Comprehensive analysis of radiosensitivity in head and neck squamous cell carcinoma. (June 2021)

• Record Type: Journal Article
• Authors: Li, Guangqi; Jiang, Yuanjun; Li, Guang; Qiao, Qiao
• Is Part Of: Radiotherapy and oncology. Volume 159(2021)
• Page Start: 126
• Page End: 135
• Publication Date: 2021-06
• Subjects: HNSCC head and neck squamous cell carcinoma -- DEGs differentially expressed genes -- WGCNA weighted gene co-expression network analysis -- PFI progression-free interval -- tr-PFI treatment related progression-free interval -- TFs transcription factors; Radioresistance -- Single cell sequencing -- Deconvolution -- Immune checkpoint blockade -- TCGA; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2021.03.017
• Languages: English
• ISSNs: 0167-8140

Abstract

Highlights: This research developed an approach to explore radiosensitivity at multi-levels. The atypical HNSCC subtype exhibited a higher sensitivity than other subtypes. Different HNSCC subtypes share common and distinct mechanisms of radioresistance. Enhanced cancer-immune interaction through PD1 & TIM3 contributes to radioresistance. Abstract: Background: Radioresistance is a major barrier to the successful treatment of head and neck squamous cell carcinoma (HNSCC). Methods: We took advantage of different types of data, including single-cell sequencing data, bulk tissue sequencing data and deconvolution data, to conduct a comprehensive analysis of HNSCC radiosensitivity at the cellular, patient, and cell type levels. Single-cell transcriptomes for 1388 primary cancer cells from a previous study were analysed. The TCGA HNSCC dataset including 499 primary HNSCC samples with RNA-seq data, DNA methylation data and clinical information were used for bulk tissue sequencing analyses and deconvolution. Results: We found that radiosensitivity clustering of HNSCC cells was highly consistent with molecular typing, where cancer cells of the atypical subtype exhibited a higher sensitivity than those of the classical and basal subtypes. The common radioresistant gene modules of the classical and basal subtypes were mainly associated with cell division and cell cycle regulation; the classical subtype specific radioresistant module was mainly associated with metabolic pathways; and the basal radioresistant subtype specific modules included two epithelial differentiation-related modules and a module mainly associated with endoplasmic reticulum, apoptosis and focal adhesion. We developed a radioresistance score using genes that affect both the cancer cell response to radiation and the patient response to radiotherapy. An enhanced cancer-immune interaction through the PD1-PDL1/PDL2 and TIM3-Galectin9 pathways was observed in radioresistant tumours, with foldchange = 2.88 (PD1), 1.44 (PDL1), 3.22 (PDL2), 1.47 (TIM3), 1.88 (Galectin9) respectively and FDR < 0.001. Transcriptional activities related to the hypoxia response, p53 pathway, NF-kappa-B pathway and inflammatory response were abnormally activated in the radioresistant tumours (FDR < 0.05). Conclusions: This study comprehensively discussed the radioresistance of HNSCC, identified a group of HNSCCs that were likely to benefit from combined radiotherapy and immune checkpoint blockade, and proposed new targets for the treatment of radioresistant HNSCC.