Identification of Novel Survival Related lncRNA-miRNA-mRNA Competing Endogenous RNA Network Associated with Immune Infiltration in Colorectal Cancer

Abstract Background: Increasing studies have reported that long noncoding RNAs (lncRNAs) play critical roles in the initiation and progression of carcinogenesis. However, the underlying regulatory mechanisms of lncRNA related competing endogenous RNA (ceRNA) network in colorectal cancer (CRC) are not fully understood.Methods: Dysregulated microRNAs (miRNAs) in CRC samples were screened from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. After that, the key miRNAs were filtered out through a comprehensive assessment of their expression levels and prognostic values. Subsequently, the targeted downstream mRNAs and upstream lncRNAs of the key miRNAs were predicted by using multiple bioinformatic databases. A ceRNA network was constructed by using Cytoscape, and the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed on this network using the DAVID database. Ultimately, expression levels and prognostic values of the lncRNAs and mRNAs were evaluated, and a survival related ceRNA network was constructed and visualized by using Cytoscape. In addition, the Gene Set Enrichment Analysis (GSEA) software package was employed to identify the pathways in which this survival related ceRNA network was enriched. Furthermore, correlations of ceRNA network with immune infiltration level were estimated by the Tumor Immune Estimation Resource (TIMER) databases.Results: In total, 28 dysregulated miRNAs were obtained, and two of them were identified as key miRNAs based on expression levels and prognostic values analyses. Subsequently, a total of three upstream lncRNAs and 309 downstream mRNAs were predicted by using bioinformatic tools, and two key lncRNAs and eight key mRNAs were identified by expression and survival analysis. A ceRNA regulatory network associated with the prognosis of CRC patients was constructed. Furthermore, GSEA analysis indicated the possible association of key mRNAs with CRC onset and progression. Importantly, immune infiltration analysis revealed that the ceRNA network was remarkably associated with infiltration abundance of multiple immune cells and expression levels of immune checkpoints.Conclusions: We constructed a survival related ceRNA regulatory network in human CRC, NEAT1 and XIST are potential prognostic factors that affect CRC onset and progression by targeting miR-195-5p.

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Comprehensive analysis of ceRNA networks reveals prognostic lncRNAs related to immune infiltration in colorectal cancer

BMC Cancer ◽

10.1186/s12885-021-07995-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jingyi Chen ◽

Yuxuan Song ◽

Mei Li ◽

Yu Zhang ◽

Tingru Lin ◽

...

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Target Genes ◽

Immune Cell ◽

Pearson Correlation ◽

Enrichment Analysis ◽

Cell Types ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cerna Network

Abstract Background Competing endogenous RNA (ceRNA) represents a class of RNAs (e.g., long noncoding RNAs [lncRNAs]) with microRNA (miRNA) binding sites, which can competitively bind miRNA and inhibit its regulation of target genes. Increasing evidence has underscored the involvement of dysregulated ceRNA networks in the occurrence and progression of colorectal cancer (CRC). The purpose of this study was to construct a ceRNA network related to the prognosis of CRC and further explore the potential mechanisms that affect this prognosis. Methods RNA-Seq and miRNA-Seq data from The Cancer Genome Atlas (TCGA) were used to identify differentially expressed lncRNAs (DElncRNAs), microRNAs (DEmiRNAs), and mRNAs (DEmRNAs), and a prognosis-related ceRNA network was constructed based on DElncRNA survival analysis. Subsequently, pathway enrichment, Pearson correlation, and Gene Set Enrichment Analysis (GSEA) were performed to determine the function of the genes in the ceRNA network. Gene Expression Profiling Interactive Analysis (GEPIA) and immunohistochemistry (IHC) were also used to validate differential gene expression. Finally, the correlation between lncRNA and immune cell infiltration in the tumor microenvironment was evaluated based on the CIBERSORT algorithm. Results A prognostic ceRNA network was constructed with eleven key survival-related DElncRNAs (MIR4435-2HG, NKILA, AFAP1-AS1, ELFN1-AS1, AC005520.2, AC245884.8, AL354836.1, AL355987.4, AL591845.1, LINC02038, and AC104823.1), 54 DEmiRNAs, and 308 DEmRNAs. The MIR4435-2HG- and ELFN1-AS1-associated ceRNA subnetworks affected and regulated the expression of the COL5A2, LOX, OSBPL3, PLAU, VCAN, SRM, and E2F1 target genes and were found to be related to prognosis and tumor-infiltrating immune cell types. Conclusions MIR4435-2HG and ELFN1-AS1 are associated with prognosis and tumor-infiltrating immune cell types and could represent potential prognostic biomarkers or therapeutic targets in colorectal carcinoma.

