LINC01980 facilitates esophageal squamous cell carcinoma progression via regulation of miR-190a-5p/MYO5A pathway

Circ-FNDC3B Functions as an Oncogenic Factor in Esophageal Squamous Cell Carcinoma via Upregulating MYO5A by Absorbing miR-136-5p and miR-370-3p

Circular RNAs (circRNAs) are a class of key regulators in cancers via regulating gene levels by acting as sponges of miRNAs. This study was devoted to explore the functional mechanism of circRNA fibronectin type III domain-containing protein 3B (circ-FNDC3B) in esophageal squamous cell carcinoma (ESCC). RNA levels were examined via reverse transcription-quantitative polymerase chain reaction assay. Cell viability detection was performed using Cell Counting Kit-8 assay. The proliferation ability was determined through colony formation assay and EDU assay. Flow cytometry was applied for analysis of apoptosis. Invasion ability was assessed via transwell assay. Target binding was analyzed by dual-luciferase reporter assay. The protein expression was measured using western blot. In vivo research was conducted via xenograft model in mice. Circ-FNDC3B exhibited significant upregulation in ESCC tissues and cells. Downregulation of circ-FNDC3B inhibited ESCC cell proliferation and invasion but accelerated cell apoptosis. Circ-FNDC3B interacted with miR-136-5p or miR-370-3p. The function of circ-FNDC3B was achieved by sponging miR-136-5p or miR-370-3p. Myosin VA (MYO5A) acted as a downstream target of miR-136-5p or miR-370-3p. MYO5A reversed miR-136-5p/miR-370-3p-induced tumor inhibition in ESCC cells. Circ-FNDC3B targeted miR-136-5p or miR-370-3p to affect MYO5A expression. Circ-FNDC3B knockdown reduced tumor growth in vivo by inhibiting miR-136-5p or miR-370-3p-mediated MYO5A expression. These findings demonstrated that circ-FNDC3B contributed to malignant progression of ESCC cells via miR-136-5p/MYO5A or miR-370-3p/MYO5A axis.

Altered long non-coding RNAs expression in normal and diseased primary human airway epithelial cells exposed to diesel exhaust particles

BACKGROUND

Exposure to diesel exhaust particles (DEP) has been linked to a variety of adverse health effects, including increased morbidity and mortality from cardiovascular diseases, chronic obstructive pulmonary disease (COPD), metabolic syndrome, and lung cancer. The epigenetic changes caused by air pollution have been associated with increased health risks. However, the exact molecular mechanisms underlying the lncRNA-mediated pathogenesis induced by DEP exposure have not been revealed.

METHODS

Through RNA-sequencing and integrative analysis of both mRNA and lncRNA profiles, this study investigated the role of lncRNAs in altered gene expression in healthy and diseased human primary epithelial cells (NHBE and DHBE-COPD) exposed to DEP at a dose of 30 μg/cm2.

RESULTS

We identified 503 and 563 differentially expressed (DE) mRNAs and a total of 10 and 14 DE lncRNAs in NHBE and DHBE-COPD cells exposed to DEP, respectively. In both NHBE and DHBE-COPD cells, enriched cancer-related pathways were identified at mRNA level, and 3 common lncRNAs OLMALINC, AC069234.2, and LINC00665 were found to be associated with cancer initiation and progression. In addition, we identified two cis-acting (TMEM51-AS1 and TTN-AS1) and several trans-acting lncRNAs (e.g. LINC01278, SNHG29, AC006064.4, TMEM51-AS1) only differentially expressed in COPD cells, which could potentially play a role in carcinogenesis and determine their susceptibility to DEP exposure.

CONCLUSIONS

Overall, our work highlights the potential importance of lncRNAs in regulating DEP-induced gene expression changes associated with carcinogenesis, and individuals suffering from COPD are likely to be more vulnerable to these environmental triggers.

