scholarly journals Identification of lncRNAs associated with lung squamous cell carcinoma prognosis in the competitive endogenous RNA network

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7727 ◽  
Author(s):  
Lingyu Qi ◽  
Tingting Zhang ◽  
Yan Yao ◽  
Jing Zhuang ◽  
Cun Liu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Molecular Mechanisms ◽  
Lung Squamous Cell Carcinoma ◽  
Differentially Expressed ◽  
Cerna Network ◽  
Verification Methods ◽  
Competitive Endogenous Rna

Background Long noncoding RNAs (lncRNAs) play a role in the formation, development, and prognosis of various cancers. Our study aimed to identify prognostic-related lncRNAs in lung squamous cell carcinoma (LUSC), which may provide new perspectives for individualized treatment of patients. Materials and Methods The RNA sequencing (lncRNA, microRNA (miRNA), mRNA) data and clinical information related to LUSC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed RNA sequences were used to construct the competitive endogenous RNA (ceRNA) network. In present study, we mainly used two prognostic verification methods, Cox analysis and survival analysis, to identify the prognostic relevance of specific lncRNAs and construct prognostic model of lncRNA. Results Datasets on 551 samples of lncRNA and mRNA and 523 miRNA samples were retrieved from the TCGA database. Analysis of the normal and LUSC samples identified 170 DElncRNAs, 331 DEmiRNAs, and 417 DEmRNAs differentially expressed RNAs. The ceRNA network contained 27 lncRNAs, 43 miRNAs, and 11 mRNAs. Furthermore, we identified seven specific lncRNAs (ERVH48-1, HCG9, SEC62-AS1, AC022148.1, LINC00460, C5orf17, LINC00261) as potential prognostic factors after correlation analysis, and five of the seven lncRNAs (AC022148.1, HCG9, LINC00460, C5orf17, LINC00261) constructed a prognostic model of LUSC. Conclusion In present study, we identified seven lncRNAs in the ceRNA network that are associated with potential prognosis in LUSC patients, and constructed a prognostic model of LUSC which can be used to assess the prognosis risk of clinical patients. Further biological experiments are needed to elucidate the specific molecular mechanisms underlying them.

scholarly journals Competitive Endogenous RNA Network Construction and Comparison of Lung Squamous Cell Carcinoma in Smokers and Nonsmokers

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yan Yao ◽  
Tingting Zhang ◽  
Lingyu Qi ◽  
Ruijuan Liu ◽  
Gongxi Liu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Differential Expression Analysis ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cerna Network

Background. Lung squamous cell carcinoma (LUSC) is a subtype of highly malignant lung cancer with poor prognosis, for which smoking is the main risk factor. However, the underlying genetic and molecular mechanisms of smoking-related LUSC remain largely unknown. Methods. We mined existing LUSC-related mRNA, miRNA, and lncRNA transcriptome data and corresponding clinical data from The Cancer Genome Atlas (TCGA) database and divided them into smoking and nonsmoking groups, followed by differential expression analysis. Functional enrichment analysis of the unique differentially expressed mRNAs of the two groups was performed using the DAVID database. Subsequently, the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network of LUSC in smoking and nonsmoking groups was constructed. Finally, survival analyses were performed to determine the effects of differentially expressed lncRNAs/mRNAs/miRNAs that were involved in the ceRNA network on overall survival and to discover the hub genes. Results. A total of 1696 lncRNAs, 125 miRNAs, and 3246 mRNAs and 1784 lncRNAs, 96 miRNAs, and 3229 mRNAs with differentially expressed profiles were identified in the smoking and nonsmoking groups, respectively. The ceRNA network and survival analysis revealed four lncRNAs (LINC00466, DLX6-AS1, LINC00261, and AGBL1), one miRNA (hsa-mir-210), and two mRNAs (CITED2 and ENPP4), with the potential as biomarkers for smoking-related LUSC diagnosis and prognosis. Conclusion. Taken together, our research has identified the differences in the ceRNA regulatory networks between smoking and nonsmoking LUSC, which could lay the foundation for future clinical research.

scholarly journals Integrated genomic analyses of lung squamous cell carcinoma for identification of a possible competitive endogenous RNA network by means of TCGA datasets

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4254 ◽  
Author(s):  
Pengbo Ning ◽  
Zhongxing Wu ◽  
Aoxue Hu ◽  
Xuepeng Li ◽  
Jun He ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Noncoding Rna ◽  
Noncoding Rnas ◽  
Lung Squamous Cell Carcinoma ◽  
Expression Data ◽  
Aberrant Expression ◽  
Cerna Network ◽  
Competitive Endogenous Rna

