ceRNA Network In Gastric Cancer Research Articles

Construction of a potential long noncoding RNA prognostic model involved competitive endogenous RNA for patients with gastric cancer.

Increasing evidence has underscored the role of long noncoding RNAs (lncRNAs) make up the major proportion of the competing endogenous RNAs (ceRNAs) network and can regulate gene expression by competitively binding to miRNAs in the development and progression of tumors. Nevertheless, the role of lncRNA-mediated ceRNAs in gastric cancer (GC) and their regulatory mechanisms have not been elucidated to some extent. This study is aimed at constructing a prognostic risk model for GC based on lncRNAs. A TCGA (The Cancer Genome Atlas) dataset was analyzed using edgeR to identify differentially expressed lncRNAs (DElncRNAs) in GC tissues vs normal tissues. Subsequently, DElncRNAs that could predict GC prognosis were determined using a training set. A prognostic risk model based on the DElncRNAs was then constructed. The performance of the model was tested using a test set. The functions of these lncRNAs in GC were investigated using a lncRNA-miRNA-mRNA network. Analysis of lncRNA expression in 407 TCGA GC cases identified 3 lncRNAs that significantly correlated with prognosis. GC cases with high-risk scores showed markedly poor prognosis relative to those with low-risk scores in both the training and test sets. Univariate and multivariate Cox regression analysis of the relationship between various clinical features and prognosis found that these lncRNAs and stage significantly correlated with GC prognosis. A lncRNA-miRNA-mRNA network based on 3 lncRNAs and functional enrichment analysis of interacting mRNA indicated that these genes are enriched in various intracellular receptor signaling pathways, including regulation of muscle system process, and protein deubiquitylation. The current study provides novel insights into the lncRNA-related ceRNA network in GC and sheds lights on underlying 3 lncRNA biomarkers may be independent prognostic signatures in predicting the survival of GC patients.

Introduction of LPIN1 as a potential diagnostic and prognostic biomarker for gastric cancer via integrative bioinformatics analysis of a competing endogenous RNA network and experimental validation.

Identification of effective biomarkers is crucial for the heterogeneous disease of gastric cancer (GC). Recent studies have focused on the role of pseudogenes regulating gene expression through competing endogenous RNA (ceRNA) networks, however, the pseudogene-associated ceRNA networks in GC remain largely unknown. The current study aimed to construct and analyze a three-component ceRNA network in GC and experimentally validate a ceRNA. A comprehensive analysis was conducted on the RNA-seq and miRNA-seq data of The Cancer Genome Atlas (TCGA) stomach adenocarcinoma (STAD) dataset to identify differentially-expressed mRNAs (DEMs), pseudogenes (DEPs), and miRNAs (DEMis). Pseudogene-associated ceRNA and protein-protein interaction (PPI) networks were constructed, and functional enrichment analyses were performed. DEMs and DEPs with degree centralities≥2 were selected for survival analysis. A ceRNA was further selected for experimental validation. 10,145 DEMs, 3576 DEPs, and 66 DEMis were retrieved and a ceRNA network was then constructed by including DEMis with concurrent interactions with at least a DEM and a DEP. Functional enrichment analysis demonstrated that DEMs of the ceRNA network were significantly enriched in cancer-associated pathways. LPIN1 and WBP1L were two mRNAs showing an association with STAD patients overall survival. Expression analysis of LPIN1 showed a significant decrease in GC tumors compared to non-tumor tissues (P=0.003). Our research emphasizes the significant implications of ceRNA networks in the development of new biomarkers for the detection and prognosis of cancer. Further examination is necessary to explore the functional roles of LPIN1 in the pathogenesis of GC.

