Integrated Analysis of DNA Methylation and mRNA Expression Profiles Data to Identify Key Genes in Lung Adenocarcinoma

Evaluation of the Efficacy of OSU-2S in the Treatment of Non-Small-Cell Lung Cancer and Screening of Potential Targets of Action

(1) Background: OSU-2S is a derivative of FTY720 and exhibits significant inhibitory effects on various cancer cells. There is currently no research on the mechanism of the impact of OSU-2S on NSCLC development. We analysed and validated the hub genes and pharmacodynamic effects of OSU-2S to treat NSCLC. (2) Methods: The hub genes of OSU-2S for the treatment of NSCLC were screened in PharmMapper, genecard, and KM Plotter database by survival and expression analysis. The effect of OSU-2S on hub gene expression was verified by Western blot analysis. The ex vivo and in vivo efficacy of OSU-2S on tumour growth was verified using A549 cells and a xenografted animal model. (3) Results: A total of 7 marker genes for OSU-2S treatment of NSCLC were obtained. AURKA and S1PR1 were screened as hub genes. Significant differences in the expression of AURKA and S1PR1 between normal and lung adenocarcinoma (LUAD) tissues were found in the GEPIA2 database; Western blot showed that OSU-2S could affect p-AURKA and S1PR1 protein expression. OSU-2S significantly inhibited tumour growth in A549 cells and xenografted animal models. (4) Conclusions: Our study confirms the inhibitory effect of OSU-2S on NSCLC, screens and demonstrates its potential targets AURKA(p-AURKA) and S1PR1, and provides a research basis for treating NSCLC with OSU-2S.

CD5L-associated gene analyses highlight the dysregulations, prognostic effects, immune associations, and drug-sensitivity predicative potentials of LCAT and CDC20 in hepatocellular carcinoma

BACKGROUND

The dysregulation of CD5L has been reported in hepatocellular carcinoma (HCC). However, its functions in HCC were controversial. In this study, we aimed to identify CD5L-associated pathways and markers and explore their values in HCC diagnosis, prognosis and treatment.

METHODS

HCC datasets with gene expression profiles and clinical data in TCGA and ICGC were downloaded. The immune/stroma cell infiltrations were estimated with xCell. CD5L-associated pathways and CD5L-associated genes (CD5L-AGs) were identified with gene expression comparisons and gene set enrichment analysis (GSEA). Cox regression, Kaplan-Meier survival analysis, and least absolute shrinkage and selection operator (LASSO) regression analysis were performed. The correlations of the key genes with immune/stroma infiltrations, immunoregulators, and anti-cancer drug sensitivities in HCC were investigated. At protein level, the key genes dysregulations, their correlations and prognostic values were validated in clinical proteomic tumor analysis consortium (CPTAC) database. Serum CD5L and LCAT activity in 50 HCC and 30 normal samples were evaluated and compared. The correlations of serum LCAT activity with alpha-fetoprotein (AFP), albumin (ALB) and high-density lipoprotein (HDL) in HCC were also investigated.

RESULTS

Through systemic analyses, 14 CD5L-associated biological pathways, 256 CD5L-AGs and 28 CD5L-associated prognostic and diagnostic genes (CD5L-APDGs) were identified. A risk model consisting of LCAT and CDC20 was constructed for HCC overall survival (OS), which could discriminate HCC OS status effectively in both the training and the validation sets. CD5L, LCAT and CDC20 were shown to be significantly correlated with immune/stroma cell infiltrations, immunoregulators and 31 anti-cancer drug sensitivities in HCC. At protein level, the dysregulations of CD5L, LCAT and CDC20 were confirmed. LCAT and CDC20 were shown to be significantly correlated with proliferation marker MKI67. In serum, no significance of CD5L was shown. However, the lower activity of LCAT in HCC serum was obvious, as well as its significant positive correlations ALB and HDL concentrations.

