A Metabolic Gene Signature to Predict Overall Survival in Head and Neck Squamous Cell Carcinoma

Joint Authors

Wu, Zeng-hong
Zhou, Yue
Tang, Yun

Source

Mediators of Inflammation

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-12-30

Country of Publication

Egypt

No. of Pages

12

Main Topic

Diseases

Abstract EN

Background.

Head and neck squamous cell carcinoma (HNSCC) is a common malignancy that emanates from the lips, mouth, paranasal sinuses, oropharynx, larynx, nasopharynx, and from other pharyngeal cancers.

The availability of high-throughput expression data has made it possible to use global gene expression data to analyze the relationship between metabolic-related gene expression and clinical outcomes in HNSCC patients.

Method.

In this study, we used RNA sequencing (RNA-seq) data from the cancer genome atlas (TCGA), with validation in the GEO dataset to profile the metabolic microenvironment and define potential biomarkers for metabolic therapy.

Results.

We extracted data for 529 patients and 327 metabolic genes (198 upregulated and 129 downregulated genes) in the TCGA database.

Carbonic anhydrase 9 (CA9) and CA6 had the largest logFCs in the upregulated and downregulated genes, respectively.

Our Cox regression model data showed 51 prognostic-related genes with lysocardiolipin acyltransferase 1 (LCLAT1) and choline dehydrogenase (CHDH) being associated with the highest risk (HR=1.144, 95% CI=1.044~1.251) and the lowest risk (HR=0.580, 95% CI=0.400~0.839) in HNSCC, respectively.

We next used the ROC curve to evaluate whether the differentially expressed metabolic-related genes could serve as early predictors of HNSCC.

The findings showed an AUC of 0.745 and 0.618 in the TCGA and GEO analysis, respectively.

Besides, the ability for the genes to predict clinicopathological HNSCC status was analyzed and the data showed that the AUC for age, gender, grade, stage, T, M, and N was 0.520, 0.495, 0.568, 0.606, 0.577, 0.476, and 0.673, respectively, in the TCGA dataset.

On the other hand, the AUC for age, gender, stage, T, M, N, smoking, and HPV16-pos was 0.599, 0.531, 0.622, 0.606, 0.616, 0.550, 0.614, 0.519, and 0.397, respectively, in the GEO dataset.

Conclusion.

Taken together, our study unearths a novel metabolic gene signature for the prediction of HNSCC prognosis based on the TCGA dataset.

Our signature might point out the metabolic microenvironment disorders and provides potential treatment targets and prognostic biomarkers.

American Psychological Association (APA)

Wu, Zeng-hong& Tang, Yun& Zhou, Yue. 2020. A Metabolic Gene Signature to Predict Overall Survival in Head and Neck Squamous Cell Carcinoma. Mediators of Inflammation،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1191925

Modern Language Association (MLA)

Wu, Zeng-hong…[et al.]. A Metabolic Gene Signature to Predict Overall Survival in Head and Neck Squamous Cell Carcinoma. Mediators of Inflammation No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1191925

American Medical Association (AMA)

Wu, Zeng-hong& Tang, Yun& Zhou, Yue. A Metabolic Gene Signature to Predict Overall Survival in Head and Neck Squamous Cell Carcinoma. Mediators of Inflammation. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1191925

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1191925