scholarly journals Autophagy‐related Long Non-coding RNA Signature Associated with Prognosis of Lung Adenocarcinoma

2021 ◽  
Author(s):  
Guofei Zhang ◽  
Jiayi Shen ◽  
Zipu Yu ◽  
Gang Shen ◽  
Chengxiao Liang
Keyword(s):  
Lung Adenocarcinoma ◽  
Molecular Mechanisms ◽  
Cox Regression ◽  
Microarray Dataset ◽  
Risk Groups ◽  
The Cancer Genome Atlas ◽  
Non Coding Rna ◽  
Cancer Genome Atlas ◽  
Non Coding Rnas ◽  
Long Non Coding Rna

Abstract BackgroundEvidence suggests that long non-coding RNAs (lncRNAs) are involved in various cancers. Here, we developed and evaluated an autophagy-related prognostic lncRNA signature for lung adenocarcinoma (LUAD). ResultsUsing a publicly available microarray dataset from The Cancer Genome Atlas, we analyzed the lncRNA expression profile in a cohort of 439 LUAD patients. The lncRNA-mRNA co-expression network along with univariate and multivariate Cox regression analyses were used to determine 15 autophagy-related lncRNA signatures that were significantly correlated with patient overall survival. Autophagy-related lncRNA signatures stratified patients into high- and low-risk groups with significantly different survival (hazard ratio = 3.256, 95% confidence interval = 2.858–4.101, P < 0.001). The lncRNA signature was further confirmed in other independent datasets. Moreover, the lncRNA signature had prognostic value independent of routine clinical factors. Functional analysis indicated that autophagy-related lncRNA signatures may be involved in LUAD via known autophagy-related pathways. ConclusionsThis newly identified autophagy-related lncRNA signature is a more powerful prognostic tool than the clinicopathological factors routinely used to predict patient survival, and can provide further insights into the molecular mechanisms underlying LUAD.

scholarly journals Long Non-coding RNA Expression Profiling Identifies a Four-Long Non-coding RNA Prognostic Signature for Isocitrate Dehydrogenase Mutant Glioma

2020 ◽  
Vol 11 ◽  
Author(s):  
Yusheng Chen ◽  
Yang Guo ◽  
Hang Chen ◽  
Fengjin Ma
Keyword(s):  
Isocitrate Dehydrogenase ◽  
Microarray Dataset ◽  
Risk Groups ◽  
The Cancer Genome Atlas ◽  
Regulation Mechanism ◽  
Non Coding Rna ◽  
Clinicopathologic Factors ◽  
Cox Analysis ◽  
Long Non Coding Rna ◽  
Genome Atlas

Background: Isocitrate dehydrogenase (IDH) mutant is one of the most robust and important genetic aberrations in glioma. However, the underlying regulation mechanism of long non-coding RNA (lncRNA) in IDH mutant glioma has not been systematically portrayed.Methods:In this work, 775 IDH mutant glioma samples with transcriptome data, including 167 samples from the Chinese Glioma Genome Atlas (CGGA) RNAseq dataset, 390 samples from The Cancer Genome Atlas (TCGA) dataset, 79 samples from GSE16011 dataset, and 139 samples from CGGA microarray dataset, were enrolled. R language and GraphPad Prism software were applied for the statistical analysis and graphical work.Results: By comparing the differentially lncRNA genes between IDH mutant and IDH wild-type glioma samples, a four-lncRNA (JAG1, PVT1, H19, and HAR1A) signature was identified in IDH mutant glioma patients. The signature model was established based on the expression level and the regression coefficient of the four lncRNA genes. IDH mutant glioma samples could be successfully stratified into low-risk and high-risk groups in CGGA RNAseq, TCGA, GSE16011, and CGGA microarray databases. Meanwhile, multivariate Cox analysis showed that the four-lncRNA signature was an independent prognostic biomarker after adjusting for other clinicopathologic factors. Moreover, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the immune response and cellular metabolism were significantly associated with the four-lncRNA risk signature.Conclusion: Taken together, the four-lncRNA risk signature was identified as a novel prognostic marker for IDH mutant glioma patients and may potentially lead to improvements in the lives of glioma patients.

scholarly journals A long non-coding RNA signature predicts survival for glioblastoma as prognostic biomarkers