CONCLUSIONS

CD5L, LCAT and CDC20 were dysregulated in HCC both at mRNA and protein levels. The LCAT-CDC20 signature might be new predicator for HCC OS. The associations of the three genes with HCC microenvironment and anti-cancer drug sensitivities would provide new clues for HCC immunotherapy and chemotherapy.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

Integration of gene expression and DNA methylation identifies epigenetically controlled modules related to PM2.5 exposure

Air pollution has been associated with adverse health effects across the life-course. Although underlying mechanisms are unclear, several studies suggested pollutant-induced changes in transcriptomic profiles. In this meta-analysis of transcriptome-wide association studies of 656 children and adolescents from three European cohorts participating in the MeDALL Consortium, we found two differentially expressed transcript clusters (FDR p < 0.05) associated with exposure to particulate matter < 2.5 µm in diameter (PM_2.5) at birth, one of them mapping to the MIR1296 gene. Further, by integrating gene expression with DNA methylation using Functional Epigenetic Modules algorithms, we identified 9 and 6 modules in relation to PM_2.5 exposure at birth and at current address, respectively (including NR1I2, MAPK6, TAF8 and SCARA3). In conclusion, PM_2.5 exposure at birth was linked to differential gene expression in children and adolescents. Importantly, we identified several significant interactome hotspots of gene modules of relevance for complex diseases in relation to PM_2.5 exposure.

Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis

Lung squamous cell carcinoma (LUSC) is often diagnosed at the advanced stage with poor prognosis. The mechanisms of its pathogenesis and prognosis require urgent elucidation. This study was performed to screen potential biomarkers related to the occurrence, development and prognosis of LUSC to reveal unknown physiological and pathological processes. Using bioinformatics analysis, the lung squamous cell carcinoma microarray datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were analyzed to identify differentially expressed genes (DEGs). Furthermore, PPI and WGCNA network analysis were integrated to identify the key genes closely related to the process of LUSC development. In addition, survival analysis was performed to achieve a prognostic model that accomplished good prediction accuracy. Three hundred and thirty–seven up–regulated and 119 down-regulated genes were identified, in which four genes have been found to play vital roles in LUSC development, namely CCNA2, AURKA, AURKB, and FEN1. The prognostic model contained 5 genes, which were all detrimental to prognosis. The AUC of the established prognostic model for predicting the survival of patients at 1, 3, and 5 years was 0.692, 0.722, and 0.651 in the test data, respectively. In conclusion, this study identified several biomarkers of significant interest for additional investigation of the therapies and methods of prognosis of lung squamous cell carcinoma.

Identification of key genes in non-small cell lung cancer by bioinformatics analysis

Background

Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors in the world, and it has become the leading cause of death of malignant tumors. However, its mechanisms are not fully clear. The aim of this study is to investigate the key genes and explore their potential mechanisms involving in NSCLC.

Methods

We downloaded gene expression profiles GSE33532, GSE30219 and GSE19804 from the Gene Expression Omnibus (GEO) database and analyzed them by using GEO2R. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes were used for the functional and pathway enrichment analysis. We constructed the protein-protein interaction (PPI) network by STRING and visualized it by Cytoscape. Further, we performed module analysis and centrality analysis to find the potential key genes. Finally, we carried on survival analysis of key genes by GEPIA.

Results

In total, we obtained 685 DEGs. Moreover, GO analysis showed that they were mainly enriched in cell adhesion, proteinaceous extracellular region, heparin binding. KEGG pathway analysis revealed that transcriptional misregulation in cancer, ECM-receptor interaction, cell cycle and p53 signaling pathway were involved in. Furthermore, PPI network was constructed including 249 nodes and 1,027 edges. Additionally, a significant module was found, which included eight candidate genes with high centrality features. Further, among the eight candidate genes, the survival of NSCLC patients with the seven high expression genes were significantly worse, including CDK1, CCNB1, CCNA2, BIRC5, CCNB2, KIAA0101 and MELK. In summary, these identified genes should play an important role in NSCLC, which can provide new insight for NSCLC research.

