Comprehensive analysis of competitive endogenous RNAs network associated with head and neck squamous cell carcinoma

Fang, Xiaonan; Yin, Miao; Li, Hua; Liang, Cheng; Xu, Cong; Gao, Yang; Zhang, Huaxiang

doi:10.1038/s41598-018-28957-y

Cited by 55 publications

(56 citation statements)

References 47 publications

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“…Another point of emphasis derived from the present overview is the growing integration among omics data obtained on the same cohort of patients. Even if these experiences are still limited for HNSCC and in terms of types of omics employed and amount of published studies [23,27,43,58,66,76], these initiatives enabling to better dissect cancer complexity deserve further investigations. Moreover, we can expect that new approaches based on artificial intelligence will be available in the next future dealing with more complex data even integrating multi-omics layers [94].…”

Section: Discussionmentioning

confidence: 99%

“…A large portion of the studies regarded mRNA signatures (33/61) , while a minor portion of the studies considered miRNA signatures (11/61) [52][53][54][55][56][57][58][59][60][61][62] and other non-coding RNA signatures (13/61) [63][64][65][66][67][68][69][70][71][72][73][74][75][76]. Only 4/61 [77][78][79][80] studies identified signatures by a high-throughput omics analysis of methylated DNA.…”

Section: Analysis Of Recent Epigenomics and Transcriptomics Datamentioning

confidence: 99%

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Transcriptomics and Epigenomics in head and neck cancer: available repositories and molecular signatures

et al. 2020

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For many years, head and neck squamous cell carcinoma (HNSCC) has been considered as a single entity. However, in the last decades HNSCC complexity and heterogeneity have been recognized. In parallel, high-throughput omics techniques had allowed picturing a larger spectrum of the behavior and characteristics of molecules in cancer and a large set of omics web-based tools and informative repository databases have been developed. The objective of the present review is to provide an overview on biological, prognostic and predictive molecular signatures in HNSCC. To contextualize the selected data, our literature survey includes a short summary of the main characteristics of omics data repositories and web-tools for data analyses. The timeframe of our analysis was fixed, encompassing papers published between January 2015 and January 2019. From more than 1000 papers evaluated, 61 omics studies were selected: 33 investigating mRNA signatures, 11 and 13 related to miRNA and other non-coding-RNA signatures and 4 analyzing DNA methylation signatures. More than half of identified signatures (36) had a prognostic value but only in 10 studies selection of a specific anatomical sub-site (8 oral cavity, 1 oropharynx and 1 both oral cavity and oropharynx) was performed. Noteworthy, although the sample size included in many studies was limited, about one-half of the retrieved studies reported an external validation on independent dataset(s), strengthening the relevance of the obtained data. Finally, we highlighted the development and exploitation of three gene-expression signatures, whose clinical impact on prognosis/prediction of treatment response could be high. Based on this overview on omics-related literature in HNSCC, we identified some limits and strengths. The major limits are represented by the low number of signatures associated to DNA methylation and to non-coding RNA (miRNA, lncRNA and piRNAs) and the availability of a single dataset with multiple omics on more than 500 HNSCC (i.e. TCGA). The major strengths rely on the integration of multiple datasets through meta-analysis approaches and on the growing integration among omics data obtained on the same cohort of patients. Moreover, new approaches based on artificial intelligence and informatic analyses are expected to be available in the next future.

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Section: Discussionmentioning

confidence: 99%

Section: Analysis Of Recent Epigenomics and Transcriptomics Datamentioning

confidence: 99%

Transcriptomics and Epigenomics in head and neck cancer: available repositories and molecular signatures

et al. 2020

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“…Expression of mRNAs, miRNAs, and lncRNAs could also be obtained from sequencing data, alternation of which could influence the function and metabolism of cells through ceRNA triplets. With the development of bioinformatics technology, data analysis or mining methods have been applied to studies of ceRNA triplets or networks [9]. For example, lncRNAs acted as ceRNAs regulating genes were found to be involved in left ventricular systolic function [10].…”

Section: Introductionmentioning

confidence: 99%

A susceptibility biomarker identification strategy based on significantly differentially expressed ceRNA triplets for ischemic cardiomyopathy

et al. 2020

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Ischemic cardiomyopathy (ICM) is a common human heart disease that causes death. No effective biomarkers for ICM could be found in existing databases, which is detrimental to the in-depth study of this disease. In the present study, ICM susceptibility biomarkers were identified using a proposed strategy based on RNA-Seq and miRNA-Seq data of ICM and normal samples. Significantly differentially expressed competing endogenous RNA (ceRNA) triplets were constructed using permutation tests and differentially expressed mRNAs, miRNAs and lncRNAs. Candidate ICM susceptible genes were screened out as differentially expressed genes in significantly differentially expressed ceRNA triplets enriched in ICM-related functional classes. Finally, eight ICM susceptibility genes and their significantly correlated lncRNAs with high classification accuracy were identified as ICM susceptibility biomarkers. These biomarkers would contribute to the diagnosis and treatment of ICM. The proposed strategy could be extended to other complex diseases without disease biomarkers in public databases.

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“…Most recent studies on the ceRNA network consider miRNAs to be gene regulators that act alone, and they ignore the influence of other regulatory factors on the ceRNA network, such as epigenetic factors, transcription factors and gene copy number variation factors (19). Losing sight of these critical factors may lead to spurious miRNA-gene interactions, which may cause false positive results in the ceRNA network.…”

Section: Introductionmentioning

confidence: 99%

Multi-Omics Integration Reveals a Competitive Endogenous RNAs Network for the Identification of Progression Biomarkers and the Stratification of Patients Diagnosed With Nephroblastoma

Wang

Liang

et al. 2020

Front. Oncol.

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Specific types of nephroblastoma (Wilms' tumor, WT) are known to associate with poor overall survival. Emerging experimental evidence has demonstrated that competitive endogenous RNA (ceRNA) networks have important roles in regulating cancer occurrence, but the roles of ceRNAs in regulating the WT progression and the patient outcomes remain unclear. Using the multi-omics data of 132 WT patients collected from TARGET database, an integration analysis pipeline was performed to construct a highly reliable ceRNA network. As results, a total of 147 nodes (116 mRNAs, 15 miRNAs, and 16 lncRNAs) were identified and used to explore the underlying mechanism for WT progression. WGCNA analysis further identified several prognostic molecules, including hsa-mir-93, LINC00087 and RP5-1086K13, that significantly associated with the overall survival rate. And, enrichment analysis verified the participation of these molecules in tumor-related pathways, such as those controlling autophagy and cadherin-mediated adhesion. Importantly, the WT patients were classified into three categories according to the ceRNA network, which significantly correlated with the overall survival. In conclusion, the ceRNA network could be a promising tool to further validate the prognostic biomarkers and categories of patients diagnosed with WT.

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Comprehensive analysis of competitive endogenous RNAs network associated with head and neck squamous cell carcinoma

Cited by 55 publications

References 47 publications

Transcriptomics and Epigenomics in head and neck cancer: available repositories and molecular signatures

Transcriptomics and Epigenomics in head and neck cancer: available repositories and molecular signatures

A susceptibility biomarker identification strategy based on significantly differentially expressed ceRNA triplets for ischemic cardiomyopathy

Multi-Omics Integration Reveals a Competitive Endogenous RNAs Network for the Identification of Progression Biomarkers and the Stratification of Patients Diagnosed With Nephroblastoma

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