LncRNA BDNF-AS suppresses colorectal cancer cell proliferation and migration by epigenetically repressing GSK-3β expression

E2F1 Mediates Traumatic Brain Injury and Regulates BDNF-AS to Promote the Progression of Alzheimer's Disease

Traumatic brain injury (TBI) is one of the important risk factors for the development of Alzheimer's disease (AD). However, the molecular mechanism by which TBI promotes the progression of AD is not elucidated. In this study, we showed that the abnormal production of E2F1 is a major factor in promoting the neuropathological and cognitive deterioration of AD post-TBI. We found that repeated mild TBI can aggravate the neuropathology of AD in APP/PS1 mice. At the same time, the co-expression of E2F1 and beta-site APP cleaving enzyme 1 (BACE1) was upregulated when the mouse hippocampus was dissected. BACE1 is recognized as a rate-limiting enzyme for the production of Aβ. Here, we speculate that E2F1 may play a role in promoting BACE1 expression in AD. Therefore, we collected peripheral blood from patients with AD. Interestingly, there is a positive correlation between E2F1 and brain-derived neurotrophic factor-antisense (BDNF-AS), whereas BDNF-AS in AD can promote the expression of BACE1 and exhibit a neurotoxic effect. We established a cell model and found a regulatory relationship between E2F1 and BDNF-AS. Therefore, based on our results, we concluded that E2F1 regulates BDNF-AS, promotes the expression of BACE1, and affects the progression of AD. Furthermore, E2F1 mediates the TBI-induced neurotoxicity of AD.

Propofol Inhibits Glioma Stem Cell Growth and Migration and Their Interaction with Microglia via BDNF-AS and Extracellular Vesicles

Glioblastoma (GBM) is the most common and aggressive primary brain tumor. GBM contains a small subpopulation of glioma stem cells (GSCs) that are implicated in treatment resistance, tumor infiltration, and recurrence, and are thereby considered important therapeutic targets. Recent clinical studies have suggested that the choice of general anesthetic (GA), particularly propofol, during tumor resection, affects subsequent tumor response to treatments and patient prognosis. In this study, we investigated the molecular mechanisms underlying propofol's anti-tumor effects on GSCs and their interaction with microglia cells. Propofol exerted a dose-dependent inhibitory effect on the self-renewal, expression of mesenchymal markers, and migration of GSCs and sensitized them to both temozolomide (TMZ) and radiation. At higher concentrations, propofol induced a large degree of cell death, as demonstrated using microfluid chip technology. Propofol increased the expression of the lncRNA BDNF-AS, which acts as a tumor suppressor in GBM, and silencing of this lncRNA partially abrogated propofol's effects. Propofol also inhibited the pro-tumorigenic GSC-microglia crosstalk via extracellular vesicles (EVs) and delivery of BDNF-AS. In conclusion, propofol exerted anti-tumor effects on GSCs, sensitized these cells to radiation and TMZ, and inhibited their pro-tumorigenic interactions with microglia via transfer of BDNF-AS by EVs.

Colon cancer transcriptome

Over the last four decades, methodological innovations have continuously changed transcriptome profiling. It is now feasible to sequence and quantify the transcriptional outputs of individual cells or thousands of samples using RNA sequencing (RNA-seq). These transcriptomes serve as a connection between cellular behaviors and their underlying molecular mechanisms, such as mutations. This relationship, in the context of cancer, provides a chance to unravel tumor complexity and heterogeneity and uncover novel biomarkers or treatment options. Since colon cancer is one of the most frequent malignancies, its prognosis and diagnosis seem to be critical. The transcriptome technology is developing for an earlier and more accurate diagnosis of cancer which can provide better protectivity and prognostic utility to medical teams and patients. A transcriptome is a whole set of expressed coding and non-coding RNAs in an individual or cell population. The cancer transcriptome includes RNA-based changes. The combined genome and transcriptome of a patient may provide a comprehensive picture of their cancer, and this information is beginning to affect treatment decision-making in real-time. A full assessment of the transcriptome of colon (colorectal) cancer has been assessed in this review paper based on risk factors such as age, obesity, gender, alcohol use, race, and also different stages of cancer, as well as non-coding RNAs like circRNAs, miRNAs, lncRNAs, and siRNAs. Similarly, they have been examined independently in the transcriptome study of colon cancer.