Survival analysis and functional annotation of long non-coding RNAs in lung adenocarcinoma

Long non-coding RNAs (lncRNAs) are a subclass of non-protein coding transcripts that are involved in several regulatory processes and are considered as potential biomarkers for almost all cancer types. This study aims to investigate the prognostic value of lncRNAs for lung adenocarcinoma (LUAD), the most prevalent subtype of lung cancer. To this end, the processed data of The Cancer Genome Atlas LUAD were retrieved from GEPIA and circlncRNAnet databases, matched with each other and integrated with the analysis results of a non-small cell lung cancer plasma RNA-Seq study. Then, the data were filtered in order to separate the differentially expressed lncRNAs that have a prognostic value for LUAD. Finally, the selected lncRNAs were functionally annotated using a bioinformatic and systems biology approach. Accordingly, we identified 19 lncRNAs as the novel LUAD prognostic lncRNAs. Also, based on our results, all 19 lncRNAs might be involved in lung cancer-related biological processes. Overall, we suggested several novel biomarkers and drug targets which could help early diagnosis, prognosis and treatment of LUAD patients.

CDC20 associated with cancer metastasis and novel mushroom‑derived CDC20 inhibitors with antimetastatic activity

Aberrant expression of cell division cycle 20 (CDC20) is associated with malignant progression and poor prognosis in various types of cancer. The development of specific CDC20 inhibitors may be a novel strategy for the treatment of cancer with elevated expression of CDC20. The aim of the current study was to elucidate the role of CDC20 in cancer cell invasiveness and to identify novel natural inhibitors of CDC20. The authors found that CDC20 knockdown inhibited the migration of chemoresistant PANC‑1 pancreatic cancer cells and the metastatic MDA‑MB‑231 breast cancer cell line. By contrast, the overexpression of CDC20 by plasmid transfection promoted the metastasizing capacities of the PANC‑1 cells and MCF‑7 breast cancer cells. It was also identified that a triterpene mixture extracted from the mushroom Poria cocos (PTE), purified triterpenes dehydropachymic acid, and polyporenic acid C (PPAC) downregulated the expression of CDC20 in PANC‑1 cells dose‑dependently. Migration was also suppressed by PTE and PPAC in a dose‑dependent manner, which was consistent with expectations. Taken together, the present study is the first, to the best of our knowledge, to demonstrate that CDC20 serves an important role in cancer metastasis and that triterpenes from P. cocos inhibit the migration of pancreatic cancer cells associated with CDC20. Further investigations are in progress to investigate the specific mechanism associated with CDC20 and these triterpenes, which may have future potential use as natural agents in the treatment of metastatic cancer.

Aneuploidy: Cancer strength or vulnerability?

Aneuploidy is a very rare and tissue‐specific event in normal conditions, occurring in a low number of brain and liver cells. Its frequency increases in age‐related disorders and is one of the hallmarks of cancer. Aneuploidy has been associated with defects in the spindle assembly checkpoint (SAC). However, the relationship between chromosome number alterations, SAC genes and tumor susceptibility remains unclear. Here, we provide a comprehensive review of SAC gene alterations at genomic and transcriptional level across human cancers and discuss the oncogenic and tumor suppressor functions of aneuploidy. SAC genes are rarely mutated but frequently overexpressed, with a negative prognostic impact on different tumor types. Both increased and decreased SAC gene expression show oncogenic potential in mice. SAC gene upregulation may drive aneuploidization and tumorigenesis through mitotic delay, coupled with additional oncogenic functions outside mitosis. The genomic background and environmental conditions influence the fate of aneuploid cells. Aneuploidy reduces cellular fitness. It induces growth and contact inhibition, mitotic and proteotoxic stress, cell senescence and production of reactive oxygen species. However, aneuploidy confers an evolutionary flexibility by favoring genome and chromosome instability (CIN), cellular adaptation, stem cell‐like properties and immune escape. These properties represent the driving force of aneuploid cancers, especially under conditions of stress and pharmacological pressure, and are currently under investigation as potential therapeutic targets. Indeed, promising results have been obtained from synthetic lethal combinations exploiting CIN, mitotic defects, and aneuploidy‐tolerating mechanisms as cancer vulnerability.