Role of Long Intergenic Noncoding RNAs in Cancers with an Overview of MicroRNA Binding

Long intergenic noncoding RNAs are transcripts originating from the regions without annotated coding genes. They are located mainly in the nucleus and regulate gene expression. Long intergenic noncoding RNAs can be also found in the cytoplasm acting as molecular sponges of certain microRNAs. This is crucial in various biological and signaling pathways. Expression levels of many long intergenic noncoding RNAs are disease related. In this article, we focus on the long intergenic noncoding RNAs and their relation to different types of cancer. Studies showed that abnormal expression of long intergenic noncoding RNA deregulates signaling pathways due to the disrupted free microRNA pool. Hampered signaling pathways leads to abnormal cell proliferation and restricts cell death, thus resulting in oncogenesis. This review highlights promising therapeutic targets and enables the identification of potential biomarkers specific for a certain type of cancer. Moreover, we provide an outline of long intergenic noncoding RNAs/microRNA axes, which might be applied in further detailed experiments broadening our knowledge about the cellular role of those RNA species.

A novel risk model construction and immune landscape analysis of gastric cancer based on cuproptosis-related long noncoding RNAs

Recent studies have identified cuproptosis, a new mechanism of regulating cell death. Accumulating evidence suggests that copper homeostasis is associated with tumorigenesis and tumor progression, however, the clinical significance of cuproptosis in gastric cancer (GC) is unclear. In this study, we obtained 26 prognostic cuproptosis-related lncRNAs (CRLs) based on 19 cuproptosis-related genes (CRGs) via Pearson correlation analysis, differential expression analysis, and univariate Cox analysis. A risk model based on 10 CRLs was established with the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and multivariate Cox proportional hazards model to predict the prognosis and immune landscape of GC patients from The Cancer Genome Atlas (TCGA). The risk model has excellent accuracy and efficiency in predicting prognosis of GC patients (Area Under Curve (AUC) = 0.742, 0.803, 0.806 at 1,3,5 years, respectively, P < 0.05). In addition, we found that the risk score was negatively correlated with the infiltration of natural killer (NK) cells and helper T cells, while positively correlated with the infiltration of monocytes, macrophages, mast cells, and neutrophils. Moreover, we evaluated the difference in drug sensitivity of patients with different risk patterns. Furthermore, low-risk patients showed higher tumor mutation burden (TMB) and better immunotherapy response than high-risk patients. In the end, we confirmed the oncogenic role of AL121748.1 which exhibited the highest Hazard Ratio (HR) value among 10 CRLs in GC via cellular functional experiments. In conclusion, our risk model shows a significant role in tumor immunity and could be applied to predict the prognosis of GC patients.

The clinical prognostic value of long noncoding RNA HAND2-AS1 in cancer patients: A study based on meta-analysis and TCGA data (PRISMA)

BACKGROUND

The heart and neural crest derivatives expressed 2 antisense RNA 1 (HAND2-AS1) is a novel long noncoding RNA aberrantly expressed in human malignancies. We aimed to analyze the available data to evaluate the clinical prognostic significance of HAND2-AS1 in tumors.

METHODS

In this meta-analysis, electronic databases, including PubMed Cochrane Library, EMBASE, Medline, Web of Science, CNKI, and Wanfang, were searched from their inception up to December 1, 2021. The pooled hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated to assess the relationship of HAND2-AS1expression level with prognosis and clinicopathological features in cancer patients. The publication bias was identified by Begg's test, and the sensitivity analysis was also performed.

RESULTS

A total of 10 articles with 615 patients were included in the present meta-analysis. The combined results revealed that low expression of HAND2-AS1 was associated with poor overall survival (OS) (HR = 0.48, 95% CI: 0.36-0.64, P < .001) in a variety of cancers. In addition, the decrease in HAND2-AS1 expression was also correlated with poor differentiation (OR = 4.36, 95% CI: 2.15-8.87, P < .001) and lymph node metastasis (OR = 0.26, 95% CI: 0.13-0.54, P < .001). The cancer genome atlas (TCGA) dataset further demonstrated that low expression of HAND2-AS1 was associated with poor OS and disease-free survival.

CONCLUSIONS

Our results of this meta-analysis indicated that HAND2-AS1 may be a prognostic marker and even a therapeutic target for human cancer.

