Development of a novel prognostic signature derived from essential genes in head and neck squamous cell carcinoma

• Published in: Journal of oral pathology & medicine Vol. 52; no. 7; pp. 610 - 618
• Main Authors: Dai, Yibin, Yao, Qin, Wang, Ziyu, Diao, Pengfei, Wang, Dongmiao, Yan, Enshi, Wang, Yanling
• Format: Journal Article
• Language: English
• Published: Denmark Wiley Subscription Services, Inc 01.08.2023
• Subjects: 1-Phosphatidylinositol 3-kinase; AKT protein; Carcinoma, Squamous Cell - pathology; Cell cycle; CRISPR; essential gene; Genes, Essential; Head & neck cancer; Head and neck carcinoma; Head and Neck Neoplasms - genetics; head and neck squamous cell carcinoma; Humans; MAP kinase; Medical prognosis; Notch1 protein; p53 Protein; Phosphatidylinositol 3-Kinases - genetics; Precision Medicine; Prognosis; prognostic biomarker; Squamous cell carcinoma; Squamous Cell Carcinoma of Head and Neck - genetics; survival; prognostic biomarker; essential gene; survival; head and neck squamous cell carcinoma
• ISSN: 0904-2512; 1600-0714
• DOI: 10.1111/jop.13435

Background Substantial heterogeneity in head and neck squamous cell carcinoma (HNSCC) compromise accurate patient stratification and personalized treatment planning. Current molecular classification is largely based on genes with highly variable expression without considering their functional roles. Here, we sought to identify HNSCC essential genes for patient stratification and prognostication. Methods Essential genes for HNSCC were screened from genome‐wide CRISPR knockout datasets. Candidates were further identified through univariate Cox regression. The least absolute shrinkage and selection operator was utilized to develop the prognostic signature. Candidate essential genes were exploited to classify patients into subgroups by consensus clustering. Survival outcomes, genomic alterations, signaling activities, and therapeutic vulnerabilities were compared between patient subgroups. Results Sixty‐eight genes were identified as candidates and utilized to develop an 8‐gene prognostic signature. Patients were segregated into two clusters with distinct survival rates across multiple cohorts based on upregulated essential genes. Cluster 2 exhibited higher TP53, CDKN2A, and NOTCH1 mutations, higher stromal activities, worse prognosis as well as and sensitivities to cell cycle inhibitors. Cluster 1 was characterized by a better prognosis and susceptibility to PI3K/AKT and MAPK inhibitors. Conclusion Our study developed a novel and robust prognostic signature and classification derived from essential genes for HNSCC, which sheds new light on HNSCC precision oncology.