Background: IO efficacy in LA/M HNSCC patients is limited. Identifying biomarkers of resistance and response is crucial to better stratify patients. We characterized the genomic and transcriptomic landscape of IO-naive HNSCC patients to identify specific genomic and transcriptomic signatures of response to IO. Methods: We analyzed baseline FFPE samples of 176 LA/M HNSCC patients treated with IO from CHECK'UP (NCT03412058) and TOPNIVO (NCT03226756) trials, for whom baseline RNAseq data were available. A penalized Cox model with Elastic Net procedure was used to identify gene signatures associated with PFS and OS. Using a resampling procedure, a bootstrap selection stability (BSS) index was computed for each gene and only those with a BSS > 30% were included in the final model to determine a score for both PFS and OS. In addition, 149 paired tumor and germline DNA were sequenced using whole exome. For biostatistics analysis using genomic alterations, only variants (SNVs, Indels, CNVs) in oncogenes, tumor suppressor genes with a variant allele frequency (VAF) of at least 10% and altered signaling pathways were considered. Results: The cohort (median age 62.5 yo) included a majority of oropharynx (39.8%) and oral cavity (29.8%) tumors, 77.8% males, 62.3% with alcohol and 81.7% with tobacco use history and 60.0% of them were metastatic. Objective response rate was 17.4%, median PFS and OS were 1.9 months (mo) (95%CI=[1.8-2.5]) and 8.1 mo (95%CI=[6.1-9.7]), respectively (median follow-up of 33.3 mo, 95%CI=[28.7-36.5]). The most frequent genomic alterations affected CCND1 , CDKN2A , FAT1 , TERT , TP53 genes and a gain of 3q26-q28. In univariable analyses, the presence of TERT or FAT1 alteration were significantly associated with worse PFS. After adjustment for clinical variable, the presence of FAT1 alteration and the upregulation of Hippo signalling pathway remained associated with worse PFS. The presence of TERT mutation was also associated with worse OS whereas the PI3K/AKT/mTOR pathway was associated with improved OS in univariable and multivariable analysis, respectively. Among the 500 most differentially expressed transcripts, 21- and 18-gene expression signatures were selected to assess their association with PFS and OS, respectively. C-Index was 0.72 and 0.71 (0.58 and 0.57 after internal bootstrap validation) for PFS and OS, respectively. Scores were dichotomized using time-dependent ROC Curve (Low vs High) and HR adjusted for clinical factors were 3.62 (95%CI = [2.42; 5.43]) and 3.86 (95%CI = [2.52; 5.91]; p<0.0001) for PFS and OS, respectively. Conclusions: We identified robust transcriptomic signatures and genomic alterations strongly associated with IO resistance, offering potential biomarkers for patient stratification. TERT or FAT1 alteration were associated with worse prognosis.