Comprehensive Analysis of SLC17A9 and Its Prognostic Value in Hepatocellular Carcinoma

Background

Solute carrier family 17 member 9 (SLC17A9) encodes a member of a family of transmembrane proteins that are involved in the transport of small molecules. SLC17A9 is involved in the occurrence and development of various cancers, but its biological role in liver hepatocellular carcinoma (LIHC) is unclear.

Methods

The expression level of SLC17A9 was assessed using The Cancer Genome Atlas (TCGA) database and immunohistochemistry of tumor tissues and adjacent normal liver tissues. The receiver operating characteristic (ROC) and R software package performed diagnosis and prognosis. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes functional enrichment and co-expression of SLC17A9, gene–gene interaction (GGI), and protein–protein interaction (PPI) networks were performed using R, GeneMANIA, and STRING. Western blot, real-time quantitative PCR (RT-qPCR), immunofluorescence, colony formation, wound scratch assay, ATP production assays, and high connotation were applied to determine the effect of SLC17A9 knockdown on HEPG2 (hepatocellular liver carcinoma) cells. TIMER, GEPIA, and TCGA analyzed the relationship between SLC17A9 expression and immune cells, m6A modification, and ferroptosis.

Results

SLC17A9 expression in LIHC tissues was higher than in normal liver tissues (p < 0.001), and SLC17A9 was related to sex, DSS (disease-specific survival), and PFI (progression-free interval) (p = 0.015, 0.006, and 0.023). SLC17A9 expression has diagnostic (AUC: 0.812; CI: 0.770–0.854) and prognostic potential (p = 0.015) in LIHC. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) functional enrichment analysis showed that SLC17A9 was closely related to neuronal cell body, presynapse, axonogenesis, PI3K/Akt signaling pathway. GGI showed that SLC17A9 was closely related to MYO5A. PPI showed that SLC17A9 was closely related to SLC18A3. SLC17A9 silencing inhibited HepG2 cells proliferation, migration, colony formation, and reduced their ATP level. SLC17A9 expression level was related to immune cells: B cells (r = 0.094, P = 8.06E-02), CD4⁺ T cells (r = 0.184, P = 5.95E-04), and macrophages (r = 0.137, P = 1.15E-02); m6A modification: HNRNPC (r = 0.220, p < 0.001), METTL3 (r = 0.180, p < 0.001), and WTAP (r = 0.130, p = 0.009); and ferroptosis: HSPA5 (r = 0.240, p < 0.001), SLC7A11 (r = 0.180, p < 0.001), and FANCD2 (r = 0.280, p < 0.001).

Conclusion

Our data show that SLC17A9 may influence LIHC progression. SLC17A9 expression correlates with tumor immune infiltration, m6A modification, and ferroptosis in LIHC and may have diagnostic and prognostic value in LIHC.

Immune-Related LncRNAs to Construct a Prognosis Risk-Assessment Model for Gastric Cancer

Background: Gastric cancer is a prevalent cause of tumor death. Tumor immunotherapy aims to reshape the specific immunity to tumors in order to kill the tumor. LncRNAs play a pivotal role in regulating the tumor immune microenvironment. Herein, immune-related lncRNAs were used to establish a prognosis risk-assessment model for gastric cancer and provide personalized predictions while providing insights and targets for gastric cancer treatment to enhance patient prognosis. Methods: Gastric adenocarcinoma transcriptome and clinical data were acquired from the The Cancer Genome Atlas (TCGA) database to screen the immune-related lncRNAs. Then, LASSO COX regression was utilized to construct the prognosis risk-assessment model. Afterward, the reliability of the model was evaluated the relationship between immune infiltration, clinical characteristics, and the model was analyzed. Results: We identified 13 lncRNAs and constructed the prognosis assessment model. According to the median risk score of the training set, the patients were assigned to different risk groups. Overall survival time was shorter in the high-risk group. In the high-risk group, higher infiltration of mono-macrophages, dendritic cells, CD4+ T cells, and CD8+ T cells was observed. Moreover, the model was positively related to tumor metastasis. Conclusion: The prognosis risk-assessment model developed in this research can effectively predict the prognosis of gastric cancer patients. This tool is expected to be further applied to clinics in the future, thus providing a novel target for immunotherapy in gastric cancer patients.