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Development of a Novel Immune Infiltration-Related ceRNA Network and Prognostic Model for Sarcoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.652300 ◽

2021 ◽

Vol 9 ◽

Author(s):

Deyao Shi ◽

Shidai Mu ◽

Feifei Pu ◽

Binlong Zhong ◽

Binwu Hu ◽

...

Keyword(s):

Regulatory Network ◽

Immune Cell ◽

Tumor Development ◽

Clinical Information ◽

The Cancer Genome Atlas ◽

Immune Infiltration ◽

Cerna Network ◽

Related Risk ◽

Study Gene Expression ◽

Score Model

Due to the rarity and heterogeneity, it is challenging to explore and develop new therapeutic targets for patients with sarcoma. Recently, immune cell infiltration in the tumor microenvironment (TME) was widely studied, which provided a novel potential approach for cancer treatment. The competing endogenous RNA (ceRNA) regulatory network has been reported as a critical molecular mechanism of tumor development. However, the role of the ceRNA regulatory network in the TME of sarcoma remains unclear. In this study, gene expression data and clinical information were obtained from The Cancer Genome Atlas (TCGA) sarcoma datasets, and an immune infiltration-related ceRNA network was constructed, which comprised 14 lncRNAs, 13 miRNAs, and 23 mRNAs. Afterward, we constructed an immune infiltration-related risk score model based on the expression of IRF1, MFNG, hsa-miR-940, and hsa-miR-378a-5p, presenting a promising performance in predicting the prognosis of patients with sarcoma.

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Construction of a ceRNA network of hub genes affecting immune infiltration in ovarian cancer identified by WGCNA

BMC Cancer ◽

10.1186/s12885-021-08711-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Rongjia Su ◽

Chengjuan Jin ◽

Lina Zhou ◽

Yannan Cao ◽

Menghua Kuang ◽

...

Keyword(s):

Ovarian Cancer ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Clinical Information ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Immune Checkpoints ◽

Hub Genes ◽

The Real ◽

Cerna Network

Abstract Background Ovarian cancer is the leading cause of death among gynecological malignancies. Immunotherapy has demonstrated potential effects in ovarian cancer. However, few studies on immune-related prognostic signatures in ovarian cancer have been reported. This study aimed to identify hub genes associated with immune infiltrates to provide insight into the immune regulatory mechanisms in ovarian cancer. Methods Raw data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and University of California, Santa Cruz (UCSC) Xena websites. Single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network analysis (WGCNA) were used to identify hub genes. Kaplan-Meier analysis and differential expression analysis were applied to explore the real hub genes. Results Through ssGSEA and WGCNA, 7 hub genes (LY9, CD5, CXCL9, IL2RG, SLAMF1, SLAMF6, and SLAMF7) were identified. Finally, LY9 and SLAMF1 were recognized as the real hub genes in immune infiltrates of ovarian cancer. LY9 and SLAMF1 are classified as SLAM family receptors involved in the activation of hematopoietic cells and the pathogenesis of multiple malignancies. Furthermore, 12 lncRNAs and 43 miRNAs significantly related to the 2 hub genes were applied to construct a lncRNA-miRNA-mRNA ceRNA network. The lncRNA-miRNA-mRNA ceRNA network shows upstream regulatory sites of the 2 hub genes. Conclusions These findings improve our understanding of the regulatory mechanism of and reveal potential immune checkpoints for immunotherapy for ovarian cancer.

