Long noncoding RNA GSTM3TV2 upregulates LAT2 and OLR1 by competitively sponging let-7 to promote gemcitabine resistance in pancreatic cancer.
ABSTRACT: BACKGROUND:Chemoresistance is one of the main causes of poor prognosis in pancreatic cancer patients. Understanding the mechanisms implicated in chemoresistance of pancreatic cancer is critical to improving patient outcomes. Recent evidences indicate that the long noncoding RNAs (lncRNAs) are involving in chemoresistance of pancreatic cancer. However, the mechanisms of lncRNAs contribute to resistance in pancreatic cancer and remain largely unknown. The objective of this study is to construct a chemoresistance-related lncRNA-associated competing endogenous RNA (ceRNA) network of pancreatic cancer and identify the key lncRNAs in regulating chemoresistance of the network. METHODS:Firstly, lncRNA expression profiling of gemcitabine-resistant pancreatic cancer cells was performed to identify lncRNAs related to chemoresistance by microarray analysis. Secondly, with insights into the mechanism of ceRNA, we used a bioinformatics approach to construct a chemoresistance-related lncRNAs-associated ceRNA network. We then identified the topological key lncRNAs in the ceRNA network and demonstrated its function or mechanism in chemoresistance of pancreatic cancer using molecular biological methods. Further studies evaluated its expression to assess its potential association with survival in patients with pancreatic cancer. RESULTS:Firstly, we demonstrated that lncRNAs were dysregulated in gemcitabine-resistant pancreatic cancer cells. We then constructed a chemoresistance-related lncRNA-associated ceRNA network and proposed that lncRNA Homo sapiens glutathione S-transferase mu 3, transcript variant 2 and noncoding RNA (GSTM3TV2; NCBI Reference Sequence: NR_024537.1) might act as a key ceRNA to enhance chemoresistance by upregulating L-type amino acid transporter 2 (LAT2) and oxidized low-density lipoprotein receptor 1(OLR1) in pancreatic cancer. Further studies demonstrated that GSTM3TV2, overexpressed in gemcitabine-resistant cells, enhanced the gemcitabine resistance of pancreatic cancer cells in vitro and in vivo. Mechanistically, we identified that GSTM3TV2 upregulated LAT2 and OLR1 by competitively sponging let-7 to promote gemcitabine resistance. In addition, we revealed that the expression levels of GSTM3TV2 were significantly increased in pancreatic cancer tissues and were associated with poor prognosis. CONCLUSION:Our results suggest that GSTM3TV2 is a crucial oncogenic regulator involved in chemoresistance and could be a new therapeutic target or prognostic marker in pancreatic cancer.
Project description:BACKGROUND:Reprogrammed energy metabolism has become an emerging hallmark of cancer in recent years. Transporters have been reported to be amino acid sensors involved in controlling mTOR recruitment and activation, which is crucial for the growth of both normal and tumor cells. L-type amino acid transporter 2 (LAT2), encoded by the SLC7A8 gene, is a Na+-independent neutral amino acid transporter and is responsible for transporting neutral amino acids, including glutamine, which can activate mTOR. Previous studies have shown that LAT2 was overexpressed in gemcitabine-resistant pancreatic cancer cells. However, the role of LAT2 in chemoresistance in pancreatic cancer remains uncertain and elusive. METHODS:The effects of LAT2 on biological behaviors were analyzed. LAT2 and LDHB levels in tissues were detected, and the clinical value was evaluated. RESULTS:We demonstrated that LAT2 emerged as an oncogenic protein and could decrease the gemcitabine sensitivity of pancreatic cancer cells in vitro and in vivo. The results of a survival analysis indicated that high expression levels of both LAT2 and LDHB predicted a poor prognosis in patients with pancreatic cancer. Furthermore, we found that LAT2 could promote proliferation, inhibit apoptosis, activate glycolysis and alter glutamine metabolism to activate mTOR in vitro and in vivo. Next, we found that gemcitabine combined with an mTOR inhibitor (RAD001) could reverse the decrease in chemosensitivity caused by LAT2 overexpression in pancreatic cancer cells. Mechanistically, we demonstrated that LAT2 could regulate two glutamine-dependent positive feedback loops (the LAT2/p-mTORSer2448 loop and the glutamine/p-mTORSer2448/glutamine synthetase loop) to promote glycolysis and decrease gemcitabine (GEM) sensitivity in pancreatic cancer. CONCLUSION:Taken together, our data reveal that LAT2 functions as an oncogenic protein and could regulate glutamine-dependent mTOR activation to promote glycolysis and decrease GEM sensitivity in pancreatic cancer. The LAT2-mTOR-LDHB pathway might be a promising therapeutic target in pancreatic cancer.
