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Long non-coding RNA LCAL62 / LINC00261 is associated with lung adenocarcinoma prognosis.

ABSTRACT: Background:More than half of non-small cell lung cancer (NSCLC) patients present with metastatic disease at initial diagnosis with an estimated five-year survival rate of ~5%. Despite advances in understanding primary lung cancer oncogenesis metastatic disease remains poorly characterized. Recent studies demonstrate important roles of long non-coding RNAs (lncRNAs) in tumor physiology and as prognostic markers. Therefore, we present the first transcriptome analysis to identify lncRNAs altered in metastatic lung adenocarcinoma leading to the discovery and characterization of the lncRNA LCAL62 as a prognostic biomarker. Patients and methods:RNA-Seq, microarray, nanoString expression, and clinical data from 1,116 LUAD patients across six independent cohorts and 83 LUAD cell lines were used to discover and evaluate the survival association of metastasis associated lncRNAs. Coexpression and gene set enrichment analyses were used to establish gene regulatory networks and implicate metastasis associated lncRNAs in specific biological processes. Results:Our integrative analysis discovered LCAL62 as the most down-regulated lncRNA in metastasis. Further low LCAL62 expression promoted aggressive phenotypes and regulated genes associated with metastasis (such as metastasis repressor FOXA2). Low LCAL62 expression corresponded to poor overall patient survival across five independent lung adenocarcinoma cohorts (n = 881) including our own nanoString validation cohort. Conclusion:We discovered that LCAL62 was down-regulated in lung cancer progression to promote invasive phenotypes, and lower expression was significantly associated with poor patient outcome and aggressive lung adenocarcinoma.

SUBMITTER: Dang HX

PROVIDER: S-EPMC7062942 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Long non-coding RNA <i>LCAL62 / LINC00261</i> is associated with lung adenocarcinoma prognosis.

Dang Ha X HX White Nicole M NM Rozycki Emily B EB Felsheim Brooke M BM Watson Mark A MA Govindan Ramaswamy R Luo Jingqin J Maher Christopher A CA

Heliyon 20200305 3

<h4>Background</h4>More than half of non-small cell lung cancer (NSCLC) patients present with metastatic disease at initial diagnosis with an estimated five-year survival rate of ~5%. Despite advances in understanding primary lung cancer oncogenesis metastatic disease remains poorly characterized. Recent studies demonstrate important roles of long non-coding RNAs (lncRNAs) in tumor physiology and as prognostic markers. Therefore, we present the first transcriptome analysis to identify lncRNAs al ...[more]

PMID: 32181394

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Project description:PurposeColon adenocarcinoma (COAD) is the most common type of colorectal cancer (CRC) and is associated with poor prognosis. Emerging evidence has demonstrated that glycosylation by long noncoding RNAs (lncRNAs) was associated with COAD progression. To date, however, the prognostic values of glycosyltransferase (GT)-related lncRNAs in COAD are still largely unknown.MethodsWe obtained the expression matrix of mRNAs and lncRNAs in COAD from The Cancer Genome Atlas (TCGA) database. Then, the univariate Cox regression analysis was conducted to identify 33 prognostic GT-related lncRNAs. Subsequently, LASSO and multivariate Cox regression analysis were performed, and 7 of 33 GT-related lncRNAs were selected to conduct a risk model. Gene set enrichment analysis (GSEA) was used to analyze gene signaling pathway enrichment of the risk model. ImmuCellAI, an online tool for estimating the abundance of immune cells, and correlation analysis were used to explore the tumor-infiltrating immune cells in COAD. Finally, the expression levels of seven lncRNAs were detected in colorectal cancer cell lines by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).ResultsA total of 1,140 GT-related lncRNAs were identified, and 7 COAD-specific GT-related lncRNAs (LINC02381, MIR210HG, AC009237.14, AC105219.1, ZEB1-AS1, AC002310.1, and AC020558.2) were selected to conduct a risk model. Patients were divided into high- and low-risk groups based on the median of risk score. The prognosis of the high-risk group was worse than that of the low-risk group, indicating the good reliability and specificity of our risk model. Additionally, a nomogram based on the risk score and clinical traits was built to help clinical decisions. GSEA showed that the risk model was significantly enriched in metabolism-related pathways. Immune infiltration analysis revealed that five types of immune cells were significantly different between groups, and two types of immune cells were negatively correlated with the risk score. Besides, we found that the expression levels of these seven lncRNAs in tumor cells were significantly higher than those in normal cells, which verified the feasibility of the risk model.ConclusionThe efficient risk model based on seven GT-related lncRNAs has prognostic potential for COAD, which may be novel biomarkers and therapeutic targets for COAD patients.