Role of long noncoding RNAs; BDNF-AS and 17A and their relation to GABAergic dysfunction in Egyptian epileptic patients

Epilepsy is a chronic neurological disorder characterized by recurrent unprovoked seizures. Lately, long noncoding RNAs (lncRNAs) have been increasingly appreciated as regulators of epilepsy-related processes, however, their functional role in its pathogenesis is still to be explored. This study investigated the expression levels of lncRNAs; BDNF-AS and 17A in the sera of Egyptian patients with idiopathic generalized and symptomatic focal epilepsy and correlated their levels with brain-derived neurotrophic factor (BDNF), phosphorylated cAMP reaction element -binding protein (p-CREB), gamma- aminobutyric acid (GABA) and glutamate, to underline their related molecular mechanism. A total of 70 epileptic patients were divided into two clinical types, besides 30 healthy controls of matched age and sex. The expression levels of both lncRNAs were markedly upregulated in epileptic groups versus the healthy control group with predominance in the symptomatic focal one. Epileptic patients showed significantly lower levels of BDNF, p-CREB, GABA along with significant increase of glutamate levels and glutamate/ GABA ratio, especially in symptomatic focal versus idiopathic generalized epileptic ones. The obtained data raised the possibility that these lncRNAs might be involved in the pathogenesis of epilepsy via inhibition of GABA/p-CREB/BDNF pathway. The study shed light on the putative role of these lncRNAs in better diagnosis of epilepsy, particularly symptomatic focal epilepsy.

A Prognostic Cuproptosis-Related LncRNA Signature for Colon Adenocarcinoma

Background

Cuproptosis, a recently discovered form of cell death, is caused by copper levels exceeding homeostasis thresholds. Although Cu has a potential role in colon adenocarcinoma (COAD), its role in the development of COAD remains unclear.

Methods

In this study, 426 patients with COAD were extracted from the Cancer Genome Atlas (TCGA) database. The Pearson correlation algorithm was used to identify cuproptosis-related lncRNAs. Using the univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO) was used to select cuproptosis-related lncRNAs associated with COAD overall survival (OS). A risk model was established based on the multivariate Cox regression analysis. A nomogram model was used to evaluate the prognostic signature based on the risk model. Finally, mutational burden and sensitivity analyses of chemotherapy drugs were performed for COAD patients in the low- and high-risk groups.

Result

Ten cuproptosis-related lncRNAs were identified and a novel risk model was constructed. A signature based on ten cuproptosis-related lncRNAs was an independent prognostic predictor for COAD. Mutational burden analysis suggested that patients with high-risk scores had higher mutation frequency and shorter survival.

Conclusion

Constructing a risk model based on the ten cuproptosis-related lncRNAs could accurately predict the prognosis of COAD patients, providing a fresh perspective for future research on COAD.

Risk Stratification and Validation of Eleven Autophagy-Related lncRNAs for Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC), the most prevalent subtype of esophageal cancer, ranks sixth in cancer-related mortality, making it one of the deadliest cancers worldwide. The identification of potential risk factors for ESCC might help in implementing precision therapies. Autophagy-related lncRNAs are a group of non-coding RNAs that perform critical functions in the tumor immune microenvironment and therapeutic response. Therefore, we aimed to establish a risk model composed of autophagy-related lncRNAs that can serve as a potential biomarker for ESCC risk stratification. Using the RNA expression profile from 179 patients in the GSE53622 and GSE53624 datasets, we found 11 lncRNAs (AC004690.2, AC092159.3, AC093627.4, AL078604.2, BDNF-AS, HAND2-AS1, LINC00410, LINC00588, PSMD6-AS2, ZEB1-AS1, and LINC02586) that were co-expressed with autophagy genes and were independent prognostic factors in multivariate Cox regression analysis. The risk model was constructed using these autophagy-related lncRNAs, and the area under the receiver operating characteristic curve (AUC) of the risk model was 0.728. To confirm that the model is reliable, the data of 174 patients from The Cancer Genome Atlas (TCGA) esophageal cancer dataset were analyzed as the testing set. A nomogram for ESCC prognosis was developed using the risk model and clinic-pathological characteristics. Immune function annotation and tumor mutational burden of the two risk groups were analyzed and the high-risk group displayed higher sensitivity in chemotherapy and immunotherapy. Expression of differentially expressed lncRNAs were further validated in human normal esophageal cells and esophageal cancer cells. The constructed lncRNA risk model provides a useful tool for stratifying risk and predicting the prognosis of patients with ESCC, and might provide novel targets for ESCC treatment.

