Omics-based exploration of biomarkers and therapeutic targets in olfactory neuroblastoma

Olfactory Neuroblastoma (ONB) is a rare and aggressive malignant tumor with a complex, heterogeneous pathogenesis. Although various omics studies have been conducted for ONB recently, there is still no omics evidence summary for ONB. Therefore, this study systematically reviews and synthesizes evidence across multiple omics layers for identifying biomarkers and therapeutic targets of ONB, aiming to advance the translation of molecular insights into clinical applications, including subtype classification, targeted therapy, and drug development.

We conducted a systematic review following the PRISMA 2020 guidelines and registered with PROSPERO (ID: CRD420251128889). Five databases were searched up to 31st May 2025 for original studies that applied single- or multi-omics analyses to ONB. Risk of bias was assessed using the JBI Case Series Checklist.

A total of 24 studies were included, covering genomics (11/24), transcriptomics (5/24), proteomics (1/24), and multi-omics integration (7/24). Genomic studies identified recurrent mutations (e.g., TP53, IDH2), chromosomal alterations (e.g., 1p, 3p, 13q), and pathway-level changes (e.g., PI3K/AKT/mTOR, chromatin remodeling). Transcriptomic studies revealed Basal, Neural, and Mesenchymal subtypes, with NEUROD1 and EZH2 serving as key biomarkers. For proteomics, one immunohistochemistry-focused study reports markers such as Trk proteins and GRP78. Multi-omics studies integrated subtyping, tumor-origin hypotheses, and immune landscape characterization, supporting biomarkers such as IDH2, NEUROD1, and EZH2, and highlighting heterogeneity. However, there is very limited functional validation (only one study) and limited AI/ML usage (two studies), despite their potential to assist with small cohorts and multimodal integration.

This review consolidates current evidence on candidate biomarkers and therapeutic targets for ONB, highlighting the vital role of omics-based approaches in elucidating its molecular mechanisms. To advance the field, future research should focus on standardizing methods, validating findings in larger, more diverse groups, and integrating multi-omics techniques with AI-driven analyses to enhance diagnostic precision and develop targeted treatments.