β-catenin signaling pathway by targeting miR-532-3p

Long non-coding RNAs (lncRNAs) participate in the development of ovarian cancer (OC). The present study aimed to explore the roles of long intergenic non-protein coding RNA 1094 (LINC01094) in OC. LINC01094 and microRNA (miR)-532-3p expression in OC tissues and cells were measured using reverse transcription-quantitative PCR. Cell migration and invasion were detected using wound healing assays and Transwell assays, respectively. The binding of LINC01094 or β-catenin to miR-126-5p was detected using a Dual-luciferase reporter assay, and protein expression was confirmed using western blot analysis. The expression level of LINC01094 in patients with OC was higher in OC tissues compared with in adjacent tissues, and LINC01094 was upregulated in OC cell lines. In addition, LINC01094 overexpression promoted the viability, migration, invasion and cell cycle progression of OC cells, and inhibited OC cell apoptosis. Moreover, LINC01094 negatively regulated miR-532-3p in OC cells and tissues. miR-532-3p overexpression decreased the viability, migration, invasion and cell cycle progression of OC cells alongside downregulation of Wnt/β-catenin signaling pathway protein expression, as well as increasing OC cell apoptosis. Inhibition of LINC01094 with small interfering (si)-LINC01094 and overexpression of LINC01094 respectively reversed the effect of miR-532-3p inhibitor and mimics on OC cells. miR-532-3p could directly target β-catenin, and miR-532-3p inhibitor increased β-catenin expression, while si-LINC01094 attenuated this effect. In addition, LINC01094 overexpression promoted tumor growth in vivo by regulating miR-532-3p. Taken together, LINC01094 promoted the growth, migration, invasion and Wnt/β-catenin signaling pathway expression of OC cells by modulating miR-532-3p.

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

Background

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

Results

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

Conclusions

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

Supplementary Information

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

GLIDR promotes the progression of glioma by regulating the miR-4677-3p/MAGI2 axis

Gliomas are the most common and fatal primary brain tumors. Growing evidence suggests that long non-coding RNAs (lncRNAs) constitute novel and potential therapeutic targets for glioma. However, the biological role of glioblastoma down-regulated RNA (GLIDR) in glioma remains largely elusive. In the current study, we used quantitative real-time polymerase chain reaction (qRT-PCR) to detect GLIDR expression in glioma cells. Cell counting kit 8 (CCK-8) assay, colony formation assay, JC-1 staining, and flow cytometry were used to evaluate the role of GLIDR in proliferation and apoptosis of glioma cells. Western blotting was performed to assess the effect of GLIDR on the level of apoptosis-related proteins. In addition, bioinformatics prediction, RNA immunoprecipitation (RIP), RNA pull-down, and luciferase reporter gene assays were used to study the regulatory mechanisms of GLIDR in glioma. GLIDR was found to be highly expressed in glioma cells and silencing of GLIDR inhibited cell proliferation and promoted apoptosis. Functionally, GLIDR bound to miR-4677-3p that directly targeted membrane-associated guanylate kinase, WW, and PDZ domain-containing protein 2 (MAGI2). Our data showed that GLIDR affects the proliferation and apoptosis of glioma cells by targeting miR-4677-3p to regulate the expression of MAGI2. In conclusion, our study determined the oncogenic role of GLIDR in glioma, which may provide a new perspective for the treatment of glioma.