AUTHOR=Ming Ruijie , Wang Enhao , Wei Jiahui , Shen Jinxiong , Zong Shimin , Xiao Hongjun TITLE=The Prognostic Value of the DNA Repair Gene Signature in Head and Neck Squamous Cell Carcinoma JOURNAL=Frontiers in Oncology VOLUME=11 YEAR=2021 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.710694 DOI=10.3389/fonc.2021.710694 ISSN=2234-943X ABSTRACT=Purpose

To construct a prognostic signature composed of DNA repair genes to effectively predict the prognosis of patients with head and neck squamous cell carcinoma (HNSCC).

Methods

After downloading the transcriptome and clinical data of HNSCC from the Cancer Genome Atlas (TCGA), 499 patients with HNSCC were equally divided into training and testing sets. In the training set, 13 DNA repair genes were screened using univariate proportional hazard (Cox) regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct a risk model, which was validated in the testing set.

Results

In the training and testing sets, there were significant differences in the clinical outcomes of patients in the high- and low-risk groups showed by Kaplan-Meier survival curves (P < 0.001). Univariate and multivariate Cox regression analyses showed that the risk score had independent prognostic predictive ability (P < 0.001). At the same time, the immune cell infiltration, immune score, immune-related gene expression, and tumor mutation burden (TMB) of patients with HNSCC were also different between the high- and low-risk groups (P < 0.05). Finally, we screened several chemotherapeutics for HNSCC, which showed significant differences in drug sensitivity between the high- and low-risk groups (P < 0.05).

Conclusion

This study constructed a 13-DNA-repair-gene signature for the prognosis of HNSCC, which could accurately and independently predict the clinical outcome of the patient. We then revealed the immune landscape, TMB, and sensitivity to chemotherapy drugs in different risk groups, which might be used to guide clinical treatment decisions.