Expression characteristics of long non-coding RNA in colon adenocarcinoma and its potential value for judging the survival and prognosis of patients: bioinformatics analysis based on The Cancer Genome Atlas database

Background

To investigate the expression characteristics of long non-coding RNA (lncRNA) in colon adenocarcinoma (COAD) and its potential value in predicting the prognosis of patient survival.

Methods

We downloaded COAD-related RNA sequencing (RNA-seq) data and patient survival data from The Cancer Genome Atlas (TCGA). The data were analyzed for lncRNA expression differences, subjected to Cox regression analysis for survival rate, and Kaplan-Meier (KM) survival curves were plotted to analyze the role of the key genes related to prognostic survival by pathway enrichment analysis.

Results

The data of 494 COAD clinical samples from TCGA were analyzed; 204 lncRNAs were differentially expressed, 156 were up-regulated, and 48 were down-regulated. The 10 genes with the most significant expression differences were Linc02418, Blacat1, ELFN1-AS1, CRNDE, AC002384.1, AL353801.1, LINC01645, AC073283.2, AC087379.1, and LINC00484. Cox regression analysis of 204 lncRNA genes showed that 23 lncRNA genes with significant effects on the prognosis and survival rate of COAD patients were obtained when P<0.05 was used as the threshold. With P≤0.001 as the threshold, the KM curves of 4 genes (Linc02257, Linc02474, Ac010789.1, Ac083967.1) were statistically significant (P<0.05). The gene Linc02257 was selected for Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and it was revealed that the inheritance of Linc02257-regulated gene expression was closely related to tumor development, such as collagen-containing extracellular matrix, organogenesis, activity of membrane protein receptors, and ion channel activity. The signaling pathways regulated by Linc02257 were also closely related to tumors, such as neuroactive ligand-receptor interaction, the PI3K-AKT signaling pathway, calcium signaling pathway, and protein digestion and absorption.

Conclusions

In COAD, lncRNA is differentially expressed and plays an important role in the disease regulation. It has potential application value in the diagnosis, targeted therapy, and prognosis of COAD patients.

The long and short non-coding RNAs modulating EZH2 signaling in cancer

Non-coding RNAs (ncRNAs) are a large family of RNA molecules with no capability in encoding proteins. However, they participate in developmental and biological processes and their abnormal expression affects cancer progression. These RNA molecules can function as upstream mediators of different signaling pathways and enhancer of zeste homolog 2 (EZH2) is among them. Briefly, EZH2 belongs to PRCs family and can exert functional roles in cells due to its methyltransferase activity. EZH2 affects gene expression via inducing H3K27me3. In the present review, our aim is to provide a mechanistic discussion of ncRNAs role in regulating EZH2 expression in different cancers. MiRNAs can dually induce/inhibit EZH2 in cancer cells to affect downstream targets such as Wnt, STAT3 and EMT. Furthermore, miRNAs can regulate therapy response of cancer cells via affecting EZH2 signaling. It is noteworthy that EZH2 can reduce miRNA expression by binding to promoter and exerting its methyltransferase activity. Small-interfering RNA (siRNA) and short-hairpin RNA (shRNA) are synthetic, short ncRNAs capable of reducing EZH2 expression and suppressing cancer progression. LncRNAs mainly regulate EZH2 expression via targeting miRNAs. Furthermore, lncRNAs induce EZH2 by modulating miRNA expression. Circular RNAs (CircRNAs), like lncRNAs, affect EZH2 expression via targeting miRNAs. These areas are discussed in the present review with a focus on molecular pathways leading to clinical translation.