2020 ◽  
Author(s):  
Zhenzhe Li ◽  
Zhonghua Lv ◽  
Lei Yu ◽  
Sibin Zhang ◽  
Yingjie Wang ◽  
...  
Keyword(s):  
Noncoding Rna ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Differential Analysis ◽  
Cox Regression Analysis ◽  
Non Coding Rna ◽  
Cancer Genome Atlas ◽  
The Central Nervous System ◽  
Long Non Coding Rna

Abstract Background: Glioblastoma (GBM) is one of the most fatal tumors in the central nervous system. Its prognosis is very poor. There is increasing evidence that long noncoding RNA (lncRNA) participates in the biological process of glioblastoma. Nevertheless, the role of lncRNA in predicting the prognosis of GBM is still uncertain. Methods: In this study, using RNA-Seq and clinical follow-up data of GBM patients from The Cancer Genome Atlas (TCGA), we performed differential analysis of lncRNA, univariable and multivariable Cox regression analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Ontology (GO) analysis.Results: We identified four lncRNAs closely interrelated with survival and prognosis of GBM patients. This lncRNA signature was effective in both the training set and the testing set, and it was independent to clinical factors.Conclusions: Our data suggested that the four lncRNAs could be used as promising biomarkers for predicting prognosis in GBM patients.

scholarly journals Comprehensive analysis of competitive endogenous RNA associated with immune infiltration in lung adenocarcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wenjie Chen ◽  
Wen Li ◽  
Zhenkun Liu ◽  
Guangzhi Ma ◽  
Yunfu Deng ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Mast Cells ◽  
Correlation Analysis ◽  
Lung Adenocarcinoma ◽  
Molecular Mechanisms ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Cerna Network ◽  
Monocytes And Macrophages ◽  
Competitive Endogenous Rna

AbstractTo identify the prognostic biomarker of the competitive endogenous RNA (ceRNA) and explore the tumor infiltrating immune cells (TIICs) which might be the potential prognostic factors in lung adenocarcinoma. In addition, we also try to explain the crosstalk between the ceRNA and TIICs to explore the molecular mechanisms involved in lung adenocarcinoma. The transcriptome data of lung adenocarcinoma were obtained from The Cancer Genome Atlas (TCGA) database, and the hypergeometric correlation of the differently expressed miRNA-lncRNA and miRNA-mRNA were analyzed based on the starBase. In addition, the Kaplan–Meier survival and Cox regression model analysis were used to identify the prognostic ceRNA network and TIICs. Correlation analysis was performed to analysis the correlation between the ceRNA network and TIICs. In the differently expressed RNAs between tumor and normal tissue, a total of 190 miRNAs, 224 lncRNAs and 3024 mRNAs were detected, and the constructed ceRNA network contained 5 lncRNAs, 92 mRNAs and 10 miRNAs. Then, six prognostic RNAs (FKBP3, GPI, LOXL2, IL22RA1, GPR37, and has-miR-148a-3p) were viewed as the key members for constructing the prognostic prediction model in the ceRNA network, and three kinds of TIICs (Monocytes, Macrophages M1, activated mast cells) were identified to be significantly related with the prognosis in lung adenocarcinoma. Correlation analysis suggested that the FKBP3 was associated with Monocytes and Macrophages M1, and the GPI was obviously related with Monocytes and Macrophages M1. Besides, the LOXL2 was associated with Monocytes and Activated mast cells, and the IL22RA1 was significantly associated with Monocytes and Macrophages M1, while the GPR37 and Macrophages M1 was closely related. The constructed ceRNA network and identified Monocytes, Macrophages M1 and activated Mast cells are all prognostic factors for lung adenocarcinoma. Moreover, the crosstalk between the ceRNA network and TIICs might be a potential molecular mechanism involved.

ADAMTS9-AS2: A functional long non-coding RNA in tumorigenesis

2021 ◽  
Vol 27 ◽  
Author(s):  
Wen Xu ◽  
Bei Wang ◽  
Yuxuan Cai ◽  
Jinlan Chen ◽  
Xing Lv ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Signaling Pathways ◽  
Therapeutic Target ◽  
Molecular Mechanisms ◽  
Human Cancer ◽  
Migration Inhibition ◽  
Cancer Proliferation ◽  
Non Coding Rna ◽  
Non Coding Rnas ◽  
Long Non Coding Rna