A new strategy to identify ADAM12 and PDGFRB as a novel prognostic biomarker for matrine regulates gastric cancer via high throughput chip mining and computational verification

BackgroundGastric cancer is a life-threatening disease that poses a serious risk to human health. Although there are numerous molecular targets for gastric cancer in clinical practice, they often exhibit low specificity and sensitivity. Consequently, this can result in a low early diagnosis rate, delayed treatment, and poor prognosis for patients with gastric cancer. Hence, it remains crucial to identify more precise diagnostic markers for this disease. MethodsThis study utilized ceRNA chips and bioinformatics methods to investigate the key genes and mechanisms involved in matrine intervention in gastric cancer cells. ResultsADAM12 and PDGFRB are the key genes that are down-regulated after matrine intervention in gastric cancer cells. By conducting bioinformatics analysis, two ceRNA regulatory axes were identified, which are associated with the prognosis of gastric cancer. These axes are lncRNA DGCR5/hsa-miR-206/ADAM12 and circRNA ITGA3/hsa-miR-24-3p/PDGFRB. ConclusionThe low expression of ADAM12 may weaken the digestion of extracellular matrix (ECM) molecules, which can result in the invasion and metastasis of tumor cells. This occurs without the catalysis of ECM proteases, thereby impacting the invasion and metastasis of gastric cancer cells. Additionally, the analysis of immune infiltration suggests that ADAM12 and PDGFRB may influence changes in the tumor immune microenvironment, thereby affecting the occurrence and development of gastric cancer. This study contributes to a deeper understanding of the role of the matrine-related ceRNA network in gastric cancer, providing a reference for clinical diagnosis and treatment. It holds significant importance in discovering new drug treatment targets.

Identification of a novel MSI-related ceRNA network for predicting the prognosis and immunotherapy response of gastric cancer

Mounting evidence has underscored the pivotal role of the competitive endogenous RNA (ceRNA) regulatory networks among various cancers. However, the behavior characteristics and complexity of the ceRNA network in Gastric cancer (GC) remains unclear. In this study, we aimed to clarify a Microsatellite instability (MSI)-related ceRNA regulatory network and identify potential prognostic markers associated with GC.We extracted transcriptome data of GC patients from The Cancer Genome Atlas (TCGA) and identified differentially expressed lncRNAs, miRNAs and mRNAs based on MSI status. A hub ceRNA network including 1 lncRNAs (MIR99AHG), 2 miRNAs and 26 mRNAs specific to MSI was established in GC. We further constructed a prognostic model with seven target mRNAs by Lasso Cox regression, which yielded AUC values of 0.76. The prognostic model was further validated in an external independent dataset that integrated three GEO datasets. The characterization of immune cell infiltration and immunotherapy effects between high-risk and low-risk groups were then analyzed. Immune cell infiltration was significantly different between high- and low-risk groups based on risk scores. GC patients with lower risk scores correlated with better immune checkpoint inhibitor therapy (ICI) response. We further validated the expression and regulatory relationship of the ceRNA network in vitro experiments, and also confirmed the relationship between MIR99AHG and PD-L1.Our research provides in-depth insights on the role of MSI-related ceRNA in GC and the prognosis and ICIs therapy response of GC patients can be assessed by the risk model based on MSI-related ceRNA network.

H19 may regulate the immune cell infiltration in carcinogenesis of gastric cancer through miR-378a-5p/SERPINH1 signaling

BackgroundIncreasing studies have indicated that noncoding RNA (ncRNA)-mediated competing endogenous RNA (ceRNA) network serves as a significant role in cancer progression, but the underlying regulatory mechanisms of which in gastric cancer (GC) remain largely unclear.MethodsBased on Gene Expression Omnibus and The Cancer Genome Atlas datasets, potential biomarkers for GC were screened and validated by machine learning. Then, upstream regulatory ncRNA of potential biomarkers was identified to construct a novel ceRNA network in GC through means of stepwise reverse prediction and validation. Ultimately, tumor immune cell infiltration analysis was performed based on the EPIC algorithm.ResultsA total of 188 differentially expressed genes (DEGs) were screened, and three candidate diagnostic biomarkers (FAP, PSAPL1, and SERPINH1) for GC were identified and validated. Subsequently, H19 and miR-378a-5p were identified as upstream regulatory ncRNAs that could potentially bind SERPINH1 in GC. Moreover, Immune infiltration analysis revealed that each component in the ceRNA network (H19/miR-378a-5p/SERPINH1) was significantly correlated with the infiltration abundances of diverse tumor-infiltrating immune cells.ConclusionsH19 may regulate the immune cell infiltration in carcinogenesis of GC through miR-378a-5p/SERPINH1 signaling.