MicroRNA-363-3p, negatively regulated by long non-coding RNA small nucleolar RNA host gene 5, inhibits tumor progression by targeting Aurora kinase A in colorectal cancer

MicroRNA-363-3p (miR-363-3p), reportedly, exhibits a tumor-suppressive role in human malignancies. Herein, our research was designed to further explain the functions and molecular mechanisms of miR-363-3p in the progression of colorectal cancer (CRC). With in vitro models, this study found that miR-363-3p was markedly under-expressed in CRC tissues and cells, and its overexpression suppressed the viability, migration, and invasion of CRC cells, and promoted cell apoptosis, whereas inhibiting miR-363-3p expression exhibited an opposite role. Additionally, aurora kinase A (AURKA), capable of counteracting the impacts of miR-363-3p on malignant biological behaviors of CRC cells, was identified as a direct target of miR-363-3p. Besides, miR-363-3p was sponged by long non-coding RNA small nucleolar RNA host gene 5 (SNHG5), which suppressed miR-363-3p expression. This research shows that SNHG5/miR-363-3p/AURKA axis partakes in CRC progression.

Exosomal-long non-coding RNAs journey in colorectal cancer: Evil and goodness faces of key players

Exosomes are nano-vesicles (NVs) secreted by cells and take part in cell-cell communications. Lately, these exosomes were proved to have dual faces in cancer. Actually, they can contribute to carcinogenesis through epithelial-mesenchymal transition (EMT), angiogenesis, metastasis and tumor microenvironment (TME) of various cancers, including colorectal cancer (CRC). On the other hand, they can be potential targets for cancer treatment. CRC is one of the most frequent tumors worldwide, with incidence rates rising in the recent decades. In its early stage, CRC is asymptomatic with poor treatment outcomes. Therefore, finding a non-invasive, early diagnostic biomarker tool and/or suitable defender to combat CRC is mandatory. Exosomes provide enrichment and safe setting for their cargos non-coding RNAs (ncRNAs) and proteins, whose expression levels can be upregulated ordown-regulated in cancer. Hence, exosomes can be used as diagnostic and/or prognostic tools for cancer. Moreover, exosomes can provide a novel potential therapeutic modality for tumors via loading with specific chemotherapeutic agents, with the advantage of possible tumor targeting. In this review, we will try to collect and address recent studies concerned with exosomes and their cargos' implications for CRC diagnosis and/or hopefully, treatment.

A concise review on the role of BDNF-AS in human disorders

Brain-derived neurotrophic factor-antisense (BDNF-AS) is a long non-coding RNA with tens of alternatively spliced variants being transcribed from 11p14 cytogenetic band. As a naturally occurring anti-sense, it regulates expression of BDNF, a factor which as essential roles in the pathoetiology of neurodevelopmental diseases. Notably, BDNF-AS has been reported to be down-regulated in colorectal cancer, osteosarcoma, esophageal cancer, glioblastoma, prostate cancer, cervical cancer and breast cancer. This lncRNA has direct/indirect functional interactions with GSK-3β, EZH2, miR-214, PABPC1, RAX2, DLG5, p53 and ADAR as well as RNH1/TRIM21/mTOR signaling. In prostate and breast cancers, down-regulation of BDNF-AS has been associated with poor clinical outcome. In the present review, we assessed the existing literature on the role of BDNF-AS in this process and summarized the available data in three distinct sections based of the methodology of experiments and source of expression assays. We also summarized the role of BDNF-AS in non-neoplastic conditions.

N6-Methylandenosine-Related lncRNAs Predict Prognosis and Immunotherapy Response in Bladder Cancer