Project description:Pancreatic adenocarcinoma (PAAD) is a highly aggressive and metastatic cancer characterized by poor survival rates. Long non-coding RNAs (lncRNAs) play important roles in various biological processes, including cancer and PAAD. To identify the specific lncRNAs associated with PAAD and analyze their function, we constructed a global triple network based on the competitive endogenous RNA (ceRNA) theory and RNA-seq data from The Cancer Genome Atlas. Using 182 PAAD cases, we established a lncRNA-miRNA-mRNA co-expression network, which was composed of 43 lncRNA nodes, 253 mRNA nodes, 11 miRNA nodes, and 475 edges. Six lncRNAs in the ceRNA network were closely related to overall survival, and a three-lncRNA signature predicted survival of PAAD patients. Protein-protein interaction network data revealed that five genes were associated with overall survival. These results provide novel insight into the function of a lncRNA-associated ceRNA network in the pathogenesis of PAAD, and indicate that the identified three-lncRNA signature may serve as an independent prognostic marker in PAAD.
Project description:Background:Long noncoding RNAs (lncRNAs) play important roles in competing endogenous RNA (ceRNA) networks involved in the development and progression of various cancers, including muscle-invasive bladder cancer (MIBC). Purpose:This study aims to construct the lncRNA-associated ceRNA network and identify lncRNA signatures correlated with the clinical features of MIBC tissue samples from The Cancer Genome Atlas (TGCA) database. Methods:The differential expression profiles of MIBC associated lncRNAs, miRNAs and mRNAs were obtained from TCGA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to determine the principal functions of significantly dysregulated mRNAs. The dysregulated lncRNA-associated ceRNA network of MIBC was constructed based on the bioinformatics data, and the correlations between lncRNA expression and clinical features were analyzed using a weighted gene coexpression network analysis (WGCNA). Six cancer specific lncRNAs from the ceRNA network were randomly selected to detect their expression in 32 paired MIBC tissue samples and 5 bladder cancer cell lines using quantitative real-time polymerase chain reaction (qRT-PCR). Results:The ceRNA network was constructed with 30 lncRNAs, 13 miRNAs and 32 mRNAs. Seventeen lncRNAs in the ceRNA network correlated with certain clinical features, and only 1 lncRNA (MIR137HG) correlated with the overall survival (OS) of patients with MIBC (log-rank test P<0.05). GO and KEGG analyses revealed roles for the potential mRNA targets of MIR137HG in epithelial cell differentiation and the peroxisome proliferator-activated receptor (PPAR) and tumor necrosis factor (TNF) signaling pathways. The expression data from TCGA were highly consistent with the verification results of the MIBC tissue samples and bladder cancer cell lines. Conclusion:These findings improve our understanding of the regulatory mechanism of the lncRNA-miRNA-mRNA ceRNA network and reveal potential lncRNAs as prognostic biomarkers of MIBC.
Project description:Long noncoding RNAs (lncRNAs) regulate gene expression by acting with microRNAs (miRNAs). However, the roles of cancer specific lncRNA and its related competitive endogenous RNAs (ceRNA) network in hepatocellular cell carcinoma (HCC) are not fully understood. The lncRNA profiles in 372 HCC patients, including 372 tumor and 48 adjacent non-tumor liver tissues, from The Cancer Genome Atlas (TCGA) and NCBI GEO omnibus (GSE65485) were analyzed. Cancer specific lncRNAs (or HCC related lncRNAs) were identified and correlated with clinical features. Based on bioinformatics generated from miRcode, starBase, and miRTarBase, we constructed an lncRNA-miRNA-mRNA network (ceRNA network) in HCC. We found 177 cancer specific lncRNAs in HCC (fold change ? 1.5, P < 0.01), 41 of them were also discriminatively expressed with gender, race, tumor grade, AJCC tumor stage, and AJCC TNM staging system. Six lncRNAs (CECR7, LINC00346, MAPKAPK5-AS1, LOC338651, FLJ90757, and LOC283663) were found to be significantly associated with overall survival (OS, log-rank P < 0.05). Collectively, our results showed the lncRNA expression patterns and a complex ceRNA network in HCC, and identified a complex cancer specific ceRNA network, which includes 14 lncRNAs and 17 miRNAs in HCC.