Project description:BackgroundCuproptosis or copper-dependent cell death is a newly identified non-apoptotic cell death pathway which plays a critical role in the development of multiple cancers. Long non-coding RNAs (lncRNAs) are increasingly recognized as crucial regulators of programmed cell death and lung adenocarcinoma (LUAD) development, and a comprehensive understanding of cuproptosis-related lncRNAs may improve prognosis prediction of LUAD. However, few studies have explored the association of cuproptosis-related lncRNAs with the prognosis of LUAD.MethodsThe RNA sequencing data and corresponding clinical information of patients were extracted from The Cancer Genome Atlas (TCGA) database. Five hundred LUAD patients were randomly divided into a training (n=250) and a testing cohort (n=250). Pearson correlations were performed to identify cuproptosis-related lncRNAs, and univariate Cox regression was performed to screen prognostic lncRNAs. A cuproptosis-related lncRNAs prognostic signature (CLPS) was constructed by the least absolute shrinkage and selection operator Cox regression. Kaplan-Meier analysis, receiver operating characteristic curves, and multivariate Cox regression were performed to verify the prognostic performance of CLPS. Additionally, immune cell infiltration was estimated using the single-sample gene-set enrichment analysis. pRRophetic algorithm and Tumor Immune Dysfunction and Exclusion algorithm were used to assess the immunotherapy and chemotherapy response, respectively.ResultsCLPS was established based on 61 cuproptosis-related prognostic lncRNAs and exhibited a satisfactory performance predicting LUAD patients' survival (area under the curve at 1, 3, 5 years was 0.784, 0.749, 0.775, respectively). multivariate Cox analysis confirmed the independent prognostic effect of CLPS (hazard ratio: 1.128; 95% confidence interval: 1.071-1.189; P<0.001), and a nomogram containing it exhibited robust validity in prognostic prediction. We further demonstrated a higher CLPS-risk score was associated with lower levels of signatures including immune cell infiltration, immune activation, and immune checkpoints.ConclusionsThe CLPS serves as an effective predictor for the prognosis and therapeutic responses of LUAD patients. Our findings provide promising novel biomarkers and therapeutic targets for LUAD.

Project description:Lung adenocarcinoma (LUAD) is the most common histological lung cancer, and it is the leading cause of cancer-related deaths worldwide. LncRNA-AL139385.1 (ENSG00000275880) is a novel lncRNA that is abnormally expressed in various cancer types including LUAD. However, the underlying biological function and potential mechanisms of AL139385.1 driving the progression of LUAD remain unclear. In this study, we investigated the role of AL139385.1 in LUAD and found that DNA hypomethylation was positively correlated with AL139385.1 expression in LUAD. Moreover, we uncover that the expression of AL139385.1 in LUAD tissues was significantly higher than that of AL139385.1 expression in adjacent normal tissues. Kaplan-Meier survival analysis showed that patients with higher AL139385.1 expression correlated with adverse overall survival and progression-free survival. Receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) value of AL139385.1 was 0.808. Correlation analysis showed that AL139385.1 expression was associated with immune infiltration in LUAD. We also found that AL139385.1 was upregulated in LUAD cancer tissues and cell lines. Knockdown of AL139385.1 significantly inhibited cell proliferation and migration abilities of LUAD. Finally, we constructed a ceRNA network that includes hsa-miR-532-5p and four mRNAs (GALNT3, CYCS, EIF5A, and ITGB4) specific to AL139385.1 in LUAD. Subsequent Kaplan-Meier survival analysis suggested that polypeptide N-acetylgalactosaminyltransferase 3 (GALNT3), cytochrome c, somatic (CYCS), eukaryotic translation initiation factor 5A (EIF5A), and integrin subunit beta 4 (ITGB4), were potential prognostic biomarkers for patients with LUAD. In conclusion, this finding provides possible mechanisms underlying the abnormal upregulation of AL139385.1 as well as a comprehensive view of the AL139385.1-mediated competing endogenous RNAs (ceRNA) network in LUAD, thereby highlighting its potential role in diagnosis and therapy.

Dataset Information

Long non-coding RNA LCAL62 / LINC00261 is associated with lung adenocarcinoma prognosis.

Publications

Long non-coding RNA <i>LCAL62 / LINC00261</i> is associated with lung adenocarcinoma prognosis.

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