J Bone Oncol. 2026 Sep 16;61:100803. doi: 10.1016/j.jbo.2026.100803. eCollection 2026 Dec.

ABSTRACT

Osteosarcoma relapse surveillance remains dominated by scheduled imaging because salvage treatment depends on anatomical confirmation of pulmonary, local or extrapulmonary recurrence. However, radiological recurrence may occur after a biologically active phase in which residual viable disease or micrometastatic progression is already present but not yet localizable. This clinical-translational review reframes postoperative osteosarcoma surveillance as an action-linked decision workflow rather than a comparison of isolated biomarker technologies. Current evidence suggests that tumor-informed circulating tumor DNA (ctDNA) sequencing provides the strongest osteosarcoma-specific minimal residual disease (MRD) signal, with postoperative positivity associated with inferior event-free survival and, in selected patients, molecular detection preceding imaging-confirmed relapse or progression. Cell-free DNA methylation may offer a mutation-independent adjunct, whereas circulating tumor cells, extracellular vesicles and circulating microRNAs remain exploratory signals without validated postoperative surveillance actions. Chest computed tomography (CT) and local magnetic resonance imaging (MRI) remain indispensable for disease localization and treatment planning, while diffusion-weighted imaging, dynamic contrast-enhanced MRI and radiomics currently provide mainly local viability or risk-enrichment information rather than proven surveillance-intervention evidence. The near-term role of integrated biomarkers is therefore not to replace guideline-based imaging, but to define protocolized pathways for molecular-positive/imaging-negative, imaging-positive/molecular-negative, concordant high-risk and concordant low-risk states. Future studies should test whether biomarker-triggered reassessment improves clinically meaningful outcomes, including resectability, second complete remission, clinical trial access, patient burden and survival, rather than simply documenting recurrence earlier.

PMID:42824543 | PMC:PMC13628598 | DOI:10.1016/j.jbo.2026.100803

Signal Transduct Target Ther. 2026 Sep 28;11(1):418. doi: 10.1038/s41392-026-02875-2.

ABSTRACT

Hepatocellular carcinoma (HCC) exhibits a suboptimal response to immune checkpoint blockade (ICB) therapy; to overcome this resistance, we aimed to delineate key immune resistance factors via multi-omics analysis, develop strategies to block their immunosuppressive axes, and engineer a targeted nanosystem to enhance immunotherapy efficacy against PD-1 resistance in HCC. Using transcriptomic and proteomic data from anti-PD-1-treated HCC patients, along with functional validation in murine models and mechanistic molecular and cell biology studies, we identified transketolase-like 1 (TKTL1) as a dual-nature biomarker where overexpression predicted poor baseline prognosis yet enhanced response to ICB. Mechanistically, TKTL1 diverts glucose flux into glycolysis rather than pentose phosphate pathway (PPP), recruiting USP9X to deubiquitinate and stabilize HIF-1α, which upregulates HK2 to amplify glycolytic output and lactate accumulation. This metabolic rewiring orchestrates dual immunosuppressive circuits through HIF-1α-driven CCL4 secretion recruiting PD-L1^high dendritic cells (DCs), coupled with lactate-induced TRIM28^K408 lactylation that stabilizes PD-L1 by blocking ubiquitin-mediated degradation. We engineered a hepatoma-membrane-coated MnO₂ nanosystem (CQLH) co-delivering a TKTL1 inhibitor and lactate oxidase, which disrupted the TKTL1-HIF-1α-HK2 axis, depleted lactate, and reprogrammed the tumor microenvironment, thereby enhanced anti-PD-1 therapy to suppress tumor growth, especially in TKTL1^high tumors. These findings define a critical "TKTL1-glycolysis-lactate-DC" axis driving anti-PD-1 sensitivity in HCC, position TKTL1 as both a potential biomarker for ICB response and a tractable therapeutic target, and demonstrate that the targeted CQLH nanosystem overcomes resistance and enhances anti-PD-1 efficacy, offering a precision immunotherapeutic strategy for TKTL1^high HCC.

PMID:42802226 | PMC:PMC13616917 | DOI:10.1038/s41392-026-02875-2

Biochim Biophys Acta Rev Cancer. 2026 Sep 15:189717. doi: 10.1016/j.bbcan.2026.189717. Online ahead of print.

ABSTRACT

Breast cancer deaths are mainly caused by metastasis to distant organs, not by the primary tumor. Bone, lung, liver, and brain are the most common metastatic sites, each showing different clinical behaviors and treatment responses-a pattern often called metastatic organotropism. Bulk omics can provide tissue-level information, but they fall short in identifying rare metastasis-initiating clones or capturing how tumor cells adapt to distinct organ microenvironments. With recent progress in single-cell sequencing, multi-omics integration, and spatial profiling, it is now possible to study metastasis at much finer cellular and spatial resolution. In this review, we synthesize current evidence from two complementary perspectives. First, we summarize pan-organ programs associated with metastatic competence, including partial epithelial-mesenchymal transition, lineage plasticity, stem-like states, stress tolerance, metabolic flexibility, immune evasion, and stromal-vascular remodeling. Second, we discuss how these programs are reshaped by organ-specific microenvironments: osteolytic and mixed bone remodeling and marrow dormancy in bone, inflammatory vascular niches in lung, tolerogenic antigen presentation and hepatic metabolism in liver, and blood-brain/blood-tumor barrier constraints, glial crosstalk, neuronal interactions, and lipid-metabolic adaptation in brain. We also highlight how CTC/CTM profiling, spatial mapping, and longitudinal integration refine the understanding of dissemination, dormancy, colonization, outgrowth, and treatment resistance. Although these approaches hold translational promise, most remain at the discovery or early validation stage and require assay simplification, prospective testing, and cross-center standardization. Overall, single-cell and spatial multi-omics are reframing breast cancer metastasis as a dynamic, multi-stage, and tissue-shaped process, providing a foundation for future biomarker development and mechanism-guided therapeutic strategies.

PMID:42744123 | DOI:10.1016/j.bbcan.2026.189717