Integrative bioinformatics analysis identifies LINC01614 as a potential prognostic signature in esophageal cancer

Background

Esophageal cancer (EC) is one of the most common gastrointestinal cancers and the incidence is on the increase in recent years. The aim of the present study was to assess novel long non-coding RNA (lncRNA) biomarkers for the prognosis of EC through the analysis of gene expression microarrays.

Methods

Three datasets (GSE53622, GSE53624, and GSE53625) were downloaded from the Gene Expression Omnibus (GEO) database and EC patients’ clinical information were from The Cancer Genome Atlas (TCGA) databases. Differentially expressed genes (DEGs) were screened by comparing tumor tissues with normal tissues using limma R package. The Gene Expression Profiling Interactive Analysis 2 (GEPIA2) database was used to obtain the novel lncRNAs and their co-expression genes in EC and these were visualized with the Cytoscape software. The Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology Based Annotation System (KOBAS) database was used to analyze the functions enrichment of selected DEGs. Cell Counting Kit-8 (CCK8) and Transwell assays were used to further confirm the function of target lncRNAs.

Results

We identified 24 differentially expressed (DE) lncRNAs and 659 DE mRNAs from the intersection of GEO and TCGA databases. And we found that only LINC01614 was concerned with a candidate prognostic signature in EC. “Extracellular matrix (ECM)-receptor interaction” and “PI3K-Akt signaling pathway” were observed, and we constructed a lncRNA-mRNA co-expression network for EC that includes LINC01614 and 64 mRNAs. The results of CCK8 and Transwell assays showed that suppression of LINC01614 inhibited EC cell proliferation and migration.

Conclusions

Our study might provide LINC01614 as a novel lncRNA biomarker for diagnosis and prognosis in EC.

Identification of a Hypoxia-Related lncRNA Biomarker Signature for Head and Neck Squamous Cell Carcinoma

Purpose. Hypoxia is a leading hallmark of tumors, which is associated with carcinogenicity and dismal patient outcome. In this project, we tended to detect the prognostic value of hypoxic lncRNA and further generate a hypoxic lncRNA-based model in head and neck squamous cell carcinoma (HNSCC). Methods. We integrated the transcriptome and clinical information of HNSCC based on TCGA dataset. Univariate-multivariate Cox analysis was implemented to develop the signature according to hypoxia-related lncRNAs (HRlncRNAs) with greatly prognostic power in HNSCC. Next, the biomarker signature was tested using survival analysis and ROC plots. Moreover, we used GSEA to uncover the potential pathways of HRlncRNAs, and CIBERSORT and ssGSEA tools were applied to mirror the immune status of HNSCC patients. Results. Nine HRlncRNAs (LINC00460, AC144831.1, AC116914.2, MIAT, MSC-AS1, LINC01980, MYOSLID, AL357033.4, and LINC02195) were determined to develop a HRlncRNA-related signature (HRLS). High-HRLS group was associated with dismal patient outcome using survival analysis. Moreover, the HRLS was superior to classical clinical traits in forecasting survival rate of samples with HNSCC. GSEA unearthed the top six hallmarks in the HRLS-high group individuals. In addition, the HRLS was also bound up with the infiltration of macrophages, CD8 T cells, and activated mast cells. Conclusion. Our nominated nine-HRlncRNA risk model is robust and valuable tool for forecasting patient outcome in HNSCC.

Construction and Comprehensive Prognostic Analysis of a Novel Immune-Related lncRNA Signature and Immune Landscape in Gastric Cancer

Gastric cancer (GC) is a malignant tumor with high mortality and poor prognosis. Immunotherapies, especially immune checkpoint inhibitors (ICI), are widely used in various tumors, but patients with GC do not benefit much from immunotherapies. Therefore, effective predictive biomarkers are urgently needed for GC patients to realize the benefits of immunotherapy. Recent studies have indicated that long noncoding RNAs (lncRNAs) could be used as biomarkers in the immune landscape of multiple tumors. In this study, we constructed a novel immune-related lncRNA (irlncRNA) risk model to predict the survival and immune landscape of GC patients. First, we identified differentially expressed irlncRNAs (DEirlncRNAs) from RNA-Seq data of The Cancer Genome Atlas (TCGA). By using various algorithms, we constructed a risk model with 11 DEirlncRNA pairs. We then tested the accuracy of the risk model, demonstrating that the risk model has good efficiency in predicting the prognosis of GC patients. Inner validation sets were further used to confirm the effectiveness of the risk model. In addition, our risk model has a preferable performance in predicting the immune infiltration status of tumors, immune checkpoint status of the patients, and immunotherapy score. In conclusion, our risk model may provide insights into the prognosis of and immunotherapy strategy for GC.

