Hypoxia-regulated non-coding RNAs in OSCC liquid biopsy: from molecular mechanisms to AI-driven precision oncology

Oral squamous cell carcinoma (OSCC) is characterized by late-stage diagnosis and high recurrence rates. Intratumoral hypoxia, driven by hypoxia-inducible factors 1α and 2α (HIF-1α/HIF-2α), orchestrates aggressive phenotypes including epithelial-mesenchymal transition (EMT), metabolic reprogramming, stemness maintenance, and therapeutic resistance. Non-coding RNAs (ncRNAs) serve as central post-transcriptional regulators of these hypoxic adaptations and offer promising non-invasive biomarker potential.

A systematic literature search of the PubMed database was executed on May 15, 2026, using structured Boolean combinations of Medical Subject Headings (MeSH) terms and high-accuracy text keywords targeting OSCC, hypoxia pathways (HIF-1α/HIF-2α), non-coding RNA classes (miRNAs, lncRNAs, circRNAs), and liquid biopsy media (saliva, plasma, serum, exosomes).

Hypoxic stress stabilizes HIF-1α during acute oxygen deprivation and HIF-2α during chronic adaptation, driving widespread dysregulation across the non-coding transcriptome. HIF-1α-activated "hypoxemirs" (e.g., miR-210) and oncogenic lncRNAs (MALAT1, H19, HOTAIR) coordinate early glycolytic switching and invasive EMT cascades. Conversely, chronic HIF-2α activation regulates specific downstream targets (e.g., lncRNA RAB11B-AS1, NEAT1) linked to persistent microvascular remodeling and cancer stem cell preservation. Closed-loop circular RNAs (e.g., circCDR1as, hsa-circ-0001030) display enhanced structural resistance to exonuclease degradation and act as molecular sponges within competing endogenous RNA (ceRNA) networks. When encapsulated within extracellular vesicles (exosomes) or secreted into saliva and blood, these stable transcripts provide a longitudinal window into tumor microenvironment dynamics. Incorporating artificial intelligence (AI) machine learning models improves multi-transcript signature filtering, while microfluidic point-of-care (POC) devices offer a practical roadmap for decentralized diagnostic deployment.

Hypoxia-responsive ncRNAs isolated from liquid biopsies represent promising candidates for OSCC precision oncology. However, routine clinical translation remains restricted as most candidate biomarkers are currently in Phase 1 discovery or Phase 2 early biofluid validation stages. Widespread clinical adoption is limited by pre-analytical sample handling variability, a lack of universally stable internal reference controls, cohort heterogeneity, insufficient prospective multi-center validation, and regulatory approval barriers.