An ion-channel-gene-based prediction model for head and neck squamous cell carcinoma: Prognostic assessment and treatment guidance

Abstract

PurposeHead and neck squamous cell carcinoma (HNSCC) is a very diverse malignancy with a poor prognosis. The purpose of this study was to develop a new signature based on 12 ion channel genes to predict the outcome and immune status of HNSCC patients.MethodsClinicopathological information and gene sequencing data of HNSCC patients were generated from the Cancer Genome Atlas and Gene Expression Omnibus databases. A set of 323 ion channel genes was obtained from the HUGO Gene Nomenclature Committee database and literature review. Using univariate Cox regression analysis, the ion channel genes related to HNSCC prognosis were identified. A prognostic signature and nomogram were then created using machine learning methods. Kaplan-Meier analysis was used to explore the relevance of the risk scores and overall survival (OS). We also investigated the association between risk scores, tumor immune infiltration, and gene mutational status. Finally, we detected the expression levels of the signature genes by quantitative real-time polymerase chain reaction, western blotting, and immunohistochemistry.ResultsWe separated the patients into high- and low-risk groups according to the risk scores computed based on these 12 ion channel genes, and the OS of the low-risk group was significantly longer (p<0.001). The area under the curve for predicting 3-year survival was 0.729. Univariate and multivariate analyses showed that the 12-ion-channel-gene risk model was an independent prognostic factor. We also developed a nomogram model based on risk scores and clinicopathological variables to forecast outcomes. Furthermore, immune cell infiltration, gene mutation status, immunotherapy response, and chemotherapeutic treatment sensitivity were all linked to risk scores. Moreover, high expression levels of ANO1, AQP9, and BEST2 were detected in HNSCC tissues, whereas AQP5, SCNN1G, and SCN4A expression was low in HNSCC tissues, as determined by experiments.ConclusionThe 12-ion-channel-gene prognostic signatures have been demonstrated to be highly efficient in predicting the prognosis, immune microenvironment, gene mutation status, immunotherapy response, and chemotherapeutic sensitivity of HNSCC patients.

Molecular subtyping and the construction of a predictive model of colorectal cancer based on ion channel genes

“…Ion channels, transmembrane proteins responsible for selective ion transport, play a critical role in regulating tumor cell behavior [ 43 – 45 ] and the TME [ 46 ]. Their widespread presence in cells makes them valuable indicators for cancer diagnosis, therapeutic targeting, and prognosis [ 47 ]. Therefore, the classification of CRC patients into subtypes based on ion channel gene expression holds significant study value, which was demonstrated by the results of this study.…”

An angiogenesis-associated gene-based signature predicting prognosis and immunotherapy efficacy of head and neck squamous cell carcinoma patients

“…The TCGA database, data sets GSE41613 (Han et al 2022 ; Liu et al 2023 ) and GSE127165 (Yan et al 2022 ) from the GEO database, and the clinical parameters of the HNSCC samples were downloaded and used to generate the normalized gene expression data. In addition, the combat function is used to eliminate batch effect differences between datasets.…”

Deciphering COPS5 influence on immune infiltration and prognosis in head and neck squamous cell carcinoma

“…Several studies have made significant progress in establishing prognostic models for HNSCC to predict patient survival. These models have been constructed using various biological factors and gene sets, including immune-related long non-coding RNAs [ 14 ], immune infiltration-related genes [ 15 ], ferroptosis-related genes [ 16 ], N6 methyladenosine (m6A) regulator-related genes [ 17 ], and ion channel related genes [ 18 ]. These models, constructed using Lasso regression, have proven effectiveness in predicting patient survival rates, as well as the response to of immunotherapy.…”