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Competing Endogenous RNA of Snail and Zeb1 UTR in Therapeutic Resistance of Colorectal Cancer

International Journal of Molecular Sciences ◽

10.3390/ijms22179589 ◽

2021 ◽

Vol 22 (17) ◽

pp. 9589

Author(s):

Nam Hee Kim ◽

Sang Hyun Song ◽

Yun Hee Choi ◽

Kyu Ho Hwang ◽

Jun Seop Yun ◽

...

Keyword(s):

Colorectal Cancer ◽

Cancer Progression ◽

Epithelial Mesenchymal Transition ◽

Transcript Abundance ◽

The Cancer Genome Atlas ◽

Therapeutic Resistance ◽

Competing Endogenous Rna ◽

Mesenchymal Transition ◽

Cerna Network ◽

Gene Sets

The epithelial-mesenchymal transition (EMT) comprises an important biological mechanism not only for cancer progression but also in the therapeutic resistance of cancer cells. While the importance of the protein abundance of EMT-inducers, such as Snail (SNAI1) and Zeb1 (ZEB1), during EMT progression is clear, the reciprocal interactions between the untranslated regions (UTRs) of EMT-inducers via a competing endogenous RNA (ceRNA) network have received little attention. In this study, we found a synchronized transcript abundance of Snail and Zeb1 mediated by a non-coding RNA network in colorectal cancer (CRC). Importantly, the trans-regulatory ceRNA network in the UTRs of EMT inducers is mediated by competition between tumor suppressive miRNA-34 (miR-34) and miRNA-200 (miR-200). Furthermore, the ceRNA network consisting of the UTRs of EMT inducers and tumor suppressive miRs is functional in the EMT phenotype and therapeutic resistance of colon cancer. In The Cancer Genome Atlas (TCGA) samples, we also found genome-wide ceRNA gene sets regulated by miR-34a and miR-200 in colorectal cancer. These results indicate that the ceRNA networks regulated by the reciprocal interaction between EMT gene UTRs and tumor suppressive miRs are functional in CRC progression and therapeutic resistance.

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Pyroptosis-related Prognosis Model, Immunocyte Infiltration Characterization, and Competing Endogenous RNA Network of Glioblastoma

10.21203/rs.3.rs-1095246/v1 ◽

2021 ◽

Author(s):

Min-Rui Ding ◽

Yan-Jie Qu ◽

Xiao Peng ◽

Jin-Fang Chen ◽

Meng-Xue Zhang ◽

...

Keyword(s):

Immune Response ◽

Risk Score ◽

Noncoding Rna ◽

Prognostic Markers ◽

Risk Group ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Competing Endogenous Rna ◽

