Integrated Transcriptomic Analysis of NOTCH1- and MYB-Associated Immune Features in SACC

Salivary adenoid cystic carcinoma (SACC) is an immunologically cold malignancy with limited response to current immunotherapies. Integrated transcriptomic profiling of peripheral blood, primary tumors, lung metastases, and a two-donor single-cell dataset revealed compartment-specific expression signatures and, through computational inference, systemic immune dysregulation marked by hematopoietic suppression, T-cell exhaustion, compensatory myelopoiesis, and an immature B-cell expansion. To explore the transcriptional basis of this peripheral immune aberration, blood-derived RNA-seq was interrogated, identifying only 32 unique genes meeting |log2FC| > 1 and q < 0.05 among 34,999 transcripts; qPCR confirmed concordant upregulation of IL33 and CCL14, providing directional rather than confirmatory support, suggesting peripheral immune molecular aberrations that still require validation through broader differential gene expression validation. Complementing this transcriptomic signature, detection of MYB-NFIB fusion transcripts matching tumor tissue in one patient’s blood suggested that tumor-derived signals may access the circulation, although cohort validation remains necessary. Extending these peripheral observations to tissue compartments, we applied expression stratification, correlation networks, ligand-receptor mapping, and a virtual gain-loss model to computationally predict regulatory associations involving IL17RB/OLIG1/NOTCH1 in primary tumors and a CD24/IL17RB/MYB/MYBL2/CXCL13/CXCR5 module in lung metastases. At the single-cell level, cluster 10 emerged as a cell-cycle-high tumor population with transcriptional overlap with proliferating immune progenitors, providing a potential cellular basis for tumor cell entry into the circulation. Collectively, these computational inferences generate testable hypotheses for multicompartment immune dysregulation in SACC, positioning IL17RB as a candidate molecule that warrants prospective validation in SACC-specific preclinical models.