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Characterization of Molecular Subtypes in Head and Neck Squamous Cell Carcinoma With Distinct Prognosis and Treatment Responsiveness.

ABSTRACT: Head and neck squamous cell carcinoma (HNSCC) is one of the most aggressive malignancies with complex phenotypic, etiological, biological, and clinical heterogeneities. Previous studies have proposed different clinically relevant subtypes of HNSCC, but little is known about its corresponding prognosis or suitable treatment strategy. Here, we identified 101 core genes from three prognostic pathways, including mTORC1 signaling, unfold protein response, and UV response UP, in 124 pairs of tumor and matched normal tissues of HNSCC. Moreover, we identified three robust subtypes associated with distinct molecular characteristics and clinical outcomes using consensus clustering based on the gene expression profiles of 944 HNSCC patients from four independent datasets. We then integrated the genomic information of The Cancer Genome Atlas (TCGA) HNSCC cohort to comprehensively evaluate the molecular features of different subtypes and screen for potentially effective therapeutic agents. Cluster 1 had more arrested oncogenic signaling, the highest immune cell infiltration, the highest immunotherapy and chemotherapeutic responsiveness, and the best prognosis. By contrast, Cluster 3 showed more activated oncogenic signaling, the lowest immune cell infiltration, the lowest immunotherapy and chemotherapy responsiveness, and the worst prognosis. Our findings corroborate the molecular diversity of HNSCC tumors and provide a novel classification strategy that may guide for prognosis and treatment allocation.

SUBMITTER: Zhang P

PROVIDER: S-EPMC8476885 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundChromatin regulators (CRs) serve as indispensable factors in tumor biological processes by influencing tumorigenesis and the immune microenvironment and have been identified in head and neck squamous cell carcinoma (HNSCC). Hence, CR-related genes (CRRGs) are considered potential biomarkers for predicting prognosis and immune infiltration in HNSCC. In this study, we established a novel signature for predicting the prognosis and immunotherapeutic response of HSNCC.MethodsA total of 870 CRRGs were obtained according to previous studies. Subsequently, patients in the TCGA-HNSC cohort were divided into different clusters based on the expression of prognostic CRRGs. Kaplan‒Meier (K‒M) survival analysis was conducted to compare the prognosis in clusters, and the CIBERSORT and ssGSEA methods assessed the immune infiltration status. In addition, the differences in immunotherapeutic responses were determined based on the TICA database. Furthermore, the differentially expressed CRRGs between clusters were identified, and the predictive signature was established according to the results of univariate Cox, least absolute shrinkage and selection operator regression analysis, and multivariate Cox. The predictive effects of the risk model were evaluated according to the area under the receiver operating characteristic (ROC) curve (AUC) in both the training and external test cohorts. A nomogram was established, and survival comparisons, functional enrichment analyses, and immune infiltration status and clinical treatment assessments were performed. In addition, the hub gene network and related analysis were conducted with the Cytohubba application.ResultsBased on the expression of prognostic CRRGs, patients were divided into two clusters, in which Cluster 1 exhibited a better prognosis, more enriched immune infiltration, and a better immunotherapeutic response but exhibited chemotherapy sensitivity. The AUC values of the 1-, 3- and 5- year ROC curves for the risk model were 0.673, 0.732, and 0.692, respectively, as well as 0.645, 0.608, and 0.623 for the test set. In addition, patients in the low-risk group exhibited more immune cell enrichment and immune function activation, as well as a better immunotherapy response. The hub gene network indicated ACTN2 as the core gene differentially expressed between the two risk groups.ConclusionWe identified molecular subtypes and established a novel predictive signature based on CRRGs. This effective CRRS system can possibly provide a novel research direction for exploring the correlation between CRs and HNSCC and requires further experimental validation.

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Characterization of Molecular Subtypes in Head and Neck Squamous Cell Carcinoma With Distinct Prognosis and Treatment Responsiveness.

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