Circ_0061265 competitively binds to microRNA-885-3p to promote the development of gastric cancer by upregulating AURKA expression

BackgroundCircular RNAs (circRNAs) represent a class of newly identified transcripts that act as competing endogenous RNAs (ceRNAs) to modulate gene expression by competing for the shared microRNAs (miRNAs) in humans. In this study, we set out to investigate the role of the circRNA-miRNA-mRNA ceRNA network in gastric cancer (GC).MethodsA differential analysis on GC-related circRNAs, miRNAs and mRNAs was performed utilizing the R language “limma” package, followed by GO and KEGG enrichment analyses. The Cytoscape visualization software was used to construct the circRNA-miRNA-mRNA ceRNA network. RT-qPCR, Western blot assay, immunohistochemistry, RNA pull down, RIP and dual luciferase gene reporter assay were conducted to verify the expression of the related circRNA, miRNA and mRNA and their interaction in GC tissues and cells.ResultsThe bioinformatics analysis screened 13 circRNAs, 241 miRNAs and 7483 mRNAs related to GC. Ten DEmRNAs (AURKA, BUB1, CCNF, FEN1, FGF2, ITPKB, CDKN1A, TRIP13, KNTC1 and KIT) were identified from the constructed PPI network and module analysis, among which AURKA was the most critical. A circ_0061265-miRNA-885-3p-AURKA ceRNA network was constructed. In vitro cell experiment demonstrated significantly upregulated circ_0061265 and AURKA, but downregulated miR-885-3p in GC. Moreover, circ_0061265 promoted the occurrence of GC by competitively binding to miRNA-885-3p to regulate AURKA expression.ConclusionOur work validated that circ_0061265 may increase AURKA expression by competitively binding to miRNA-885-3p, thereby promoting GC development.

Pepsinogen C expression-related lncRNA/circRNA/mRNA profile and its co-mediated ceRNA network in gastric cancer.

The expression of pepsinogen C (PGC) is considered an ideal negative biomarker of gastric cancer, but its pathological mechanisms remain unclear. This study aims to analyze competing endogenous RNA (ceRNA) networks related to PGC expression at a post-transcriptional level and build an experimental basis for studying the role of PGC in the progression of gastric cancer. RNA sequencing technology was used to detect the differential expression (DE) profiles of PGC-related long non-coding (lnc)RNAs, circular (circ)RNAs, and mRNAs. Ggcorrplot R package and online database were used to construct DElncRNAs/DEcircRNAs co-mediated PGC expression-related ceRNA networks. In vivo and in vitro validations were performed using quantitative reverse transcription-PCR (qRT-PCR). RNA sequencing found 637 DEmRNAs, 698 DElncRNAs, and 38 DEcircRNAs. The PPI network of PGC expression-related mRNAs consisted of 503 nodes and 1179 edges. CFH, PPARG, and MUC6 directly interacted with PGC. Enrichment analysis suggested that DEmRNAs were mainly enriched in cancer-related pathways. Eleven DElncRNAs, 13 circRNAs, and 35 miRNA-mRNA pairs were used to construct ceRNA networks co-mediated by DElncRNAs and DEcircRNAs that were PGC expression-related. The network directly related to PGC was as follows: SNHG16/hsa_circ_0008197-hsa-mir-98-5p/hsa-let-7f-5p/hsa-let-7c-5p-PGC. qRT-PCR validation results showed that PGC, PPARG, SNHG16, and hsa_circ_0008197 were differentially expressed in gastric cancer cells and tissues: PGC positively correlated with PPARG (r = 0.276, P = 0.009), SNHG16 (r = 0.35, P = 0.002), and hsa_circ_0008197 (r = 0.346, P = 0.005). PGC-related DElncRNAs and DEcircRNAs co-mediated complicated ceRNA networks to regulate PGC expression, thus affecting the occurrence and development of gastric cancer at a post-transcriptional level. Of these, the network directly associated with PGC expression was a SNHG16/hsa_circ_0008197-mir-98-5p/hsa-let-7f-5p/hsa-let-7c-5p - PGC axis. This study may form a foundation for the subsequent exploration of the possible regulatory mechanisms of PGC in gastric cancer.