Both lncRNAs and the N6-methyladenosine (m6A) modification are key regulators of tumorigenesis and innate immunity. However, little is known about the m6A modification of lncRNAs and their clinical and immune relevance in bladder cancer. In this study, we identified m6A-related lncRNAs using Pearson correlation analysis in The Cancer Genome Atlas (TCGA) and the IMvigor210 datasets. Next, univariate Cox regression was performed using the TCGA dataset to filter prognostic m6A-related lncRNAs, which were further subjected to the least absolute shrinkage and selection operator (LASSO) Cox regression to establish a 12 m6A-related lncRNA prognostic score (m6A-LRS). The m6A-LRS was validated in the IMvigor210 dataset. In addition, high m6A-LRS tumors, characterized by decreased tumor mutation load and neoantigen load, showed poorer response to immunotherapy than those with low m6A-LRS in the IMvigor210 dataset. Further, we constructed an m6A-LRS-based nomogram that demonstrated a strong ability to predict overall survival in patients with bladder cancer. Moreover, enrichment analysis revealed that tumor-associated biological processes, oncogenic signaling, and tumor hallmarks were commonly associated with a high m6A-LRS. Gene set variation analysis also indicated that high m6A-LRS was associated with activation of canonical oncogenic signatures, such as the epithelial-to-mesenchymal transition, cell cycle regulators, and DNA replication, as well as activation of immunosuppressive signatures, such as the T-cell exhaustion and pan-fibroblast-TGF-β response signatures. Furthermore, we observed distinct tumor microenvironment cell infiltration characteristics between high- and low-risk tumors. High m6A-LRS tumors showed reduced infiltration of CD8+ T-cells and enhanced infiltration of macrophages and fibroblasts. Additionally, we established a competing endogenous RNA network based on the12 m6A-related lncRNAs. Finally, three lncRNAs (SNHG16, SBF2-AS1, and BDNF-AS) were selected for further validation. The qualitative PCR assay on 10 pairs of bladder cancer and adjacent normal control samples validated the differential expression, and methylated RNA immunoprecipitation (MeRIP) analysis demonstrated a robust m6A enrichment in T24 bladder cancer cells compared with normal uroepithelial cells (SVHUC-1). In conclusion, this study introduced an m6A-related lncRNA signature that identified a subgroup of patients with poor prognoses and suboptimal immune responses, thus providing novel approaches for treatment response prediction and patient stratification in bladder cancer.

Long non-coding RNAs in colorectal cancer: Novel oncogenic mechanisms and promising clinical applications

Colorectal cancer (CRC) is the third most common malignancy and ranks as the second leading cause of cancer-related deaths worldwide. Despite the improvements in CRC diagnosis and treatment approaches, a considerable proportion of CRC patients still suffers from poor prognosis due to late disease detections and lack of personalized disease managements. Recent evidences have not only provided important molecular insights into their mechanistic behaviors but also indicated that identification of cancer-specific long non-coding RNAs (LncRNAs) could benefit earlier disease detections and improve treatment outcomes in patients suffering from CRC. LncRNAs have raised extensive attentions as they participate in various hallmarks of CRC. The mechanistic evidence gleaned in the recent decade clearly reveals that lncRNAs exert their oncogenic roles by regulating autophagy, epigenetic modifications, enhancing stem phenotype and modifying tumor microenvironment. In view of their pleiotropic functional roles in malignant progression, and their frequently dysregulated expression in CRC patients, they have great potential to be reliable diagnostic and prognostic biomarkers, as well as therapeutic targets for CRC. In the present review, we will focus on the oncogenic roles of lncRNAs and related mechanisms in CRC as well as discuss their clinical potential in the early diagnosis, prognostic prediction and therapeutic translation in patients with this malignancy.

Mechanisms of long non-coding RNA function in colorectal cancer tumorigenesis

Colorectal cancer (CRC) is one of the most common cancers globally. Although a variety of CRC screening methods have been developed, many patients are diagnosed at advanced stages of CRC with tumor invasion and distance metastasis. Several studies have suggested the long noncoding RNAs (lncRNAs) as one of the main contributors in CRC tumorigenesis, although the exact underlying mechanism of lncRNAs in CRC is still unknown. Numerous studies have indicated aberrant expression of lncRNAs in CRC through different modes of action such as cell proliferation, apoptosis, cell cycle, DNA repair response, drug-resistance, migration, and metastasis. Furthermore, lncRNA polymorphisms can influence the risk of CRC development. Accordingly, lncRNAs can be served as promising diagnostic or prognostic biomarkers and also desired therapeutic targets affecting the outcome of patients with CRC. In this review, we summarized the updated and novel evidence that identifies different roles of lncRNAs in the tumorigenesis of CRC.

