Our analysis included the TCGA pan-cancer atlas dataset, which includes 10,522 tumors across 33 cancer types including 528 HNSCC samples. The following data is available at gdc.cancer.gov/node/977: cancer type, p53 mutation status, chromosome arm aneuploidy status, miR-34a expression, and mRNA gene expression. Only samples with both miR expression profiling and mutation or mRNA expression profiling were considered. Correlation between miR-34a and MET mRNA was quantified with Pearson’s correlation coefficient, and correlation coefficients with Bonferroni-corrected p-value ≤0.05 were considered statistically significant. The Mann-Whitney U test was used to compare expression between different groups of samples. We generated survival curves of HNSCC cases in the TCGA- cohort according to the expression status of the MET gene stratified based on HPV status. A group cutoff of “quartile” was identified, and the Kaplan–Meier curve was plotted. Univariate and multivariable Cox proportional hazards regression was used to assess association with overall survival controlling for different covariates using R software. Estimation of individual immune subtype fractions by xCell in TCGA samples is publicly available at xcell.ucsf.edu.