Project description:Background:The specific functional roles of long noncoding RNAs (lncRNAs) as ceRNAs in colon cancer and their potential implications for colon cancer prognosis remain unclear. In the present study, a genome-wide analysis was performed to investigate the potential lncRNA-mediated ceRNA interplay in colon cancer based on the "ceRNA hypothesis." The prognostic value of the lncRNAs was evaluated. Methods:A dysregulated lncRNA-associated ceRNA network was constructed based on the miRNA, lncRNA, and mRNA expression profiles in combination with the miRNA regulatory network by using an integrative computational method. Molecular biological techniques, including qPCR and gene knockdown techniques, were used to verify candidate targets in colon cancer. Survival analysis was performed to identify the candidate lncRNAs with prognostic value. Results:Our network analysis uncovered several novel lncRNAs as functional ceRNAs through crosstalk with miRNAs. The QRT-PCR assays of patient tissues as well as gene knockdown colon cancer cells confirmed the expression of top lncRNAs and their correlation with target genes in the ceRNA network. Functional enrichment analysis predicted that differentially expressed lncRNAs might participate in broad biological functions associated with tumor progression. Moreover, these lncRNAs may be involved in a range of cellular pathways, including the apoptosis, PI3K-AKT, and EGFR signaling pathways. The survival analysis showed that the expression level of several lncRNAs in the network was correlated with the prognosis of patients with colon cancer. Conclusions:This study uncovered a dysregulated lncRNA-associated ceRNA network in colon cancer. The function of the identified lncRNAs in colon cancer was preliminarily explored, and their potential prognostic value was evaluated. Our study demonstrated that lncRNAs could potentially serve as important regulators in the development and progression of colon cancer. Candidate prognostic lncRNA biomarkers in colon cancer were identified.
Project description:It is increasing evidence that ceRNA activity of long non-coding RNAs (lncRNAs) played critical roles in both normal physiology and tumorigenesis. However, functional roles and regulatory mechanisms of lncRNAs as ceRNAs in pancreatic ductal adenocarcinoma (PDAC), and their potential implications for early diagnosis remain unclear. In this study, we performed a genome-wide analysis to investigate potential lncRNA-mediated ceRNA interplay based on "ceRNA hypothesis". A dysregulated lncRNA-associated ceRNA network (DLCN) was constructed by utilizing sample-matched miRNA, lncRNA and mRNA expression profiles in PDAC and normal samples in combination with miRNA regulatory network. The results of network analysis uncovered seven novel lncRNAs as functional ceRNAs whose aberrant expression will result in the extensive variation in tumorigenic or tumor-suppressive gene expression through DLCN at the post-transcriptional level contributing to PDAC. Therefore, we developed a 7-lncRNA signature (termed LncRisk-7) based on the expression data of seven lncRNAs and SVM algorithm as a novel diagnostic tool to improve early diagnosis of PDAC. The LncRisk-7 achieved high performance in distinguishing PDAC patients from nonmalignant pancreas samples in the discovery cohort and was further confirmed in another two independent validation cohorts. Functional analysis demonstrated that seven lncRNA biomarkers act as ceRNAs involving the regulation of cell death, cell adhesion and cell cycle. This study will help to improve our understanding of the lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of PDAC and provide novel lncRNAs as candidate diagnostic biomarkers or potential therapeutic targets.
Project description:BACKGROUND:Recently, increasing evidence has uncovered the roles of mRNA-miRNA-lncRNA network in multiple human cancers. However, a systematic mRNA-miRNA-lncRNA network linked to pancreatic cancer prognosis is still absent. METHODS:Differentially expressed genes (DEGs) were first identified by mining GSE16515 and GSE15471 datasets. DAVID database was utilized to conduct functional enrichment analysis. Protein-protein interaction (PPI) network was built using STRING database, and hub genes were identified by Cytoscape plug-in CytoHubba. Upstream miRNAs and lncRNAs of mRNAs were predicted by miRTarBase and miRNet, respectively. Expression, survival and correlation analysis for genes, miRNAs and lncRNAs were performed via GEPIA, Kaplan-Meier plotter and starBase. RESULTS:734 and 180 upregulated and downregulated significant DEGs were identified, respectively. Functional enrichment analysis revealed that they were significantly enriched in focal adhesion, pathways in cancer and metabolic pathways. According to node degree, hub genes in the PPI networks were screened, such as TGFB1 and ALB. Among the top 20 hub genes, 7 upregulated genes and 2 downregulated hub genes had significant prognostic values in pancreatic cancer. 33 miRNAs were predicted to target the 9 key genes. But only high expression of 8 miRNAs indicated favorable prognosis in pancreatic cancer. Then, 90 lncRNAs were predicted to potentially bind to the 8 miRNAs. SCAMP1, HCP5, MAL2 and LINC00511 were finally identified as key lncRNAs. By combination of results from expression, survival and correlation analysis demonstrated that MMP9/ITGB1-miR-29b-3p-HCP5 competing endogenous RNA (ceRNA) sub-network was linked to prognosis of pancreatic cancer. CONCLUSIONS:In a word, we established a novel mRNA-miRNA-lncRNA sub-network, among which each RNA may be utilized as a prognostic biomarker of pancreatic cancer.