LncRNA regulation: New frontiers in epigenetic solutions to drug chemoresistance

Long-noncoding RNAs (lncRNAs) have been shown to participate in sensitizing or de-sensitizing cancer cells to chemical drugs during cancer therapeutics. Notably, a plethora of lncRNAs have been confirmed to be associated with epigenetic controllers and regulate histone protein modification or DNA methylation states in the process of gene transcription. This correlation between lncRNAs and epigenetic regulators can induce the expression of core genes to trigger drug resistance. In addition, epigenetic signatures are considered to be effective and attractive biomarkers for monitoring drug therapeutic effects because they are inheritable, dynamic, and reversible. Therefore, the regulatory mechanism between lncRNAs and epigenetic machinery can serve as a novel indicator and target to overcome or reverse drug resistance in cancer therapy. In this review, we also presented a curated selection of computational tools (including online databases and network analysis) in the area of epigenetics. A classic workflow for lncRNA expression network analysis is presented, providing guidance for non-bioinformaticians to identify significant correlation between lncRNAs and other biomolecules.

circHIPK3 Acts as Competing Endogenous RNA and Promotes Non-Small-Cell Lung Cancer Progression through the miR-107/BDNF Signaling Pathway

Circular RNAs (circRNAs) act as a crucial part in many human diseases, particularly in cancers. circRNA HIPK3 (circHIPK3) is a special circRNA that may participate in the oncogenesis of non-small-cell lung cancer (NSCLC), even though its latent regulatory mechanism is not very clear. Here, we studied the roles of circHIPK3 in NSCLC. qRT-PCR assay was applied to study the expression of circHIPK3 in NSCLC. The influence of circHIPK3 on NSCLC was estimated by silencing circHIPK3 and miR-107 mock transfection and brain-derived neurotrophic factor (BDNF) overexpression, and the correlation between circHIPK3, miR-107, and BDNF was evaluated by dual-luciferase reporter assay. The results showed that circHIPK3 expression was upregulated in NSCLC cells. circHIPK3 knockdown inhibited the migration and proliferation of NSCLC cells by promoting the expression of miR-107. circHIPK3 could be used as a miR-107 sponge to promote BDNF cell proliferation. The dual-luciferase reporter assay proved that miR-107 was the target of circHIPK3, and miR-107 had an interaction with the 3′untranslated region of BDNF. miR-107 overexpression inhibited BDNF-mediated NSCLC cell proliferation. These results indicate that circHIPK3 promotes tumor progression through a new circHIPK3/miR-107/BDNF axis, which offers potential markers and medical treatment for NSCLC.

LDNFSGB: prediction of long non-coding rna and disease association using network feature similarity and gradient boosting

BACKGROUND

A large number of experimental studies show that the mutation and regulation of long non-coding RNAs (lncRNAs) are associated with various human diseases. Accurate prediction of lncRNA-disease associations can provide a new perspective for the diagnosis and treatment of diseases. The main function of many lncRNAs is still unclear and using traditional experiments to detect lncRNA-disease associations is time-consuming.

RESULTS

In this paper, we develop a novel and effective method for the prediction of lncRNA-disease associations using network feature similarity and gradient boosting (LDNFSGB). In LDNFSGB, we first construct a comprehensive feature vector to effectively extract the global and local information of lncRNAs and diseases through considering the disease semantic similarity (DISSS), the lncRNA function similarity (LNCFS), the lncRNA Gaussian interaction profile kernel similarity (LNCGS), the disease Gaussian interaction profile kernel similarity (DISGS), and the lncRNA-disease interaction (LNCDIS). Particularly, two methods are used to calculate the DISSS (LNCFS) for considering the local and global information of disease semantics (lncRNA functions) respectively. An autoencoder is then used to reduce the dimensionality of the feature vector to obtain the optimal feature parameter from the original feature set. Furthermore, we employ the gradient boosting algorithm to obtain the lncRNA-disease association prediction.

CONCLUSIONS

In this study, hold-out, leave-one-out cross-validation, and ten-fold cross-validation methods are implemented on three publicly available datasets to evaluate the performance of LDNFSGB. Extensive experiments show that LDNFSGB dramatically outperforms other state-of-the-art methods. The case studies on six diseases, including cancers and non-cancers, further demonstrate the effectiveness of our method in real-world applications.

Integration analysis of long non-coding RNA (lncRNA) role in tumorigenesis of colon adenocarcinoma

Background

Colon adenocarcinoma (COAD) is one of the most common gastrointestinal cancers globally. Molecular aberrations of tumor suppressors and/or oncogenes are the main contributors to tumorigenesis. However, the exact underlying mechanisms of COAD pathogenesis are clearly not known yet. In this regard, there is an urgent need to indicate promising potential diagnostic and prognostic biomarkers in COAD patients.