Excavating novel diagnostic and prognostic long non-coding RNAs (lncRNAs) for head and neck squamous cell carcinoma: an integrated bioinformatics analysis of competing endogenous RNAs (ceRNAs) and gene co-expression networks

Long non-coding RNAs (lncRNAs) have been demonstrated to fine-tune gene regulations that govern a broad spectrum of oncogenic processes. Nonetheless, our understanding of the roles of lncRNAs and their interactions with miRNAs and mRNAs in HNSCC is still highly rudimentary. Here, we present a comprehensive bioinformatics analysis in which competing endogenous RNA (ceRNA) network construction and weighted gene co-expression network analysis (WGCNA) were combined to explore novel diagnostic and prognostic lncRNAs for HNSCC. Differentially expressed mRNAs (DEGs), miRNAs (DEMs) and lncRNAs (DELs) were identified based on the RNA sequencing data and clinical data retrieved from TCGA database. LncRNA-regulated ceRNA networks were constructed based on the interactive RNA pairs predicted by miRDB, miRcode and TargetScan. WGCNA was conducted to identify lncRNAs that were significantly correlated with patient overall survival (OS) and HNSCC tumor. RT-qPCR was employed to validate the expression of lncRNAs in HNSCC cell lines and patient sera. A ceRNA network consisting of 90 DEGs, 7 DEMs and 67 DELs associated with clinical traits was established. WGCNA and Kaplan-Meier survival analysis revealed that 5 DELs (MIR4435-2 HG, CASC9, LINC01980, STARD4-AS1 and MIR99AHG) were significantly correlated with OS of HNSCC patients, whereas DEL PART1 was most significantly correlated with the HNSCC tumor. The in silico predicted expression patterns of PART1, LINC01980 and MIR4435-2 HG were further validated in HNSCC cell lines and patient sera. Collectively, the present study provided novel insights into the lncRNA-regulated ceRNA networks in HNSCC and identified novel lncRNAs that harbor diagnostic and prognostic potentials for HNSCC.Abbreviations BP, biological process. CC, cellular component. ceRNA, competing endogenous RNA. DEG, differential expressions of mRNA. DEL, differentially expressed lncRNA. DEM, differentially expressed miRNA. ESCC, esophageal squamous cell carcinoma. FPKM, Fragments Per Kilobase Million. GO, Gene Ontology. GS, gene significance. HNSCC, head and neck squamous cell carcinoma. KEGG, Kyoto Encyclopedia of Genes and Genomes. LncRNA, long non-coding RNA. MCC, Maximal Clique Centrality. ME, module eigengenes. MF, molecular functions. MM, module membership. MRE, miRNA-binding site. MYO5A, Myosin-Va. PART1, prostate androgen-regulated transcript 1. RBM3, RNA‑binding motif protein 3. TCGA, The Cancer Genome Atlas. TOM, topological overlap measure. TSCC, tongue squamous cell carcinoma. WGCNA, weighted gene co-expression network analysis.

Crosstalk between lncRNAs and miRNAs in gastrointestinal cancer drug resistance

Gastrointestinal cancers are one of the most prevalent malignancies worldwide. Dysregulation of lncRNAs by epigenetic alteration is crucial in gastrointestinal carcinogenesis. Epigenetic alteration includes DNA methylation, chromatin remodeling, histone modifications, and deregulated-gene expression by miRNAs. LncRNAs are involved in biological processes, including, uncontrolled cell division, migration, invasion, and resistance to apoptosis and drugs. Multiple-drug resistance (MDR) is a crucial obstacle in effective chemotherapy for gastrointestinal cancers. MDR can be associated with the prognosis and diagnosis of patients receiving chemotherapeutic agents (i.e. cisplatin, oxaliplatin, platinum, 5-fluorouracil, gefitinib, methotrexate, taxol, cetuximab, docetaxel, and gemcitabine). In this review, we focused on recently known lncRNAs and their relation with miRNAs and chemotherapeutic drugs, and their modulation in gastrointestinal cancers. Moreover, we mentioned the future prospective and clinical application of lncRNAs as a critical indicator and biomarker in diagnosis, prognosis, staging, grading, and treatment of gastrointestinal cancers.

