Dataset Information

Identification and Clinical Validation of 4-lncRNA Signature for Predicting Survival in Head and Neck Squamous Cell Carcinoma.

ABSTRACT: Background:The prognosis of patients with head and neck squamous cell carcinoma (HNSCC) is still poor due to the lack of effective prognostic biomarkers. lncRNA is an important survival prognostic indicator and has important biological functions in tumorigenesis. Methods:RNA-seq was re-annotated, and comprehensive clinical information was obtained from the GEO database. Univariate and multivariate Cox regression analyses were used to construct the lncRNA prognosis signature. Gene set enrichment analysis (GSEA) enrichment analysis method is used to explore the possible mechanism of the selected lncRNA influencing HNSCC development. The rms package was used to calculate the C-index to evaluate the overall prediction performance between different signature. PCR is used to detect the expression of selected lncRNA in cancer and adjacent tissues. Results:In the GSE65858 training cohort, 124 probes significantly related to prognosis were identified, 11 significant lncRNAs were further selected by rbsurv dimensionality reduction analysis. Finally, 4-lncRNA signature was constructed by multivariate Cox analysis. This signature was associated with tumor-associated pathway and is an independent factor of the patient's prognosis. 4-lncRNA signature has strong robustness and can exert stable prediction performance in different cohorts. A nomogram comprising the prognostic model to predict the overall survival was established. The 4-lncRNA signature was significantly upregulated in HNSCC samples. Conclusion:The predictive model and nomogram will enable patients to be more accurately managed in trials and clinical practices and could be applied as a new prognostic model for predicting survival of HNSCC patients.

SUBMITTER: Ji Y

PROVIDER: S-EPMC7457573 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification and Clinical Validation of 4-lncRNA Signature for Predicting Survival in Head and Neck Squamous Cell Carcinoma.

Ji Yanping Y Xue Yu Y

OncoTargets and therapy 20200821

<h4>Background</h4>The prognosis of patients with head and neck squamous cell carcinoma (HNSCC) is still poor due to the lack of effective prognostic biomarkers. lncRNA is an important survival prognostic indicator and has important biological functions in tumorigenesis.<h4>Methods</h4>RNA-seq was re-annotated, and comprehensive clinical information was obtained from the GEO database. Univariate and multivariate Cox regression analyses were used to construct the lncRNA prognosis signature. Gene ...[more]

PMID: 32904613

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Project description:Background: Long non-coding RNA (lncRNA) plays a significant role in the development, establishment, and progression of head and neck squamous cell carcinoma (HNSCC). This article aims to develop an immune-related lncRNA (irlncRNA) model, regardless of expression levels, for risk assessment and prognosis prediction in HNSCC patients. Methods: We obtained clinical data and corresponding full transcriptome expression of HNSCC patients from TCGA, downloaded GTF files to distinguish lncRNAs from Ensembl, discerned irlncRNAs based on co-expression analysis, distinguished differentially expressed irlncRNAs (DEirlncRNAs), and paired these DEirlncRNAs. Univariate Cox regression analysis, LASSO regression analysis, and stepwise multivariate Cox regression analysis were then performed to screen lncRNA pairs, calculate the risk coefficient, and establish a prognosis model. Finally, the predictive power of this model was validated through the AUC and the ROC curves, and the AIC values of each point on the five-year ROC curve were calculated to select the maximum inflection point, which was applied as a cut-off point to divide patients into low- or high-risk groups. Based on this methodology, we were able to more effectively differentiate between these groups in terms of survival, clinico-pathological characteristics, tumor immune infiltrating status, chemotherapeutics sensitivity, and immunosuppressive molecules. Results: A 13-irlncRNA-pair signature was built, and the ROC analysis demonstrated high sensitivity and specificity of this signature for survival prediction. The Kaplan-Meier analysis indicated that the high-risk group had a significantly shorter survival rate than the low-risk group, and the chi-squared test certified that the signature was highly related to survival status, clinical stage, T stage, and N stage. Additionally, the signature was further proven to be an independent prognostic risk factor via the Cox regression analyses, and immune infiltrating analyses showed that the high-risk group had significant negative relationships with various immune infiltrations. Finally, the chemotherapeutics sensitivity and the expression level of molecular markers were also significantly different between high- and low-risk groups. Conclusion: The signature established by paring irlncRNAs, with regard to specific expression levels, can be utilized for survival prediction and to guide clinical therapy in HNSCC.

Dataset Information

Identification and Clinical Validation of 4-lncRNA Signature for Predicting Survival in Head and Neck Squamous Cell Carcinoma.

Publications

Identification and Clinical Validation of 4-lncRNA Signature for Predicting Survival in Head and Neck Squamous Cell Carcinoma.

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