Identification of a competing endogenous RNA axis related to gastric cancer.

Competing endogenous RNA (ceRNA) pathways play pivotal roles in the formation and progression of gastric cancer (GC). Employing multi-omics analysis, we sought to identify a ceRNA network associated with GC progression. We analyzed3Gene Expression Omnibus datasets as well as data from The Cancer Genome Atlas to identify genes that were differentially expressed in GC tissues. A total of 84 upregulated genes and 106 downregulated genes were found. Enrichment analysis indicated that some pathways were strongly linked with tumor formation and progression. We also screened hub genes to establish a lncRNA-miRNA-mRNA network. We ultimately identified 8 hub genes, 6 key miRNAs and 4 key lncRNAs that interact within a common ceRNA network. Correlation analysis and in vitro experiments were conducted to verify the regulatory effect of the ceRNA network in GC. A knockdown assay confirmed that the DLGAP1-AS1/miR-203a-3p/THBS2 axis is a ceRNA network involved in GC progression. In this study, we elucidated the role of the DLGAP1-AS1/miR-203a-3p/THBS2 ceRNA network in the progression of GC. These molecules maybe evaluated as therapeutic targets and prognostic biomarkers for GC.

Construction and Analysis of the Tumor-Specific mRNA-miRNA-lncRNA Network in Gastric Cancer.

Weighted correlation network analysis (WGCNA) is a statistical method that has been widely used in recent years to explore gene co-expression modules. Competing endogenous RNA (ceRNA) is commonly involved in the cancer gene expression regulation mechanism. Some ceRNA networks are recognized in gastric cancer; however, the prognosis-associated ceRNA network has not been fully identified using WGCNA. We performed WGCNA using datasets from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) to identify cancer-associated modules. The criteria of differentially expressed RNAs between normal stomach samples and gastric cancer samples were set at the false discovery rate (FDR) < 0.01 and |fold change (FC)| > 1.3. The ceRNA relationships obtained from the RNAinter database were examined by both the Pearson correlation test and hypergeometric test to confirm the mRNA–lncRNA regulation. Overlapped genes were recognized at the intersections of genes predicted by ceRNA relationships, differentially expressed genes, and genes in cancer-specific modules. These were then used for univariate and multivariate Cox analyses to construct a risk score model. The ceRNA network was constructed based on the genes in this model. WGCNA-uncovered genes in the green and turquoise modules are those most associated with gastric cancer. Eighty differentially expressed genes were observed to have potential prognostic value, which led to the identification of 12 prognosis-related mRNAs (KIF15, FEN1, ZFP69B, SP6, SPARC, TTF2, MSI2, KYNU, ACLY, KIF21B, SLC12A7, and ZNF823) to construct a risk score model. The risk genes were validated using the GSE62254 and GSE84433 datasets, with 0.82 as the universal cutoff value. 12 genes, 12 lncRNAs, and 35 miRNAs were used to build a ceRNA network with 86 dysregulated lncRNA–mRNA ceRNA pairs. Finally, we developed a 12-gene signature from both prognosis-related and tumor-specific genes, and then constructed a ceRNA network in gastric cancer. Our findings may provide novel insights into the treatment of gastric cancer.

The prognostic value of COL3A1/FBN1/COL5A2/SPARC-mir-29a-3p-H19 associated ceRNA network in Gastric Cancer through bioinformatic exploration.

