Photobiomodulation Meets Mechanotransduction: Immune and Cellular Cross-Talk during Orthodontic Tooth Movement

Orthodontic tooth movement (OTM) is governed by a highly coordinated cascade of cellular and molecular events triggered by mechanical forces. At the heart of this process lies the dynamic interplay between osteoblasts, osteoclasts, periodontal ligament (PDL) cells, and components of the immune system. This review begins with an overview of the key cellular players in OTM and the biological foundations of force-induced bone remodeling, highlighting the critical roles of mechanotransduction, cytokine-mediated signaling, and extracellular matrix turnover. Building upon these principles, we explore the fundamentals of photobiomodulation and its broader clinical applications in dentistry, with particular emphasis on Low-Level Laser Therapy (LLLT). Recent systematic reviews have assessed its clinical value in orthodontics, reporting variable outcomes in terms of accelerating tooth movement and alleviating treatment-related discomfort. A central theme of this review is the emerging recognition of LLLT as a modulator of intercellular cross-talk during OTM. We analyze how photonic energy may interfere with or amplify mechanical stimuli at the cellular level, integrating into mechanosensitive pathways such as MAPK, Wnt/β-catenin, and PI3K/Akt. Special attention is given to the influence of LLLT on reciprocal interactions between osteoblasts, osteoclasts, and the PDL stromal environment, as well as on LLLT-mediated cross-talk between innate and adaptive immune mechanisms under mechanical stress, a dimension of OTM biology that has received limited attention in previous reviews. Additionally, we evaluate the role of LLLT in regulating apoptosis and autophagy, key processes for cellular adaptation in the mechanically active microenvironment. By bridging photonic and mechanical signaling, LLLT may offer a novel strategy for fine-tuning biological remodeling in orthodontics. Recognition of its immunomodulatory capacity could inform targeted, evidence-based protocols that optimize both treatment efficiency and patient outcomes.