Identification of genes and analysis of prognostic values in nonsmoking females with non-small cell lung carcinoma by bioinformatics analyses

Background

This study was performed to identify disease-related genes and analyze prognostic values in nonsmoking females with non-small cell lung carcinoma (NSCLC).

Materials and methods

Gene expression profile GSE19804 was downloaded from the Gene Expression Omnibus (GEO) database and analyzed by using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for the functional and pathway enrichment analysis. Then, the Search Tool for the Retrieval of Interacting Genes, Cytoscape, and Molecular Complex Detection were used to construct the protein–protein interaction (PPI) network and identify hub genes. Finally, the Kaplan–Meier plotter online tool was used for the overall survival analysis of hub genes.

Results

A cohort of 699 differentially expressed genes was screened, and they were mainly enriched in the terms of ECM–receptor interaction, focal adhesion, and cell adhesion molecules. A PPI network was constructed, and 15 hub genes were identified base on the subset of PPI network. Then, two significant modules were detected and several genes were found to be associated with the cell cycle pathway. Finally, nine hub genes’ (UBE2C, DLGAP5, TPX2, CCNB2, BIRC5, KIF20A, TOP2A, GNG11, and ANXA1) expressions were found to be associated with the prognosis of the patients.

Conclusion

Overall, we propose that the cell cycle pathway may play an important role in nonsmoking females with NSCLC and the nine hub genes may be further explored as potential targets for NSCLC diagnosis and treatment.

In vivo and in vitro effects of hyperplasia suppressor gene on the proliferation and apoptosis of lung adenocarcinoma A549 cells

Lung adenocarcinoma is the most common subtype of non-small cell lung cancer (NSCLC). Hyperplasia suppressor gene (HSG) has been reported to inhibit cell proliferation, migration, and remodeling in cardiovascular diseases. However, there lacks systematic researches on the effect of HSG on the apoptosis and proliferation of lung adenocarcinoma A549 cells and data of in vivo experiments. The present study aims to investigate the effects of HSG gene silencing on proliferation and apoptosis of lung adenocarcinoma A549 cells. The human lung adenocarcinoma A549 cell was selected to construct adenovirus vector. Reverse transcription-quantitative PCR (RT-qPCR) and Western blot analysis were conducted to detect expressions of HSG and apoptosis related-proteins. Cell Counting Kit (CCK)-8 assay was performed to assess A549 cell proliferation and flow cytometry to analyze cell cycle and apoptosis rate. The BALB/C nude mice were collected to establish xenograft model. Silenced HSG showed decreased mRNA and protein expressions of HSG, and elevated A549 cell survival rates at the time point of 24, 48, and 72 h. The ratio of cells at G₀/G₁ phase and apoptosis rate decreased and the ratio of cells at S- and G₂/M phases increased following the silencing of HSG. There were decreases of B cell lymphoma-2 (Bcl-2)-associated X protein (Bax), Caspase-3, and Caspase-8 expressions but increases in Bcl-2 induced by silenced HSG. As for the xenograft in nude mice, tumor volume increased, and apoptosis index (AI) decreased after HSG silencing. These results indicate that HSG gene silencing may promote the proliferation of A549 cells and inhibit the apoptosis. HSG may be a promising target for the treatment of lung adenocarcinoma.