Cerna Network ◽

Prognosis Model

Abstract Background: Glioblastoma (GBM) has a high incidence rate, invasive growth, and easy recurrence, and the current therapeutic effect is less than satisfying. Pyroptosis plays an important role in morbidity and progress of GBM. Meanwhile, the tumor microenvironment (TME) is involved in the progress and treatment tolerance of GBM. In the present study, we analyzed prognosis model, immunocyte infiltration characterization, and competing endogenous RNA (ceRNA) network of GBM on the basis of pyroptosis-related genes (PRGs).Methods: The transcriptome and clinical data of 155 patients with GBM and 120 normal subjects were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). Lasso (Least absolute shrinkage and selection operator) Cox expression analysis was used in predicting prognostic markers, and its predictive ability was tested using a nomogram. A prognostic risk score formula was constructed, and CIBERSORT, ssGSEA algorithm, Tumor IMmune Estimation Resource (TIMER), and TISIDB database were used in evaluating the immunocyte infiltration characterization and tumor immune response of differential risk samples. A ceRNA network was constructed with Starbase, mirtarbase, and lncbase, and the mechanism of this regulatory axis was explored using Gene Set Enrichment Analysis (GSEA). Results: Five PRGs (CASP3, NLRP2, TP63, GZMB, and CASP9) were identified as the independent prognostic biomarkers of GBM. Prognostic risk score formula analysis showed that the low-risk group had obvious survival advantage compared with the high-risk group, and significant differences in immunocyte infiltration and immune related function score were found. In addition, a ceRNA network of messenger RNA (CASP3, TP63)–microRNA (hsa-miR-519c-5p)–long noncoding RNA (GABPB1-AS1) was established. GSEA analysis showed that the regulatory axis played a considerable role in the extracellular matrix (ECM) and immune inflammatory response.Conclusions: Pyroptosis and TME-related independent prognostic markers were screened in this study, and a prognosis risk score formula was established for the first time according to the prognosis PRGs. TME immunocyte infiltration characterization and immune response were assessed using ssGSEA, CIBERSORT algorithm, TIMER, and TISIDB database. Besides a ceRNA network was built up. This study not only laid foundations for further exploring pyroptosis and TME in improving prognosis of GBM, but also provided a new idea for more effective guidance on clinical immunotherapy to patients and developing new immunotherapeutic drugs.

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Prognostic Value and Immune Infiltration of ARMC10 in Pancreatic Adenocarcinoma Via Integrated Bioinformatics Analyses

10.21203/rs.3.rs-936587/v1 ◽

2021 ◽

Author(s):

Tianhao Li ◽

Xiaohan Qin ◽

Cheng Qin ◽

Bangbo Zhao ◽

Hongtao Cao ◽

...

Keyword(s):

Pancreatic Adenocarcinoma ◽

Formation Rate ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Expression Level ◽

Primary Therapy ◽

Migration Ability ◽

Bioinformatics Analyses ◽

Immune Infiltration

Abstract Background: Armadillo repeat-containing 10 (ARMC10) is involved in the progression of multiple types of tumors. Pancreatic adenocarcinoma (PAAD) is a lethal disease with poor survival and prognosis.Methods: We acquired the data of ARMC10 in PAAD patients from the cancer genome atlas (TCGA) and gene expression omnibus (GEO) datasets and compared the expression level with normal pancreatic tissues. We evaluated the relevance between ARMC10 expression and clinicopathological factors, immune infiltration degree and prognosis in PAAD.Results: High expression of ARMC10 was relevant to T stage, M stage, pathologic stage, histologic grade, residual tumor, primary therapy outcome (P<0.05) and related to lower Overall-Survival (OS), Disease-Specific Survival (DSS), and Progression-Free Interval (PFI). Gene set enrichment analysis showed that ARMC10 was related to methylation in neural precursor cells (NPC), G alpha (i) signaling events, APC targets, energy metabolism, potassium channels and IL10 synthesis. The expression level of ARMC10 was positively related to the abundance of T helper cells and negatively to that of plasmacytoid dendritic cells (pDCs). Knocking down of ARMC10 could lead to lower proliferation, invasion, migration ability and colony formation rate of PAAD cells in vitro.Conclusions: Our research firstly discovered ARMC10 as a novel prognostic biomarker for PAAD patients and played a crucial role in immune regulation in PAAD.

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Identification of a gene set correlated with immune status in ovarian cancer by transcriptome-wide data mining

10.21203/rs.3.rs-17604/v1 ◽

2020 ◽

Author(s):

Lili Fan ◽

Han Lei ◽

Ying Lin ◽

Zhengwei Zhou ◽

Guang Shu ◽

...