Increasing studies on malignant tumors have proposed a new competing endogenous RNA (ceRNA) regulatory mechanism that mRNA, miRNA and lncRNA interact with each other. However, the mRNA-miRNA-lncRNA associated ceRNA network in gastric cancer remains unknown. We used online bioinformatic softwares to predict the hub genes and their upstream miRNAs and lncRNAs in gastric cancer, and then performed survival analyses. After collecting gastric cancer tissue samples and performing PCR experiments, the correlations among predicted mRNA, miRNA and lncRNA were further verified. A total of 101 up-regulated significant differentially expressed genes (DEGs) and 219 down-regulated significant DEGs in gastric cancer were confirmed. Functional enrichment analyses of these significant DEGs indicated that they were potentially enriched in some pathways involved in tumor malignant biological processes or metabolism. Then, we identified 20 hub genes in the PPI networks. Combined with expression and survival analyses, 8 up-regulated genes and 1 down-regulated gene were identified as central genes and acted as important prognostic roles in gastric cancer. 17 miRNAs were confirmed that might potentially regulate the expressions of these central genes. But only 8 out of them indicated better outcome in gastric cancer. Further, 79 lncRNAs were predicted that might have the potence to combine with the 8 central miRNAs. The lncRNA H19 was eventually defined as a central lncRNA by survival analyses. Stimultaneously, we found that there were certain interactions among lncRNA, miRNA and mRNAs in 50 gastric cancer tissues by qRT-PCR. Moreover, the high expression of H19 is associated with advanced TNM stage, primary tumor and lymph nodes, indicating a poor prognosis. In summary, we uncovered the prognostic value of COL3A1/FBN1/COL5A2/SPARC-mir-29a-3p-H19 ceRNA network in gastric cancer.

Comprehensive Analysis of Aberrantly Expressed ceRNA network in gastric cancer with and without H.pylori infection

Objective: This study mainly focused on revealing ceRNA network in gastric cancer (GC) with Hp infection after comparing with GC without Hp infection and exploring the biological function and prognostic relevance of related molecules.Methods: The RNA expression profile data of GC patients with or without Hp infection were extracted from TCGA GDC data portal, including 20 GC cases with Hp infection and 168 GC cases without Hp infection. Differentially expressed lncRNAs, miRNAs and mRNAs were unveiled by package edgeR of R, and lncRNA-miRNA-mRNA ceRNA network was constructed by integrating the miRNA target information and the expression data of lncRNAs, miRNAs and mRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of aberrantly expressed mRNAs were performed to identify the related biological functions and pathologic pathways, and protein-protein interaction (PPI) network was constructed by STRING database. The overall survival (OS) of aberrantly expression lncRNAs and miRNAs were analyzed by package survival of R. A total of 30 gastric cancer tissues were used to validate the bioinformatics analysis results by real-time PCR.Results: Among the 32 differentially expressed miRNAs, 27 differentially expressed lncRNAs and 257 differentially expressed mRNAs were identified by comparing GC patients with and without Hp infection. Totally 10 miRNA, 11 lncRNA, 219 mRNA were included to build ceRNA network. GO and KEGG analysis revealed that differentially expressed mRNAs involved in the ceRNA network were mainly involved in extracellular exosomes, structural molecular activities, proteolysis and P13K-Akt signaling pathways. And PPI analysis obtained six hub genes of NTS, APOC3, OTX2, KRT13, CALCA, GNG4. Survival analysis showed that four lncRNAs (LINC01254, LINC01287, LINC01524, U95743.1) and four miRNAs (miR-302a, miR-302b, miR-1286, miR-378g) were associated with overall survival of GC with Hp infection. The real-time PCR results showed that, the levels of LINCO1254, LINCO1287, LINCO1524, U95743.1 were significantly higher in Hp positive GC patients than Hp negative patients (P=0.02, 0.048, 0.04, 0.036, respectively).Conclusion: Using TCGA database for data mining, we have successfully constructed a ceRNA regulatory network of GC with Hp infection, consisting of 10 lncRNAs, 11 miRNAs and 219 mRNAs. These findings might provide critical clues for the regulatory role of ceRNA network in the development of GC with Hp infection.

