To examine the temporal and causal relationships among microbiota disturbance, local metabolic and transcriptional changes

The gap

Evidence profile

Sourced from the future-work section and future work of the source papers, classified as general, drawn from work published between 2025 and 2026, spanning 3 journals. Those papers have been cited 14 times in total.

Supporting evidence — 3 representative gaps

• Gut microbiota disturbance disrupts osteonal organization and mechanical competence during postnatal cortical bone maturation in rabbits with local metabolic and transcriptional remodeling (2026) · Frontiers in Cell and Developmental Biology · doi

  to examine the temporal and causal relationships among microbiota disturbance, local metabolic and transcriptional changes, osteonal organization and cortical bone strength - to determine whether microbiota-related regulation contributes to osteonal remodeling in pathological or regenerative settings, including osteoporosis and fracture repair - combining dynamic bone labeling, higher-resolution three-dimensional imaging and cell-specific molecular assays to further strengthen the interpretation of osteonal remodeling

  generalfuture-work section
  Keywords: examine temporal causal relationships among microbiota disturbance local
• Advances in the association between tumor immune microenvironment remodeling in osteosarcoma and the risk of pathological fractures (2026) · Frontiers in Genetics · doi

  In summary, multidimensional immune remodeling of the osteosarcoma TIME drives a pathological microenvironment that tightly couples immunosuppression with bone destruction through RANKL/RANK/OPG axis imbalance, activation of pro-osteoclastic cytokine networks, MMP-mediated ECM degradation, the hypoxia- HIF-1alpha pathway, and exosomal signal transduction, representing a critical driving force in the development of pathological fractures. Traditional PF risk assessment systems based primarily on mechanical parameters urgently need to integrate TIME-related biomarkers to establish more precise immune-mechanical composite risk models. Several important limitations of the current evidence base, however, must be acknowledged. First, the majority of mechanistic insights derive from preclinical models, including in vitro co-culture and murine xenograft systems, and their direct translatability to human OS remains to be confirmed. Second, a number of immune-bone crosstalk pathways incorporated into the proposed integrated model are inferred from studies in other bone malignancies or inflammatory bone diseases rather than demonstrated directly in OS. Third, protective and context- dependent are responses within undercharacterized and may modulate or oppose the predominantly immunosuppressive narrative described in this review. Fourth, virtually the OS TIME immune all therapeutic strategies discussed beyond mifamurtide lack OS-specific randomized clinical trial evidence, and the translational timeline from preclinical concept to clinical practice is uncertain. for therapy ICIs with anti-RANKL Future research should focus on: (i) developing validated TIME- related PF risk prediction biomarker panels such as serum RANKL/ OPG ratios, exosomal miRNA profiles, and circulating TAM (ii) exploring optimal combination subtype quantification; sequences and bisphosphonates; (iii) achieving precise co-targeting of TIME immunosuppressive cells and osteoclasts within nanoparticle drug delivery systems; and (iv) conducting prospective clinical studies to verify the actual reduction in PF incidence through TIME spatial strategies. As intervention transcriptomics, and organoid increasingly applied, the mechanistic understanding of the OS TIME-fracture relationship will continue to deepen, providing new scientific functional foundations preservation and survival improvement in osteosarcoma patients. single-cell technologies are the dual goals of for achieving omics, A key translational challenge remains: integrating the Tumor Inflammation Score (TIS), bone destruction imaging parameters such as cortical erosion rate, and circulating biomarkers including RANKL and MMP-9 into a clinically applicable precision prediction system for pathological fracture in osteosarcoma constitutes the central challenge and most important breakthrough opportunity for future translational research.

  generalfuture workevidence 5/5
  Keywords: time bone immune rankl osteosarcoma pathological risk systems clinical translational destruction exosomal mechanical parameters related
• Immune cells: the key mediator between the gut microbiota and osteoporosis (2025) · Frontiers in Immunology · cited 14× · doi

  The GM regulates bone metabolism through multiple mechanisms, including modulation of inflammatory factors, alterations in metabolites, and interactions with the immune and endocrine systems, as well as maintenance of intestinal barrier integrity. This review focuses on the interactions between GM and immune cells, and between immune cells and OP, aiming to elucidate and establish a comprehensive GM-immune cell-OP crosstalk network. Intervention strategies based on the microbiota-immune-bone axis show therapeutic potential in OP management, with promising applications of probiotics, prebiotics, dietary patterns, FMT, and engineered microbes. Nevertheless, numerous challenges remain unresolved, and future efforts should prioritize the following aspects. Although preliminary insights into the GM-immune-bone axis have been established, the precise regulatory mechanisms remain to be fully elucidated. The considerable heterogeneity of GM and their metabolites, coupled with their multi-pathway, multi-receptor, and multi-target modes of action, make it exceptionally challenging to decipher their exact mechanisms. Future mechanistic studies should prioritize understanding how specific microbial species influence bone metabolism through distinct immune cells. Microbiome research may hold the key to accelerating progress in this area. Although multi-omics approaches—as discussed in Section 5—have helped correlate microbial and immune signatures with bone metabolic markers, the underlying mechanisms remain elusive. Future investigations should employ integrated biological animal models, combining advanced transcriptomic, proteomic, and multi- omics technologies to systematically unravel the mechanisms of microbial communities and their metabolites, thereby facilitating the development of robust biomarkers for precision medicine. On the other hand, a substantial body of preclinical evidence supports the role of the GM in indirectly improving skeletal health through immune cell mediators, corroborating the mechanisms discussed herein. However, translating these foundational insights into effective and clinically viable applications remains a major challenge. In contrast, clinical studies in this area remain scarce and have produced inconsistent outcomes, particularly due to a lack of high-quality trials. Interindividual variability and microbial heterogeneity likely contribute to these discrepancies. For instance, to address compositional variability in the microbiome, future approaches could employ personalized bacterial profiling to select appropriate microbial consortia for precision therapeutics aimed at restoring skeletal health. Equally critical is the design of microbial interventions—such as FMT and engineered microbes—that can safely, precisely, and effectively target the immune system to maintain bone metabolic homeostasis. There is an urgent need for large-scale, multicenter RCTs with long-term follow-up, which must incorporate appropriate patient stratification based on complex microbial or metabolic signatures to rigorously evaluate the impact of microbiota-targeted therapies on key clinical outcomes and enhance the scientific rigor and translational credibility of the evidence.

  generalfuture workevidence 5/5
  Keywords: immune microbial bone mechanisms multi remain future metabolites cells metabolic metabolism interactions cell based microbiota

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