Dataset Information

A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma.

ABSTRACT: Head and neck squamous cell carcinoma (HNSCC) is a common malignant cancer that accounts for 5-10% of all cancers. This study aimed to identify essential genes associated with the prognosis of HNSCC and construct a powerful prognostic model for the risk assessment of HNSCC. RNAseq expression profile data for the patients with HNSCC were obtained from the TCGA database (GEO). A total of 500 samples with full clinical following-up were randomly divided into a training set and a validation set. The training set was used to screen for differentially expressed lncRNAs. Single-factor survival analysis was performed to obtain lncRNAs that associated with prognosis. A robust likelihood-based survival model was constructed to identify the lncRNAs that are essential for the prognosis of HNSCC. A co-expression network between genes and lncRNAs was also constructed to identify lncRNAs co-expressed with genes to serve as the final signature lncRNAs for prognosis. Finally, the prognostic effect of the signature lncRNAs was tested by multi-factor survival analysis and a scoring model for the prognosis of HNSCC was constructed. Moreover, the results of the validation set and the relative expression levels of the signature lncRNAs in the tumour and the adjacent tissue were consistent with the results of the training set. The 5 lncRNAs were distributed among 3 expression modules. Further KEGG pathway enrichment analysis showed that these 3 co-expressed modules participate in different pathways, and many of these pathways are associated with the development and progression of disease. Therefore, we proposed that the 5 validated lncRNAs can be used to predict the prognosis of HNSCC patients and can be applied in postoperative treatment and follow-up.

SUBMITTER: Liu G

PROVIDER: S-EPMC6189101 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma.

Liu Guancheng G Zheng Jinyang J Zhuang Liming L Lv Yunxia Y Zhu Gangcai G Pi Leiming L Wang Junchen J Chen Changhan C Li Zhexuan Z Liu Jiangyi J Chen Liangjuan L Cai Gengming G Zhang Xin X

Scientific reports 20181015 1

Head and neck squamous cell carcinoma (HNSCC) is a common malignant cancer that accounts for 5-10% of all cancers. This study aimed to identify essential genes associated with the prognosis of HNSCC and construct a powerful prognostic model for the risk assessment of HNSCC. RNAseq expression profile data for the patients with HNSCC were obtained from the TCGA database (GEO). A total of 500 samples with full clinical following-up were randomly divided into a training set and a validation set. The ...[more]

PMID: 30323196

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Project description:Background: Cuproptosis has been recognized as a novel regulatory cell death, which has been confirmed to promote the occurrence and development of tumors. However, whether cuproptosis-related lncRNA has an impact on the prognosis of squamous cell carcinoma of the head and neck (HNSCC) is still unclear. Methods: In total, 501 HNSCC tumor samples and 44 normal were downloaded from the TCGA database. Cuproptosis-related lncRNAs were obtained by co-expressed analysis. We got prognostic lncRNA that was associated with cuproptosis by using univariate Cox regression analysis and LASSO Cox regression. Then we constructed and validated the prognostic signature of HNSCC and analyzed the immune landscape of the signature. Results: The Prognostic Signature is based on 10 cuproptosis-related lncRNAs including AC090587.1, AC004943.2, TTN-AS1, AL162458.1, AC106820.5, AC012313.5, AL132800.1, WDFY3-AS2, CDKN2A-DT, and AL136419.3. The results of overall survival, risk score distribution, and survival status in the low-risk group were better than those in the high-risk group. In addition, all immune checkpoint genes involved were significantly different between the two risk groups (p < 0.05). The risk score was positively correlated with Eosinophils. M0 and M2 phenotype macrophages, mast cells activated, NK cells activated, and negatively related with B cells naive, mast cells resting, plasma cells, CD8T cells, T cells follicular helper, T cells regulatory (Tregs). Consensus clustering was identified in molecular subtypes of HNSC. More high-risk samples concentrated in Cluster1, which had a higher Tumor Immune Dysfunction and Exclusion (TIDE) score and Single Nucleotide Polymorphisms (SNP) alternation than Cluster2. Conclusion: Our study elucidated the correlation between cuproptosis-related lncRNA with prognosis and immune landscape of HNSCC, which may provide references for further research on the exploration of the mechanism and functions of the prognosis for HNSCC.

Project description:Background: Head and neck squamous cell carcinoma (HNSCC) is a common malignancy of the mucosal epithelium of the oral cavity, pharynx, and larynx. Laryngeal squamous cell carcinoma (LSCC) and oral squamous cell carcinoma are common HNSCC subtypes. Patients with metastatic HNSCC have a poor prognosis. Therefore, identifying molecular markers for the development and progression of HNSCC is essential for improving early diagnosis and predicting patient outcomes. Methods: Gene expression RNA-Seq data and patient clinical traits were obtained from The Cancer Genome Atlas-Head and Neck Squamous Cell Carcinoma (TCGA-HNSC) and Gene Expression Omnibus databases. Differentially expressed gene (DEG) screening was performed using the TCGA-HNSC dataset. Intersection analysis between the DEGs and a list of core matrisome genes obtained from the Matrisome Project was used to identify differentially expressed matrisome genes. A prognostic model was established using univariate and multivariate Cox regression analyses, least absolute shrinkage, and selection operator (LASSO) regression analysis. Immune landscape analysis was performed based on the single-sample gene set enrichment analysis algorithm, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, prognostic value, receiver operating characteristic curve analysis, and gene mutation analyses. Immunohistochemical results regarding prognostic protein levels were obtained from the Human Protein Atlas. Single-gene RNA-sequencing data were obtained from GSE150321 and GSE172577 datasets. CCK-8 and Transwell assays were used to confirm cell proliferation and migration. Results: A total of 1,779 DEGs, including 939 upregulated and 840 downregulated genes, between tumor and normal samples were identified using the TCGA-HNSC microarray data. Intersection analysis revealed 52 differentially expressed matrisome-related genes. After performing univariate and multivariate Cox regression and LASSO analyses, a novel prognostic model based on six matrisome genes (FN1, LAMB4, LAMB3, DMP1, CHAD, and MMRN1) for HNSCC was established. This risk model can successfully predict HNSCC survival. The high-risk group had worse prognoses and higher enrichment of pathways related to cancer development than the low-risk group. Silencing LAMB4 in HNSCC cell lines promoted cell proliferation and migration. Conclusion: This study provides a novel prognostic model for HNSCC. Thus, FN1, LAMB4, LAMB3, DMP1, CHAD, and MMRN1 may be the promising biomarkers for clinical practice.

Dataset Information

A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma.

Publications

A Prognostic 5-lncRNA Expression Signature for Head and Neck Squamous Cell Carcinoma.

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