TCGA dataset‑based construction and integrated analysis of aberrantly expressed long non‑coding RNA mediated competing endogenous RNA network in gastric cancer

The aberrant expression of long non‑coding RNAs (lncRNAs) has been confirmed to play a pivotal role in tumor initiation and development. LncRNAs can interact with microRNAs (miRNAs) as competing endogenous RNAs (ceRNAs) to regulate the expression of target genes in various cancers. In the present study, the authors investigated the functions of lncRNAs as ceRNAs in gastric cancer (GC) and their implications for the prognosis. The RNA sequencing profiles of 372tumor samples and 32adjacent non‑tumor gastric samples were downloaded from The Cancer Genome Atlas (TCGA) database. The differential expression of RNAs was identified using the 'edgeR' package in Rlanguage software. Survival analysis was estimated based on Kaplan‑Meier curves. The Gene Ontology biological processes and the Kyoto Encyclopedia of Genes and Genomes pathways were analyzed for differentially expressed mRNAs. Finally, a total of 999lncRNAs, 137miRNAs and 1629mRNAs were identified as differentially expressed (DE) in GC with log fold change (FC) thresholds>2 and adjusted P‑values<0.01. A ceRNA network was constructed with 65DElncRNAs, nine DEmiRNAs and 24DEmRNAs. Of the 65DElncRNAs in the ceRNA network, nine were identified to be significantly associated with overall survival (P<0.05). A total of four DElncRNAs from the ceRNA network were validated by reverse transcription‑quantitative polymerase chain reaction and revealed to be associated with tumorigenesis and/or progression. In conclusion, the results of the present study provide information on the role of the ceRNA network in GC. These identified novel lncRNAs are potential candidate biomarkers and require further studies.

Sa1608 - Comprehensive Bioinformatic Analysis of Aberrantly Expressed Profiles of Mirnas and Lncrnas with the Associated Cerna Network in Gastric Cancer

Sa1608 - Comprehensive Bioinformatic Analysis of Aberrantly Expressed Profiles of Mirnas and Lncrnas with the Associated Cerna Network in Gastric Cancer

Comprehensive analysis of aberrantly expressed lncRNAs and construction of ceRNA network in gastric cancer.

Gastric cancer remains fifth most common cancer often diagnosed at an advanced stage and is the second leading cause of cancer-related death worldwide. Long non-coding RNAs (lncRNAs) involved in various cellular pathways are essential for tumor occurrence and progression and they have high potential to promote or suppress the expression of many genes. In this study, we profiled 19 selected cancer-associated lncRNAs in thirty gastric adenocarcinomas and matching normal tissues by qRT-PCR. Our results showed that most of the lncRNAs were significantly upregulated (12/19). Further, we performed bioinformatic screening of miRNAs that share common miRNA response elements (MREs) with lncRNAs and their downstream mRNA targets. The prediction identified three microRNAs (miR-21, miR-145 and miR-148a) and five gastric cancer-specific target genes (EGFR, KLF4, DNMT1 and AGO4) which also showed strong correlation with lncRNAs in regression analysis. Finally, we constructed an integrated lncRNA-miRNA-mRNA interaction network of the candidate genes to understand the post-transcriptional gene regulation. The ceRNA network analysis revealed that the differentially regulated miR-21 and miR-148a were playing as central candidates coordinating sponging activity of the lncRNAs analyzed (H19, TUG1 and MALAT1) in this study and the overexpression of H19 and miR-21 could be a signature event of gastric tumorigenesis that could serve as prognostic indicators and therapeutic targets.

