Amirreza Pashapouryeganeh
1 
, Rosa Hosseinzadegan
2 
, Mahnaz Baradaran
3, Maryam Azarian
1, Mohammad Mahjoubi
1, Arash Haji Kamanaj Olia
1, Atefeh Dehghanitafti
1, Rezvan Shahparvary
1, Haniyeh Ghasrsaz
1, Asra Idani
1, Seyed Hasan Fazlazar Sharabiani
4, Reza Khalili Dizaji
4, Moein Hossein Pourfeizi
5, Qumars Behfar
1* 
, Alireza Azani
1*, Touraj Asvadi Kermani
5*1 Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
2 Department of Biology, Payame Noor University, Tehran, Iran
3 Department of Pathology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
4 Faculty of Medicine, Islamic Azad University, Tabriz Branch, Tabriz, Iran
5 Department of Thoracic Surgery, School of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
Abstract
Pancreatic cancer (PC) remains one of the most lethal malignancies worldwide, characterized by late diagnosis, rapid progression, and poor therapeutic response. Despite incremental advances, survival rates remain dismal, indicating the urgent need for innovative diagnostic and therapeutic strategies. Micro ribonucleic acid (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. Moreover, they have emerged as the critical modulators of PC pathogenesis and influence key oncogenic and tumor-suppressive pathways, including KRAS, NF-κB, and AKT/STAT3. Dysregulated miRNAs (e.g., miR-21 and miR-155) drive tumor proliferation, epithelial-mesenchymal transition, and chemoresistance. Conversely, tumor-suppressive miRNAs (e.g., miR-34a) inhibit these processes, highlighting their dual biological roles. Mounting evidence supports the value of circulating and extracellular vesicle-associated miRNAs in distinguishing PC from benign lesions. In addition, integrated biomarker panels combining miRNAs with CA19-9 have achieved sensitivities and specificities exceeding 90%, outperforming conventional assays. Furthermore, machine-learning models have enhanced the predictive power of miRNA signatures for personalized diagnosis. Therapeutically, miRNA modulation offers novel opportunities. Strategies include restoring tumor-suppressive miRNAs or inhibiting oncogenic ones using antagomirs and delivery systems, such as nanoparticles and viral vectors. Emerging approaches, such as CRISPR-Cas9 gene editing, further expand this potential. Preclinical studies demonstrate the efficacy of miRNA-based interventions in reducing tumor growth, though clinical translation is limited by delivery challenges. In conclusion, miRNAs represent a multifaceted frontier in PC research, serving as noninvasive biomarkers and promising therapeutic targets. Overall, continued integration of molecular biology with computational innovations is poised to accelerate the implementation of miRNA-based precision oncology.