Keyword(s):

Ovarian Cancer ◽

Immune Cell ◽

Good Prognosis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Survival Prognosis ◽

Immune Activity ◽

Gene Set ◽

Immune Infiltration ◽

Keywords Ovarian Cancer

Abstract Background : Ovarian cancer (OC) is a serious tumor disease in gynecology. Many papers have reported that high tumor mutational burden (TMB) can generate many neoantigens to result in a higher degree of tumor immune infiltration, so our study aims to predict the key molecules in OC immunotherapy by combined TMB with immunoactivity-related gene. Method: We divided OC cases into two groups: the low & high TMB group hinged on the somatic mutation data from the Cancer Genome Atlas (TCGA). We also used single-sample gene set enrichment analysis (ssGSEA) scores of immune cell types to conduct unsupervised clustering of OC patients in the TCGA cohort and some of them were defined as the low & high immunity group. Besides, to further understand the function of these genes, we conducted Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, protein-protein interaction network, survival prognosis analysis and immune infiltration analysis. Finally, the effects on prognosis and immunotherapy in OC patients were explored by the Group on Earth Observations verification the patients' responses to immunotherapy. Results: We found that the higher the TMB was associated with the higher OC grades. Moreover, both high TMB and high immunity were significantly correlated with a good prognosis of OC. Then, 14 up-regulated differential expression genes (Up-DEGs) that were closely related to the prognosis of OC patients were screened according to the high TMB group and the high immunity group. Next, pathway analysis revealed that Up-DGEs were mainly involved in immune response and T cell proliferation. Finally, four genes had a good prognosis and were validated in the GEO dataset which included CXCL13, FCRLA, PLA2G2D, and MS4A1. We also identified that four genes had a good prognosis in melanoma patients treated with anti-PD-L1 and anti-CTLA-4 in the TIDE database. Conclusion: High TMB can promote immune cell infiltration and increases immune activity. And our analysis also demonstrated that the higher the TMB, the higher the immune activity, the better the prognosis of OC. Altogether, we found that CXCL13, FCRLA, PLA2G2D, and MS4A1 may be biomarkers for OC immunotherapy. Keywords: ovarian cancer, TMB, immune cells infiltration, survival prognosis.

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Hypoxic Characteristic in the Immunosuppressive Microenvironment of Hepatocellular Carcinoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.611058 ◽

2021 ◽

Vol 12 ◽

Author(s):

Zhuomao Mo ◽

Daiyuan Liu ◽

Dade Rong ◽

Shijun Zhang

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Cancer Genome ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Immune Checkpoints ◽

Immune Cell Infiltration ◽

Immunosuppressive Microenvironment

Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC.Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score.Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts.Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.

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Hsa_circ_0004831 serves as a blood-based prognostic biomarker for colorectal cancer and its potentially circRNA-miRNA-mRNA regulatory network construction

10.21203/rs.3.rs-55340/v3 ◽

2020 ◽

Author(s):

Linlin Xing ◽

Mengyan Xia ◽

Xin Jiao ◽

Ling Fan

Keyword(s):

Colorectal Cancer ◽

Extracellular Vesicles ◽

Regulatory Network ◽

Prognostic Biomarker ◽

Qpcr Assay ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Expression Level ◽

