Dataset Information

Fifteen mRNA-lncRNA expression-based signature predicted the survival of late-staged head and neck squamous cell carcinoma.

ABSTRACT: Background: Gene expression is necessary for regulation in almost all biological processes, at the same time, it is related to the prognosis for head and neck squamous cell carcinoma (HNSCC). The prognosis of late-staged HNSCC is important because of its guiding significance on the therapy strategies.

Methods: In this work, we analyzed the relationship between gene expression and HNSCC in The Cancer Genome Atlas (TCGA) cohort, and optimized the panel with random forest survival analysis. Subsequently, a Cox multivariate regression-based model was developed to predict the clinical outcome of HNSCC. The performance of the model was assayed in the training cohort and validated in another three independent cohorts (GSE41614, E-TABM-302, E-MTAB-1328). The underlying pathways significantly associated with the model were identified. According to the results, patients of low-score group (median survival months: 27.4, 95% CI: 18.2-43) had a significant poor survival than those of high-score group (median survival months: 69.4, 95% CI: 58.7-72.1, P=2.7e-5), and the observation was repeatable in the other validation cohorts. Further analysis revealed that the model performed better than the other clinical indicators and is independent of these indicators.

Results: Comparison revealed that the model performed better than existing models for late HNSCC prognosis. Gene set enrichment analysis (GSEA) elucidated that the model was significantly associated with various cell processes and pathways.

SUBMITTER: Ren H

PROVIDER: S-EPMC7327439 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Fifteen mRNA-lncRNA expression-based signature predicted the survival of late-staged head and neck squamous cell carcinoma.

Ren He H Li Huaping H Li Ping P Xu Yuhui Y Liu Gang G Sun Liping L

Bioscience reports 20200701 7

<h4>Background</h4>Gene expression is necessary for regulation in almost all biological processes, at the same time, it is related to the prognosis for head and neck squamous cell carcinoma (HNSCC). The prognosis of late-staged HNSCC is important because of its guiding significance on the therapy strategies.<h4>Methods</h4>In this work, we analyzed the relationship between gene expression and HNSCC in The Cancer Genome Atlas (TCGA) cohort, and optimized the panel with random forest survival anal ...[more]

PMID: 32500914

Similar Datasets

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

Fifteen mRNA-lncRNA expression-based signature predicted the survival of late-staged head and neck squamous cell carcinoma.

Publications

Fifteen mRNA-lncRNA expression-based signature predicted the survival of late-staged head and neck squamous cell carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets