Developing and validating the model of tumor-infiltrating immune cell to predict survival in patients receiving radiation therapy for head and neck squamous cell carcinoma

Ting Xu; Mengting Xu; Yiying Xu; Xiaojun Cai; Michael J Brenner; Joshua Twigg; Zhaodong Fei; Chuanben Chen

doi:10.21037/tcr-23-2345

Developing and validating the model of tumor-infiltrating immune cell to predict survival in patients receiving radiation therapy for head and neck squamous cell carcinoma

Transl Cancer Res. 2024 Jan 31;13(1):394-412. doi: 10.21037/tcr-23-2345. Epub 2024 Jan 29.

Authors

Ting Xu^#¹, Mengting Xu^#¹, Yiying Xu¹, Xiaojun Cai¹, Michael J Brenner², Joshua Twigg³, Zhaodong Fei¹, Chuanben Chen¹

Affiliations

¹ Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
² Department of Otolaryngology-Head and Neck Surgery, University of Michigan Medical School, Ann Arbor, MI, USA.
³ School of Dentistry, University of Leeds, Leeds, UK.

^# Contributed equally.

Abstract

Background: Radiotherapy (RT) is a mainstay of head and neck squamous cell carcinoma (HNSCC) treatment. Due to the influence of RT on tumor cells and immune/stromal cells in microenvironment, some studies suggest that immunologic landscape could shape treatment response. To better predict the survival based on genomic data, we developed a prognostic model using tumor-infiltrating immune cell (TIIC) signature to predict survival in patients undergoing RT for HNSCC.

Methods: Gene expression data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Data from HNSCC patients undergoing RT were extracted for analysis. TIICs prevalence in HNSCC patients was quantified by gene set variation analysis (GSVA) algorithm. TIICs and post-RT survival were analyzed using univariate Cox regression analysis and used to construct and validate a tumor-infiltrating cells score (TICS).

Results: Five of 26 immune cells were significantly associated with HNSCC prognosis in the training cohort (all P<0.05). Kaplan-Meier (KM) survival curves showed that patients in the high TICS group had better survival outcomes (log-rank test, P<0.05). Univariate analyses demonstrated that the TICS had independent prognostic predictive ability for RT outcomes (P<0.05). Patients with high TICS scores showed significantly higher expression of immune-related genes. Functional pathway analyses further showed that the TICS was significantly related to immune-related biological process. Stratified analyses supported integrating TICS and tumor mutation burden (TMB) into individualized treatment planning, as an adjunct to classification by clinical stage and human papillomavirus (HPV) infection.

Conclusions: The TICS model supports a personalized medicine approach to RT for HNSCC. Increased prevalence of TIIC within the tumor microenvironment (TME) confers a better prognosis for patients undergoing treatment for HNSCC.

Keywords: Head and neck squamous cell carcinoma (HNSCC); gene set variation analysis (GSVA); human papillomavirus (HPV); radiotherapy (RT); tumor-infiltrating immune cell (TIIC).