Identifying 8-mRNAsi Based Signature for Predicting Survival in Patients With Head and Neck Squamous Cell Carcinoma via Machine Learning

Abstract

Cancer stem cells (CSCs) have been characterized by several exclusive features that include differentiation, self-renew, and homeostatic control, which allows tumor maintenance and spread. Recurrence and therapeutic resistance of head and neck squamous cell carcinomas (HNSCC) have been identified to be attributed to CSCs. However, the biomarkers led to the development of HNSCC stem cells remain less defined. In this study, we quantified cancer stemness by mRNA expression-based stemness index (mRNAsi), and found that mRNAsi indices were higher in HNSCC tissues than that in normal tissue. A significantly higher mRNAsi was observed in HPV positive patients than HPV negative patients, as well as in male patients than in female patients. The 8-mRNAsi signature was identified from the genes in two modules which were mostly related to mRNAsi screened by weighted gene co-expression network analysis. In this prognostic signatures, high expression of RGS16, LYVE1, hnRNPC, ANP32A , and AIMP1 focus in promoting cell proliferation and tumor progression. While ZNF66, PIK3R3 , and MAP2K7 are associated with a low risk of death. The riskscore of eight signatures have a powerful capacity for 1-, 3-, 5-year of overall survival prediction (5-year AUC 0.77, 95% CI 0.69–0.85). These findings based on stemness indices may provide a novel understanding of target therapy for suppressing HNSCC stem cells.

Immune- and Stemness-Related Genes Revealed by Comprehensive Analysis and Validation for Cancer Immunity and Prognosis and Its Nomogram in Lung Adenocarcinoma

“…To define signatures to quantify stemness and to estimate the degree of carcinogenic dedifferentiation, previous studies utilized a set of logistic regression machine learning algorithms (OCLR) to generate a stemness index (14). In recent years, its significance had been confirmed by the bioinformatics analysis in various tumors (31,32), which also included the stemness indices of LUAD (15)(16)(17)(18). However, few studies have combined stemness indices and immunity to construct models and explore stem cell index and immune-related differential genes in LUAD.…”

Characterization of Interplay Between Autophagy and Ferroptosis and Their Synergistical Roles on Manipulating Immunological Tumor Microenvironment in Squamous Cell Carcinomas

“…Cancer stem cells (CSCs) are characterized by differentiation, self-renewal, and homeostatic control, which allowing tumor maintenance and spread. Increasing evidence has demonstrated that recurrence and therapeutic resistance of SCCs are attributed to CSCs (51). Here, this study quantified cancer stemness by mRNAsi in SCCs.…”

Aminoacyl-tRNA synthetases of the multi-tRNA synthetase complex and their role in tumorigenesis

“…Proteolytic cleavage of AIMP1 generates the multi-functional inflammatory cytokine endothelial monocyte-activating polypeptide II (EMAP II) [54] (discussed in detail below). AIMP1 has been associated with poor survival in patients with head and neck squamous cell carcinoma [81] . In laryngeal squamous cell carcinoma AIMP1, in cooperation with leukotriene A4 hydrolase (LTA4H), promotes cell proliferation, migration, and invasion by binding fascin actin-bundling protein 1 [82] .…”