TGF-β-activated lncRNA LINC00115 is a critical regulator of glioma stem-like cell tumorigenicity

Long Non-coding RNA LINC00115 Contributes to the Progression of Colorectal Cancer by Targeting miR-489-3p via the PI3K/AKT/mTOR Pathway

Long non-coding RNAs (lncRNAs) are tumor-related regulators and have been found to be involved in the underlying molecular mechanisms of colorectal cancer (CRC). However, the role of lncRNA LINC00115 during CRC progression is not entirely elucidated. In this study, we discovered that LINC00115 was significantly overexpressed in CRC, and its overexpression predicted poor patient outcomes. Downregulation of LINC00115 markedly inhibited CRC cell proliferation, increased cell apoptosis, and suppressed cell migration and invasion. Moreover, downregulation of LINC00115 led to the inactivation of PI3K/AKT/mTOR signaling. Bioinformatics analysis identified miR-489-3p as a candidate target of LINC00115. Furthermore, we revealed an inverse correlation between LINC00115 and miR-489-3p in CRC tissues. Importantly, by luciferase reporter assay, we found that miR-489-3p might directly target LINC00115, and downregulation of miR-489-3p could rescue the biological effects induced by the absence of LINC0015. In conclusion, our findings demonstrated that LINC00115 serves as an oncogene in CRC metastasis. Deeper understanding of the LINC00115/miR-489-3p axis might provide potential therapeutic targets against CRC metastasis.

Long non-coding RNAs and TGF-β signaling in cancer

Cancer is driven by genetic mutations in oncogenes and tumor suppressor genes and by cellular events that develop a misregulated molecular microenvironment in the growing tumor tissue. The tumor microenvironment is guided by the excessive action of specific cytokines including transforming growth factor-β (TGF-β), which normally controls embryonic development and the homeostasis of young or adult tissues. As a consequence of the genetic alterations generating a given tumor, TGF-β can preserve its homeostatic function and attempt to limit neoplastic expansion, whereas, once the tumor has progressed to an aggressive stage, TGF-β can synergize with various oncogenic stimuli to facilitate tumor invasiveness and metastasis. TGF-β signaling mechanisms via Smad proteins, various ubiquitin ligases, and protein kinases are relatively well understood. Such mechanisms regulate the expression of genes encoding proteins or non-coding RNAs. Among non-coding RNAs, much has been understood regarding the regulation and function of microRNAs, whereas the role of long non-coding RNAs is still emerging. This article emphasizes TGF-β signaling mechanisms leading to the regulation of non-coding genes, the function of such non-coding RNAs as regulators of TGF-β signaling, and the contribution of these mechanisms in specific hallmarks of cancer.

Identification of a competing endogenous RNA network associated with prognosis of pancreatic adenocarcinoma

Background

Emerging evidence suggests that competing endogenous RNAs plays a crucial role in the development and progress of pancreatic adenocarcinoma (PAAD). The objective was to identify a new lncRNA-miRNA-mRNA network as prognostic markers, and develop and validate a multi-mRNAs-based classifier for predicting overall survival (OS) in PAAD.

Methods

Data on pancreatic RNA expression and clinical information of 445 PAAD patients and 328 normal subjects were downloaded from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Genotype-Tissue Expression (GTEx). The weighted correlation network analysis (WGCNA) was used to analyze long non-coding RNA (lncRNA) and mRNA, clustering genes with similar expression patterns. MiRcode was used to predict the sponge microRNAs (miRNAs) corresponding to lncRNAs. The downstream targeted mRNAs of miRNAs were identified by starBase, miRDB, miRTarBase and Targetscan. A multi-mRNAs-based classifier was develop using least absolute shrinkage and selection operator method (LASSO) COX regression model, which was tested in an independent validation cohort.

Results

A lncRNA-miRNA-mRNA co-expression network which consisted of 60 lncRNAs, 3 miRNAs and 3 mRNAs associated with the prognosis of patients with PAAD was established. In addition, we constructed a 14-mRNAs-based classifier based on a training cohort composed of 178 PAAD patients, of which the area under receiver operating characteristic (AUC) in predicting 1-year, 3-year, and 5-year OS was 0.719, 0.806 and 0.794, respectively. The classifier also shown good prediction function in independent verification cohorts, with the AUC of 0.604, 0.639 and 0.607, respectively.

Conclusions

A novel competitive endogenous RNA (ceRNA) network associated with progression of PAAD could be used as a reference for future molecular biology research.