Blood Samples ◽

Tumorigenesis And Progression

Abstract Background: Colorectal cancer (CRC) is a common malignant tumor with unsatisfactory overall prognosis. CircRNAs could be promising prognostic biomarkers in cancers, and play important role in the process of tumorigenesis and progression. Here, we explored the role of hsa_circ_0004831 in blood extracellular vesicles and its prognostic value in CRC. Methods: The circRNA and mRNA expression level matrix in extracellular vesicles of CRC and normal samples were obtained from the exoRBase database. The corresponding miRNA expression level matrix in extracellular vesicles was downloaded from the BBCancer database. Differentially expressed circRNAs, miRNAs and mRNAs were identified using the limma package of R software at the cut-off criteria of fold change (FC) > 2 and adj. p < 0.05. RT-qPCR assay was conducted to measure hsa_circ_0004831 expression level in CRC blood samples. A circRNA-miRNA-mRNA regulatory network of hsa_circ_0004831 was constructed based on competitive endogenous RNA mechanism and differentially expressed genes. The mRNAs co-expressed with hsa_circ_0004831 were screened at the cut-off criteria of pearson |r| > 0.3 and p < 0.05. Gene set enrichment analysis (GSEA) based on co-expressed mRNAs was used to explore the potential molecular function of hsa_circ_0004831. Results: Differentially expressed circRNAs, miRNAs and mRNAs were identified and hsa_circ_0004831 had a FC value of 3.92 in CRC blood extracellular vesicles. The RT-qPCR assay showed that the hsa_circ_0004831 was up-regulated in CRC blood samples. The overall survival analysis found that high expression of hsa_circ_0004831 was linked with poorer prognosis. Finally, a circRNA-miRNA-mRNA regulatory network of hsa_circ_0004831 was constructed based on down-regulated miR-4326 and 12 up-regulated mRNAs. GSEA indicated that mRNAs co-expressed with hsa_circ_0004831 were involved in EMT, WNT and p53 signaling pathways.Conclusions: The study confirmed the up-regulation of hsa_circ_0004831 in CRC, and it may act as a vital prognostic biomarker. The circRNA-miRNA-mRNA regulatory network of hsa_circ_0004831 could be used to uncover the tumorigenesis and progression of CRC.

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Competing endogenous RNA (ceRNA) hypothetic model based on comprehensive analysis of long non-coding RNA expression in lung adenocarcinoma

PeerJ ◽

10.7717/peerj.8024 ◽

2019 ◽

Vol 7 ◽

pp. e8024 ◽

Cited By ~ 5

Author(s):

Xiwen Wang ◽

Rui Su ◽

Qiqiang Guo ◽

Jia Liu ◽

Banlai Ruan ◽

...

Keyword(s):

Lung Cancer ◽

Inverse Correlation ◽

The Cancer Genome Atlas ◽

Competing Endogenous Rna ◽

Cerna Network ◽

Kaplan Meier ◽

Non Coding Rna ◽

Pathway Analyses ◽

Lung Adenocarcinomas ◽

Cancer Tissues

Background Non-small cell lung cancer (NSCLC) is a major subtype of lung cancer with high malignancy and bad prognosis, consisted of lung adenocarcinomas (LUAD) and lung squamous cell carcinomas (LUSC) chiefly. Multiple studies have indicated that competing endogenous RNA (ceRNA) network centered long noncoding RNAs (lncRNAs) can regulate gene expression and the progression of various cancers. However, the research about lncRNAs-mediated ceRNA network in LUAD is still lacking. Methods In this study, we analyzed the RNA-seq database from The Cancer Genome Atlas (TCGA) and obtained dysregulated lncRNAs in NSCLC, then further identified survival associated lncRNAs through Kaplan–Meier analysis. Quantitative real time PCR (qRT-PCR) was performed to confirm their expression in LUAD tissues and cell lines. The ceRNA networks were constructed based on DIANA-TarBase and TargetScan databases and visualized with OmicShare tools. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to investigate the potential function of ceRNA networks. Results In total, 1,437 and 1,699 lncRNAs were found to be up-regulated in LUAD and LUSC respectively with 895 lncRNAs overlapping (|log2FC| > 3, adjusted P value <0.01). Among which, 222 lncRNAs and 46 lncRNAs were associated with the overall survival (OS) of LUAD and LUSC, and 18 out of 222 up-regulated lncRNAs were found to have inverse correlation with LUAD patients’ OS (|log2FC| > 3, adjusted P value < 0.02). We selected 3 lncRNAs (CASC8, LINC01842 and VPS9D1-AS1) out of these 18 lncRNAs and confirmed their overexpression in lung cancer tissues and cells. CeRNA networks were further constructed centered CASC8, LINC01842 and VPS9D1-AS1 with 3 miRNAs and 100 mRNAs included respectively. Conclusion Through comprehensively analyses of TCGA, our study identified specific lncRNAs as candidate diagnostic and prognostic biomarkers for LUAD. The novel ceRNA network we created provided more insights into the regulatory mechanisms underlying LUAD.

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