Project description:Long non-coding RNAs (LncRNAs) can act as competing endogenous RNA (ceRNA) involving in tumor initiation and progression. Nevertheless, the prognostic roles of lncRNAs in lncRNA-related ceRNA network of melanoma remain elusive. In this study, RNA sequence profiles were downloaded from The Cancer Genome Atlas (TCGA) database, and there were 2020 differentially expressed messenger RNAs (DEmRNAs), 438 differentially expressed lncRNAs (DElncRNAs) and 65 differentially expressed microRNAs (DEmiRNAs) between primary and metastasis melanoma patients. A ceRNA regulatory network was constructed based on the DElncRNAs-DEmiRNAs and DEmiRNAs-DEmRNAs interactions, which contained 39 lncRNAs, 10 miRNAs, and 16 mRNAs. Furthermore, univariate and multivariate Cox regression analysis were carried out to establish a 7-lncRNA prognostic signature. Subsequently, the area under the curve (AUC) value of the receiver operating characteristic (ROC) curve and the Kaplan-Meier risk survival analysis revealed the significant performance of this signature. Finally, pathway enrichment analyses implied that lncRNA MIR205HG and MIAT were associated with multiple cancer-related pathways, especially epidermis development and immune response. The current study provides novel insights into the lncRNA-related ceRNA network and the potential of lncRNAs to be candidate prognostic biomarkers and therapeutic targets in melanoma.
Project description:BACKGROUND Long noncoding RNAs (lncRNAs) have been revealed to function as competing endogenous RNAs (ceRNAs), which can seclude the common microRNAs (miRNAs) and hence prevent the miRNAs from binding to their ancestral gene. Nonetheless, the role of lncRNA-mediated ceRNAs in prostate cancer has not yet been elucidated. MATERIAL AND METHODS Using The Cancer Genome Atlas (TCGA) database, lncRNA, miRNA, and mRNA profiles from 499 prostate cancer tissues and 52 normal prostate tissues were analyzed with the R package "DESeq" to identify the differentially expressed RNAs. GO and KEGG pathway analyses were performed using "DAVID6.8" and R packages "Clusterprofile." The ceRNA network in prostate cancer was constructed using miRDB, miRTarBase, and TargetScan databases. Survival analysis was performed with Kaplan-Meier analysis. RESULTS A total of 376 lncRNAs, 33 miRNAs, and 687 mRNAs were identified as significant factors in tumorigenesis. Based on the hypothesis that the ceRNA network (lncRNA-miRNA-mRNA regulatory axis) is involved in prostate cancer and forms competitive interrelations between miRNA and mRNA or lncRNA, we constructed a ceRNA network that included 23 lncRNAs, 6 miRNAs, and 2 mRNAs that were differentially expressed in prostate cancer. Only 3 lncRNAs (LINC00308, LINC00355, and OSTN-AS1) had a significant association with survival (P<0.05). The 3 prostate cancer-specific lncRNA were validated in prostate cancer cell lines PC3 and DU145 using qRT-PCR. CONCLUSIONS We demonstrated the differential lncRNA expression profiles in prostate cancer, which provides new insights for future studies of the ceRNA network and its regulatory mechanisms in prostate cancer.
Project description:Recent studies indicate that long noncoding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs) to indirectly regulate mRNAs through shared microRNAs, which represents a novel layer of RNA crosstalk and plays critical roles in the development of tumor. However, the global regulation landscape and characterization of these lncRNA related ceRNA crosstalk in cancers is still largely unknown. Here, we systematically characterized the lncRNA related ceRNA interactions across 12 major cancers and the normal physiological states by integrating multidimensional molecule profiles of more than 5000 samples. Our study suggest the large difference of ceRNA regulation between normal and tumor states and the higher similarity across similar tissue origin of tumors. The ceRNA related molecules have more conserved features in tumor networks and they play critical roles in both the normal and tumorigenesis processes. Besides, lncRNAs in the pan-cancer ceRNA network may be potential biomarkers of tumor. By exploring hub lncRNAs, we found that these conserved key lncRNAs dominate variable tumor hallmark processes across pan-cancers. Network dynamic analysis highlights the critical roles of ceRNA regulation in tumorigenesis. By analyzing conserved ceRNA interactions, we found that miRNA mediate ceRNA regulation showed different patterns across pan-cancer; while analyzing the cancer specific ceRNA interactions reveal that lncRNAs synergistically regulated tumor driver genes of cancer hallmarks. Finally, we found that ceRNA modules have the potential to predict patient survival. Overall, our study systematically dissected the lncRNA related ceRNA networks in pan-cancer that shed new light on understanding the molecular mechanism of tumorigenesis.