Construction of an 11-microRNA-based signature and a prognostic nomogram to predict the overall survival of head and neck squamous cell carcinoma patients

Abstract

Background Head and neck squamous cell carcinoma (HNSCC) is a fatal malignancy owing to the lack of effective tools to predict overall survival (OS). MicroRNAs (miRNAs) play an important role in HNSCC occurrence, development, invasion and metastasis, significantly affecting the OS of patients. Thus, the construction of miRNA-based risk signatures and nomograms is desirable to predict the OS of patients with HNSCC. Accordingly, in the present study, miRNA sequencing data of 71 HNSCC and 13 normal samples downloaded from The Cancer Genome Atlas (TCGA) were screened to identify differentially expressed miRNAs (DEMs) between HNSCC patients and normal controls. Based on the exclusion criteria, the clinical information and miRNA sequencing data of 67 HNSCC samples were selected and used to establish a miRNA-based signature and a prognostic nomogram. Forty-three HNSCC samples were assigned to an internal validation cohort for verifying the credibility and accuracy of the primary cohort. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore the functions of 11 miRNA target genes. Results In total, 11 DEMs were successfully identified. An 11-miRNA risk signature and a prognostic nomogram were constructed based on the expression levels of these 11 DEMs and clinical information. The signature and nomogram were further validated by calculating the C-index, area under the curve (AUC) in receiver-operating characteristic curve analysis, and calibration curves, which revealed their promising performance. The results of the internal validation cohort shown the reliable predictive accuracy both of the miRNA-based signature and the prognostic nomogram. GO and KEGG analyses revealed that a mass of signal pathways participated in HNSCC proliferation and metastasis. Conclusion Overall, we constructed an 11-miRNA-based signature and a prognostic nomogram with excellent accuracy for predicting the OS of patients with HNSCC.

Ferroptosis-Related Long Non-Coding RNA signature predicts the prognosis of Head and neck squamous cell carcinoma

“…Every year, there are over 655,000 new HNSCC cases (globally), resulting in 90,000 deaths 2 . Tobacco smoking, alcohol consumption and human papillomavirus (HPV) infection are important risk factors for developing HNSCC 3 . Moreover, Epstein-Barr virus (EBV) is strongly associated with nasopharyngeal carcinoma (NPC) 4 .…”

The Prediction of a 3-Protein-Based Model on the Prognosis of Head and Neck Squamous Cell Carcinoma

“…With major advances in bioinformatics, proteomics, and techniques of gene analysis, a great deal of researchers has contributed themselves to developing signatures using different methods for predicting the prognosis of patients with head and neck cancer. Prognostic signatures have been developed using miRNA [28,29], alternative splicing [30], immune function molecules [31], and a signature according to m 6 A RNA methylation regulators [32].…”

miRNAs as Biomarkers for Diagnosing and Predicting Survival of Head and Neck Squamous Cell Carcinoma Patients

“…Some research shows that miRNA expression profile in solid tumors is significantly altered from that of healthy tissue [8]. Since miRNAs are stably expressed in human tissues and are linked with the initiation and progression of cancer, they could serve as biomarkers for diagnosis, prediction of response to therapy and treatment outcome [9]. Research on HNSCC indicated that many miRNAs are differentially expressed in cancer tissue, with some classified as oncogenic, and others as tumor suppressors [10].…”

“…Since miRNAs play a crucial role in cancer development, many studies have investigated the application of miRNA expression analysis as a prognostic tool for HNSCC. Recently published data showed that expression of miRNAs in healthy and tumor tissue of oral squamous cell carcinoma can be associated with patient prognosis, and could be used to predict recurrence and patient survival [9,12]. Several studies demonstrated that expression of miRNAs in patients' serum could be used as a factor predicting patients' survival, disease progression, or risk of developing side effects [13][14][15].…”