Downregulation of HOXA3 in lung adenocarcinoma and its relevant molecular mechanism analysed by RT-qPCR, TCGA and in silico analysis

Recent studies have indicated that homeobox A3 (HOXA3) functions as a carcinogen in colon cancer and the methylation level of HOXA3 is significantly increased in lung adenocarcinoma (LUAD) tissues. However, at least to the best of our knowledge, few studies to date have been performed on HOXA3 in non-small cell lung cancer (NSCLC). Therefore, further studies on HOXA3 expression in NSCLC and the potential regulatory mechanisms are urgently required. In this study, HOXA3 expression in 55 tissues of cases of NSCLC and corresponding non-lung cancer tissues was detected by reverse transcription-quantitative PCR (RT-qPCR). In addition, the clinical significance of HOXA3 expression in NSCLC was evaluated using the Cancer Genome Atlas (TCGA) database. Bioinformatics analysis was then performed to elucidate the potential molecular mechanisms of action of HOXA3. Furthermore, the potential target microRNAs (miRNAs or miRs) of HOXA3 were predicted using miRWalk2.0. Based on Gene Expression Omnibus (GEO) and TGCA databases, standardized mean difference (SMD) and sROC methods were used for meta-analyses of the expression of potential target miRNAs of HOXA3 in NSCLC to evaluate their association with HOXA3. The results revealed that the HOXA3 expression levels in NSCLC, LUAD and lung squamous cell carcinoma (LUSC) were 0.1130±0.1398, 0.1295±0.16890 and 0.0906±0.0846, respectively. These values were all decreased compared with the normal tissues (0.1877±0.1975, 0.2337±0.2405 and 0.1249±0.0873, respectively, P<0.05). The TCGA database also revealed the low expression trend of HOXA3. The downregulation of HOXA3 may play an important role in the progression and the poor prognosis of LUAD. The TCGA database also suggested that HOXA3 in LUAD and LUSC tissues exhibited certain mutational levels. In addition, the methylation levels in the NSCLC, LUAD and LUSC tissues significantly increased [NSCLC: fold change (FC), 1.3226; P<0.001; LUAD: FC, 1.2712; P<0.001; and LUSC: FC, 1.3786; P<0.001]. According to the analyses using the Kyoto Encyclopedia of Genes and Genomes (KEGG), we found that the co-expression HOXA3 genes were mainly associated with the focal adhesion signalling pathway and the ECM-receptor interaction signalling pathway. Furthermore, the predicted miRNA, miR-372-3p, exhibited a high expression in both the NSCLC and LUAD tissues (P<0.05). On the whole, the findings of this study indicate that low HOXA3 expression may play a certain role in LUAD; however, its association with LUSC still requires further investigation. HOXA3 function may be achieved through different pathways or target miRNAs. However, the specific underlying mechanisms need to be confirmed through various functional studies.

Gene promoter and exon DNA methylation changes in colon cancer development - mRNA expression and tumor mutation alterations

Background

DNA mutations occur randomly and sporadically in growth-related genes, mostly on cytosines. Demethylation of cytosines may lead to genetic instability through spontaneous deamination. Aims were whole genome methylation and targeted mutation analysis of colorectal cancer (CRC)-related genes and mRNA expression analysis of TP53 pathway genes.

Methods

Long interspersed nuclear element-1 (LINE-1) BS-PCR followed by pyrosequencing was performed for the estimation of global DNA metlyation levels along the colorectal normal-adenoma-carcinoma sequence. Methyl capture sequencing was done on 6 normal adjacent (NAT), 15 adenomatous (AD) and 9 CRC tissues. Overall quantitative methylation analysis, selection of top hyper/hypomethylated genes, methylation analysis on mutation regions and TP53 pathway gene promoters were performed. Mutations of 12 CRC-related genes (APC, BRAF, CTNNB1, EGFR, FBXW7, KRAS, NRAS, MSH6, PIK3CA, SMAD2, SMAD4, TP53) were evaluated. mRNA expression of TP53 pathway genes was also analyzed.

