Data mining on identifying diagnosis and prognosis biomarkers in head and neck squamous carcinoma

Abstract

AbstractHead and neck squamous carcinoma (HNSC) induces high cancer-related death worldwide. The biomarker screening on diagnosis and prognosis is of great importance. This research is aimed to explore the specific diagnostic and prognostic biomarkers for HNSC through bioinformatics analysis. The mutation and dysregulation data were acquired from UCSC Xena and TCGA databases. The top ten genes with mutation frequency in HNSC were TP53 (66%), TTN (35%), FAT1 (21%), CDKN2A (20%), MUC16 (17%), CSMD3 (16%), PIK3CA (16%), NOTCH1 (16%), SYNE1 (15%), LRP1B (14%). A total of 1,060 DEGs were identified, with 396 up-regulated and 665 downregulated in HNSC patients. Patients with lower expression of ACTN2 (P = 0.039, HR = 1.3), MYH1 (P = 0.005, HR = 1.5), MYH2 (P = 0.035, HR = 1.3), MYH7 (P = 0.053, HR = 1.3), and NEB (P = 0.0043, HR = 1.5) exhibit longer overall survival time in HNSC patients. The main DEGs were further analyzed by pan-cancer expression and immune cell infiltration analyses. MYH1, MYH2, and MYH7 were dysregulated in the cancers. Compared with HNSC, their expression levels are lower in the other types of cancers. MYH1, MYH2, and MYH7 were expected to be the specific diagnostic and prognostic molecular biomarkers of HNSC. All five DEGs have a significant positive correlation with CD4+T cells and macrophages.