NR2F1-AS1/miR-190a/PHLDB2 Induces the Epithelial-Mesenchymal Transformation Process in Gastric Cancer by Promoting Phosphorylation of AKT3

The median survival time of patients with advanced gastric cancer (GC) who received radiotherapy and chemotherapy was <1 year. Epithelial-mesenchymal transformation (EMT) gives GC cells the ability to invade, which is an essential biological mechanism in the progression of GC. The long non-coding RNA (lncRNA)-based competitive endogenous RNA (ceRNA) system has been shown to play a key role in the GC-related EMT process. Although the AKT pathway is essential for EMT in GC, the relationship between AKT3 subtypes and EMT in GC is unclear. Here, we evaluated the underlying mechanism of ceRNA involving NR2F1-AS1/miR-190a/PHLDB2 in inducing EMT by promoting the expression and phosphorylation of AKT3. The results of bioinformatics analysis showed that the expression of NR2F1-AS1/miR-190a/PHLDB2 in GC was positively associated with the pathological features, staging, poor prognosis, and EMT process. We performed cell transfection, qRT-PCR, western blot, cell viability assay, TUNEL assay, Transwell assay, cell morphology observation, and double luciferase assay to confirm the regulation of NR2F1-AS1/miR-190a/PHLDB2 and its effect on EMT transformation. Finally, GSEA and GO/KEGG enrichment analysis identified that PI3K/AKT pathway was positively correlated to NR2F1-AS1/miR-190a/PHLDB2 expression. AKT3 knockout cells were co-transfected with PHLDB2-OE, and the findings revealed that AKT3 expression and phosphorylation were essential for the PHLDB2-mediated EMT process. Thus, our results showed that NR2F1-AS1/miR-190a/PHLDB2 promoted the phosphorylation of AKT3 to induce EMT in GC cells. This study provides a comprehensive understanding of the underlying mechanism involved in the EMT process as well as the identification of new EMT markers.

miR-190a-5p regulates cardiomyocytes response to ferroptosis via directly targeting GLS2

Ferroptosis is a novel identified form of regulated cell death that has been implied in the pathology of myocardial infarction (MI). However, the regulation mechanisms of ferroptosis in cardiomyocyte are still elusive. MiRNAs are a group of small non-coding RNAs that play crucial roles in various biological activities. Till now, little is known about the role of miRNA in the ferroptosis of cardiomyocytes. In the current study, we found that miR-190a-5p negatively regulate ferroptosis via directly targeting GLS2 in rat cardiomyocyte H9c2 cells. Forced expression of miR-190a-5p inhibited GLS2, resulting in downregulation of ROS, MDA and Fe ²⁺ accumulation. Meanwhile, inhibition of miR-190a-5p caused upregulation of GLS2, resulting in opposite effects which could be blocked by GLS2 inhibitor compound 968. In summary, our findings suggest that miR-190a-5p plays an essential role in regulation of ferroptosis of cardiomyocytes and suggest a potential therapeutic target for MI.

Long Noncoding RNA WDFY3-AS2 Represses the Progression of Esophageal Cancer through miR-18a/PTEN Axis

Background

Understanding the role of lncRNAs in the development of human malignancies is necessary for the targeted therapy of malignant tumors, including esophageal cancer (EC). Nevertheless, the specific role and regulatory mechanism of lncRNA WDFY3-AS2 in EC are still unclear. Here, we examined the functional role and regulatory mechanism of WDFY3-AS2 in EC.

