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<p>Osteosarcoma (OS) is a quintessential “cold tumor,” and outcomes for patients with metastatic or recurrent disease have remained poor for decades. The failure of immune checkpoint inhibitors (ICIs) in OS reflects a multilayered immunosuppressive architecture rather than a single dominant lesion. This review deconstructs three principal barriers within that architecture: (1) physical T-cell exclusion driven by a dense fibrotic stroma and aberrant vasculature; (2) a myeloid-dominant suppressive network enriched for Tumor-Associated Macrophages (TAMs) and Myeloid-Derived Suppressor Cells (MDSCs); and (3) Antigen Presentation Machinery (APM) defects, most commonly loss of MHC-I/B2M. In parallel, the primary tumor actively engineers the pulmonary environment through exosomes and Neutrophil Extracellular Traps (NETs), establishing a Pre-metastatic Niche (PMN) that facilitates lung metastasis.</p><p>Integrating evidence from single-cell and spatial omics, multi-modal imaging (radiomics, digital pathology), and liquid biopsy (ctDNA-minimal residual disease [MRD]), this review translates biological “decoding” of the OS microenvironment into a hypothesis-generating operational framework. We propose an “OS-TME Subtyping V1.0” model in which subtypes are treated as dynamic, dominant-barrier system states rather than fixed biological classes. In its current conceptual form, state assignment is envisioned as a semi-structured, rule-based process using concordant signals from pathology/spatial readouts, imaging surrogates, and ctDNA/immune context; mixed or discordant cases are intentionally retained as indeterminate states for reassessment rather than forcibly classified. On this basis, we outline a sequential “De-suppression → Priming → Checkpoint” logic tailored to different barrier-dominant states. For myeloid-dominant states, we prioritize myeloid reprogramming (e.g., CSF1R/CCR2-axis targeting) combined with immunogenic priming. For dense fibrotic stroma/angio-abnormal states, we emphasize up-front vessel/stroma remodeling before checkpoint therapy. For APM-defective states, we discuss MHC-independent approaches targeting B7-H3 or GD2 (e.g., CAR-T/NK cells, antibody-drug conjugates), while explicitly acknowledging target heterogeneity, trafficking barriers, and on-target/off-tumor risk.</p><p>To narrow the translational gap, we further outline a perioperative “Window of Opportunity” (WoO) trial prototype and a conceptual “Cold-to-Hot Readiness Index (RI)” that integrates dynamic imaging, pathology, and MRD monitoring. The RI is presented only as an illustrative, hypothesis-generating summary variable intended for retrospective stratification, simulation modeling, or biomarker-guided early-phase trial design, rather than near-term routine clinical decision-making. Together, these elements define a theoretical blueprint for iterative state assessment and adaptive therapeutic sequencing in osteosarcoma.</p>

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A conceptual blueprint for “turning cold to hot” in Osteosarcoma: from TME stratification hypotheses to adaptive therapeutic prospects

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月15日

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  • Bai Yang,
  • Shu Liu,
  • Bingcheng Liu,
  • Tianwen Ye,
  • Xiao Ma,
  • Tengfei Song

摘要

Osteosarcoma (OS) is a quintessential “cold tumor,” and outcomes for patients with metastatic or recurrent disease have remained poor for decades. The failure of immune checkpoint inhibitors (ICIs) in OS reflects a multilayered immunosuppressive architecture rather than a single dominant lesion. This review deconstructs three principal barriers within that architecture: (1) physical T-cell exclusion driven by a dense fibrotic stroma and aberrant vasculature; (2) a myeloid-dominant suppressive network enriched for Tumor-Associated Macrophages (TAMs) and Myeloid-Derived Suppressor Cells (MDSCs); and (3) Antigen Presentation Machinery (APM) defects, most commonly loss of MHC-I/B2M. In parallel, the primary tumor actively engineers the pulmonary environment through exosomes and Neutrophil Extracellular Traps (NETs), establishing a Pre-metastatic Niche (PMN) that facilitates lung metastasis.

Integrating evidence from single-cell and spatial omics, multi-modal imaging (radiomics, digital pathology), and liquid biopsy (ctDNA-minimal residual disease [MRD]), this review translates biological “decoding” of the OS microenvironment into a hypothesis-generating operational framework. We propose an “OS-TME Subtyping V1.0” model in which subtypes are treated as dynamic, dominant-barrier system states rather than fixed biological classes. In its current conceptual form, state assignment is envisioned as a semi-structured, rule-based process using concordant signals from pathology/spatial readouts, imaging surrogates, and ctDNA/immune context; mixed or discordant cases are intentionally retained as indeterminate states for reassessment rather than forcibly classified. On this basis, we outline a sequential “De-suppression → Priming → Checkpoint” logic tailored to different barrier-dominant states. For myeloid-dominant states, we prioritize myeloid reprogramming (e.g., CSF1R/CCR2-axis targeting) combined with immunogenic priming. For dense fibrotic stroma/angio-abnormal states, we emphasize up-front vessel/stroma remodeling before checkpoint therapy. For APM-defective states, we discuss MHC-independent approaches targeting B7-H3 or GD2 (e.g., CAR-T/NK cells, antibody-drug conjugates), while explicitly acknowledging target heterogeneity, trafficking barriers, and on-target/off-tumor risk.

To narrow the translational gap, we further outline a perioperative “Window of Opportunity” (WoO) trial prototype and a conceptual “Cold-to-Hot Readiness Index (RI)” that integrates dynamic imaging, pathology, and MRD monitoring. The RI is presented only as an illustrative, hypothesis-generating summary variable intended for retrospective stratification, simulation modeling, or biomarker-guided early-phase trial design, rather than near-term routine clinical decision-making. Together, these elements define a theoretical blueprint for iterative state assessment and adaptive therapeutic sequencing in osteosarcoma.