Background: Long non-coding RNAs (lncRNA) have been identified as novel molecular regulators in cancers. LncRNA ADAMTS9-AS2 can mediate the occurrence and development of cancer through various ways such as regulating miRNAs, activating the classical signaling pathways in cancer, and so on, which have been studied by many scholars. In this review, we summarize the molecular mechanisms of ADAMTS9-AS2 in different human cancers. Methods: Through a systematic search of PubMed, lncRNA ADAMTS9-AS2 mediated molecular mechanisms in cancer are summarized inductively. Results: ADAMTS9-AS2 aberrantly expression in different cancers is closely related to cancer proliferation, invasion, migration, inhibition of apoptosis. The involvement of ADAMTS9-AS2 in DNA methylation, mediating PI3K / Akt / mTOR signaling pathways, regulating miRNAs and proteins, and such shows its significant potential as a therapeutic cancer target. Conclusion: LncRNA ADAMTS9-AS2 can become a promising biomolecular marker and a therapeutic target for human cancer.

scholarly journals Long Non-Coding RNA (lncRNA) in Oral Squamous Cell Carcinoma: Biological Function and Clinical Application

Cancers ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 5944
Author(s):  
Jianfei Tang ◽  
Xiaodan Fang ◽  
Juan Chen ◽  
Haixia Zhang ◽  
Zhangui Tang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Non Coding Rna ◽  
Potential Applications ◽  
Non Coding Rnas ◽  
Long Non Coding Rna

Oral squamous cell carcinoma (OSCC) is a type of malignancy with high mortality, leading to poor prognosis worldwide. However, the molecular mechanisms underlying OSCC carcinogenesis have not been fully understood. Recently, the discovery and characterization of long non-coding RNAs (lncRNAs) have revealed their regulatory importance in OSCC. Abnormal expression of lncRNAs has been broadly implicated in the initiation and progress of tumors. In this review, we summarize the functions and molecular mechanisms regarding these lncRNAs in OSCC. In addition, we highlight the crosstalk between lncRNA and tumor microenvironment (TME), and discuss the potential applications of lncRNAs as diagnostic and prognostic tools and therapeutic targets in OSCC. Notably, we also discuss lncRNA-targeted therapeutic techniques including CRISPR-Cas9 as well as immune checkpoint therapies to target lncRNA and the PD-1/PD-L1 axis. Therefore, this review presents the future perspectives of lncRNAs in OSCC therapy, but more research is needed to allow the applications of these findings to the clinic.

scholarly journals Overexpression of Long Non-Coding RNA ZXF2 Promotes Lung Adenocarcinoma Progression Through c-Myc Pathway

2015 ◽  
Vol 35 (6) ◽  
pp. 2360-2370 ◽  
Author(s):  
Ze-Tian Yang ◽  
Zhihong Li ◽  
Xian-Guo Wang ◽  
Tao Tan ◽  
Frank Yi ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Lung Adenocarcinoma ◽  
Tumor Progression ◽  
Molecular Mechanisms ◽  
A549 Cells ◽  
Potential Interaction ◽  
Migration And Invasion ◽  
Relative Expression Level ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Objective: To investigate the expression of long non-coding RNA ZXF2 in lung adenocarcinoma tissues and its effect on cell proliferation, migration and invasion. Methods: Forty pairs of cancerous and adjacent non-cancerous lung adenocarcinoma specimens were collected for the studies. Quantitative real-time PCR was used to analyze the expression of ZXF2 in tumor tissues and adjacent normal tissues. The expression of ZXF2 was correlated with patients' clinico-pathological data. Molecular pathway controlled by ZXF2 was explored by using small interfering RNA (siRNA) technology. CCK-8 cell proliferation assay, flow cytometry analysis and transwell assays were used to evaluate cell proliferation, migration and invasion. Results: The expression of ZXF2 was 2 fold or higher in 27 out of 40 (67.5%) cases of lung adenocarcinoma specimens than that in non-cancerous tissues (P<0.05). The relative expression level of ZXF2 was positively correlated with tumor lymph node metastasis (χ2=8.485, P<0.05) and poor prognosis of the patients (p=0.0217). In order to explore the molecular mechanisms of ZXF2 mediated tumor progression, ZXF2 expression was inhibited by siRNA in A549 cells, a highly aggressive and metastatic lung adenocarcinoma cell line. We found that siRNA-ZXF2 treatment inhibited cell proliferation (P<0.01) leading to cell cycle arrest (P<0.01). The cell migration and invasion were suppressed by siRNA-ZXF2 treatment (P<0.01). Further biochemical studies revealed that the knockdown of ZXF2 led to down regulation of c-Myc signaling. Conclusion: ZXF2 was overexpressed in lung adenocarcinoma tissues and the high expression of ZXF was closely related to tumor progression through c-Myc related pathway. Given the fact that both ZXF2 and c-Myc are located in the same chromosome 8q24.2 loci, the potential interaction between ZXF2 and c-Myc might be a novel target for treatment of lung adenocarcinoma.