The etiology of cancer includes aberrant cellular homeostasis where a compromised RNA regulatory network is a prominent contributing factor. In particular, noncoding RNAs including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) were recently shown to play important roles in the initiation, progression, and metastasis of human cancers. Nonetheless, a mechanistic understanding of noncoding RNA functions in lung squamous cell carcinoma (LUSC) is lacking. To fill this critical gap in knowledge, we obtained mRNA, miRNA, and lncRNA expression data on patients with LUSC from the updated Cancer Genome Atlas (TCGA) database (2016). We successfully identified 3,366 mRNAs, 79 miRNAs, and 151 lncRNAs as key contributing factors of a high risk of LUSC. Furthermore, we hypothesized that the lncRNA–miRNA–mRNA regulatory axis positively correlates with LUSC and constructed a competitive endogenous RNA (ceRNA) network of LUSC by targeting interrelations with significantly aberrant expression data between miRNA and mRNA or lncRNA. Six ceRNAs (PLAU, miR-31-5p, miR-455-3p, FAM83A-AS1, MIR31HG, and MIR99AHG) significantly correlated with survival (P < 0.05). Finally, real-time quantitative PCR analysis showed that PLAU is significantly upregulated in SK-MES-1 cells compared with 16-BBE-T cells. Taken together, our findings represent new knowledge for a better understanding the ceRNA network in LUSC biology and pave the way to improved diagnosis and prognosis of LUSC.

scholarly journals Multiomics Differences in Lung Squamous Cell Carcinoma Patients with High Radiosensitivity Index Compared with Those with Low Radiosensitivity Index

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yajing Du ◽  
Sujuan Yuan ◽  
Xibing Zhuang ◽  
Qi Zhang ◽  
Tiankui Qiao
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Pair Interaction ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Cerna Network ◽  
Gene Sets

Objectives. Radiosensitivity Index (RSI) can predict intrinsic radiotherapy sensitivity. We analyzed multiomics characteristics in lung squamous cell carcinoma between high and low RSI groups, which may help understand the underlying molecular mechanism of radiosensitivity and guide optional treatment for patients in the future. Methods. The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) data were used to download clinical data, mRNA, microRNA, and lncRNA expression. Differential analyses, including mRNA, miRNA, lncRNA, and G.O. and KEGG, and GSVA analyses, were performed with R. Gene set enrichment analysis was done by GSEA. miRNA-differentially expressed gene network and ceRNA network were analyzed and graphed by the Cytoscape software. Results. In TCGA data, 542 patients were obtained, including 171 in the low RSI group (LRSI) and 371 in the high RSI group (HRSI). In RNAseq, 558 significantly differentially expressed genes (DEGs) were obtained. KRT6A was the most significantly upregulated gene and IDO1 was the most significantly downregulated gene. In miRNAseq, miR-1269a was the most significantly upregulated. In lncRNAseq, LINC01871 was the most upregulated. A 66-pair interaction between differentially expressed genes and miRNAs and an 11-pair interaction between differential lncRNAs and miRNAs consisted of a ceRNA network, of which miR-184 and miR-490-3p were located in the center. In the GEO data, there were 40 DEGs. A total of 17 genes were founded in both databases, such as ADAM23, AHNAK2, BST2, COL11A1, CXCL13, FBN2, IFI27, IFI44L, MAGEA6, and PTGR1. GSVA analysis revealed 31 significant pathways. GSEA found 87 gene sets enriched in HRSI and 91 gene sets in LRSI. G.O. and KEGG of RNA expression levels revealed that these genes were most enriched in T cell activation and cytokine−cytokine receptor interaction. Conclusions. Patients with lung squamous cell carcinoma have different multiomics characteristics between two groups. These differences may have an essential significance with radiotherapy effect.

scholarly journals Development and validation of an individualized immune prognostic model in stage I–III lung squamous cell carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qi-Fan Yang ◽  
Di Wu ◽  
Jian Wang ◽  
Li Ba ◽  
Chen Tian ◽  
...  
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Stage I ◽  
Tissue Samples ◽  
Mutation Burden

AbstractLung squamous cell carcinoma (LUSC) possesses a poor prognosis even for stages I–III resected patients. Reliable prognostic biomarkers that can stratify and predict clinical outcomes for stage I–III resected LUSC patients are urgently needed. Based on gene expression of LUSC tissue samples from five public datasets, consisting of 687 cases, we developed an immune-related prognostic model (IPM) according to immune genes from ImmPort database. Then, we comprehensively analyzed the immune microenvironment and mutation burden that are significantly associated with this model. According to the IPM, patients were stratified into high- and low-risk groups with markedly distinct survival benefits. We found that patients with high immune risk possessed a higher proportion of immunosuppressive cells such as macrophages M0, and presented higher expression of CD47, CD73, SIRPA, and TIM-3. Moreover, When further stratified based on the tumor mutation burden (TMB) and risk score, patients with high TMB and low immune risk had a remarkable prolonged overall survival compared to patients with low TMB and high immune risk. Finally, a nomogram combing the IPM with clinical factors was established to provide a more precise evaluation of prognosis. The proposed immune relevant model is a promising biomarker for predicting overall survival in stage I–III LUSC. Thus, it may shed light on identifying patient subset at high risk of adverse prognosis from an immunological perspective.

scholarly journals Identifying an lncRNA-Related ceRNA Network to Reveal Novel Targets for a Cutaneous Squamous Cell Carcinoma