Methods

In the current study, level 3 RNA-Seq and miR-Seq data and corresponding clinical data of colon adenocarcinoma (COAD) were retrieved from the TCGA database. The “limma” package in R software was utilized to indicate the differentially expressed genes. For in silico functional analysis, GO and KEGG signaling pathways were conducted. PPI network was constructed based on the STRING online database by Cytoscape 3.7.2. A ceRNA network was also constructed by “GDCRNATools” package in R software. Kaplan-Meier survival analysis (log-rank test) and ROC curve analysis were used to indicate the diagnostic and prognostic values of the biomarkers.

Results

The differential expression data demonstrated that 2995 mRNAs, 205 lncRNAs, and 345 miRNAs were differentially expressed in COAD. The GO and KEGG pathway analysis indicated that the differentially expressed mRNAs were primarily enriched in canonical processes in cancer. The PPI network showed that the CDKN2A, CCND1, MYC, E2F, CDK4, BRCA2, CDC25B, and CDKN1A proteins were the critical hubs. In addition, the Kaplan-Meier analysis revealed that 215 mRNAs, 14 lncRNAs, and 39 miRNAs were associated with overall survival time in the patients. Also, the ceRNA network data demonstrated that three lncRNAs including MIR17HG, H19, SNHG1, KCNQ1OT1, MALAT1, GAS5, SNHG20, OR2A1-AS1, and MAGI2-AS3 genes were involved in the development of COAD.

Conclusions

Our data suggested several promising lncRNAs in the diagnosis and prognosis of patients with COAD.

Long noncoding RNAs as potential biomarkers in retinoblastoma: a systematic review and meta-analysis

Background

Retinoblastoma is the most common malignant rare intraocular tumor of childhood. Long noncoding RNAs (lncRNAs) have been reported participating in its progression, but their significance remains inconclusive. We conducted this systematic review and meta-analysis to explore specific lncRNA biomarker in patients with retinoblastoma.

Materials and methods

Eligible articles were searched from the Pubmed, Web of Science, Embase and the Cochrane library. Hazard ratios (HRs) and odds ratios (ORs) were extracted or calculated to evaluate the relationship between lncRNAs and retinoblastoma. The meta-analysis part was conducted with STATA v.15 software.

Results

A total of 9 articles with 834 retinoblastoma patients are yielded. Heterogeneity among HRs of overall survival (OS) is notably high (I² = 91.3%, p < 0.001). Subgroup analysis suggests that elevated expression of lncRNA BDNF-AS and MT1JP are favorable factors in OS (pooled HR = 1.89, 95% CI 1.72-2.07, I² = 0%). Six articles included optic nerve invasion as a clinicopathological outcome and showed a notable correlation (pooled HR = 2.38, 95% CI 1.26-3.50, I² = 0.0%). We validate our analysis via the public dataset and also sum up the studies of lncRNA BDNF-AS and MT1JP in other cancers.

Conclusion

Differential expression of lncRNAs has been reported in retinoblastoma. Some of them showed potential in retinoblastoma prognosis and progression.

In silico analyses identify lncRNAs: WDFY3-AS2, BDNF-AS and AFAP1-AS1 as potential prognostic factors for patients with triple-negative breast tumors

BACKGROUND

Long non-coding RNAs (lncRNAs) are characterized as having 200 nucleotides or more and not coding any protein, and several been identified as differentially expressed in several human malignancies, including breast cancer.

METHODS

Here, we evaluated lncRNAs differentially expressed in triple-negative breast cancer (TNBC) from a cDNA microarray data set obtained in a previous study from our group. Using in silico analyses in combination with a review of the current literature, we identify three lncRNAs as potential prognostic factors for TNBC patients.

RESULTS

We found that the expression of WDFY3-AS2, BDNF-AS, and AFAP1-AS1 was associated with poor survival in patients with TNBCs. WDFY3-AS2 and BDNF-AS are lncRNAs known to play an important role in tumor suppression of different types of cancer, while AFAP1-AS1 exerts oncogenic activity.

CONCLUSION

Our findings provided evidence that WDFY3-AS2, BDNF-AS, and AFAP1-AS1 may be potential prognostic factors in TNBC development.