The functions of long non-coding RNAs in neural stem cell proliferation and differentiation

The capacities for neural stem cells (NSCs) self-renewal with differentiation are need to be precisely regulated for ensuring brain development and homeostasis. Recently, increasing number of studies have highlighted that long non-coding RNAs (lncRNAs) are associated with NSC fate determination during brain development stages. LncRNAs are a class of non-coding RNAs more than 200 nucleotides without protein-coding potential and function as novel critical regulators in multiple biological processes. However, the correlation between lncRNAs and NSC fate decision still need to be explored in-depth. In this review, we will summarize the roles and molecular mechanisms of lncRNAs focusing on NSCs self-renewal, neurogenesis and gliogenesis over the course of neural development, still more, dysregulation of lncRNAs in all stage of neural development have closely relationship with development disorders or glioma. In brief, lncRNAs may be explored as effective modulators in NSCs related neural development and novel biomarkers for diagnosis and prognosis of neurological disorders in the future.

Identification of m6A-related genes and m6A RNA methylation regulators in pancreatic cancer and their association with survival

BACKGROUND

N6-methyladenosine (m6A) modification holds an important position in tumorigenesis and metastasis because it can change gene expression and even function in multiple levels including RNA splicing, stability, translocation and translation. In present study, we aim to conducted comprehensive investigation on m6A RNA methylation regulators and m6A-related genes in pancreatic cancer and their association with survival time.

METHODS

Based on Univariate Cox regression analysis, protein-protein interaction analysis, LASSO Cox regression, a risk prognostic model, STRING, Spearman and consensus clustering analysis, data from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database was used to analyze 15 m6A RNA methylation regulators that were widely reported and 1,393 m6A-related genes in m6Avar.

RESULTS

We found that 283 candidate m6A RNA methylation-related genes and 4 m6A RNA methylation regulatory factors, including RNA binding motif protein 15 (RBM15), methyltransferase like 14 (METTL14), fat mass and obesity-associated protein (FTO), and α-ketoglutarate-dependent dioxygenase AlkB homolog 5 (ALKBH5), differed significantly among different stages of the American Joint Committee on Cancer (AJCC) staging system. Protein-protein interaction analysis indicated epidermal growth factor receptor (EGFR), plectin-1 (PLEC), BLM RecQ like helicase (BLM), and polo like kinase 1 (PLK1) were closely related to other genes and could be considered as hub genes in the network. The results of LASSO Cox regression and the risk prognostic model indicated that AJCC stage, stage T and N, KRAS mutation status and x8q23.3 CNV fragment mutation differed significantly between the high-risk and the low-risk subgroups. The AUCs of 1 to 5 years after surgery were all more than 0.7 and increased year by year. Finally, we found KRAS mutation status and AJCC stage differed significantly among these groups after TCGA samples divided into subgroups with k=7. Moreover, we identified four m6A RNA methylation related genes expressed significantly differently among these seven subgroups, including collagen type VII alpha 1 chain (COL7A1), branched chain amino acid transaminase 1 (BCAT1), zinc finger protein 596 (ZNF596), and PLK1.

CONCLUSIONS

Our study systematically analyzed the m6A RNA methylation related genes, including expression, protein-protein interaction, potential function, and prognostic value and provides important clues to further research on the function of RNA m6A methylation and its related genes in pancreatic cancer.

System level characterization of small molecule drugs and their affected long noncoding RNAs

Long noncoding RNAs (lncRNAs) have multiple regulatory roles and are involved in many human diseases. A potential therapeutic strategy based on targeting lncRNAs was recently developed. To gain insight into the global relationship between small molecule drugs and their affected lncRNAs, we constructed a small molecule lncRNA network consisting of 1206 nodes (1033 drugs and 173 lncRNAs) and 4770 drug-lncRNA associations using LNCmap, which reannotated the microarray data from the Connectivity Map (CMap) database. Based on network biology, we found that the connected drug pairs tended to share the same targets, indications, and side effects. In addition, the connected drug pairs tended to have a similar structure. By inferring the functions of lncRNAs through their co-expressing mRNAs, we found that lncRNA functions related to the modular interface were associated with the mode of action or side effects of the corresponding connected drugs, suggesting that lncRNAs may directly/indirectly participate in specific biological processes after drug administration. Finally, we investigated the tissue-specificity of drug-affected lncRNAs and found that some kinds of drugs tended to have a broader influence (e.g. antineoplastic and immunomodulating drugs), whereas some tissue-specific lncRNAs (nervous system) tended to be affected by multiple types of drugs.