Validation of the 18F-FDG PET image biomarker model predicting late xerostomia after head and neck cancer radiotherapy.

BACKGROUND AND PURPOSE: Previously, PET image biomarkers (PET-IBMs) - the 90th percentile standardized uptake value (P90-SUV) and the Mean SUV (Mean-SUV) of the contralateral parotid gland (cPG) - were identified as predictors for late-xerostomia following head and neck cancer (HNC) radiotherapy. The aim of the current study was to assess in an independent validation cohort whether these pre-treatment PET-IBM can improve late-xerostomia prediction compared to the prediction with baseline xerostomia and mean cPG dose alone. MATERIALS AND METHODS: The prediction endpoint was patient-rated moderate-to-severe xerostomia at 12 months after radiotherapy. The PET-IBMs were extracted from pre-treatment 18 F-FDG PET images. The performance of the model (base model) with baseline xerostomia and mean cPG dose alone and models with additionally P90-SUV or Mean-SUV were tested in the current independent validation cohort. Specifically, model discrimination (area under the curve: AUC) and calibration (calibration plot) were evaluated. RESULTS: The current validation cohort consisted of 137 patients of which 40% developed moderate-to-severe xerostomia at 12 months. Both the PET-P90 model (AUC:PET-P90 = 0.71) and the PET-Mean model (AUC: PET-Mean = 0.70) performed well in the current validation cohort. Moreover, their performance were improved compared to the base model (AUC:base model= 0.68). The calibration plots showed a good fit of the prediction to the actual rates for all tested models. CONCLUSION: PET-IBMs showed an improved prediction of late-xerostomia when added to the base model in this validation cohort. This contributed to the published hypothesis that PET-IBMs include individualized information and can serve as a pre-treatment risk factor for late-xerostomia.

A two-stage genome-wide association study of radiation-induced acute toxicity in head and neck cancer.

BACKGROUND: Most head and neck cancer (HNC) patients receive radiotherapy (RT) and develop toxicities. This genome-wide association study (GWAS) was designed to identify single nucleotide polymorphisms (SNPs) associated with common acute radiation-induced toxicities (RITs) in an HNC cohort. METHODS: A two-stage GWAS was performed in 1279 HNC patients treated with RT and prospectively scored for mucositis, xerostomia, sticky saliva, and dysphagia. The area under the curve (AUC) was used to estimate the average load of toxicity during RT. At the discovery study, multivariate linear regression was used in 957 patients, and the top-ranking SNPs were tested in 322 independent replication cohort. Next, the discovery and the replication studies were meta-analyzed. RESULTS: A region on 5q21.3 containing 16 SNPs showed genome-wide (GW) significance association at P-value < 5.0 × 10-8 with patient-rated acute xerostomia in the discovery study. The top signal was rs35542 with an adjusted effect size of 0.17*A (95% CI 0.12 to 0.23; P-value < = 3.78 × 10-9). The genome wide significant SNPs were located within three genes (EFNA5, FBXL17, and FER). In-silico functional analysis showed these genes may be involved in DNA damage response and co-expressed in minor salivary glands. We found 428 suggestive SNPs (P-value < 1.0 × 10-5) for other toxicities, taken to the replication study. Eleven of them showed a nominal association (P-value < 0.05). CONCLUSIONS: This GWAS suggested novel SNPs for patient-rated acute xerostomia in HNC patients. If validated, these SNPs and their related functional pathways could lead to a predictive assay to identify sensitive patients to radiation, which may eventually allow a more individualized RT treatment.