Targeting MicroRNAs in the perioperative window to prevent surgery-induced metastasis and postoperative cancer recurrence
Year: 2026
Type: article
Abstract: Surgery remains a central curative treatment for many solid tumors; however, postoperative recurrence and distant metastasis continue to limit long-term survival. The perioperative period is increasingly recognised as a biologically active window during which surgical trauma, inflammation, wound repair, hypoxia, platelet activation, immunosuppression, anaesthetic exposure, and extracellular vesicle signalling may influence the survival and outgrowth of residual tumour cells, circulating tumour cells, and dormant micrometastases. MicroRNAs are particularly relevant in this context because they regulate coordinated gene networks involved in tumor survival, epithelial–mesenchymal plasticity, angiogenesis, immune escape, and metastatic niche formation. OncomiRs such as miR-21, miR-10b, miR-155, miR-210, and miR-221/222 may promote recurrence-associated signaling, whereas tumor-suppressive miRNAs including miR-34a, the miR-200 family, let-7, miR-126, miR-143/145, and miR-29 may restrict metastatic progression. This review provides a translational framework linking surgery-induced host responses with miRNA-mediated metastatic regulation. It discusses perioperative immune and stromal remodeling, anesthetic and analgesic influences, exosomal miRNAs, biomarker-guided monitoring, therapeutic delivery systems, safety concerns, and clinical trial design. Although perioperative miRNA therapy is not yet a validated clinical intervention, serial miRNA profiling combined with ctDNA, circulating tumor cells, cytokines, and clinicopathological variables may support future precision strategies to identify high-risk patients and guide recurrence-prevention studies. The key challenge is to suppress pro-metastatic signaling without impairing wound healing, infection control, or postoperative recovery.
Source: Frontiers in Pharmacology
Authors: Bin Yao, Binsong Qiu, Yin Zhang, Wei Feng
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7225377125