Genome-Wide Identification of a Novel Eight-lncRNA Signature to Improve Prognostic Prediction in Head and Neck Squamous Cell Carcinoma

Yang, Bowen; Shen, Jiming; Chen, Ying; Che, Xiaofang; Qu, Xiujuan; Liu, Yunpeng; Teng, Yuee; Li, Zhi

doi:10.3389/fonc.2019.00898

Cited by 33 publications

(24 citation statements)

References 37 publications

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“…The purpose of the risk score is to determine a uniform signature for subsequent prognostic prediction. The risk score formula was as follows ( Cheng et al, 2015 ; Yang et al, 2019 ):

…”

Section: Methodsmentioning

confidence: 99%

A Five Immune-Related lncRNA Signature as a Prognostic Target for Glioblastoma

Sun

Wang

et al. 2021

Front. Mol. Biosci.

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Background: A variety of regulatory approaches including immune modulation have been explored as approaches to either eradicate antitumor response or induce suppressive mechanism in the glioblastoma microenvironment. Thus, the study of immune-related long noncoding RNA (lncRNA) signature is of great value in the diagnosis, treatment, and prognosis of glioblastoma.Methods: Glioblastoma samples with lncRNA sequencing and corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) database. Immune-lncRNAs co-expression networks were built to identify immune-related lncRNAs via Pearson correlation. Based on the median risk score acquired in the training set, we divided the samples into high- and low-risk groups and demonstrate the survival prediction ability of the immune-related lncRNA signature. Both principal component analysis (PCA) and gene set enrichment analysis (GSEA) were used for immune state analysis.Results: A cohort of 151 glioblastoma samples and 730 immune-related genes were acquired in this study. A five immune-related lncRNA signature (AC046143.1, AC021054.1, AC080112.1, MIR222HG, and PRKCQ-AS1) was identified. Compared with patients in the high-risk group, patients in the low-risk group showed a longer overall survival (OS) in the training, validation, and entire TCGA set (p = 1.931e-05, p = 1.706e-02, and p = 3.397e-06, respectively). Additionally, the survival prediction ability of this lncRNA signature was independent of known clinical factors and molecular features. The area under the ROC curve (AUC) and stratified analyses were further performed to verify its optimal survival predictive potency. Of note, the high-and low-risk groups exhibited significantly distinct immune state according to the PCA and GSEA analyses.Conclusions: Our study proposes that a five immune-related lncRNA signature can be utilized as a latent indicator of prognosis and potential therapeutic approach for glioblastoma.

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“…The purpose of the risk score is to determine a uniform signature for subsequent prognostic prediction. The risk score formula was as follows ( Cheng et al, 2015 ; Yang et al, 2019 ):

…”

Section: Methodsmentioning

confidence: 99%

A Five Immune-Related lncRNA Signature as a Prognostic Target for Glioblastoma

Sun

Wang

et al. 2021

Front. Mol. Biosci.

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“…At present, lncRNAs and miRNAs are believed to play an important role in tumorigenesis and have been identified as potential prognostic markers for HNSCC. Yang et al [ 8 ] established an 8-lncRNA signature associated with the prognosis of HNSCC, and Hess et al [ 9 ] identified prognostic 5-miRNA signature to independently predict disease control and survival in HNSCC patients. However, autophagy, as a crucial mechanism in tumorigenesis and progression, has not been studied on the effect of autophagy-associated genes on the prognosis of HNSCC.…”

Section: Introductionmentioning

confidence: 99%

Autophagy-Related Signature for Head and Neck Squamous Cell Carcinoma

Cheng

Yuan

2020

Disease Markers

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Background. Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies in the world, with low survival and poor quality of life. Autophagy-associated genes (ATGs) have been reported to be involved in the initiation and progression of malignancies. Here, we aimed to investigate the association between autophagy-associated genes and the outcomes in HNSCC patients. Methods. We obtained ATGs with prognostic values by analyzing the datasets from The Cancer Genome Atlas (TCGA) and Human Autophagy Database (HADb). The enrichment functions of autophagy differential genes were analyzed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The Kaplan-Meier method was applied to the survival curve analysis. A prognostic autophagy-related gene signature was established, and its independence was verified. Results. We acquired a total of 529 samples and 232 ATGs; further, we identified 45 genes associated with prognosis and built a prognosis autophagy signature based on risk score of 15 genes. Patients were divided into two groups based on risk scores. The Kaplan-Meier curve illustrated that the survival rate of the high-risk group was significantly lower than that of the low-risk group in both the training group and validation group. The ROC curve revealed that the risk score had the highest AUC value in the 3rd and 5th years, reaching 0.703 and 0.724, which are higher than other risk factors such as gender, age, and TNM stage. The nomogram further confirmed its weight in the prognosis of HNSCC patients. Through KEGG and GO enrichment analyses, we observed that ATGs were involved in the tumorigenesis and invasion of tumor by various mediating pathways. We gained 3 hub genes (MAP1LC3B, FADD, and LAMP1) and further analyzed the survival curves, mutations, differential expressions, and their roles in tumors on the online websites. Conclusion. We identified a novel autophagy-related signature that may provide promising biomarker genes for the treatment and prognosis of HNSCC. We need to validate its prognostic value by applying it to the clinic.

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“…They are involved in gene expression regulation at both the transcriptional and translational levels, and participate in tumorigenesis and tumor metastases [ 112 , 113 ]. Therefore, lncRNAs expression are promising biomarkers of cancer detection and expansion [ 114 ]. LncRNAs are found to play an important role also in HNSCC development.…”

Section: The Hnscc Epigenetic Landscape and Its Clinical Implicatimentioning

confidence: 99%

Head and Neck Squamous Cell Carcinoma: Epigenetic Landscape

et al. 2020

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Head and neck squamous carcinoma (HNSCC) constitutes the sixth most prevalent cancer worldwide. The molecular pathogenesis of HNSCC includes disorders in cell cycle, intercellular signaling, proliferation, squamous cell differentiation and apoptosis. In addition to the genetic mutations, changes in HNSCC are also characterized by the accumulation of epigenetic alterations such as DNA methylation, histone modifications, non-coding RNA activity and RNA methylation. In fact, some of them may promote cancer formation and progression by controlling the gene expression machinery, hence, they could be used as biomarkers in the clinical surveillance of HNSCC or as targets for therapeutic strategies. In this review, we focus on the current knowledge regarding epigenetic modifications observed in HNSCC and its predictive value for cancer development.

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Genome-Wide Identification of a Novel Eight-lncRNA Signature to Improve Prognostic Prediction in Head and Neck Squamous Cell Carcinoma

Cited by 33 publications

References 37 publications

A Five Immune-Related lncRNA Signature as a Prognostic Target for Glioblastoma

A Five Immune-Related lncRNA Signature as a Prognostic Target for Glioblastoma

Autophagy-Related Signature for Head and Neck Squamous Cell Carcinoma

Head and Neck Squamous Cell Carcinoma: Epigenetic Landscape

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