Characterizing the salivary RNA landscape to identify potential diagnostic, prognostic, and follow-up biomarkers for breast cancer.

Abstract

Breast cancer (BC) diagnostics and prognostics traditionally rely on invasive tissue biopsies, presenting limitations for large-scale screening and continuous patient monitoring. Salivary biomarkers have recently emerged as a compelling noninvasive and accessible alternative, offering significant potential for population-level screening and long-term monitoring of BC. In this study, we conducted a comprehensive salivary transcriptomic profiling of BC patients using high-throughput RNA sequencing. Our analysis captured a wide spectrum of RNA species, including mRNAs, lncRNAs, miRNAs, and snRNAs, highlighting their collective contributions in the molecular landscape of BC patient saliva. We identified robust human gene expression signatures that distinguish BC patients from healthy individuals. Importantly, we discovered RNA profiles that were differentially expressed relative to control samples, enabling the discrimination of noninvasive, invasive, and mixed histological types, as well as hormone receptor-positive molecular subtypes. These salivary markers showed substantial concordance with established tumor gene expression datasets, strengthening their potential relevance in clinical stratification. Furthermore, we identified subsets of salivary genes associated with nodal involvement and others linked to poor survival outcomes, highlighting their potential as prognostic indicators. A prospective follow-up analysis revealed a decline in the expression of several cancer-related salivary transcripts 1-year posttreatment, indicating that salivary RNA might also reflect treatment response over time. This study establishes a proof-of-concept for salivary RNA biomarkers as a versatile, accessible, and robust tool for BC diagnosis, prognosis, and follow-up, paving the way for innovative biomarker-driven strategies in oncology.