Long non-coding RNA PTENP1 functions as a ceRNA to modulate PTEN level by decoying miR-106b and miR-93 in gastric cancer

Recent studies have shown that competing endogenous RNAs (ceRNAs) play an important role in the regulation of gene expression, and participate in a wide range of biological processes, including carcinogenesis. Long non-coding RNA PTENP1, the pseudogene of PTEN tumor suppressor, has been reported to exert its tumor suppressive function via modulation of PTEN expression in many malignancies. However, whether a PTENP1∼miRNA∼PTEN ceRNA network exists and how it functions in gastric cancer (GC) remains elusive. In order to identify and characterize the PTENP1∼miRNA∼PTEN ceRNA network in GC, we first determined PTENP1 levels in clinical GC samples and found that PTENP1 and PTEN were concurrently downregulated in these samples. We further demonstrated that PTENP1 could act as a ceRNA to sponge miR-106b and miR-93 from targeting PTEN for downregulation using a novel ceRNA in vitro gradient assay. Thus, we revealed a tumor suppressive role of PTENP1 as ceRNA in GC and pinpointed the specific miRNAs decoyed by PTENP1, highlighting the emerging roles of ceRNAs in the biological regulation of GC cells and their possible clinical significance.

Integrated analysis of long non-coding RNA competing interactions reveals the potential role in progression of human gastric cancer.

Abnormal expression of long non-coding RNAs (lncRNAs) have been shown to play an important role in tumor biology. The Cancer Genome Atlas (TCGA) platform is a large sample sequencing database of lncRNAs, and further analysis of the associations between these data and patients' clinical related information can provide new approaches to find the functions of lncRNA. In the present study, 361 RNA sequencing profiles of gastric cancer (GC) patients were selected from TCGA. Then, we constructed the lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network of GC. There were 25 GC specific lncRNAs (fold change >2, p<0.05) identified, 19 of them were included in ceRNA network. Subsequently, we selected these 19 key lncRNAs and analyzed the correlations with clinical features and overall survival, 14 of them were discriminatively expressed with tumor size, tumor grade, TNM stage and lymphatic metastasis (p<0.05). In addition, eight lncRNAs (RPLP0P2, FOXD2-AS1, H19, TINCR, SLC26A4-AS1, SMIM10L2A, SMIM10L2B and SNORD116-4) were found to be significantly associated with overall survival (log-rank p<0.05). Finally, two key lncRNAs HOTAIR and UCA1 were selected for validation of their expression levels in 82 newly diagnosed GC patients by qRT-PCR. Results showed that the fold changes between TCGA and qRT-PCR were 100% in agreement. In addition, we also found that HOTAIR was significantly correlated with tumor size and lymphatic metastasis (p<0.05), and UCA1 was significantly correlated with tumor size, TNM stage and lymphatic metastasis (p<0.05). The clinical relevance of the two lncRNAs and the bioinformatics analysis results were almost the same. Overall, our study showed the GC specific lncRNAs expression patterns and a ceRNA network in GC. Clinical features related to GC specific lncRNAs also suggested these lncRNAs are worthwhile for further study as novel candidate biomarkers for the clinical diagnosis of GC and potential indicators for prognosis.

Noncoding RNAs in gastric cancer: Research progress and prospects.

Noncoding RNAs (ncRNAs) have attracted much attention in cancer research field. They are involved in cellular development, proliferation, differentiation and apoptosis. The dysregulation of ncRNAs has been reported in tumor initiation, progression, invasion and metastasis in various cancers, including gastric cancer (GC). In the past few years, an accumulating body of evidence has deepened our understanding of ncRNAs, and several emerging ncRNAs have been identified, such as PIWI-interacting RNAs (piRNAs) and circular RNAs (circRNAs). The competing endogenous RNA (ceRNA) networks include mRNAs, microRNAs, long ncRNAs (lncRNAs) and circRNAs, which play critical roles in the tumorigenesis of GC. This review summarizes the recent hotspots of ncRNAs involved in GC pathobiology and their potential applications in GC. Finally, we briefly discuss the advances in the ceRNA network in GC.