Research Appraisalother

MicroRNAs in oncology: a translational perspective in the era of AI

Nature reviews. Clinical oncologyJurj, Ancuta, Dragomir, Mihnea P, Li, Ziyi et al.1 Apr 2026DOI

Clinical Snapshot

60CEBM

Evidence: Moderateother

PICO Framework

P — Population	Cancer patients and healthy individuals across various cancer types
I — Intervention	MicroRNA-based diagnostic tools and therapeutic interventions
C — Comparator	Traditional biomarkers and therapeutic approaches
O — Outcomes	Diagnostic accuracy, therapeutic efficacy, clinical translation potential

Bottom Line

This comprehensive review synthesises three decades of microRNA research in oncology, highlighting their dual roles as tumour suppressors and oncogenes. While miRNAs show promise as biomarkers and therapeutic targets, clinical translation remains challenging. The integration of artificial intelligence may accelerate biomarker discovery and clinical trial design. However, the narrative review format limits quantitative assessment of clinical utility. Australian clinicians should note that miRNA-based diagnostics and therapeutics remain largely investigational, with limited TGA-approved applications. The field shows promise but requires robust clinical validation before routine implementation. Current evidence supports continued research investment but cautions against premature clinical adoption without proper validation studies.

Evidence: Moderate

Key Findings

P Value: Not applicable for narrative review
Effect Size: Not quantified - narrative synthesis only
Primary Outcome: miRNAs demonstrate context-dependent roles as tumour suppressors or oncogenes across cancer types
Nnt Or Sensitivity: Diagnostic sensitivity and specificity vary by miRNA panel and cancer type - specific values not synthesised
Confidence Interval: Not applicable for narrative review

Clinical Application

Limited by current TGA approval pathways for miRNA-based diagnostics and therapeutics Relevant to Australian oncology practice; however, most miRNA-based tools remain investigational and not PBS-listed. Integration with existing Cancer Australia guidelines needed. Broad applicability to Australian cancer patients across multiple tumour types

Abstract

Over the past three decades, knowledge of microRNA (miRNA) biology has advanced from the initial discovery of their regulatory functions to the finding of abnormal activity in leukaemias, and then to a comprehensive understanding of the roles of miRNAs in both normal physiology and most diseases, with cancer being extensively studied. miRNA dysregulation contributes to tumorigenesis, with certain miRNAs acting as either tumour suppressors or oncogenic factors in a context-dependent manner. A subset of miRNAs have shown promise as tumour biomarkers and therapeutic targets in preclinical studies, with several miRNA-based diagnostic tools and treatments progressing to clinical trials. Artificial intelligence (AI) and machine learning techniques began to be introduced into cancer research and oncology a decade ago and are now on the verge of revolutionizing biomarker identification and clinical trials. In this Review, we highlight important roles of miRNAs in cancer biology and their potential as diagnostic tools and therapeutic targets. In particular, we discuss emerging challenges and opportunities presented by AI-driven data analysis and combinatorial strategies, and how advances in these areas have addressed previous doubts on the clinical translation of miRNA-based biomarkers and therapeutics.

References

1.Jurj, A., Dragomir, M. P., Li, Z., & Calin, G. A. (2026). MicroRNAs in oncology: a translational perspective in the era of AI. Nature Reviews Clinical Oncology. https://doi.org/10.1126/science.aam8526

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