bioRxivCancer BiologyPreprint
Orphan Non-Coding RNAs Drive Tumorigenesis and Enable Pre-Diagnostic Detection in HPV-Negative Head and Neck Cancer
Hoang C B Nguyen, Lishi Li, Benedict Choi, Mehran KarimzadehiD, Jack GhannamiD, Jeffrey WangiD, Yana Al-InayaiD, Gjystina LumajiD, Fereydoun HormozdiariiD, Allen L. FengiD, Jeremy D. RichmoniD, Daniel G. Deschler, Mark Alex VarvaresiD, Daniel L. FadeniD, Derrick T. LiniD, Hani GoodarziiD
Abstract
HPV-negative head and neck squamous cell carcinoma (HNSCC) lacks reliable biomarkers for early detection and molecular stratification. We recently described orphan non-coding RNAs (oncRNAs) as a class of cancer-emergent small RNAs that arise from cryptic promoters largely silent in normal tissues. Here, we define the comprehensive landscape of oncRNAs in HNSCC. Using TCGA and CPTAC-3 data, we demonstrate that these transcripts are not only tumor-specific but provide digital fingerprints that accurately stratify tumors by anatomical site. Moving from association to function, we investigated whether these emergent transcripts actively drive tumorigenesis. We focused on oncRNA64585, a transcript highly enriched in oral cavity tumors and associated with tumor progression. Its depletion significantly impaired proliferation in vitro and suppressed tumor growth in syngeneic murine models. Mechanistically, transcriptomic and chromatin accessibility profiling revealed that oncRNA64585 regulates transcriptional programs governing cell cycle progression and apoptosis through interaction with the Polycomb Repressive Complex 2 (PRC2). Finally, we demonstrate the clinical utility of these signatures: oncRNA profiles in plasma predicted oral cavity cancer with >90% accuracy up to four years prior to clinical diagnosis. These findings establish oncRNAs as active drivers of HNSCC biology and potent tools for early detection and therapeutic targeting.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: cell type annotation
- research focus: drug response / drug discovery
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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