Results

According to the LINE-1 methylation results, overall hypomethylation was observed along the normal-adenoma-carcinoma sequence. Within top50 differential methylated regions (DMRs), in AD-N comparison TP73, NGFR, PDGFRA genes were hypermethylated, FMN1, SLC16A7 genes were hypomethylated. In CRC-N comparison DKK2, SDC2, SOX1 genes showed hypermethylation, while ERBB4, CREB5, CNTN1 genes were hypomethylated. In certain mutation hot spot regions significant DNA methylation alterations were detected. The TP53 gene body was addressed by hypermethylation in adenomas. APC, TP53 and KRAS mutations were found in 30, 15, 21% of adenomas, and in 29, 53, 29% of CRCs, respectively. mRNA expression changes were observed in several TP53 pathway genes showing promoter methylation alterations.

Conclusions

DNA methylation with consecutive phenotypic effect can be observed in a high number of promoter and gene body regions through CRC development.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4609-x) contains supplementary material, which is available to authorized users.

Genetic variation in CDH13 gene was associated with non-small cell lung cancer (NSCLC): A population-based case-control study

Cadherin 13 (CDH13, T-cadherin, H-cadherin) has been identified as an anti-oncogene in various cancers. Recent studies have reported that downregulation of H-cadherin in cancers is associated with CDH13 promoter hypermethylation, which could be affected by the single nucleotide polymorphisms (SNPs) near CpG sites in the CDH13 promoter. In the current study, we investigated and analyzed the association of seven SNPs (rs11646213, rs12596316, rs3865188, rs12444338, rs4783244, rs12051272 and rs7195409) with non-small cell lung cancer (NSCLC) using logistic regression analysis. SNPs rs11646213, rs12596316, rs3865188 and rs12444338 are located in the promoter region, rs4783244 and rs12051272 are located in intron 1, and rs7195409 is located in intron 7. A total of 454 patients with NSCLC were placed into a NSCLC group and 444 healthy controls were placed into a control group, all participants were recruited to genotype the SNPs using Taqman assay. Our results showed that the allelic frequencies of rs11646213 were significantly different between NSCLC and control groups (P = 0.006). In addition, the association analysis of these SNPs stratified into NSCLC pathologic stages I+II and III+IV showed that the allelic frequencies rs7195409 had a significant difference between NSCLC pathologic stages I+II and III+IV (P = 0.006). Our results indicated that the rs11646213 and rs7195409 in CDH13 could be associated with NSCLC or its pathologic stages in the Chinese Han population.

Identification of dysregulated long non-coding RNAs/microRNAs/mRNAs in TNM I stage lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the primary subtype in lung cancer, which is the leading cause of cancer-related death worldwide. This study aimed to investigate the aberrant expression profiling of long non-coding RNA (lncRNA) in TNM I stage (stage I) LUAD. The lncRNA/mRNA/miRNA expression profiling of stage I LUAD and adjacent non-tumor tissues from 4 patients were measured by RNA-sequencing. Total of 175 differentially expressed lncRNAs (DELs), 1321 differentially expressed mRNAs (DEMs) and 94 differentially expressed microRNAs (DEMIs) were identified in stage I LUAD. DEMI-DEM regulatory network consisted of 544 nodes and 1123 edge; miR-200 family members had high connectivity with DEMs. In DEL-DEM co-expression network, CDKN2B-AS1, FENDRR and LINC00312 had the high connectivity with DEMs, which co-expressed with 105, 63 and 61 DEMs, respectively. DEL-DEMI-DEM network depicted the links among DELs, DEMI and DEMs. Identified DEMs were significantly enriched in cell adhesion molecules, focal adhesion and tight junction of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways; and enriched in cell adhesion, angiogenesis and regulation of cell proliferation of Gene Ontology biological processes. Quantitative real-time polymerase chain reaction results were generally consistent with our bioinformatics analyses. LINC00312 and FENDRR had diagnostic value for LUAD patients in The Cancer Genome Atlas database. Our study might lay the foundation for illumination of pathogenesis of LUAD and identification of potential therapeutic targets and novel diagnosis biomarkers for LUAD patients.