scholarly journals ITGB1-DT/ARNTL2 axis may be a novel biomarker in lung adenocarcinoma: a bioinformatics analysis and experimental validation

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bai-Quan Qiu ◽  
Xia-Hui Lin ◽  
Song-Qing Lai ◽  
Feng Lu ◽  
Kun Lin ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Prognostic Effect ◽  
Cancer Genome Atlas

Abstract Background Lung cancer is one of the most lethal malignant tumors that endangers human health. Lung adenocarcinoma (LUAD) has increased dramatically in recent decades, accounting for nearly 40% of all lung cancer cases. Increasing evidence points to the importance of the competitive endogenous RNA (ceRNA) intrinsic mechanism in various human cancers. However, behavioral characteristics of the ceRNA network in lung adenocarcinoma need further study. Methods Groups based on SLC2A1 expression were used in this study to identify associated ceRNA networks and potential prognostic markers in lung adenocarcinoma. The Cancer Genome Atlas (TCGA) database was used to obtain the patients' lncRNA, miRNA, and mRNA expression profiles, as well as clinical data. Informatics techniques were used to investigate the effect of hub genes on prognosis. The Cox regression analyses were performed to evaluate the prognostic effect of hub genes. The methylation, GSEA, and immune infiltration analyses were utilized to explore the potential mechanisms of the hub gene. The CCK-8, transwell, and colony formation assays were performed to detect the proliferation and invasion of lung cancer cells. Results We eventually identified the ITGB1-DT/ARNTL2 axis as an independent fact may promote lung adenocarcinoma progression. Furthermore, methylation analysis revealed that hypo-methylation may cause the dysregulated ITGB1-DT/ARNTL2 axis, and immune infiltration analysis revealed that the ITGB1-DT/ARNTL2 axis may affect the immune microenvironment and the progression of lung adenocarcinoma. The CCK-8, transwell, and colonu formation assays suggested that ITGB1-DT/ARNTL2 promotes the progression of lung adenocarcinoma. And hsa-miR-30b-3p reversed the ITGB1/ARNTL2-mediated oncogenic processes. Conclusion Our study identified the ITGB1-DT/ARNTL2 axis as a novel prognostic biomarker affects the prognosis of lung adenocarcinoma.

An Autophagy-related Long Non-coding RNA Signature for Breast Cancer

2021 ◽  
Vol 24 ◽  
Author(s):  
Feng Jiang ◽  
Chuyan Wu ◽  
Ming Wang ◽  
Ke Wei ◽  
Jimei Wang
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
Risk Groups ◽  
Low Risk ◽  
Optimal Cutoff ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Background: The most prevalent malignant tumor in women is breast cancer (BC). Autophagic therapies have been identified for their contribution in BC cell death. Therefore, the potential prognostic role of long non-coding RNA (lncRNA) related to autophagy in patients with BC was examined. Methods: The lncRNAs expression profiles were derived from The Cancer Genome Atlas (TCGA) database. Throughout univariate Cox regression and multivariate Cox regression test, lncRNA with BC prognosis have been differentially presented. We then defined the optimal cutoff point between high and low-risk groups. The receiver operating characteristic (ROC) curves were drawn to test this signature. In order to examine possible signaling mechanisms linked to these lncRNAs, the Gene Set Enrichment Analysis (GSEA) has been carried out. Results: Based on the lncRNA expression profiles for BC, a 9 lncRNA signature associated with autophagy was developed. The optimal cutoff value for high-risk and low-risk groups was used. The high-risk group had less survival time than the low-risk group. The result of this lncRNA signature was highly sensitive and precise. GSEA study found that the gene sets have been greatly enriched in many cancer pathways. Conclusions: Our signature of 9 lncRNAs related to autophagy has prognostic value for BC, and these lncRNAs related to autophagy may play an important role in BC biology.

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