Biology ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 432
Author(s):  
Yaqin Xu ◽  
Yingying Dong ◽  
Yunhua Deng ◽  
Qianrong Qi ◽  
Mi Wu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Biological Process ◽  
Normal Skin ◽  
Expression Patterns ◽  
Therapeutic Targets ◽  
Cutaneous Squamous Cell Carcinoma ◽  
Differentially Expressed ◽  
Cerna Network

A cutaneous squamous cell carcinoma (cSCC) derived from keratinocytes is the second most common cause of non-melanoma skin cancer. The accumulation of the mutational burden of genes and cellular DNA damage caused by the risk factors (e.g., exposure to ultraviolet radiation) contribute to the aberrant proliferation of keratinocytes and the formation of a cSCC. A cSCC encompasses a spectrum of diseases that range from recursor actinic keratosis (AK) and squamous cell carcinoma (SCC) in situ (SCCIS) to invasive cSCCs and further metastatic SCCs. Emerging evidence has revealed that lncRNAs are involved in the biological process of a cSCC. According to the ceRNA regulatory theory, lncRNAs act as natural miRNA sponges and interact with miRNA response elements, thereby regulating the mRNA expression of their down-stream targets. This study was designed to search for the potential lncRNAs that may become potential therapeutic targets or biomarkers of a cSCC. Considering the spirit of the study to be adequately justified, we collected microarray-based datasets of 19 cSCC tissues and 12 normal skin samples from the GEO database (GSE42677 and GSE45164). After screening the differentially expressed genes via a limma package, we identified 24 differentially expressed lncRNAs (DElncRNAs) and 3221 differentially expressed mRNAs (DEmRNAs). The miRcode, miRTarBase, miRDB and TargetScan databases were used to predict miRNAs that could interact with DElncRNAs and DEmRNAs. A total of 137 miRNA-lncRNA and 221 miRNA-mRNA pairs were retained in the ceRNA network, consisting of 31 miRNAs, 11 DElncRNAs and 155 DEmRNAs. For the functional analysis, the top enriched biological process was enhancer sequence-specific DNA binding in Gene Ontology (GO) terms. The FoxO signaling pathway, autophagy and cellular senescence were the top enrichment terms based on a Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The combination of a STRING tool and Cytoscape software (plug-in MCODE) identified five core mRNAs and built a core mRNA-associated ceRNA network. The expression for five identified core mRNAs and their related nine lncRNAs was validated using the external dataset GSE7553. Finally, one lncRNA HLA-F-AS1 and three mRNAs named AGO4, E2F1 and CCND1 were validated with the same expression patterns. We speculate that lncRNA HLA-F-AS1 may sponge miR-17-5p or miR-20b-5p to regulate the expression of CCND1 and E2F1 in the cSCC. The present study may provide potential diagnostic and therapeutic targets for cSCC patients.

scholarly journals How Long Non-Coding RNAs and MicroRNAs Mediate the Endogenous RNA Network of Head and Neck Squamous Cell Carcinoma: a Comprehensive Analysis

2018 ◽  
Vol 50 (1) ◽  
pp. 332-341 ◽  
Author(s):  
Guomiao Zhao ◽  
Yaru Fu ◽  
Zhifang Su ◽  
Rongling wu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Cancer Metastasis ◽  
Lung Squamous Cell Carcinoma ◽  
Neck Squamous Cell Carcinoma ◽  
Differentially Expressed ◽  
Clinical Prognosis ◽  
Non Coding Rnas

Background/Aims: Long non-coding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs) to compete for microRNAs (miRNAs) in cancer metastasis. Head and neck squamous cell carcinoma (HNSCC) is one of the most common human cancers and rare biomarkers could predict the clinical prognosis of this disease and its therapeutic effect. Methods: Weighted gene co-expression network analysis (WGCNA) was performed to identify differentially expressed mRNAs (DEmRNAs) that might be key genes. GO enrichment and protein–protein interaction (PPI) analyses were performed to identify the principal functions of the DEmRNAs. An lncRNA-miRNA-mRNA network was constructed to understand the regulatory mechanisms in HNSCC. The prognostic signatures of mRNAs, miRNAs, and lncRNAs were determined by Gene Expression Profiling Interactive Analysis (GEPIA) and using Kaplan–Meier survival curves for patients with lung squamous cell carcinoma. Results: We identified 2,023 DEmRNAs, 1,048 differentially expressed lncRNAs (DElncRNAs), and 82 differentially expressed miRNAs (DEmiRNAs). We found that eight DEmRNAs, 53 DElncRNAs, and 16 DEmiRNAs interacted in the ceRNA network. Three ceRNAs (HCG22, LINC00460 and STC2) were significantly correlated with survival. STC2 transcript levels were significantly higher in tumour tissues than in normal tissues, and the STC2 expression was slightly upregulated at different stages of HNSCC. Conclusion: LINC00460, HCG22 and STC2 exhibited aberrant levels of expression and may participate in the pathogenesis of HNSCC.

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