Prediction of Radiosensitivity in Head and Neck Squamous Cell Carcinoma Based on Multiple Omics Data

Abstract

Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor. Radiotherapy (RT) is an important treatment for HNSCC, but not all patients derive survival benefit from RT due to the individual differences on radiosensitivity. A prediction model of radiosensitivity based on multiple omics data might solve this problem. Compared with single omics data, multiple omics data can illuminate more systematical associations between complex molecular characteristics and cancer phenotypes. In this study, we obtained 122 differential expression genes by analyzing the gene expression data of HNSCC patients with RT (N = 287) and without RT (N = 189) downloaded from The Cancer Genome Atlas. Then, HNSCC patients with RT were randomly divided into a training set (N = 149) and a test set (N = 138). Finally, we combined multiple omics data of 122 differential genes with clinical outcomes on the training set to establish a 12-gene signature by two-stage regularization and multivariable Cox regression models. Using the median score of the 12-gene signature on the training set as the cutoff value, the patients were divided into the high- and low-score groups. The analysis revealed that patients in the low-score group had higher radiosensitivity and would benefit from RT. Furthermore, we developed a nomogram to predict the overall survival of HNSCC patients with RT. We compared the prognostic value of 12-gene signature with those of the gene signatures based on single omics data. It suggested that the 12-gene signature based on multiple omics data achieved the best ability for predicting radiosensitivity. In conclusion, the proposed 12-gene signature is a promising biomarker for estimating the RT options in HNSCC patients.

Keywords: gene signature; head and neck squamous cell carcinoma; multiple omics data; radiosensitivity; radiotherapy.

FIGURE 1

Workflow of constructing a gene signature for predicting RT response in HNSCC.

FIGURE 2

Kaplan–Meier survival and time-dependent ROC curves on the training (A,B) and test (C,D) sets according to the 12-gene signature.

FIGURE 3

The prognostic values of the 12-gene signature in all HNSCC patients. (A) Kaplan–Meier analysis of overall survival in 476 patients according to the 12-gene signature. (B) Kaplan–Meier survival curves of patients with/without RT in the low-score group. (C) Kaplan–Meier survival curves of patients with/without RT in the high-score group.

FIGURE 4

The Kaplan–Meier survival analysis of the 12-gene signature in all HNSCC patients in the high- and low-score groups on clinical subgroups of T 1-2 (A), T 3-4 (B), N 0-1 (C), N 2-3 (D), Stage 1-2 (E), Stage 3-4 (F), Grade 1-2 (G) and Grade 3-4 (H).

FIGURE 5

Evaluation of the nomogram on predicting the OS of HNSCC patients with RT. (A) Nomogram for predicting the 3-year and 5-year OS in HNSCC with RT. (B) Calibration plots of the nomogram on the training and test sets. The 45-degree line represents the real outcomes. (C) Time-dependent ROC curves of 3-year OS prediction using the nomogram on the training and test sets.

FIGURE 6

Kaplan–Meier survival and time-dependent ROC curves on the test set according to the 7-gene signature (A,B) and the 3-gene signature (C,D).