IMR Press / FBL / Volume 29 / Issue 3 / DOI: 10.31083/j.fbl2903130
Open Access Original Research
Deciphering a Prognostic Signature Based on Soluble Mediators Defines the Immune Landscape and Predicts Prognosis in HNSCC
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1 Faculty of Chinese Medicine, Macau University of Science and Technology, 999078 Taipa, Macau, China
2 Clinical Medical College, Southwest Medical University, 646000 Luzhou, Sichuan, China
3 School of Stomatology, Southwest Medical University, 646000 Luzhou, Sichuan, China
4 School of Science, Minzu University of China, 100081 Beijing, China
5 First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, 300072 Tianjin, China
6 Department of Oncology, Chongqing General Hospital, 401147 Chongqing, China
7 Department of Specialty Medicine, Ohio University, Athens, OH 45701, USA
*Correspondence: (Ke Xu); (Qibiao Wu); (Guanhu Yang)
These authors contributed equally.
Front. Biosci. (Landmark Ed) 2024, 29(3), 130;
Submitted: 7 October 2023 | Revised: 29 November 2023 | Accepted: 8 January 2024 | Published: 22 March 2024
Copyright: © 2024 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.

Background: The study on Head and Neck Squamous Cell Carcinoma (HNSCC), a prevalent and aggressive form of head and neck cancer, focuses on the often-overlooked role of soluble mediators. The objective is to leverage a transcriptome-based risk analysis utilizing soluble mediator-related genes (SMRGs) to provide novel insights into prognosis and immunotherapy efficacy in HNSCC patients. Methods: We analyzed the expression and prognostic significance of 10,859 SMRGs using 502 HNSCC and 44 normal samples from the TCGA-HNSC cohort in The Cancer Genome Atlas (TCGA). The samples were divided into training and test sets in a 7:3 ratio, with an additional external validation using 40 tumor samples from the International Cancer Genome Consortium (ICGC). Key differentially expressed genes (DEGs) with prognostic significance were identified through univariate and Lasso-Cox regression analyses. A prognostic model based on 20 SMRGs was developed using Lasso and multivariate Cox regression. We assessed the clinical outcomes and immune status in high-risk (HR) and low-risk (LR) HNSCC patients utilizing the BEST databases and single-sample Gene Set Enrichment Analysis (ssGSEA). Results: The 20 SMRGs were crucial in predicting the prognosis of HNSCC, with the SMRG signature emerging as an independent prognostic indicator. Patients classified in the HR group exhibited poorer outcomes compared to those in the LR group. A nomogram, integrating clinical characteristics and risk scores, demonstrated substantial prognostic value. Immunotherapy appeared to be more effective in the LR group, possibly attributed to enhanced immune infiltration and expression of immune checkpoints. Conclusions: The model based on soluble mediator-associated genes offers a fresh perspective for assessing the pre-immune efficacy and showcases robust predictive capabilities. This innovative approach holds significant promise in advancing the field of precision immuno-oncology research, providing valuable insights for personalized treatment strategies in HNSCC.

soluble mediators
tumor microenvironment
prognostic signature
0098/2021/A2/Science and Technology Development Fund
0048/2023/AFJ/Science and Technology Development Fund
FRG-23-003-FC/Macau University of Science and Technology’s Faculty Research Grant
Fig. 1.
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