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Updated: Dec 30, 2025

RNAscope for In situ Detection of Transcriptionally Active Human Papillomavirus in Head and Neck Squamous Cell Carcinoma
Published on: March 11, 2014
Expression scoring of a small-nucleolar-RNA signature identified by machine learning serves as a prognostic predictor
Lu Xing1, Xiaoqi Zhang2, Xiaoqian Zhang3
1Shandong Key Laboratory of Oral Tissue Regeneration, School of Stomatology, Shandong University, Jinan, Shandong, China.
Abstract:
Head and neck squamous cell carcinoma (HNSCC) is a common malignancy with high mortality and poor prognosis due to a lack of predictive markers. Increasing evidence has demonstrated small nucleolar RNAs (snoRNAs) play an important role in tumorigenesis. The aim of this study was to identify a prognostic snoRNA signature of HNSCC. Survival-related snoRNAs were screened by Cox regression analysis (univariate, least absolute shrinkage and selection operator, and multivariate). The predictive value was validated in different subgroups. The biological functions were explored by coexpression analysis and gene set enrichment analysis (GSEA). One hundred and thirteen survival-related snoRNAs were identified, and a five-snoRNA signature predicted prognosis with high sensitivity and specificity. Furthermore, the signature was applicable to patients of different sexes, ages, stages, grades, and anatomic subdivisions. Coexpression analysis and GSEA revealed the five-snoRNA are involved in regulating malignant phenotype and DNA/RNA editing. This five-snoRNA signature is not only a promising predictor of prognosis and survival but also a potential biomarker for patient stratification management.
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