Materials and Methods

RT-qPCR assay was applied to measure the expression of WDFY3-AS2 and miR-18a in EC samples and cells. The luciferase reporter and RIP assays were used to check the relationship between WDFY3-AS2, miR-18a, and PTEN. Counting Clock Kit-8 (CCK-8) assay was carried out to detect cell viability, and transwell assays were used for measuring cell migration and invasion.

Results

Underexpression of WDFY3-AS2 was found in EC specimens and cells, which predicted a poor prognosis of EC patients. Reexpression of WDFY3-AS2 repressed the progression of EC via inhibiting cell proliferation, migration, and invasion. Additionally, WDFY3-AS2 was negatively correlated with miR-18a and positively with PTEN. Furthermore, we discovered that the expression of PTEN decreased by miR-18a mimic was rescued by WDFY3-AS2 overexpression.

Conclusions

WDFY3-AS2 modulates the expressional level of PTEN as a competitive endogenous RNA via sponging miR-18a in EC, which suggests that the WDFY3-AS2/miR-18a/PTEN pathway might be involved in the progression of EC.

LINC00239 Interacts with C-Myc Promoter-Binding Protein-1 (MBP-1) to Promote Expression of C-Myc in Esophageal Squamous Cell Carcinoma

Increasing evidence demonstrates that long non-coding RNAs (lncRNA) play a vital role in the progression of tumors, containing esophageal squamous cell carcinoma (ESCC). LINC00239 was reported as an oncogene in diverse kinds of cancers, whereas its specific role is still unclear in ESCC. In this study, we detected the expression and functional role of LINC00239 in ESCC specimens and cells, and investigated the molecular mechanisms of it. LINC00239 was highly expressed in ESCC tissues and cells, and was related to poor prognosis of patients with ESCC. The proliferation, metastasis, and invasion ability as well as epithelial-mesenchymal transition (EMT) process were all enhanced in LINC00239-overexpressed ESCC cells. LINC00239 was upregulated in TGF-β1-treated ESCC cells. Furthermore, LINC00239 was found to bind directly to the transcription factor c-Myc promoter-binding protein-1 (MBP-1). MBP-1 was detected to inhibit the transcription of c-Myc in ESCC. Moreover, LINC00239 could activate c-Myc transcription through influencing MBP-1-binding ability to c-Myc promoter. These data suggest that LINC00239 may act as an oncogene to promote the transcription of c-Myc by competitively combining with MBP-1 in ESCC, and may serve as a potential target for antitumor therapy in ESCC. IMPLICATIONS: LINC00239 may function as an oncogenic lncRNA in ESCC through the LINC00239/MBP-1/c-Myc axis to activate EMT process.

Long non-coding RNA BCAR4 aggravated proliferation and migration in esophageal squamous cell carcinoma by negatively regulating p53/p21 signaling pathway

Long non-coding RNA breast cancer antiestrogen resistance 4 (lncRNA BCAR4) is an independent factor on the survival prognosis of patients with multiple cancers. However, the role of lncRNA BCAR4 in esophageal squamous cell cancer (ESCC) remains unknown. Here, we unraveled that lncRNA BCAR4 was upregulated in ESCC and predicted poor prognosis. Functionally, lncRNA BCAR4 knockdown induced cell apoptosis and G1/S arrest, while inhibited cell proliferation and migration in vitro; conversely, overexpressing lncRNA BCAR4 promoted proliferation and metastasis. Mechanistically, lncRNA BCAR4 sponged miR-139-3p to upregulate ELAVL1, thereby inhibiting p53/p21 pathway in ESCC cells. In conclusion, lncRNA BCAR4 promotes ESCC tumorigenesis via regulating p53/p21 signaling pathway and develops a brand-new biomarker and medicine target for ESCC.

Ferroptosis-Related Long Non-Coding RNA signature predicts the prognosis of Head and neck squamous cell carcinoma

Background: Head and neck squamous cell carcinoma (HNSCC) are head and neck cancers. On the other hand, ferroptosis is a novel iron-dependent and ROS reliant type of cell death observed various disease conditions.

Method: We constructed a prognostic multilncRNA signature based on ferroptosis-related differentially expressed lncRNAs in HNSCC.

Results: We identified 25 differently expressed lncRNAs associated with prognosis of HNSCC. Kaplan-Meier analyses revealed the high-risk lncRNAs signature associated with poor prognosis of HNSCC. Moreover, the AUC of the lncRNAs signature was 0.782, underscoring their utility in prediction HNSCC prognosis. Indeed, our risk assessment model was superior to traditional clinicopathological features in predicting HNSCC prognosis. GSEA revealed the immune and tumor-related pathways in the low risk group individuals. Moreover, TCGA revealed T cell functions including cytolytic activity, HLA, regulation of inflammationp, co-stimulation, co-inhibition and coordination of type II INF response were significantly different between the low-risk and high-risk groups. Immune checkpoints such as PDCD-1 (PD-1), CTLA4 and LAG3, were also expressed differently between the two risk groups.

Conclusion: A novel ferroptosis-related lncRNAs signature impacts on the prognosis of HNSCC.

Long intergenic non‑coding RNA LINC01232 contributes to esophageal squamous cell carcinoma progression by sequestering microRNA‑654‑3p and consequently promoting hepatoma‑derived growth factor expression

Long intergenic non-coding RNA 01232 (LINC01232) was identified as a critical regulator of the development of pancreatic adenocarcinoma. The present study investigated the expression and regulatory roles of LINC01232 in esophageal squamous cell carcinoma (ESCC). The main aim of the present study was to elucidate the underlying mechanisms through which LINC01232 affects the malignancy of ESCC. Initially, LINC01232 expression in ESCC was analyzed using the TCGA and GTEx databases and was confirmed using reverse transcription-quantitative polymerase chain reaction. ESCC cell proliferation, apoptosis and migration and invasion were assessed using the Cell Counting kit-8 assay, flow cytometric analysis, and migration and invasion assays, respectively. ESCC tumor growth in vivo was examined using a xenograft mouse model. As shown by the results, a high LINC01232 expression was detected in ESCC tissues and cell lines. LINC01232 downregulation suppressed the proliferation, migration and invasion of ESCC cells, and promoted cell apoptosis in vitro. In addition, LINC01232 depletion restricted tumor growth in vivo. Mechanistically, LINC01232 was shown to function as an microRNA-654-3p (miR-654-3p) sponge in ESCC cells, and hepatoma-derived growth factor (HDGF) was identified as a direct target of miR-654-3p. LINC01232 could bind competitively to miR-654-3p and decrease its expression in ESCC cells, thereby promoting HDGF expression. Rescue experiments reconfirmed that the effects of LINC01232 deficiency in ESCC cells were restored by increasing the output of the miR-654-3p/HDGF axis. On the whole, the present study demonstrates that LINC01232 plays a tumor-promoting role during the progression of ESCC by regulating the miR-654-3p/HDGF axis. The LINC01232/miR-654-3p/HDGF pathway may thus provide a novel theoretical basis for the management of ESCC.

Predicting the interaction biomolecule types for lncRNA: an ensemble deep learning approach

Long noncoding RNAs (lncRNAs) play significant roles in various physiological and pathological processes via their interactions with biomolecules like DNA, RNA and protein. The existing in silico methods used for predicting the functions of lncRNA mainly rely on calculating the similarity of lncRNA or investigating whether an lncRNA can interact with a specific biomolecule or disease. In this work, we explored the functions of lncRNA from a different perspective: we presented a tool for predicting the interaction biomolecule type for a given lncRNA. For this purpose, we first investigated the main molecular mechanisms of the interactions of lncRNA-RNA, lncRNA-protein and lncRNA-DNA. Then, we developed an ensemble deep learning model: lncIBTP (lncRNA Interaction Biomolecule Type Prediction). This model predicted the interactions between lncRNA and different types of biomolecules. On the 5-fold cross-validation, the lncIBTP achieves average values of 0.7042 in accuracy, 0.7903 and 0.6421 in macro-average area under receiver operating characteristic curve and precision-recall curve, respectively, which illustrates the model effectiveness. Besides, based on the analysis of the collected published data and prediction results, we hypothesized that the characteristics of lncRNAs that interacted with DNA may be different from those that interacted with only RNA.